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Matrix-Assisted Laser Desorption Ionization–Time of Flight Mass
Spectrometry: a Fundamental Shift in the Routine Practice of Clinical
Microbiology
Andrew E. Clark,
a
Erin J. Kaleta,
b
Amit Arora,
c
Donna M. Wolk
d,e,f
Department of Veterinary Science and Microbiology, University of Arizona, Tucson, Arizona, USA
a
; Department of Laboratory Medicine and Pathology, Mayo Clinic,
Rochester, Minnesota, USA
b
; Department of Surgery, University of Arizona, Tucson, Arizona, USA
c
; Department of Pathology, University of Arizona Medical Center, Tucson,
Arizona, USA
d
; The BIO5 Institute, University of Arizona, Tucson, Arizona, USA
e
; Geisinger Health Systems, Danville, Pennsylvania, USA
f
SUMMARY ..................................................................................................................................................549
INTRODUCTION ............................................................................................................................................549
MECHANICS OF MS FOR IDENTIFICATION OF MICROBES .................................................................................................550
Mechanisms and Components Leading to Sample Ionization in MALDI-TOF MS ........................................................................551
Ion Formation within the Crystalline Deposit on the MALDI Plate .......................................................................................552
Types of Matrices Used in MALDI-TOF MS Experiments ..................................................................................................552
Mass Analyzers Used for Characterization of Ionized Clinical Specimens.................................................................................553
The Time of Flight Analyzer ..............................................................................................................................553
Linear Time of Flight Mass Spectrometry .................................................................................................................553
Reflectron ................................................................................................................................................554
ISSUES AND IMPLICATIONS FOR USE IN CLINICAL MICROBIOLOGY LABORATORIES ....................................................................554
Standardization...........................................................................................................................................554
Evolution of Intact-Cell MALDI-TOF MS...................................................................................................................554
CURRENTLY AVAILABLE COMMERCIAL PLATFORMS FOR MALDI-TOF MS IDENTIFICATION OF MICROBES.............................................554
Andromas ................................................................................................................................................556
SARAMIS Evolves to Vitek-MS.............................................................................................................................556
BioTyper ..................................................................................................................................................556
PERFORMANCE AND COMPARISON OF COMMERCIAL METHODS IN ROUTINE CLINICAL MICROBIOLOGY.............................................557
COMPARISONS BY MICROBE CATEGORY ..................................................................................................................557
GRAM-POSITIVE BACTERIA .................................................................................................................................557
Sample Processing for Identification of Gram-Positive Bacteria by MALDI-TOF MS ......................................................................558
Staphylococci ............................................................................................................................................558
Coagulase-negative staphylococci ....................................................................................................................559
Staphylococcus aureus .................................................................................................................................559
Non-S. aureus, coagulase-positive staphylococci ......................................................................................................560
Testing of clinical samples for mixed staphylococcal species..........................................................................................560
Micrococci................................................................................................................................................561
Staphylococci and MALDI-TOF MS: Future Uses and Implications .......................................................................................561
Streptococci ..............................................................................................................................................561
Beta-hemolytic streptococci ...........................................................................................................................561
(i) Group A streptococci.............................................................................................................................562
(ii) Group B streptococci ............................................................................................................................562
Streptococcus pneumoniae .............................................................................................................................563
Viridans group streptococci ...........................................................................................................................563
Nutritionally variant streptococci and related genera .................................................................................................563
Enterococcus spp. ........................................................................................................................................564
Lactococcus spp. .........................................................................................................................................564
Bacillus spp. ..............................................................................................................................................564
Listeria spp. ...............................................................................................................................................565
Corynebacterium spp. ....................................................................................................................................565
Arcanobacterium and Trueperella spp. ....................................................................................................................565
Nocardia and Mycobacteria ..............................................................................................................................566
Sample preparation methods for MALDI-TOF MS identification of mycobacteria and Nocardia spp. .................................................566
Nocardia spp. ..........................................................................................................................................566
Mycobacteria...........................................................................................................................................566
(continued)
Address correspondence to Donna M. Wolk, dmwolk@geisinger.edu.
Copyright © 2013, American Society for Microbiology. All Rights Reserved.
doi:10.1128/CMR.00072-12
July 2013 Volume 26 Number 3 Clinical Microbiology Reviews p. 547– 603 cmr.asm.org 547
GRAM-NEGATIVE BACTERIA................................................................................................................................567
Sample Preparation for Gram-Negative Bacteria .........................................................................................................567
The Enterobacteriaceae ...................................................................................................................................568
Salmonella spp. ........................................................................................................................................568
Escherichia coli and Shigella spp. .......................................................................................................................569
Proteus spp. ............................................................................................................................................570
Cronobacter spp. ......................................................................................................................................570
Enterobacter cloacae complex .........................................................................................................................571
Pantoea spp. ...........................................................................................................................................571
Plesiomonas shigelloides................................................................................................................................571
Klebsiella/Raoultella spp. ...............................................................................................................................571
Yersinia spp. ...........................................................................................................................................571
(i) Yersinia enterocolitica .............................................................................................................................572
(ii) Yersinia pestis and Yersinia pseudotuberculosis....................................................................................................572
Nonfermenting Gram-Negative Bacteria .................................................................................................................572
Acinetobacter spp. .....................................................................................................................................573
Burkholderia cepacia complex..........................................................................................................................573
Burkholderia mallei and Burkholderia pseudomallei .....................................................................................................574
Pseudomonas spp. .....................................................................................................................................574
Stenotrophomonas maltophilia.........................................................................................................................574
Fastidious Gram-Negative Bacteria .......................................................................................................................574
Sample preparation methods for MALDI-TOF MS analysis of fastidious Gram-negative rods, including dangerous bacteria .........................575
Brucella spp. ...........................................................................................................................................575
Bartonella spp. .........................................................................................................................................575
Francisella spp. ........................................................................................................................................575
Haemophilus spp. ......................................................................................................................................576
Vibrio spp. .............................................................................................................................................576
Aeromonas spp. .......................................................................................................................................576
Campylobacter spp. ....................................................................................................................................576
Helicobacter spp. ......................................................................................................................................577
Neisseria spp. ..........................................................................................................................................577
Moraxella catarrhalis ...................................................................................................................................577
Legionella spp. .........................................................................................................................................578
ANAEROBIC BACTERIA .....................................................................................................................................578
MALDI-TOF MS Sample Preparation for Identification of Anaerobic Bacteria.............................................................................579
Propionibacterium spp. ...................................................................................................................................579
Bacteroides spp. ..........................................................................................................................................580
Clostridium spp. ..........................................................................................................................................580
FUNGI: YEASTS .............................................................................................................................................580
Yeast Sample Preparation for MALDI-TOF MS ............................................................................................................581
Candida spp. .............................................................................................................................................581
Cryptococcus spp. ........................................................................................................................................582
FILAMENTOUS FUNGI AND MOLDS .......................................................................................................................582
Mold Sample Preparation for MALDI-TOF MS ............................................................................................................583
Aspergillus spp. ...........................................................................................................................................583
Fusarium spp. ............................................................................................................................................583
Dermatophytes...........................................................................................................................................584
Pseudallescheria-Scedosporium Complex .................................................................................................................584
Penicillium spp. ...........................................................................................................................................584
Lichtheimia spp. ..........................................................................................................................................584
Extended Testing of Fungal Isolates by MALDI-TOF MS: Antifungals and Epidemiology .................................................................584
USE OF MALDI-TOF MS IN EPIDEMIOLOGY ................................................................................................................585
MS IDENTIFICATION OF BACTERIA DIRECTLY FROM PATIENT SPECIMENS ...............................................................................585
Urine......................................................................................................................................................585
Cerebrospinal Fluid.......................................................................................................................................587
Identification of Bacteria Directly from Blood Cultures ...................................................................................................588
Identification of Yeast Directly from Blood Culture Broth ................................................................................................588
Extraction Methods for Identification of Microbes Directly from Blood Culture Bottles ..................................................................589
MS IDENTIFICATION OF ANTIMICROBIAL RESISTANCE....................................................................................................590
Detection of Resistance to Beta-Lactam Antibiotics in Enteric and Nonfermenting Gram-Negative Rods ...............................................590
Carbapenem-Resistant Acinetobacter baumannii.........................................................................................................590
Carbapenem-Resistant Klebsiella spp. ....................................................................................................................591
Carbapenem-Resistant Bacteroides fragilis ................................................................................................................591
MRSA and Vancomycin-Intermediate Staphylococcus aureus ............................................................................................591
Vancomycin-Resistant Enterococcus ......................................................................................................................592
FUTURE VIEW AND IMPLICATIONS ........................................................................................................................592
ACKNOWLEDGMENTS......................................................................................................................................592
REFERENCES ................................................................................................................................................592
AUTHOR BIOS ..............................................................................................................................................602
Clark et al.
548 cmr.asm.org Clinical Microbiology Reviews
SUMMARY
Within the past decade, clinical microbiology laboratories experi-
enced revolutionary changes in the way in which microorganisms
are identified, moving away from slow, traditional microbial iden-
tification algorithms toward rapid molecular methods and mass
spectrometry (MS). Historically, MS was clinically utilized as a
high-complexity method adapted for protein-centered analysis of
samples in chemistry and hematology laboratories. Today, ma-
trix-assisted laser desorption ionization–time of flight (MALDI-
TOF) MS is adapted for use in microbiology laboratories, where it
serves as a paradigm-shifting, rapid, and robust method for accu-
rate microbial identification. Multiple instrument platforms,
marketed by well-established manufacturers, are beginning to dis-
place automated phenotypic identification instruments and in
some cases genetic sequence-based identification practices. This
review summarizes the current position of MALDI-TOF MS in
clinical research and in diagnostic clinical microbiology laborato-
ries and serves as a primer to examine the “nuts and bolts” of
MALDI-TOF MS, highlighting research associated with sample
preparation, spectral analysis, and accuracy. Currently available
MALDI-TOF MS hardware and software platforms that support
the use of MALDI-TOF with direct and precultured specimens
and integration of the technology into the laboratory workflow are
also discussed. Finally, this review closes with a prospective view of
the future of MALDI-TOF MS in the clinical microbiology labo-
ratory to accelerate diagnosis and microbial identification to im-
prove patient care.
INTRODUCTION
T
imely and accurate identification of microorganisms is the un-
derlying function of any clinical microbiology laboratory and
is accomplished through a consistently evolving repertoire of lab-
oratory techniques. Historically, confirmation of microbial iden-
tification was dependent upon a hierarchy of assays separated into
stages: (i) stain-based methodologies for classification of micro-
scopic morphology to support early diagnostic and therapeutic
decisions; (ii) microbial culture for propagation of the offending
organism on agar or in liquid medium; (iii) biochemical or anti-
genic techniques for the subsequent metabolic and phenotypic
analysis of the microorganism, ultimately leading to microbe
identification; and (iv) antimicrobial susceptibility testing to con-
firm therapeutic choices or tailor therapy (1). While historical
sentiment among both microbiologists and clinicians accepted
these established protocols as reference standards (in terms of
accuracy, speed, and costs), microbiologists, clinicians, and pa-
tients were at the mercy of the microorganism’s growth rate. Ro-
bust growth and active microbial biochemistry were usually re-
quired for most determinative phenotypic assays, thus extending
the time to result by days and, in some cases, weeks.
As new technology emerged, prevailing expectations defined
standards for more rapid, accurate, and sensitive methods aimed
at optimizing patient care and therapy. For example, genetic se-
quencing uncovered numerous errors inherent to phenotypic
identification and became part of the new standard for microbial
identification (2, 3). Real-time PCR (4, 5) and fluorescence in situ
hybridization (FISH) (6–8) methods established new norms for
speed and sensitivity.
While new technology is often necessary for optimal patient
care and therapy, reagent and quality control costs often exceed
those of historical methods, thus placing an additional burden on
laboratories to define and monitor quantitative measures of cost
benefit for patients and in some cases the entire health care system.
In addition, since the technological complexity and laboratory
space design requirements can hinder test performance in re-
source-poor settings, laboratory leadership must be mindful not
to create an imbalance in the standards for laboratory practice
with societal implications.
Among the last pieces of clinical data to be reported, antibiotic
susceptibility testing further extends the time necessary for a final
determinative report for therapeutic purposes. Often, an addi-
tional 24 h is necessary for susceptibility testing to be completed by
using Kirby-Bauer disc diffusion testing, broth microdilution
methods, automated susceptibility testing (AST), and Etests.
While methods for rapid susceptibility testing, such as those re-
ported for the Vitek-2 (bioMérieux) instrument, are directly from
positive blood culture broths, these adapted methods are not al-
ways accurate enough to be reported without additional confir-
matory analysis, making them useful in some cases but not appli-
cable to all clinical situations (9).
The integration of molecular testing methodologies into deter-
minative microbial identification algorithms supported critical
advances in analytical sensitivity, allowing microbiologists to ex-
plore options other than routine culture and to begin testing pa-
tient specimens directly for the presence or absence of particular
organisms. Additionally, the ability to rapidly and uniformly test
both direct patient specimens and cultured organisms in near real
time by molecular methods transformed the microbiology labo-
ratory (1). Nucleic acid-based methods such as FISH and PCR-
based strategies drastically decreased the time to result and pro-
vided significant improvements to both laboratory workflow and
patient prognoses (6, 121). However, a significant limitation of
these molecular methods is that a majority of these assays require
advance knowledge of the characteristics of the microorgan-
ism(s), or a likelihood of that particular organism being present,
in order to select the correct assay to fit the testing application.
Moreover, in the case of polymicrobial infections, multiple mo-
lecular assays, preliminary culture and separation, or additional
downstream testing is sometimes required for full characteriza-
tion of the clinical specimen, adding to the result turnaround time
and the overall financial cost.
Gene sequencing provided an attractive option for universal
identification of fungi and bacteria. Since its implementation, it is
considered among the most definitive of all molecular microbio-
logical analyses. Although 16S rRNA and 18S rRNA gene sequenc-
ing (for bacterial and fungal identifications, respectively) are pow-
erful diagnostic tools with high discriminatory power for species-
and strain-level determinations (10), these methods are employed
primarily by large high-complexity clinical and reference labora-
tories for reflex and confirmatory testing. As with several other
molecular methodologies, rRNA gene sequencing often requires
specialized instrumentation and dedicated laboratory space and
staff. These constraints often render rRNA gene sequencing im-
practical for most laboratories; therefore, the use of automated
instruments for the phenotypic analysis of bacterial isolates still
predominates as the basis for routine microbial identification, de-
spite imperfections in accuracy, robustness, and time to identifi-
cation. In spite of nearly 20 years of clinical evidence depicting
molecular methods to be significantly faster and often more accu-
rate with respect to diagnoses, many laboratories have not yet
MALDI-TOF Mass Spectrometry in Clinical Microbiology
July 2013 Volume 26 Number 3 cmr.asm.org 549
adopted them as part of their routine practice. Clearly, the devel-
opment and validation of alternative rapid and universal identifi-
cation methods are warranted; MALDI-TOF MS methods may fill
some of these critical gaps.
One significant challenge faced by clinical microbiologists and
the diagnostic industry is the sheer breadth of testing associated
with the discipline. The diversity of etiological agents of disease
encountered in the microbiology section of the clinical laboratory
is staggering. Many pathogenic agents require dedicated diagnos-
tic testing platforms for accurate diagnosis of infection (i.e., spe-
cialized culture, molecular methods for noncultivatable or diffi-
cult-to-recover organisms, and microscopic inspection and
special staining for the characterization of some organisms, in-
cluding parasites). Add to this the above-mentioned need for
rapid and accurate results, and laboratories are left to sort through
a complex interplay between traditional and molecular methods
to achieve robust, rapid, and accurate identifications for the wide
range of organisms potentially encountered. In response, scien-
tists searched for a method which would prove to be standardized
and nearly universal in scope and which could identify pathogens
and commensals alike, using streamlined workflow with minimal
costs and expertise—that method could well be mass spectrome-
try (MS).
While automated phenotypic and molecular methods received
heavy use in clinical laboratories throughout the previous decade,
MS-based methods quietly began to develop. Originally confined
to basic research laboratories, MS methods were used consistently
to address questions that were applicable to the clinical laboratory,
including microbiological identification, taxonomy, and bacterial
cell composition. Due to its high resolving power and analytical
sensitivity, MS is mechanistically well suited to serve as a basis for
microbial identification in the clinical laboratory. Similar to high-
complexity molecular methods, the technology may at first be
relegated to large reference laboratories due to high instrument
costs; however, it is likely that MS technology could be utilized on
a routine basis, even in small laboratories if instrument costs de-
crease. If modified to allow for the analysis of a larger variety of
microbes and molecules, standardized to allow ease of use for a
highly varied workforce, and integrated into laboratory informa-
tion systems, MS methods are destined to become an integral tool
for most diagnostic microbiology laboratories.
Across the globe, the trend of the use of diagnostic MS methods
is apparent (11, 12), and while laboratory scientists await FDA
approval of the technology in the United States, some are self-
verifying the use of the technology. Sample preparation is both
simple and reproducible. Most medical laboratory scientists can
easily perform analysis of raw MS data and determine microbial
identifications with the aid of associated software. Finally, MS
technology can interface directly with the laboratory information
system (LIS) and reflex to other diagnostic testing. Thus, as MS
continues to be implemented into modern clinical microbiology
laboratories, it is important that laboratorians and clinicians alike
become familiar with this paradigm-shifting technology. In short,
MS technology is rapid, robust, customizable pursuant to the
needs of the laboratory, more cost-effective than current pheno-
typic testing methods despite the initial cost of the instrument,
and, perhaps most importantly, easy to use. In this review, the
mechanics and processes underlying MS for microbial identifica-
tion will be described and demystified to make the technology
more familiar and understandable (see Table 1 for a list of defini-
tions).
MECHANICS OF MS FOR IDENTIFICATION OF MICROBES
Mass spectrometry was historically utilized as an analytical tool of
the clinical chemist, making use of its high levels of sensitivity and
specificity in routine processes, in the diagnosis of some cancers
(13), inherited disorders (14), and novel biomarkers for disease
diagnostics (15). The earliest attempts at the use of mass spec-
trometry for the identification of bacteria predate the first descrip-
tion of matrix-assisted laser desorption ionization (MALDI) mass
spectrometry (16). The ability to analyze large biomolecules was
first realized close to 3 decades ago through the application of
so-called “soft ionization” techniques that gently ionize target
molecules in the sample, called analytes, to generate a spectrum of
components. The MALDI method was first introduced in 1987
(17) and subsequently reported in similar experiments in 1988
(18) and was honored with a shared Nobel Prize in 2002. Since
then, matrix-assisted laser desorption ionization–time of flight
mass spectrometry (MALDI-TOF MS) evolved into a rapid and
highly reliable analytical tool for the characterization of a diverse
collection of microbes encountered in the clinical laboratory (19,
20). Currently, a variety of analysis methods and MS instruments
are available, and while not all of them are currently used in com-
mercial MALDI-TOF MS diagnostic applications, it is useful to
TABLE 1 Common terms used in mass spectrometry
Term Definition
Adduct Ion formed by the interaction of an ion with one or more atoms or molecules to form an ion containing all the constituent atoms of the
precursor ion as well as the additional atoms from the associated atoms or molecules
Analyte Biomolecule or sample that is being analyzed
Chromophore Functional group in a molecule that is known to absorb light; this is necessary for the MALDI matrix in order to absorb the energy of
the laser beam
Desorption The opposite of absorption; here a substance is released from or through the surface rather than going into it
Detector The ions generated in a mass spectrometer after traveling through the flight tube ultimately hit the analyzer, where they are detected
and converted into a digital output signal
Mass analyzer Chamber having an electrostatic field; its purpose is to separate the ions coming from the source depending on their mass-to-charge
ratio so that they can be detected by the detector
Matrix Compound that is mixed with the sample that is being analyzed; the matrix protects the sample molecules from being destroyed by
direct focus of the laser beams and facilitates the sample’s vaporization and ionization
Sublimation Passing from solid to gas without going through a liquid phase
TOF Time taken by the ions to travel through the flight tube when an electrostatic potential is applied at its ends
Clark et al.
550 cmr.asm.org Clinical Microbiology Reviews
understand the diversity and modern iterations of MALDI-TOF
MS technology.
Mechanisms and Components Leading to Sample
Ionization in MALDI-TOF MS
In an MS analysis utilizing MALDI as a soft ionization mecha-
nism, a saturated solution of a low-mass organic compound,
called a matrix, is added to the sample, and the mixture is then
spotted onto a metal target plate for analysis (Fig. 1). In the case of
bacterial or fungal identification, a microbial colony is analyzed,
or in some cases, direct blood culture material, urine, cerebrospi-
nal fluid (CSF), or protein extract is used. Upon drying, the clin-
ical material and the matrix cocrystallize and form a solid deposit
of sample embedded into the matrix. The matrix is essential for
the successful ionization of the clinical sample, as it acts both as a
scaffold by which ionization can occur and as a supplier of protons
for the ionization of the clinical material. This sample-matrix
crystal, now present on the surface of the metal plate, is irradiated
by using a UV laser beam (usually, an N
2
laser beam with a wave-
length of 337 nm is utilized in commercial instruments). Irradia-
tion occurs for a short time to avoid damage or degradation of the
sample embedded in the matrix, which could be caused by excess
heating.
The laser beam is focused on a small spot on the matrix-clinical
sample crystalline surface (typically 0.05 to 0.2 mm in diameter),
and a beam attenuator is employed in the laser optics to adjust the
irradiance (defined as the intensity per unit of surface). This laser
attenuation can be individually adjusted for each measurement,
depending upon the sample type, but is usually standardized by
the manufacturer for routine applications. The interaction among
the photons from the laser and matrix molecules caused by uptake
of energy from the beam triggers a sublimation of the matrix into
a gas phase, forming a plume, which is directly followed by the
ionization of the clinical sample (Fig. 2). Other wavelengths of the
laser ranging from UV to infrared are also used in MALDI exper-
iments. UV lasers are most commonly used and include those
from most nitrogen lasers (337 nm), followed by excimer lasers,
neodymium-doped yttrium aluminum garnet (Nd:YAG) lasers
(355 nm), and, more recently, infrared lasers such as erbium-
doped yttrium aluminum garnet (Er:YAG) lasers (2.94 m) and
transversely excited atmospheric (TEA-CO
2
) lasers (10.6 m).
FIG 1 General schematic for the identification of bacteria and yeast by
MALDI-TOF MS using the intact-cell method. Bacterial or fungal growth is
isolated from plated culture media (or can be concentrated from broth culture
by centrifugation in specific cases) and applied directly onto the MALDI test
plate. Samples are then overlaid with matrix and dried. The plate is subse-
quently loaded into the MALDI-TOF MS instrument and analyzed by software
associated with the respective system, allowing rapid identification of the
organism.
FIG 2 General schematic for MS analysis of ionized microbiological isolates and clinical material. Once appropriately processed samples are added to the MALDI
plate, overlaid with matrix, and dried, the sample is bombarded by the laser. This bombardment results in the sublimation and ionization of both the sample and
matrix. These generated ions are separated based on their mass-to-charge ratio via a TOF tube, and a spectral representation of these ions is generated and
analyzed by the MS software, generating an MS profile. This profile is subsequently compared to a database of reference MS spectra and matched to either
identical or the most related spectra contained in the database, generating an identification for bacteria or yeast contained within the sample.
MALDI-TOF Mass Spectrometry in Clinical Microbiology
July 2013 Volume 26 Number 3 cmr.asm.org 551
Ion Formation within the Crystalline Deposit on the MALDI
Plate
Intense focusing of the laser beam on the sample material, mixed
with the crystalline matrix, causes irradiation by the laser and
rapid heating of matrix crystals and the dried clinical specimen
due to absorption of a large amount of energy from the beam.
Pulsation by the laser provokes both the matrix and clinical sam-
ple to rapidly sublimate from the solid phase into the gas phase
(without passing through a liquid phase), forming a plume con-
taining ions from both the matrix and the clinical sample. Al-
though the exact mechanism of ionization is not well understood,
it can be best explained by a simplified two-step mechanism con-
sisting of primary and secondary ionization events.
Soft ionization of proteins is critical for bacterial identification
methods, as it allows the analysis of large biomolecules, including
ribosomal proteins, with sizes measured up to 100 kDa (17, 18, 21,
22). Common soft ionization techniques include both electros-
pray ionization (ESI) and MALDI, both of which are techniques
currently used for the identification of bacteria and fungi based on
either proteomic fingerprints or amplification of genetic material
(11, 23).
Once ionized, proteins within the clinical specimen are ana-
lyzed by a component of the mass spectrometer called the mass
analyzer to reveal characteristic information about the composi-
tion of the sample in the context of a spectrum of mass-to-charge
(m/z) ratios (Fig. 2). The m/z ratios are electrodynamic measure-
ments of how quickly charged ions from the clinical sample ma-
terial move through the time of flight (TOF) tube and reach a
detector. Once spectra are generated, comparison to a database of
defined reference spectra leads to microbial identification. As the
protein compositions differ between bacterial species (and even
between bacterial strains and subspecies), different spectra will be
generated, allowing for discrimination between closely related or-
ganisms. In general, the m/z ratios that are generated and consid-
ered when formulating a microbial identification are ribosomal
proteins that are unique to their respective bacterial groups or
species (17, 18, 21, 22).
The first step of the hypothesized ionization mechanism in-
volves multiphoton ionization of the matrix molecule to produce
a radical cation. In short, photons from the laser bombard the
clinical sample-matrix mixture and remove an electron from a
molecule of matrix material, generating a radical cation of matrix
(M
⫹/⫹
·). The process is illustrated by the following chemical for-
mula:
M
→
hv
M
*
→
n(hv)
M
⫹·
⫹ e
⫺
Two photons are required for this reaction because the irradi-
ances of the laser are too low to allow for additional absorption in
this time scale (24).
Within this hypothesized mechanism, a caveat exists. The ion-
ization potentials (IPs) for the matrix are too high for two-photon
absorption (9 to 10 eV IP, 7.36 eV photon energy for a N
2
laser,
and 6.98 eV for an Nd:YAG laser); therefore, an alternate two-step
theory for the generation of the matrix radical, named the energy
pooling theory, is proposed. In the energy pooling model, two or
more excited-state matrix molecules produce one matrix radical
cation. This reaction is possible as the matrix molecules are
densely packed in close proximity when dried on the MALDI plate
in the solid phase (Fig. 1). This is exemplified by the presence of
matrix clusters or aggregates in the gas phase (25). The energy
pooling theory results in the following mechanism, whereby the
absorbed photon from the excited-state matrix molecule (M*) is
transferred to the second excited matrix molecule, resulting in the
formation of a cationic matrix radical (M
⫹·
), a nonradical matrix
molecule (M), and a free electron (e
⫺
):
MM
→
2hv
M
*
M
*
→
M ⫹ M
⫹·
⫹ e
⫺
The second step of this two-part reaction involves a proton
transfer event from the excited matrix molecule to the clinical
sample (A), resulting in ionization of a molecule of the clinical
sample:
M
*
⫹ A
→
(M ⫺ H) ⫹ AH
⫹
Additional ions of the clinical specimen are formed by second-
ary ion-molecule reactions between matrix-matrix and matrix-
specimen interactions. These reactions are thermodynamically fa-
vorable because the proton affinity of MALDI matrices is typically
lower than that of peptides and proteins to be analyzed in clinical
material. This is modeled by the following equations:
M
⫹·
⫹ M
→
MH
⫹
⫹ (M ⫺ H)
·
and
MH
⫹
⫹ A
→
M ⫹ AH
⫹
Types of Matrices Used in MALDI-TOF MS Experiments
Matrices used in MALDI-TOF MS experiments are generally crys-
talline solids with low vapor pressure that can easily become vol-
atilized to form ions in a vacuum (as in the context of MALDI-
TOF MS). The chemical matrix is mixed in excess with a clinical
sample and allows for production of intact, gas-phase ions from
large, nonvolatile, and thermally labile compounds such as pro-
teins. The matrix plays a key role by absorbing the laser light en-
ergy and causing a small part of the target substrate to vaporize.
Matrices should possess certain characteristics, such as having a
strong absorbance at laser wavelengths used to facilitate ioniza-
tion, stability in a vacuum to force an interaction with the coion-
ized clinical specimen, an ability to ionize the clinical specimen,
solubility in solvents that are compatible with the clinical speci-
men in order to create an effective matrix-specimen mixture, and
a complete lack of any chemical reactivity with the clinical speci-
men, to avoid unwanted alterations or damage to peptides con-
tained within the sample. In the case of MALDI-TOF MS, which
uses a UV laser, the matrix molecule must also have a strong chro-
mophore as part of its composition to help absorb energy, thus
preserving the protein fragmentation. Chromophores are selected
based on their ability to absorb specific laser wavelengths, result-
ing in electronic excitation of the matrix. A list of matrices com-
monly used for analyzing biomolecules by MALDI-TOF MS is
provided in Table 2.
Laboratories involved in basic life science research will often
vary the matrix that is utilized in order to more completely and
accurately analyze a subset of molecules from biological speci-
mens. Commonly used for analyzing proteins and triacylglycerols,
␣-cyano-4-hydroxycinnamic acid (CCA) and its derivate
4-chloro-␣-cyanocinnamic acid (Cl-CCA) have been shown to be
more efficient in proteomic analysis than other matrices (26). Si-
napinic acid is also popular due to its ability to reduce photochem-
ically generated adducts, greatly improving the mass resolution
for proteins (27). Finally, 2,5-dihydroxybenzoic acid (DHB) is
Clark et al.
552 cmr.asm.org Clinical Microbiology Reviews
another commonly used matrix for general analysis of protein
digests, carbohydrates, oligosaccharides, glycopeptides, and both
proteins and peptides below 10 kDa. This matrix is also well suited
for the negative ion MALDI-TOF MS glycolipids. With regard to
clinical identification of infectious microorganisms, a number of
matrices were investigated, with various levels of success, and are
reported elsewhere (21).
With respect to analyte ionization, MALDI has proven to be a
useful tool in molecular analysis of large compounds. Sample
preparation is simple, and it shows more tolerance to salts and
detergents than other mechanisms of soft ionization such as ESI,
aspects that are of consequence to the clinical microbiologist, as
microbial growth medium is often rich in salts, and detergents are
sometimes formed during bacterial growth. Additionally, MALDI
is often found to be more sensitive than other ionization tech-
niques, as the laser beam is focused on a small portion of the
matrix, allowing efficient energy transfer and preventing destruc-
tion of the clinical sample. Moreover, the analyte molecules are
widely separated within the matrix mixture, preventing the clus-
tering of molecular ions that can hamper analysis.
Mass Analyzers Used for Characterization of Ionized
Clinical Specimens
Following laser bombardment, ions generated from both the ma-
trix and clinical material must be analyzed to determine their re-
spective masses and identities. The mass analyzer is the compo-
nent of a mass spectrometer that functions to determine these
representative masses, aiding in the identification of the proteins
being analyzed. A variety of mass analyzers exist for measuring
ionized proteins from biological samples. In theory, no single an-
alyzer is ideal for all applications, and instruments must be se-
lected on the basis of experimental necessities. In the case of mi-
crobial diagnostics, commercial systems have been developed for
MALDI-TOF MS-based identification, but it is still necessary to
perform instrument calibration and quality control. MALDI uti-
lizes a pulsed ionization source, where a pulse of ions from the
clinical specimen is produced by an instantaneous exposure to the
laser beam. The pulsed nature of the MALDI process pairs natu-
rally with the TOF mass analyzer, which requires that all ions enter
the flight tube simultaneously (28). Additionally, the TOF mass
analyzer is ideal for MALDI, due to its virtually unlimited mass
range, which is advantageous because MALDI typically produces
singly charged molecular ions that can have a high mass-to-charge
(m/z) ratio. The implementation of mass spectrometric tech-
niques into the clinical laboratory is highly dependent upon
method standardization and reproducibility; therefore, mass
analyzers are often preselected, optimized, and marketed as
part of an instrument package dedicated to microbial identifi-
cation. Common mass analyzers used in MS analysis are listed
in Table 3.
The Time of Flight Analyzer
The time of flight (TOF) analyzer is dependent upon the principle
that applying an electrostatic field (eV) to the ionized clinical ma-
terial causes a generated ion with a charge (z) to accelerate, im-
parting to it some amount of kinetic energy (KE). The ions then
move into a field-free drift region, where the only force affecting
ionic movement is the kinetic energy from the acceleration step.
The velocity (v) of the ionized molecule from a clinical specimen
can therefore be calculated by using the following equation, where
KE is kinetic energy, m is mass, v is velocity, z is the charge of the
ion (⫹1 for MALDI), eV is the voltage applied, D is the distance to
the detector, and t is time:
KE ⫽
1
2
mv
2
⫽ zeV; v ⫽
D
t
In this context, D and eV are constant and t is measured, allow-
ing the m/z ratio to be determined. A simple mathematical rear-
rangement results in the following equation (29, 30):
t ⫽ D
冑
m
2 zeV
This equation demonstrates that drift time is directly propor-
tional to the m/z ratio. Larger ions will have a longer drift time and
smaller molecules will have a shorter drift time, demonstrating
separation of molecules based on mass (31). This allows for sepa-
ration of ions originating from clinical material based on the m/z
ratio.
Linear Time of Flight Mass Spectrometry
In linear TOF, the method most commonly used for the MS anal-
ysis of microbial specimens, ions generated from the source are
accelerated into the flight tube and enter a field-free region where
they are separated according to their velocities (and subsequently
size, as discussed above), before hitting the detector located at the
other end of the tube. The linear TOF method has high sensitivity
and high efficiency, with the ability to analyze molecules in fem-
tomolar (10
⫺15
mol/liter) and attomolar (10
⫺18
mol/liter) con-
centrations (32). However, a limitation of the linear TOF method
is that it provides a poor resolution due to the peak broadening
TABLE 2 List of common matrices used for UV-MALDI methods
Chromophore matrix(es)
a
Sample type(s) analyzed
PA, HPA, 3-aminopicolinic acid Oligonucleotides, DNA, and biopolymers
DHB Oligosaccharides
CCA Peptides and triacylglycerol
SA Proteins
HABA Peptides, proteins, glycoproteins
MBT Peptides, proteins, synthetic polymers
DHAP Glycopeptides, phosphopeptides
THAP Oligonucleotides
a
PA, picolinic acid; HPA, 3-hydroxypicolinic acid; SA, 3,5-dimethoxy-4-
hydroxycinnamic acid; HABA, 2-(⫺4-hydroxyphenylazo)benzoic acid; MBT,
2-mercaptobenzothiazole; DHAP, 2,6-dihyroxyacetophenone; THAP,
2,4,6-trihydroxyacetophenone.
TABLE 3 Common mass analyzers and their properties
Mass analyzer
Separation
property Resolution
b
Mass
accuracy
(Da) m/z range
Quadrupole Ion trajectory
stability
1,000–2,000 0.1 200–4,000 Da
Time of flight
a
Drift velocity 2,000–100,000 0.001 Up to 10 MDa
Quadrupole
ion trap
Ion trajectory
stability
1,000–2,000 0.1 200–4,000 Da
Ion cyclotron
resonance
Orbital
frequency
5,000–5,000,000 0.0001 200–20,000 Da
a
Commonly used in clinical microbiology.
b
A unitless measure used to describe resolution of peptides or proteins.
MALDI-TOF Mass Spectrometry in Clinical Microbiology
July 2013 Volume 26 Number 3 cmr.asm.org 553
that can occur due to the spatial distribution of analyte molecules
on the surface and the unequal distribution of energies from the
laser pulse. This results in ions with the same m/z having different
kinetic energies.
Pulsed-ion extraction (PIE) was designed to resolve limitations
associated with peak broadening. In PIE, there is a delay in the
application of the acceleration voltage following ionization. Ions
that gain more kinetic energy in the ionization process will drift
away from the target plate. When the acceleration voltage is ap-
plied, there is a gradient between the target plate and ground, and
the ions farther from the target will experience lower voltage and
will therefore have a lower deposited kinetic energy. This phe-
nomenon results in averaging with ions that received less kinetic
energy in the ionization process, thus normalizing the kinetic en-
ergy of ions having the same m/z ratio.
Reflectron
A reflectron is a focusing element at the end of the TOF instru-
ment that changes the direction of ion travel. A voltage is applied
to these lenses and causes a change in the trajectory of that ion.
Ions with a higher kinetic energy will penetrate the reflectron
deeper than those with a lower kinetic energy, such that the flight
path is elongated, allowing for averaging of flight times and de-
creasing peak broadening. Although a reflectron is effective at re-
ducing peak broadening, it essentially doubles the ion path; there-
fore, when sensitivity is an issue, it is necessary to use linear TOF
due to the potential for ion scattering. For this reason, when ana-
lyzing high-mass ions with MALDI-TOF MS, as in the case of
clinical material utilizing commercial MALDI-TOF MS plat-
forms, linear TOF is most commonly used.
ISSUES AND IMPLICATIONS FOR USE IN CLINICAL
MICROBIOLOGY LABORATORIES
Standardization
Although innovative and greatly informative, many initial studies
using MALDI-TOF MS were limited in scope and lacked data-
bases, standardized reagents, and protocols for the analysis of in-
tact bacterial cells. Many early investigations found that the spec-
tra generated from microorganisms exhibited a high degree of
variation under different culture conditions and among studies
performed in different laboratories (33). Early databases utilized
for microbial identification and characterization by MALDI-TOF
MS were often developed “in-house” to fit the needs of the labo-
ratory responsible for their design (34) and thus contained a high
percentage of organisms from strain collections of individual in-
vestigators, making comparisons between the results from differ-
ent laboratories difficult. While in-house databases are still con-
structed and provide valuable information toward more
discriminatory analysis (i.e., serotype, subspecies, and epidemio-
logical analyses), routine analysis is generally performed by using
proprietary databases marketed with commercial MALDI-TOF
MS systems.
Following the publication of conflicting results in some early
investigations, the issue of standardization was preliminarily ad-
dressed with regard to bacterial culture conditions (35), MS con-
ditions (36, 37), and preanalytical processing (34, 38). Addition-
ally, a shift in analytical focus away from bacterial surface
components (39), which can vary in levels of expression under
different culture conditions, toward the analysis of ribosomal pro-
teins that are ubiquitously expressed throughout all phases of
growth added to the stabilization and robustness of the generated
spectra and supported enhanced analytical capabilities. The adap-
tation of these defined methods sharply reduced the variation
among spectral profiles of isolates being analyzed, vastly improv-
ing the accuracy and reliability of MALDI-TOF MS for bacterial
identification in inter- and intralaboratory evaluations (12).
Evolution of Intact-Cell MALDI-TOF MS
Early studies evaluating the use of MALDI-TOF MS for microbial
identification focused on the ability of the technology to accu-
rately determine the identity of whole microorganisms isolated
from agar-based culture. MALDI-TOF MS provided the capabil-
ity to eliminate protein extraction methods prior to analysis, al-
lowing intact microorganisms to be simply spotted onto a solid
plate and mixed or overlaid with a matrix compound and cocrys-
tallized, which facilitates the dissociation and ionization of bacte-
rial proteins (40, 41). The intact-cell (IC) method, as it is some-
times called, provided a new and simple mechanism for rapid
analysis of bacterial components based on the generation of spe-
cific spectral fingerprints that facilitated accurate microbial iden-
tification and characterization (19, 41, 42).
Due to the simple mechanism of sample preparation, IC MS
became an attractive alternative to phenotypic and genetic meth-
ods of microorganism identification. Several preliminary studies
supported the observation that IC MALDI-TOF MS was indeed
sensitive enough to differentiate closely related organisms (43)
and perhaps even discriminate between different strains of the
same or phenotypically similar organisms (44–46), providing new
avenues for genus-, species-, and strain-level identifications.
However, as analysis of microorganisms by MALDI-TOF MS be-
came more commonplace, it became apparent that the IC method
was not always appropriate for all specimen types in spite of its
relative simplicity; problems with spectral generation from some
microbes (47, 48) and biosafety issues (49, 50) arose. In an effort to
improve spectral generation and be compliant with biosafety reg-
ulations, modified versions of sample preparation methods have
been reported for different groups of microorganisms and range
from on-plate inactivation using formic acid (FA) and matrix to
full-scale protein extraction using ethanol-based methods (Fig. 3).
CURRENTLY AVAILABLE COMMERCIAL PLATFORMS FOR
MALDI-TOF MS IDENTIFICATION OF MICROBES
Multiple platforms from a number of well-established commer-
cial manufacturers are available for MALDI-TOF MS identifica-
tion of bacteria and yeast. Spectral databases are often marketed as
part of a proprietary system, as opposed to a publicly accessible
open platform, and are constructed and maintained by their rep-
resentative manufacturers. A majority of these databases can be
expanded to accommodate spectral entries that are not included
in marketed versions. The ability to add spectra and construct
custom databases is important for further discriminatory analysis
using MALDI-TOF MS, including strain typing and epidemiolog-
ical investigations. As each proprietary system uses its own algo-
rithms, databases, software, and interpretive criteria for microbial
identification, numerical data (i.e., spectral scores) from different
commercial systems are not directly comparable (51). Compara-
tive analysis between MS systems is therefore usually performed
by using final identifications in the context of each system’s inter-
pretive algorithms. In this section, MS platforms from different
Clark et al.
554 cmr.asm.org Clinical Microbiology Reviews
FIG 3 Additional suggestions for MALDI-TOF MS sample preparations for use with different classes of microbes. Different groups of microorganisms
vary fundamentally in their cellular composition and architecture. These differences have been demonstrated to affect the quality of spectra generated
during MS experiments and, thus, the accuracy of MALDI-TOF MS-derived identifications. As such, investigators from a number of independent studies
have evaluated different methods for sample preparation of different groups of microorganisms, ranging directly from intact-cell to full-protein-
extraction-based methodologies. Results from these studies are summarized here. Proper biological safety precautions should be followed with respect to
dangerous members of these groups of organisms.
MALDI-TOF Mass Spectrometry in Clinical Microbiology
July 2013 Volume 26 Number 3 cmr.asm.org 555
manufacturers are reviewed, and data from investigations exam-
ining their ability to identify microbes in clinical settings are sum-
marized.
Andromas
The Andromas system is a database manufactured and main-
tained by Andromas SAS (Paris, France). Utilized predominantly
for clinical diagnostics in Europe, the database is available in
North America for research use only. The Andromas system uses
multiple species-specific spectral profiles for each organism in the
database to increase the robustness of identification. These spectra
are derived from either members of the same strain of bacterium
with divergent spectral profiles or the same bacterium cultured on
different types of growth media. The software separates entries
into three separate databases dedicated to the identification of
bacteria, mycobacteria, yeasts, and Aspergillus spp. When con-
structed, this database was populated with spectra generated from
direct-colony ionization only, with protein extraction not being
performed (52). Sample results are reported as a percentage of
similarity between the spectra generated by the microorganism in
question and the reference spectra that are in the database. Iden-
tifications made by Andromas are then grouped into one of three
categories, “good identification,” “identification to be con-
firmed,” and “no identification,” based upon statistical cutoff val-
ues determined by the manufacturer and by the operator.
The current and earlier iterations of Andromas were utilized in
a number of studies for the identification of both bacteria and
yeast from culture media (53–55) as well as directly from patient
specimens (53, 56). Limitations of the Andromas database have
been highlighted by Bille et al. Discrimination between species
that are closely related is problematic, a shortcoming experienced
by a number of MS and non-MS methods alike. Of particular
interest was the noted inability of the database to differentiate
Streptococcus pneumoniae from Streptococcus mitis, Escherichia coli
from Shigella, and Listeria monocytogenes from Listeria innocua
and Listeria ivanovii. In these cases, the authors used additional
downstream testing, in many cases utilizing serum agglutination
assays, to identify the bacteria of interest (53). Farfour et al. addi-
tionally evaluated a set of 659 Gram-positive rods by using Andro-
mas and compared these identifications to identifications derived
by reference methods. The database performed well but still ex-
hibited problems in providing species-level identifications for
members of Listeria spp. (52) despite the reported ability of other
commercial databases to discriminate between Listeria spp. by
incorporating a protein extraction method (57).
SARAMIS Evolves to Vitek-MS
The SARAMIS database was previously created and maintained
by AnagnosTec GmbH prior to being purchased by bioMérieux
for incorporation into the Vitek-MS platform. Prior to its in-
tegration into the Vitek-MS platform, the database was mar-
keted and sold by Shimadzu along with Axima mass spectrom-
eters as the Axima-iD Plus system, which featured linear/
reflectron combinations and high-energy collision-induced
dissociation modes, allowing for greater resolution and greater
mass accuracy than simple linear ion mode analyzers The da-
tabase uses SuperSpectra, which contained a conglomerate of
biomarkers from at least 15 individual isolates, indicative of
specific genera, species, and strains from a variety of geograph-
ical locations. These spectra were obtained following variations
in growth conditions and growth media, generating a robust
diagnostic for microbial identification. Spectra that are gener-
ated are consolidated into a list of peaks and intensities, which
is then queried against the database to identify potential
matches with archived SuperSpectra. If no statistically satisfac-
tory match can be obtained, an expanded database containing a
broader collection of spectral information is then queried in
order to generate identification. The software is also able to
perform hierarchical analysis of the spectral data to examine
changes in a population of similar microorganisms, determine
relatedness of different isolates, and generate additional
SuperSpectra for in-house database expansion (Axima-iD Plus
brochure [http://www.ssi.shimadzu.com/products/literature
/biotech/mo347_v1.pdf {accessed 19 April 2013}]). Following
acquisition of SARAMIS by bioMérieux, the manufacturers de-
veloped their own algorithms for MS-based microbial identifi-
cation and have begun marketing the database and associated
software and hardware under the name Vitek-MS (51).
BioTyper
The BioTyper system was conceived and marketed exclusively by
Bruker Daltonics and is capable of analyzing specimens including
bacterial, mycobacterial, and fungal samples in addition to sam-
ples recovered directly from positive blood culture bottles. Of all
the mass spectral analysis software programs, the BioTyper plat-
form is perhaps the most heavily utilized software package in the
United States. The software is marketed as a versatile tool for the
clinical microbiologist, including both options for batched speci-
mens and the ability to interrupt routine runs for the analysis of
specimens whose results are urgently needed as well as automatic
calibration and integration into existing laboratory information
systems. The BioTyper software package is currently sold along
with the Flex line of benchtop MALDI mass spectrometers.
Like other software systems discussed above, the BioTyper soft-
ware is an open platform allowing the user to save runs to expand
the database of stored spectra by utilizing tools included in the
software. Mass spectra are generated, and data are analyzed with
regard to spectrum peak frequency, position, and intensity. These
spectra are then compared against a library of main spectra en-
coded in the BioTyper database. These main spectra are derived
again from replicative measurements of the type strain with the
goal of generating representative spectra of the organism across a
range of biological variables. The user also has the ability to create
main spectra with the assistance of the software and to populate
the database with entries derived from microorganisms isolated
in-house.
Two distinct criteria are used to analyze the results of the spec-
tral database search: a score value and a consistency category. Log
score values range from 0.000 to 3.000 and are correlated with an
explanation of genus and species consistency within the database.
A score ranging from 2.3 to 3.000 is interpreted by the software as
a highly probable species-level identification. Log scores of be-
tween 2.00 and 2.299 represent secure genus identification and
probable species-level identification. In both cases, the results can
usually be released as a positive identification pursuant to the test-
ing algorithms implemented in the laboratory performing the
testing. Log scores ranging from 1.70 to 1.999 represent a probable
genus identification, with additional testing being required for a
positive reportable identification. Log scores ranging from 1.699
to 0 are not considered to be a reliable identification, and further
Clark et al.
556 cmr.asm.org Clinical Microbiology Reviews
sample processing, analysis, and testing are warranted (MALDI
BioTyper brochure [http://maldibiotyper.com/literature.html
{accessed 10 June 2013}]).
PERFORMANCE AND COMPARISON OF COMMERCIAL
METHODS IN ROUTINE CLINICAL MICROBIOLOGY
MALDI-TOF MS is an accurate method for routine bacterial iden-
tification, even with changing conditions such as culture medium
or pH, and interlaboratory comparison is usually good, provided
that minimal common reagents are used (35, 58–60). Most errors
in published reports are attributed to an incomplete population of
databases associated with the instruments, clerical error in data-
base assembly or during data acquisition, or an inability of the MS
spectra to differentiate similar species.
Seng et al. were the first to report the feasibility of MALDI-TOF
MS as the first-line system for routine bacterial identification in
clinical microbiology laboratories using bacterial colonies grow-
ing on agar plates (61). A total of 1,660 bacterial isolates were
identified, and discrepancies between the MALDI-TOF MS results
were verified via gene sequencing. At that time, the authors cor-
rectly identified only 84.1% of isolates to the species level by a
direct analysis of bacteria without additional protein extraction.
Stenotrophomonas maltophilia and Shigella sonnei were frequently
misidentified (7/10 [70%] 5/5 [100%] isolates, respectively). In
the case of S. maltophilia, false identification resulted because the
references of Pseudomonas hibiscicola and Pseudomonas beteli en-
tered into the BioTyper database are actually S. maltophilia. Most
of the other unidentified species were absent from the database at
the time of study.
In the first comparison of two commercially available systems
for clinical laboratory use, Cherkaoui et al. compared the Bruker
BioTyper and bioMérieux systems with their respective databases,
BioTyper and an early version of SARAMIS (62). In this study, 16S
rRNA gene sequencing was used as the gold standard for compar-
ison. Using these systems, 720 clinical isolates were identified to
the species level. Of these, 99.1% were identified with the Bruker
MALDI-TOF MS spectrometer and 88.8% were identified with
the Shimadzu MALDI-TOF MS spectrometer (of note, this data-
base was comprehensively revised since that report). Not surpris-
ingly, anaerobes were among the species most frequently not iden-
tified, probably due to the lack of reference spectra in the
databases. As in nearly all other studies, poor identification of
streptococci was observed, with an identification rate of 41% with
both systems. Mellmann et al. identified 1,116 clinical isolates by
MALDI-TOF MS using the same database and using manual and
automated phenotypic methods as the reference standard with
16S rRNA gene sequencing for discrepant testing; for Enterobac-
teriaceae, nonfermenting Gram-negative rods, staphylococci, en-
terococci, and streptococci, they achieved correct identifications
to the species level for 95.5, 79.7, 99.5, 100, and 93.7% of isolates,
respectively (12). Shigella spp. and Streptococcus mitis/Streptococ-
cus oralis were misidentified by MALDI-TOF MS, with 0/7 and 0/6
correct identifications, respectively. In contrast, correct identifi-
cation was obtained for staphylococci, enterococci, and Entero-
bacteriaceae; correct identifications to the species level for 100,
95.7, and 83.2% of isolates, respectively, were reported (63).
van Veen et al. reported similar results for 980 clinical micro-
bial isolates, including 61 yeast isolates; the overall identification
rate at the species level was 92%. After identification was verified
by using 16S rRNA gene sequencing in cases of discrepancies be-
tween MALDI-TOF MS-based identification and biochemical
identification, correct identifications were obtained at the species
level for Enterobacteriaceae, nonfermenting Gram-negative rods,
staphylococci, streptococci, and yeasts for 97.7, 92, 94.3, 84.8, and
85.2% of isolates, respectively (64). Misidentifications were asso-
ciated with a lack of spectra for some rare species and problems in
identification of viridans group streptococci (VGS) and S. pneu-
moniae; 12/21 (57.1%) isolates of viridans group streptococci
were falsely identified as S. pneumoniae.
In another study, Prod’hom et al. reported correct identifica-
tion of 1,278/1,371 clinical isolates (93.2%) to the species level
(65). The 56 discordant results were analyzed, and most errors
were due to false identification of Enterobacter cloacae as Entero-
bacter hormaechei and S. maltophilia as Pseudomonas hibiscicola
and Pseudomonas beteli. Problems with identification of Shigella
spp. and Propionibacterium acnes were also observed. In another
study, the same limitations of the database were also observed for
the identification of some species, including anaerobic bacteria;
the authors proposed that an extraction step may be necessary to
improve identification of some species (66). The identification
level improved from 82.6 to 97.3% when an extraction step was
added.
Finally, Martiny et al. compared the three commercial data-
bases, including the first report of the database planned for in vitro
diagnostics (IVD) use supported by Vitek-MS (bioMérieux). In
this study, 1,129 isolates were examined, including 73 anaerobes.
The Bruker LT BioTyper and the Vitek-MS databases performed
equally well, with correct identification of 93% of routine isolates
(67).
COMPARISONS BY MICROBE CATEGORY
With the introduction of any new technology for clinical diagnos-
tics, comprehensive reviews are undertaken to evaluate the
method against methods currently used as reference standards to
determine reproducibility, accuracy, and robustness. MALDI-
TOF MS is no exception, as a myriad of studies have appeared in
the literature in the past 5 years examining the diagnostic accuracy
of the method against phenotypic and molecular methods such as
sequencing-based approaches, Vitek 2 and API-based methodol-
ogies, and serological approaches. The focus of this section is to
highlight and summarize key findings from this large repertoire of
studies in the hopes of providing a comprehensive examination of
the dynamic clinical utility of MALDI-TOF MS for the identifica-
tion of specific groups of microbes as well as to explore the ability
of the technology and its uses for specialized testing pertaining to
specific microbial genera. Published reports of MALDI-TOF ac-
curacy for a wide variety of microbes are listed in Table 4.
GRAM-POSITIVE BACTERIA
Gram-positive bacterial species include a large number of patho-
genic bacteria both frequently and infrequently encountered in
the clinical laboratory. In general, these organisms possess large
quantities of peptidoglycan at their cell wall, which is used for the
display of a number of surface proteins involved in adhesion to
and interaction with host tissues. This thick layer of peptidoglycan
can sometimes render these bacteria more resistant to lysis than
their Gram-negative counterparts, and a number of pretreatment
or enhancement strategies were devised to counteract this, includ-
ing the addition of lysostaphin, lysozyme, mutanolysin, and pro-
teinase K to bacterial suspensions.
MALDI-TOF Mass Spectrometry in Clinical Microbiology
July 2013 Volume 26 Number 3 cmr.asm.org 557
In a thorough and well-designed study, Alatoom et al. de-
scribed the comparison of the application of whole cells (direct
colony) to protein extraction for the identification of Gram-pos-
itive cocci using the Bruker BioTyper software. A significant im-
provement in the number of isolates able to be identified to both
the genus and species levels was seen when protein extraction with
FA was performed prior to analysis (68).
The Andromas MALDI-TOF MS system was evaluated for the
routine identification of Gram-positive bacilli. In a comprehen-
sive analysis of 659 isolates, Farfour et al. reported that 594
(98.5%) of these isolates could be identified to the species level,
with most members of the genus Listeria unidentifiable beyond
the species level due to spectral peak similarity. MALDI-TOF MS
was reported to perform as well as routine identification mecha-
nisms supplemented with extended diagnostic techniques that
would have been needed to definitively identify some bacterial
isolates within the collection (52), thus demonstrating savings of
both time and resources.
Sample Processing for Identification of Gram-Positive
Bacteria by MALDI-TOF MS
The processing of Gram-positive isolates for routine identification
by MALDI-TOF MS was recently evaluated. Sample processing
for Gram-positive organisms included the application of both
whole cells as well as a protein extraction step prior to analysis. In
place of a time-consuming full protein extraction, TeKippe et al.
investigated a method using a 1-l fluoroacetic acid (FA) overlay.
Four different smearing methods were compared with respect to
plate processing: heavy and light smears of bacterial culture with
and without an overlay of FA added to that respective smear. Us-
ing the Bruker BioTyper 3.0 software, 239 aerobic Gram-positive
clinical isolates were analyzed, and results were compared to pre-
viously obtained phenotypic identifications; discrepant results
were resolved by 16S rRNA gene sequencing. Results of this study
conclusively determined that the modified FA addition signifi-
cantly enhanced identification compared to the use of whole cells.
Other important conclusions included the finding that frequent
passaging of organisms led to an increase in the number of un-
identified isolates but that incubation temperature and medium
type (blood, chocolate, etc.) did not influence MALDI-TOF MS
identification (69).
In conclusion, while more labor-intensive, protein extraction
prior to MALDI-TOF MS analysis consistently increases the abil-
ity of the technology to identify Gram-positive species. The mod-
ified FA extraction procedure described by TeKippe et al. repre-
sents a viable alternative more suited to routine clinical workflow,
but full protein extraction may still need to be utilized in cases
where the microbe is particularly difficult to process (69). Addi-
tionally, while commercial software databases were demonstrated
to be suitable for routine clinical use, the results of Christensen et
al. highlight the importance of a continuously evolving collection
of reference spectra in addition to members of the clinical labora-
tory becoming familiar with methods of in-house generation of
spectral collections for the identification of uncommon species
not currently contained within commercial databases (70).
Staphylococci
The staphylococci represent a genus of bacteria commonly en-
countered in the clinical microbiology laboratory in a wide variety
of specimen types. Like other bacterial genera, certain species of
TABLE 4 Genus-specific studies utilizing MALDI-TOF MS for bacterial
identification and characterization
Genus Species or group evaluated Reference(s)
Gram-positive organisms
Staphylococcus Coagulase-negative staphylococci 75, 79, 80
S. aureus 44, 81–86, 88, 97
Coagulase positive, non-S. aureus 89
Mixed staphylococcal species 55, 90, 91
Micrococcus Micrococcus spp. 94
Streptococcus Beta-hemolytic species 45, 99
Group A streptococci 101
Group B streptococci 103, 104
Streptococcus pneumoniae 105
Viridans group streptococci 112, 113
Nutritionally variant streptococci 70, 118
Enterococcus Enterococcus spp. 122, 123
Lactococcus Lactococcus spp. 128
Bacillus Bacillus spp. 129–131
Listeria Listeria spp. 57
Corynebacterium Corynebacterium spp. 133–135
Arcanobacterium/Trueperella Trueperella spp./A. haemolyticum 136, 137
Nocardia/mycobacteria
Nocardia Nocardia spp. 48
Mycobacterium Mycobacterium spp. 46, 152–156
Gram-negative bacteria
Enterobacteriaceae
Salmonella Salmonella spp. 161–165
Escherichia/Shigella E. coli/Shigella spp. 167
Cronobacter Cronobacter spp. 173–176
Enterobacter Enterobacter cloacae complex 177
Pantoea Pantoea spp. 178
Plesiomonas P. shigelloides 179
Klebsiella/Raoultella K. oxytoca/Raoultella spp. 180
Yersinia Yersinia spp. 181–183
Y. enterocolitica 184
Y. pestis/Y. pseudotuberculosis 185
Nonfermenting rods
Acinetobacter Acinetobacter 190–194
Burkholderia B. cepacia complex 187, 198, 199
B. mallei/B. pseudomallei 204, 205, 207
Pseudomonas Pseudomonas spp. 208
Stenotrophomonas Stenotrophomonas maltophilia 209
Fastidious organisms
Brucella Brucella spp. 211, 213
Bartonella Bartonella spp. 214
Francisella Francisella spp. 215, 216
Haemophilus Haemophilus spp. 217, 220
Vibrio Vibrio spp. 221–223
Aeromonas Aeromonas spp. 224–227
Campylobacter Campylobacter spp. 228–233
Helicobacter Helicobacter spp. 228, 231, 234, 235
Neisseria Neisseria gonorrhoeae/N.
meningitidis
234, 236, 237
Moraxella Moraxella catarrhalis 238
Legionella Legionella spp. 239–242
Anaerobic bacteria
Propionibacterium P. acnes 256
Bacteroides Bacteroides spp. 244, 257
Clostridium Clostridium spp. 258
C. difficile 261
Fungi
Yeasts
Candida Candida spp. 264, 210, 266–269
Cryptococcus Cryptococcus spp. 271–273
Filamentous fungi/molds
Aspergillus Aspergillus spp. 277–280
Fusarium Fusarium spp. 281–283
Dermatophytes 286–289
Pseudallescheria-
Scedosporium
Pseudallescheria-Scedosporium 291
Penicillium Penicillium spp. 292
Lichtheimia Lichtheimia spp. 295
Clark et al.
558 cmr.asm.org Clinical Microbiology Reviews
staphylococci are more commonly associated with disease than
others, so accurate identification of these microorganisms to the
species level often aids in making a distinction as to whether they
are clinically relevant, normal flora, or culture contaminants.
Compared to other bacterial genera, staphylococcal taxonomy re-
mains generally straightforward due to the clonal nature of the
organism. For most specimen sources, determination of major
distinctions between species can be accomplished in an acceptable
time frame by using traditional biochemical methods; however,
for body fluids, blood cultures, and tissues, additional testing is
sometimes necessary. Staphylococci cultivated from these nor-
mally sterile body sites or from an immunocompromised host are
increasingly known to cause infections (71–74); therefore, they
may require highly accurate species-level identification to rule out
contamination by skin flora. Some less frequently encountered
staphylococcal species can bear phenotypic similarities to more
commonly encountered species (i.e., coagulase activity) or share
significant genetic similarity, which can result in misidentification
by phenotypic and molecular methods, respectively.
Coagulase-negative staphylococci. Coagulase-negative staph-
ylococci (CoNS) are among the most frequently isolated bacteria
in clinical microbiology laboratories (75) and are important op-
portunistic and device-related pathogens. The organisms are well
equipped for this niche, by virtue of their capacity to produce
strong biofilms, allowing them to persist in various environments
and develop increased resistance to antibiotics (76). In addition,
the group maintains a large number of molecules that function to
provide protection from the defenses of the host immune system
(77). The term “coagulase-negative staphylococci” is somewhat a
collective grouping commonly reserved for nonhemolytic staph-
ylococcal species which are not Staphylococcus aureus; however,
this group also includes a small number of other coagulase-posi-
tive, non-S. aureus staphylococci. As such, the group is populated
with a large number of species, many of which share significant
genetic and phenotypic homology, rendering definitive identifi-
cation challenging. The correct species determination of CoNS
can be particularly difficult due to a high degree of genetic simi-
larity between species, and phenotypic tests for identification do
not always provide reliable results (78).
Currently, a number of methods are used to identify coagulase-
negative staphylococci, including both phenotypic (RapID 32)
and molecular (tufB and sodA sequencing) assays. Molecular
methods were utilized for the characterization of CoNS, with
identifications being made on the basis of housekeeping gene se-
quencing or 16S rRNA sequencing. Automated bacterial identifi-
cation systems have also been used to identify CoNS, but molec-
ular methods are often preferred due to higher levels of
discriminatory accuracy for determinative identification to the
species level.
MALDI-TOF MS has been compared to automated pheno-
typic bacterial identification systems for the identification of
CoNS. Dupont et al. compared MALDI-TOF MS linked to a con-
structed database to the Phoenix (Becton, Dickinson) and Vitek-2
(bioMérieux) systems for the identification of 234 CoNS (20 spe-
cies total) isolates from clinical laboratories, using the sequence of
the superoxide dismutase gene sodA as a reference. In all, MALDI-
TOF MS identified 93.2% of isolates correctly, with only 75.6%
and 75.2% of isolates being correctly identified with the Phoenix
and Vitek-2 systems, respectively (75). A second study, this time
using the BioTyper 2.0 software in place of an in-house database,
analyzed MALDI-TOF MS compared to tuf gene sequencing for
the identification of 62 CoNS reference isolates to the species level.
All isolates were identified to the species level, demonstrating
100% concordance with tuf gene sequencing for CoNS identifica-
tion (79).
In perhaps one of the most conclusive comparisons of pheno-
typic, molecular, and proteomic methodologies for the identifica-
tion of coagulase-negative staphylococci to date, Loonen et al.
compared the Vitek-2 and RapID 32 phenotypic methods for CoNS
to two different sequencing methods (tuf and 16S rRNA gene se-
quencing) and MALDI-TOF MS using the Bruker BioTyper data-
base. The results of this study determined that the MALDI-TOF MS
platform had a 99.3% correct identification rate when a collection of
142 strains consisting of both clinical and reference isolates was ana-
lyzed. The Vitek-2 system used in combination with tuf gene se-
quencing was suggested by those authors to be a suitable alternative
for laboratories without access to MALDI-TOF MS, an approach
which would result in additional time to definitive diagnosis and
higher cost to the patient (80). In summary, MALDI-TOF MS dem-
onstrates high diagnostic accuracy for CoNS and allows for a simple,
rapid, and cost-effective mechanism for identification of CoNS.
Staphylococcus aureus. In contrast to CoNS, Staphylococcus
aureus, the predominant pathogenic species from the genus
Staphylococcus, is routinely identified with high accuracy in labo-
ratories using long-established and well-standardized phenotypic
protocols; however, misidentifications can occur, typically con-
fused with coagulate-positive non-S. aureus species. Perhaps the
more pressing clinical challenge posed by S. aureus isolates is not
their identification per se but the determination of antimicrobial
resistance (i.e., methicillin-resistant S. aureus [MRSA] versus me-
thicillin-sensitive S. aureus [MSSA]) and the identification of cer-
tain clonal lineages in outbreak situations.
Automated methods are available to determine antimicrobial
susceptibility patterns for S. aureus but often require additional
time for the cultivation of the organism in the presence of the
antibiotic. Rapid protocols for the determination of methicillin
resistance were developed for S. aureus and are usually based upon
the detection of a variety of targets, including the mecA gene prod-
uct, the penicillin binding protein PPB2a, via slide agglutination
(Oxoid PBP2= latex agglutination test; Thermo Fisher), detection
of S. aureus-specific bacteriophage via the KeyPath MRSA/MSSA
Blood Culture Test-BT (Microphage, Longmont, CA), or detec-
tion of the staphylococcal cassette chromosome mec (SCCmec)
genetic element insertion site via real-time PCR (Cepheid, Sunny-
vale, CA, and Becton, Dickinson, Franklin Lakes, NJ). Methods
for the genetic typing of S. aureus isolates rely on molecular ap-
proaches that are costly, labor-intensive, highly complex, and
variable and, as such, are not performed in all laboratories.
While accurate genus and species identification of S. aureus can
be accomplished by MALDI-TOF MS systems, other aspects of S.
aureus characterization by MALDI-TOF MS are being investi-
gated in research settings. In 2000, MALDI-TOF MS spectral
peaks specific for different species of staphylococci and methicil-
lin-resistant isolates were identified (81). By 2002, three indepen-
dent studies utilizing MALDI-TOF MS for the analysis of S. aureus
were published (82–84).
Using two type strains of S. aureus, one MRSA and one MSSA,
and a number of clinical isolates of S. aureus, one study analyzed
the use of MALDI-TOF MS for identifying and discriminating
between different S. aureus strains. It was concluded that stable,
MALDI-TOF Mass Spectrometry in Clinical Microbiology
July 2013 Volume 26 Number 3 cmr.asm.org 559
strain-specific spectra could be derived from the two type strains,
which could be used for both identification and clonal analysis of
the clinical isolates, but a uniform profile could not be elucidated
for S. aureus (82).
Another study, utilizing 76 organisms identified as S. aureus by
the Vitek system (bioMérieux, Durham, NC) and nuc gene PCR,
reported that only 74% of these organisms could be identified by
MALDI-TOF MS and the MicrobeLynx software package as S.
aureus. The determination of methicillin resistance was also eval-
uated by MALDI-TOF MS, with varied results. Potential explana-
tions for the low accuracy of the MALDI-TOF MS identification
were listed as the incompleteness of the database and variation in
bacterial culture conditions used during the course of the study
(83).
Once MALDI-TOF MS was determined to be a viable technol-
ogy for the characterization and analysis of S. aureus, studies ex-
amining the reproducibility and standardization of testing meth-
odologies were undertaken. An inter- and intralaboratory
reproducibility study of MRSA strains determined that variation
of culture media used for propagation of S. aureus generated dif-
ferent spectral profiles but found that the variation among mass
spectrometers from different manufacturers was negligible, and it
was concluded that MALDI-TOF MS provided a rapid method for
the identification of MRSA (84). Three years later, the same group,
working with scientists from the mass spectrometer manufacturer
Shimadzu, reported a detailed optimized protocol for MALDI-
TOF MS fingerprinting of MRSA, including incubation periods,
bacterial passage analysis, preparation times, and mass spectrom-
eter settings, among other variables (44).
As MALDI-TOF MS accuracy and sensitivity improved, addi-
tional studies investigating its use for the characterization of S.
aureus were reported, with more complex aims outside the realm
of bacterial identification. One study focused on antibiotic resis-
tance and strain heterogeneity and demonstrated that MALDI-
TOF MS was suitable to characterize a small set of isogenic isolates
of MRSA and spontaneously arising MSSA isolates with different
susceptibility results for the glycopeptide antibiotic teichoplanin.
Interestingly, these isolates were considered identical by pulsed-
field gel electrophoresis (PFGE) analysis, highlighting the dis-
criminatory power of MALDI-TOF MS (85). A high-throughput
study using 134 clinical isolates of S. aureus confirmed by 16S
rRNA gene sequencing and an expanded database (MicrobeLynx)
of spectral profiles also demonstrated the high accuracy of
MALDI-TOF MS for the identification of S. aureus but advocated
for the further standardization of culture and diagnostic parame-
ters. These authors were unable to identify unique spectral mark-
ers for MRSA, in contrast to previous reports (86).
Finally, a large sample set of 602 molecularly defined S. aureus
and 412 CoNS isolates was used to assess the accuracy of BioTyper
2.0 to identify these isolates to the species level. MALDI-TOF MS
performed well for all isolates tested, with 100% concordance with
sodA or tufB sequencing for the identification of CoNS and with a
mean time to result of 22 min (87). The ability of MALDI-TOF MS
to identify MRSA lineages from ionized samples has also been
investigated, demonstrating the ability of mass spectrometry to
organize isolates into groups with high concordance compared to
the clonal complex (CC) classifications routinely used for MRSA
characterization (88). These studies demonstrate the utility of
MALDI-TOF MS and its ability to not only accurately and rapidly
identify S. aureus isolates but also potentially classify and provide
valuable epidemiological data for MRSA isolates.
Non-S. aureus, coagulase-positive staphylococci. Although
the presence of coagulase is conventionally believed to be a hall-
mark of S. aureus, other staphylococcal species do indeed produce
this enzyme and can exhibit positive results for both slide and tube
coagulase as well as protein A and staphylococcal latex. Staphylo-
cocci belonging to the Staphylococcus intermedius group (S. inter-
medius, S. pseudintermedius, and S. delphini) share many bio-
chemical similarities with S. aureus, including coagulase
production, which can hamper identification when encountered
in the clinical laboratory. Molecular methods are the most reliable
mechanism for identification of these staphylococci, but not all
clinical laboratories have on-site access to sequencing instru-
ments.
An important analysis of staphylococci belonging to the S. in-
termedius group was recently reported (89). Using the Shimadzu
instrument and the SAMARIS database, reference spectra (Super-
Spectra) were created based on unique peaks present for each
species. Sixty-nine strains were analyzed, and reference identifica-
tion was performed by using the hsp60 gene sequence. Using the
constructed database, MALDI-TOF MS demonstrated 95% sensi-
tivity and 100% specificity for S. intermedius identification (95%
confidence interval [CI], 0.68 to 0.99), 78% sensitivity and 97%
specificity for S. pseudintermedius (95% CI, 0.60 to 0.90), and 64%
sensitivity and 100% specificity for S. delphini (95% CI, 0.41 to
0.83), demonstrating a relatively reliable method for identifica-
tion of S. intermedius group staphylococci, with some improve-
ment being warranted for S. pseudintermedius and S. delphini.In
this case, MALDI-TOF MS may be utilized as a confirmatory
mechanism to differentiate different coagulase-positive staphylo-
cocci when S. aureus is not suspected.
Testing of clinical samples for mixed staphylococcal species.
A number of studies have examined the use of MALDI-TOF MS
for the identification of multiple species of staphylococci simulta-
neously in clinical samples. Multiple clinical laboratory investiga-
tions comparing MALDI-TOF MS identifications to various mo-
lecular and phenotypic methods for the identification of both
coagulase-positive staphylococci and CoNS were reported. By
identifying unique peaks in the spectra of reference strains belong-
ing to the family Micrococcaceae, a database was constructed and
queried to identify a set of 196 staphylococcal clinical isolates that
had previously been identified to the species level by both pheno-
typic (coagulase and agglutination, etc.) and molecular (sodA se-
quencing) testing. In all cases, the generated MALDI-TOF MS
spectra best matched the spectra of the reference organism of the
same species (55). In another study of 450 staphylococcal isolates
from blood cultures, representing 18 species, MALDI-TOF MS
and the BioTyper 2.0 database were compared to rpoB sequencing
for the identification of staphylococci to the species level. MALDI-
TOF MS identified 99.3% (447/450) of isolates correctly to the
species level and correctly identified all subspecies included in the
study. Also, using the BioTyper 2.0 database, a third study of 152
staphylococcal isolates consisting of 22 species reported 99.3%
agreement (151/152) with the StaphArray microarray-based
staphylococcal identification system and identified clonal lineages
among environmental and clinical isolates (90).
Conversely, using an early version of the SAMARIS database, a
collection of 186 strains consisting of 35 species and subspecies of
staphylococci of human and animal origins was compared to se-
Clark et al.
560 cmr.asm.org Clinical Microbiology Reviews
quencing of the tuf and gap genes for identification. In this study,
81.5% of identifications made by the MALDI-TOF MS were cor-
rect, compared to 98.9% of isolates identified correctly by tuf se-
quencing (91). Importantly, a database of 47 type strains was used
to analyze sequence data, exceeding the number of entries present
in the SAMARIS database at that time. Those authors rightfully
noted that of the 45 known staphylococcal species and 21 subspe-
cies, only half were cultured from human specimens. Those
authors further elaborate, citing that although the SAMARIS
database contains 38 species and subspecies, only 15 have Super-
Spectra, which appears to be a requirement for reliable identifica-
tion of staphylococci. This example demonstrates that complete-
ness of the database is paramount to the ability of MALDI-TOF
MS to correctly identify culture isolates; therefore, expansion of
current commercially available databases is warranted to provide
broader coverage of the Staphylococcus genus, including opportu-
nistic veterinary pathogens (91).
Micrococci
Similar to CoNS, the identification of micrococci also presents a
situation where an important determination must be made to
categorize the isolate as either clinically relevant or a contaminant
from the skin microflora. In a majority of cases, micrococci are
considered to be culture contaminants that are not clinically sig-
nificant; however, reports of micrococci causing serious, life-
threatening infections, particularly among patients with intravas-
cular devices (92, 93), are present in the literature. Despite the
high frequency at which these organisms are encountered in the
microbiology laboratory, identification to the genus level is gen-
erally sufficient for micrococci, and species-level identification is
rarely performed. Micrococci are often reliably differentiated
from staphylococci by virtue of the performance of a modified
oxidase (microdase) test. With respect to MALDI-TOF MS, Mi-
crococcus spp. are able to be reliably identified by using the Bio-
Typer software. In a study of environmental micrococci, isolates
were identified correctly to the genus level, but no species-level
identification could be reached due to limited entries in the data-
base (94). It is likely that with the appropriate database, species-
level discriminations could be made when necessary.
Staphylococci and MALDI-TOF MS: Future Uses and
Implications
The implementation of MALDI-TOF MS systems in microbiology
laboratories will change the way in which staphylococci are iden-
tified when isolated in routine culture and will provide physicians
and researchers with more information about CoNS and their
roles in human infections. One ongoing problem encountered by
clinical laboratories is the identification of CoNS to the species
level. As reported in the above-mentioned studies (75, 79),
MALDI-TOF MS provides an excellent tool for the accurate and
rapid identification of CoNS species and can potentially supplant
labor-intensive and high-complexity molecular testing, thus in-
creasing in-house capabilities and allowing information to be pro-
vided to physicians in a more timely manner. As more laboratories
opt for identification of CoNS to the species level, clinical re-
searchers can better define the impact of these important oppor-
tunistic pathogens. While other mass spectrometry-based systems
can provide epidemiological data to group MRSA isolates into
clonal complexes (88, 95), further investigations are warranted to
determine if MALDI-TOF can be used to provide simultaneous
identification and epidemiological data.
Although a powerful tool for bacterial analysis, the use of
MALDI-TOF MS generates some controversy regarding the char-
acterization of S. aureus susceptibility to antibiotics. There are
conflicting reports describing the ability of MALDI-TOF MS to
discriminate MRSA from MSSA (44, 84, 86), making strain char-
acterization an important area of interest for clinical microbiolo-
gists, physicians, and pharmacists. By providing a mechanism to
determine methicillin resistance in tandem with bacterial identi-
fication, patient isolation and infection control measures could be
implemented faster, thus reducing time to diagnosis and allowing
the timely administration of more appropriate antibiotic therapy.
An additional debate surrounds the capacity of MALDI-TOF MS
to identify Panton-Valentine leukocidin (PVL) from staphylo-
cocci. Conflicting publications argue both for (96) and against
(97) the use of MALDI-TOF MS to identify PVL based on the
presence of unique peaks in the mass spectra.
Streptococci
The streptococci are some of the most dynamic and medically
relevant human bacterial pathogens identified in the clinical lab-
oratory. These facultative Gram-positive bacteria are capable of
causing a variety of diseases ranging from uncomplicated pharyn-
gitis to multiple manifestations of invasive disease, including
meningitis, sepsis, and necrotizing fasciitis. The genomes of strep-
tococcal species encode a number of virulence determinants that
mediate adhesion to and invasion of both localized and systemic
tissues as well as a diverse repertoire of exotoxins and superanti-
gens, depending upon the species in question. The genus Strepto-
coccus is separated into many species but has undergone consid-
erable taxonomic changes in the past decades with the availability
of more sensitive testing methodologies. Phenotypically, the
streptococci are often classified into larger groups based on their
hemolytic activity on blood-containing media and antigenic dif-
ferences in their associated surface components. This practice has
resulted in streptococci often being referred to as either alpha-
hemolytic (viridans group streptococci/S. pneumoniae), beta-
hemolytic, or nonhemolytic when describing their appearance
and being able to be grouped into different serogroups via typing
of Lancefield antigens. Species identification of cultured strepto-
cocci is traditionally performed either by biochemical methods,
including bile solubility and antibiotic resistance patterns (op-
tochin/bacitracin sensitivity), or by agglutination testing (98).
While streptococcal taxonomy has been in a state of flux over the
previous decade, the accurate identification of these organisms in
infectious processes is essential in most cases. Here we review the
ability of MALDI-TOF MS to discriminate between different
streptococcal species and the potential pitfalls or deficiencies that
should be addressed in the near future. MALDI-TOF MS identi-
fication of Abiotrophia, a member of the so-called “nutritionally
variant streptococci,” will also be briefly considered.
Beta-hemolytic streptococci. Beta-hemolytic streptococci (BHS)
are a group of species comprised of different serogroups. These
organisms are important human pathogens, and their timely and
accurate identification is paramount in the context of infection
and is crucial to clinical diagnosis. As such, a number of pheno-
typic and molecular methods were developed for their identifica-
tion (98). BHS include Lancefield antigenic group A (S. pyogenes),
antigenic group B (S. agalactiae), antigenic group C (S. dysgalac-
MALDI-TOF Mass Spectrometry in Clinical Microbiology
July 2013 Volume 26 Number 3 cmr.asm.org 561
tiae and others), and group G (S. canis and others). The timely
identification of these organisms, particularly those of groups A
and B, is highly important to patient care. Left untreated for pro-
longed periods of time, group A streptococcal infections can man-
ifest as serious autoimmune sequelae, including glomerulone-
phritis or rheumatic fever.
The rapid identification of group B streptococci is an impor-
tant component of prenatal care in antepartum units due to the
ability of S. agalactiae to cause serious infections in newborn in-
fants. Therefore, the ability to quickly identify these organisms
when encountered in clinical specimens directly influences pa-
tient care.
The ability of MALDI-TOF MS to discriminate between bac-
terial species that appear phenotypically identical, such as some
Streptococcus spp., demonstrates the power of this tool. Studies of
beta-hemolytic streptococci depict recent improvements to
MALDI-TOF MS identification. A preliminary investigation from
2004 utilized MALDI-TOF MS to characterize the spectra gener-
ated from ionization of intact cells from three of the four major
groups of beta-hemolytic streptococci isolated from hospital pa-
tients and community members. Although the study was per-
formed before automated databases of bacterial spectra were
widely available, the investigators were able to identify differences
in the spectra of group A, C, and D streptococci with good repro-
ducibility as well as roughly begin to examine spectral differences
between strains of the same group (45).
More recently, Cherkaoui et al. described clinical microbiology
on the cusp of monumental change in the way in which clinical
laboratories analyze and routinely identify bacteria. Using the
Bruker BioTyper 2.0 database (library v. 3.1.1.0), results from a
broad sample set were compared to traditional phenotypic analy-
sis by the Vitek-2 system coupled with a latex agglutination test
(Bio-Rad) for the identification of 386 beta-hemolytic streptococ-
cal isolates from clinical specimens (99). The MALDI-TOF MS
system proved to be superior to traditional phenotypic methods
for identifying beta-hemolytic streptococcal isolates. Fifty-two
isolates of group A streptococci, 306 isolates of S. agalactiae,10
isolates of S. dysgalactiae (Lancefield group C), and 18 isolates of S.
dysgalactiae (Lancefield group G) that originated from a variety of
anatomical sites were analyzed in the clinical laboratory. MALDI-
TOF MS identification gave high-confidence identification to the
species level for all organisms tested, whereas the phenotypic
methodology used (Vitek-2) identified only 85% of the isolates
with high confidence. Discrepant analysis was performed by using
16S rRNA gene sequencing; all discrepant cases resulted in confir-
mation of the identification determined by MALDI-TOF MS and
the Bruker BioTyper database (99). This study demonstrated not
only the superior discriminatory power of MALDI-TOF MS for
beta-hemolytic streptococcal species compared to traditional
phenotypic identification methods but also the adaptability of the
instrumentation to the workflow of the clinical microbiology lab-
oratory.
(i) Group A streptococci. The group A streptococcus (GAS) S.
pyogenes is capable of causing a variety of pathologies; the two
most severe include streptococcal toxic shock syndrome and ne-
crotizing fasciitis (100). GAS is identified by the intense zone of
beta-hemolysis surrounding catalase-negative colonies grown on
media containing blood and by agglutination with antisera against
the Lancefield A antigen. Although rapid antigen detection tests
and molecular methods are available for throat swabs to diagnose
streptococcal pharyngitis, many of these direct and rapid assays
are not designed or approved for use with other clinical specimens
such as body fluids, tissue samples, blood, and wound specimens,
and therefore, bacterial culture is the current method of strepto-
coccal identification from these sources.
In a small preliminary study, Moura et al. successfully demon-
strated the potential discriminatory power of MALDI-TOF MS
for identifying and characterizing GAS isolates ( 101). Eight clini-
cal isolates and one GAS strain were analyzed. Strains included in
the study were phenotypically identified as GAS and typed by both
PCR and sequencing of the emm genetic locus. Whole bacterial
cells were utilized for MALDI-TOF MS, and the spectra were com-
pared. Those authors demonstrated that gamma irradiation of the
cells prior to MS analysis did not interfere with the generated
spectra and could be potentially introduced into the MS sample
preparation methodology as a safety control step for virulent iso-
lates. Using a combination of MS and statistical analysis, GAS
generated unique spectra that enabled them to be unequivocally
identified compared to the spectra generated by the panel of other
control organisms in the study. Additionally, GAS isolates from
invasive necrotizing fasciitis cases were grouped together in a
unique clade away from other clinical isolates based on their spec-
tral profiles and irrespective of their emm type (101).
(ii) Group B streptococci. Group B streptococci (GBS), com-
prised of S. agalactiae, are a leading cause of infectious morbidity
and mortality among neonates in the United States. Maternal col-
onization with GBS is the primary risk factor for transmission to
newborns, either in utero or during delivery; therefore, screening
mechanisms exist to identify at-risk patients and provide them
with prophylactic options. Rapid identification mechanisms for
GBS include agglutination assays, chromogenic media, and mo-
lecular testing including PCR with direct specimens. Nevertheless,
culture and subsequent identification from enrichment broth re-
main the reference standard for the recovery and identification of
GBS for prenatal patients (102). In the clinical laboratory, GBS is
identified by the CAMP test (so named for scientists Christie,
Atkins, and Munch-Petersen), hippurate hydrolysis assays, PYR,
or molecular methods.
Two studies from Lartigue et al. focused exclusively on GBS
identification by MALDI-TOF MS analysis (103, 104). The first
study investigated the ability of MALDI-TOF MS to identify 110
isolates of molecularly and serologically characterized GBS using
cellular extracts. This study also included an important phyloge-
netic component, determining that variations among proteins ex-
pressed between different serogroups of GBS influenced spectra
generated by MALDI-TOF MS but not significantly enough to
alter organism identification. All 110 GBS isolates were identified
to the species level with good confidence by using the Bruker Bio-
Typer database v.1.1, irrespective of their associated serogroup
(103). The second study investigated the ability of MALDI-TOF
MS to identify GBS and differentiate “highly virulent” lineages of
GBS. An expanded sample set of 197 GBS isolates from pregnant
females, infections of nonpregnant adults, and neonatal meningi-
tis patients was selected for analysis. Cell extracts were obtained
and analyzed by using the Bruker BioTyper v2.0 database. Consis-
tent with previous results, MALDI-TOF MS was able to identify
each of the isolates with high confidence. Moreover, the technique
was also able to discriminate highly virulent isolates of the ST-17
and ST-1 serotypes from other isolates with strong predictive val-
ues, indicating the potential of this method for future use with
Clark et al.
562 cmr.asm.org Clinical Microbiology Reviews
respect to strain identification and infection management in clin-
ical practice (104).
Streptococcus pneumoniae. S. pneumoniae is an alpha-hemo-
lytic streptococcus that is distinct from the viridans group strep-
tococci despite a close genetic relationship. In contrast to GAS and
GBS, there are fewer investigations to identify and characterize
isolates of S. pneumoniae. One study examined the ability of the
technique to differentiate conjunctivitis outbreak isolates of S.
pneumoniae based on proteomic analysis (105). The publication
demonstrates the ability of MALDI-TOF MS to identify S. pneu-
moniae isolates as well as biomarkers useful in strain typing that
could potentially offer valuable information for epidemiological
studies. In contrast, other studies have reported difficulties in
identification of S. pneumoniae, sometimes misidentified as S. mi-
tis by MALDI-TOF MS (23). This misidentification is a serious
limitation given the importance of rapid and accurate identifica-
tion of S. pneumoniae. Werno et al. reported improvements to the
database that would more reliably distinguish between these two
species (106), and Neville et al. showed similar corrections (107).
Viridans group streptococci. Accurate identification of viri-
dans group streptococci (VGS) to the species level poses a con-
siderable challenge for many clinical laboratories. This hetero-
geneous group of commensal organisms colonizes the
gastrointestinal, respiratory, and genitourinary tracts as well as
the oral mucosa and can cause localized infections. Conversely,
these organisms are known to cause systemic infections, lead-
ing to sepsis, meningitis, and endocarditis, among others, at a
variety of anatomical sites. These bacteria were quite accurately
referred to as a “grab bag” of leftover organisms once the beta-
hemolytic streptococci, pneumococci, and enterococci were
excluded (108). VGS can be separated into five major classifi-
cations, the mutans, salivarius, anginosus, mitis, and bovis
groups (109). A heavy reliance on a combination of molecular
methods and phenotypic methods is often required for com-
plete identification to the species level, as many of these organ-
isms are genetically similar (110). Further confounding the
situation is a confusing nomenclature and continually chang-
ing taxonomy within the VGS. While a thorough analysis of the
VGS is outside the scope of this review, the reader is referred to
two excellent reviews on VGS characterization, taxonomy, and
identification (108, 111). Although confounded by taxonomi-
cal and methodological challenges, the need for appropriate
identification of VGS to the species level remains, particularly
to help identify strains from blood culture bottles, where spe-
cies identification may help sort out differences between skin
contaminants and pathogens (110).
MALDI-TOF MS was utilized for the accurate identification of
VGS to the species level (43, 112). In a large study of mutans group
streptococci, MALDI-TOF MS was demonstrated to be capable
of species-level differentiation. The discriminatory power of
MALDI-TOF MS was further demonstrated by the ability of the
technique to correctly identify reference isolates that had been
misidentified previously (43). Similar results were also found in
another study based on VGS, highlighting the application of
MALDI-TOF MS analysis as a necessary quality control measure
for existing culture collections (113).
Friedrichs et al. used protein extracts from reference strains
and clinical isolates to assemble a database that was used to com-
pare the spectra generated from protein extracts from 99 consec-
utive VGS clinical isolates isolated from a variety of anatomical
sites. Importantly, it was demonstrated that members of the VGS
generated unique spectra when analyzed by MALDI-TOF MS and
that spectra from members of the same group of VGS were more
similar than those from other groups. All strains used in the study
were identified in parallel by the phenotypic RapID 32 Strep sys-
tem (bioMérieux) and by molecular methods such as 16S rRNA
analysis or by species-specific PCR. Twenty-three strains, identi-
fied as either S. oralis or S. mitis by molecular methods, were an-
alyzed by MALDI-TOF MS, and all but two were unequivocally
identified to the species level. The remaining strains were analyzed
with a different set of statistical parameters and were subsequently
identified by MALDI-TOF MS. The authors reported that
MALDI-TOF MS demonstrated 100% consistency with the results
obtained by phenotypic and molecular testing and concluded that
MALDI-TOF MS was a rapid and accurate strategy for VGS iden-
tification (112).
Nonenterococcal group D streptococci are important mem-
bers of the viridans group streptococci capable of causing a variety
of infections in humans, resulting in systemic bacteremia and en-
docarditis. One member of the group D streptococci, S. bovis, has
been associated with colorectal cancer and reviewed by others
(114). S. bovis is included in a large complex of group D strepto-
cocci (named the S. bovis-S. equinus complex), which has under-
gone recent taxonomic revision (115). Identification of members
of the S. bovis-S. equinis complex is possible through the use of
traditional biochemical analysis, but resolution to the appropriate
species and subspecies is not always possible. Molecular testing is
also challenging due to the high level of 16S rRNA sequence iden-
tity among members of this group (113). Currently, the most re-
liable method for species identification of the S. bovis-S. equinus
complex is sequence analysis of the sodA gene (113, 116). Using
both sodA sequencing and MALDI-TOF MS analysis of whole
bacterial cells, Hinse and colleagues described a high level of con-
cordance between the two methods and reliable identification to
the species level of S. bovis-S. equinus complex organisms by
MALDI-TOF MS. Importantly, the investigators utilized the com-
mercially available SARAMIS database software for spectral anal-
ysis in this study (113). Other groups have reported difficulty dis-
criminating between members of this complex of organisms using
the BioTyper version 3.0 software, with identifications being fur-
ther hampered by recent taxonomic revisions that have occurred
within the complex (117).
Nutritionally variant streptococci and related genera. Nutri-
tionally variant streptococci (NVS) represent a challenging group
of organisms to identify due to their fastidious nature and diver-
gent biochemical profiles. Once classified as members of the genus
Streptococcus, these organisms were reclassified into different gen-
era based on their genetic divergence from the genus Streptococcus.
Abiotrophia represents one genus within this classification that
was identified as the causative infectious agent in a number of
pathological processes, including infective endocarditis, sepsis,
and implant-related infections. Recently, MALDI-TOF MS was
utilized in parallel with traditional biochemical methods for the
rapid identification of Abiotrophia defectiva from a patient with
infective endocarditis. MALDI-TOF MS correctly identified the
isolated bacteria as A. defectiva, with the result confirmed by 16S
rRNA gene PCR (118).
In an analysis of catalase-negative Gram-positive cocci not be-
longing to either Streptococcus or Enterococcus spp., Christensen et
al. reported the application of MALDI-TOF MS-based identifica-
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July 2013 Volume 26 Number 3 cmr.asm.org 563
tion to a collection of 51 isolates representing 16 genera, all of
unique species, by using the Bruker BioTyper 2.0 software. Sam-
ples were processed by using 70% formic acid for protein extrac-
tion. Although low scores were obtained initially due to the lack of
the presence of these specific genera in the database, the creation
of a dedicated spectral database allowed for robust results, with no
misidentifications occurring at the genus level (70).
Enterococcus spp.
The enterococci are important human pathogens capable of caus-
ing serious infections and are often resistant to numerous antibi-
otics. There is evidence to suggest that enterococci possess specific
traits which allow them to persist in the nosocomial environment,
colonize patients, and contribute to serious infections, including
bacteremia, peritonitis, endocarditis, wound infections, and in-
fections of the urinary tract and medical devices (119). Addition-
ally, the ability of enterococci to obtain mobile genetic elements
encoding antibiotic resistance genes has contributed to their
emergence as important pathogens in the hospital environment
(120). The identification of Enterococcus spp. in the clinical labo-
ratory relies heavily on phenotypic analysis; however, rapid iden-
tifications based on molecular techniques have also been devel-
oped (121).
MALDI-TOF MS has been used for the characterization of en-
terococcal isolates from both human and environmental sources
(122, 123). Böhme et al. documented the accuracy of the Bruker
BioTyper system for identification of 30 Enterococcus spp. isolated
from blood cultures (124). In a study of E. faecalis dental isolates
from European countries, MALDI-TOF MS was able to be used to
perform cluster analysis by using MicrobeLynx software (Waters).
Based on the spectral signatures of their surface components, a
collection of 58 isolates was grouped by geographical location.
Evidence of quinupristin-dalfopristin (Synercid) susceptibility
was also provided (122). A second study utilized MALDI-TOF MS
as a bacterial source-tracking tool to characterize environmental
isolates of Enterococcus spp. Animal and human enterococcal iso-
lates were collected and analyzed to determine if MS spectra could
be used to group isolates according to their respective sources
(123). MALDI-TOF MS showed promise as a source-tracking tool
for environmental studies, but the technique required further re-
finement, particularly in the sample-processing phase of experi-
mentation.
Fang et al. recently completed a large comparative analysis of
molecular, phenotypic, and MS methods for the species-level
identification of 132 clinical Enterococcus isolates. Importantly,
two MS platforms (Bruker BioTyper version 3.0 and Vitek-MS)
were compared. Both MS systems provided identical results for all
isolates tested, and both performed equally as well as multiplex
PCR for enterococcal identification (125). In summary, these
studies demonstrate the ability of MALDI-TOF MS to generally
characterize enterococci from clinical and nonclinical sources and
provide information regarding clonal relationships and potential
distribution mechanisms.
Lactococcus spp.
Lactococci are important organisms for the maintenance of the
gastrointestinal tracts of humans and ruminant animals and for
the industrial production of fermented dairy products but are
rarely identified in clinical infections. Although perhaps less clin-
ically significant than other Gram-positive species reviewed in this
section, the lactococci are capable of causing human infections
(126, 127). In a study examining the identification and subspecies
determination of 30 strains of lactococci, Tanigawa et al. demon-
strated that analysis by MALDI-TOF MS was suitable for the iden-
tification of members of the genus Lactococcus to the species level
and was the most effective method for the discrimination of sub-
species compared to molecular methods such as housekeeping
gene sequencing by amplified fragment length polymorphism
(AFLP) analysis (128).
Bacillus spp.
Members of the genus Bacillus are Gram-positive, spore-forming,
rod-shaped bacteria that are normal inhabitants of soil and other
environmental niches. The two major pathogenic species are B.
cereus and B. anthracis, both of which are genetically related to
each other. B. cereus is responsible for a self-limiting food-borne
illness that is toxin mediated and may cause line-related bactere-
mia in neutropenic patients. In contrast, B. anthracis is a category
A bioterrorism agent that requires rapid identification and report-
ing to federal authorities upon isolation. For identification pro-
cesses, strict adherence to the Laboratory Response Network
(LRN) classification of one’s laboratory is required, following
rule-out and referral steps designated in the particular laborato-
ry’s classification for B. anthracis and other select agents. B. an-
thracis and B. cereus are highly related to each other in terms of
genetic content, sharing approximately 90% of their core ge-
nomes. In the laboratory, the two species are differentiated by the
production of capsule by B. anthracis on blood-containing media
as well as variant biochemical profiles. As the identification of B.
anthracis in patient samples has serious implications for both the
patient and the general public, rapid and accurate identification of
this organism is essential.
Early mass spectrometry-based studies of Bacillus spp. were
centered on the identification of organisms by proteomic charac-
terization of bacterial spores. Studies examining the ability of
MALDI-TOF MS to differentiate vegetative cells of B. anthracis
from B. cereus and other members of the genus have recently been
undertaken. Early investigations analyzed both vegetative cells
and spores by MS to identify unique biomarkers that could poten-
tially be used to detect their presence. As spores are the metabol-
ically dormant form of the organism, the detection of this form of
the Bacillus species life cycle would have important health impli-
cations, as the spores are also infectious. With respect to spore
proteins, a number of unique biomarkers were discovered in
spore samples, which were demonstrated to aid in identification of
different species of Bacillus.
In contrast, the clinical microbiology laboratory more com-
monly deals with the presence of vegetative cells in patient speci-
mens and traditionally uses these cells as the basis for bacterial
identification. A 1996 study examining extracted proteins from
four different species of Bacillus identified genus-, species-, and
strain-specific biomarkers, highlighting the potential of MALDI-
TOF MS for use in the identification of Bacillus spp. (129). In a
study examining 374 strains of Bacillus spp., a combination of
MALDI-TOF MS and artificial neural networks for spectral anal-
ysis was used to identify unique biomarkers for both species, and
sensitivity and specificity of 100% were achieved for differentiat-
ing B. anthracis and B. cereus. Similar to analyses with other spe-
cies, the authors noted the importance of a standardization of
culture conditions to generate reproducible spectra for analysis
Clark et al.
564 cmr.asm.org Clinical Microbiology Reviews
(130). Recently, an expanded MALDI-TOF MS-based analysis of
the genus Bacillus was undertaken by using a database constructed
based on ribosomal protein markers (131). B. cereus group organ-
isms were differentiated easily with this database, whereas 16S
rRNA gene sequence analysis proved to be more difficult. In all,
MALDI-TOF MS appears to provide a rapid and reliable method
for the identification of B. anthracis, B. cereus, and other bacilli to
the species level.
Listeria spp.
Listeriae are a group Gram-positive, rod-shaped bacteria with low
G⫹C content that are divided into six species, only two of which
are pathogenic (132). Readily found in the environment, the pre-
dominant pathogenic species of the genus, L. monocytogenes,is
responsible for contamination and food-borne illness that can
manifest as serious, life-threatening infections, including menin-
gitis, sepsis, and encephalitis. Immunocompromised patients or
patients of advanced age have increased susceptibility to infection
(74). L. monocytogenes poses a risk to pregnant patients, as the
bacteria have the ability to cross the placental barrier and infect the
fetus in utero, resulting in serious complications including neona-
tal meningitis, premature labor, and stillbirth. Thus, rapid identi-
fication of Listeria spp. is necessary for successful patient out-
comes.
Listeria spp. are readily identified by a number of biochemical
methods. Identification of these organisms to the species level
relies on detection of growth at reduced temperatures, serodiag-
nosis, hemolytic activity, and carbohydrate utilization patterns.
Testing procedures often require additional incubations and ad-
ditional subculture, prolonging the time to definitive diagnosis.
Additionally, subtyping of different Listeria species isolates re-
quires specialized testing, including serological, phage-depen-
dent, or molecular analysis. Accurate identification to the species
level and subtyping of the organism are important, as the identi-
fication of L. monocytogenes is a reportable agent to public health
authorities for food-borne outbreaks.
MALDI-TOF MS has been demonstrated to be a rapid alterna-
tive to current phenotypic and molecular methods for species
identification and subtyping of Listeria spp. In a sentinel study by
Barbuddhe and colleagues, 146 strains representing each of the six
species of Listeria were analyzed by MALDI-TOF MS and included
reference isolates in addition to isolates from outbreaks and clin-
ical isolates (57). Species-level analysis was performed, and a List-
eria-specific reference library of MS spectra was constructed by
using the Bruker BioTyper software (v.1.1). In all but 10 discrep-
ant cases, the species-level identification generated by MALDI-
TOF MS matched the previously determined identification. Upon
analysis of discrepant identifications by 16S rRNA gene sequenc-
ing, it was determined that the identification provided by the
MALDI-TOF MS system was correct and that the original species
designation of the isolate was in error. Importantly, MALDI-TOF
MS was also able to resolve clonal lineages, all of which were in
agreement with the reference method, PFGE, demonstrating the
ability of MALDI-TOF MS to be able to simultaneously provide
rapid and accurate species-level identification and genetic subtyp-
ing of Listeria species isolates (57).
Corynebacterium spp.
Corynebacteria represent a diverse group of pleomorphic bacteria
that in some cases are normal inhabitants of the skin microflora
and in other cases have the potential to cause either opportunistic
or severe disease (74). These organisms are Gram-positive, non-
spore-forming rods that are often eliminated as causative agents of
infection upon routine microbiological examination due to their
innocuous presence on the skin. In some cases, they are demon-
strated to be clinically relevant. Corynebacterium diphtheriae is
perhaps the most medically significant member of the genus and
the causative agent of diphtheria. Other toxigenic corynebacterial
species, including C. ulcerans and C. pseudotuberculosis, are also
capable of causing human infections. Although the prevalence of
infection with C. diphtheriae is low due to current vaccination
practices, rapid identification and reporting of the organism are
important due to public health concerns. Currently, a number
of identifications systems are available for the identification of
corynebacteria, including that API RapID Coryne system (bio-
Mérieux) and the BBL Crystal system (Becton Dickinson), among
others. These systems require additional incubation time in order
to develop the biochemical reactions needed for proper species-
level identification of corynebacteria. Additional testing of Co-
rynebacterium species isolates is sometimes performed to deter-
mine toxin production, including Elek immunodiffusion testing
and PCR-based methods.
An analysis of 116 isolates of Corynebacterium spp. of clinical
and veterinary origins by MALDI-TOF MS was undertaken to
investigate the discriminatory power of the technology with re-
spect to this genus (133). Isolates were collected over a period of 13
years. The reference database utilized for the study contained 138
reference spectra from 71 different Corynebacterium isolates in
addition to reference spectra for the toxigenic species derived
from type strains. Compared to rpoB sequencing, 115/116
(99.1%) isolates were correctly identified to the species level by
MALDI-TOF MS, with only 1 isolate restricted to genus-level
identification. The authors included a key point in their discus-
sion, describing the current inability of MALDI-TOF MS to dif-
ferentiate between different biovars of C. diphtheriae, but sug-
gested that this type of testing may be possible upon the
generation of an appropriate database (133).
Moving theory into practice, a second study utilized MALDI-
TOF MS to analyze outbreak strains of C. pseudodiphtheriticum in
France among cystic fibrosis (CF) patients (134). Eighteen isolates
from pediatric patients were collected over a period of almost 3
years. MALDI-TOF MS identifications of these isolates by using
the BioTyper database (Bruker) matched identifications made by
rpoB sequencing with 100% concordance and generated similar
phylogenetic relationships among corynebacterial isolates (134).
MALDI-TOF MS was also utilized as the primary mechanism
for definitive species-level identification of uncommonly encoun-
tered corynebacterial isolates (135). As databases become better
populated and more refined, studies such as these will play an
important role in both pathogen detection and the identification
of novel emerging pathogens, particularly for groups of often
overlooked organisms, such as the corynebacteria.
Arcanobacterium and Trueperella spp.
The genera Arcanobacterium and Trueperella contain Gram-posi-
tive, non-spore-forming, facultative anaerobic rods. Trueperella
was, until 2011, classified within the genus Arcanobacterium but
has since been reclassified into its own genus. These two genera
contain clinically important human and veterinary pathogens
alike. A. haemolyticum is a significant cause of pharyngitis and is
MALDI-TOF Mass Spectrometry in Clinical Microbiology
July 2013 Volume 26 Number 3 cmr.asm.org 565
often overlooked within the clinical laboratory due to its slow-
growing and fastidious nature as well as its delayed hemolytic
phenotype. Trueperella (Arcanobacterium) pyogenes is an impor-
tant veterinary pathogen and is a rare cause of infection in hu-
mans.
Using the BioTyper software, Hijazin et al. analyzed the ability
of MALDI-TOF MS to identify members of both Arcanobacterium
and Trueperella. All 98 isolates that were analyzed were correctly
identified to the species level with scores of ⬎2.0, indicating strong
matches to the database (136). The method was also utilized to
identify a novel member of the genus Trueperella, T. abortisuis,in
a publication by the same research group (137).
Nocardia and Mycobacteria
Mycobacteria, Nocardia, and aerobic actinomycetes can be signif-
icant diagnostic challenges to the clinical laboratory. Moreover,
due to the complex nature of their representative cell walls, bac-
teria from this group of organisms may require specialized pro-
cessing procedures prior to their analysis by MALDI-TOF MS in
order to obtain the most accurate results.
Sample preparation methods for MALDI-TOF MS identifica-
tion of mycobacteria and Nocardia spp. Verroken et al. described
a modified extraction method for attaining material for robust
MALDI-TOF MS material from Nocardia isolates (48). Briefly, 10
colonies of biomass were resuspended in water and boiled to pro-
mote cellular lysis. This lysate was then centrifuged to remove
cellular debris, followed by the addition of ethanol to precipitate
proteins contained within the supernatant. Precipitated proteins
were then centrifuged and dried, resuspended in 70% FA and
acetonitrile, centrifuged a final time, and then analyzed by
MALDI-TOF MS. This method provided material that could be
accurately used to analyze Nocardia isolates. Authors not utilizing
this method have reported problems analyzing actinomycetes
such as Streptomyces spp. (138).
As of now, no consensus mechanism exists for the processing
of mycobacteria for MALDI-TOF MS. Previously, direct whole
cells and FA-treated cells were utilized with success by a number of
groups, with safety being a substantial concern during routine
analysis. El Khéchine et al. rightfully described an investigation of
different methods for the inactivation and processing of mycobac-
terial samples for MALDI-TOF MS. Solubilization of bacterial
aggregates, which can impair MALDI-TOF MS analysis, was crit-
ical in their investigation, as was the avoidance excessive centrif-
ugation to minimize the potential of aerosolized exposure to lab-
oratory personnel. Through rigorous testing, the authors arrived
at a final procedure representing a synthesis of inactivation and
processing methods. Colonies were collected in screw-cap tubes
containing water and 0.5% Tween 20 and inactivated by heating at
95°C for 1 h. Inactivated samples were centrifuged, washed twice
with water, and then vortexed with glass beads to facilitate com-
plete cellular disruption. Following centrifugation, the pellet was
resuspended in FA-acetonitrile and centrifuged again. Finally, the
supernatant was deposited onto the MALDI test plate and overlaid
with matrix (50).
Nocardia spp. Nocardia spp. are ubiquitous bacteria from nu-
merous environmental sources and are not considered normal
flora when isolated from patient samples. Some species are capa-
ble of infecting humans, with a majority of infections reported in
immunocompromised patients including those with HIV/AIDS
and transplant patients (74). Diagnosis of nocardiosis with patient
specimens often requires isolation of the organism from patient
specimens, which can require extended incubation times, up to 2
weeks in some cases, for cultivation alone. Differentiation from
other filamentous bacteria is often achieved by differential stain-
ing including a modified acid-fast stain. Identification of Nocardia
organisms to the species level relies on a combination of biochem-
ical evaluation and molecular testing, with 16S rRNA sequencing
typically used as a determinative method for final identification to
the species level (139, 140). Agreement between molecular meth-
ods and biochemical analysis is between 70 and 90%, indicating
the need for more accurate and reliable testing methodologies for
the identification of Nocardia spp. (48, 140).
A single study evaluated the use of MALDI-TOF MS for the
species-level identification of Nocardia spp. (48). A panel of 153
clinical isolates was analyzed by MALDI-TOF MS and the Bio-
Typer database (v.2.0), utilizing an expanded database generated
by the investigators. This panel consisted of both clinical isolates
and reference strains of the most frequently isolated species. One
hundred ten isolates were used to generate a Nocardia-specific
database, while the remaining 43 isolates were blinded and used as
a challenge set. During database construction, distinct divisions
between different species of Nocardia could be visualized with the
MALDI-TOF MS software. The unmodified BioTyper database
was able to correctly identify 19 isolates (44%) to the genus level,
of which 10 (23%) were correctly identified to the species level.
The addition of the Nocardia-specific database significantly im-
proved identification scores such that 38/43 (88%) isolates were
identified to the genus level and 34/43 (79%) were identified cor-
rectly to the species level (48). This study provided additional
evidence that through the use of expanded databases populated
with entries of various clinical significances, the sensitivity of
MALDI-TOF MS can be dramatically improved. It may be impor-
tant in the future to include both organisms of environmental
origin as well as those of clinical origin to be able to accurately
identify organisms responsible for opportunistic infections and
other emerging pathogens.
Mycobacteria. Identification of Mycobacterium tuberculosis and
other mycobacteria from clinical specimens often requires a num-
ber of diverse techniques for observation, recovery, growth, and
characterization and space specifically engineered for biosafety. As
such, not all clinical laboratories are equipped for the culturing of
mycobacterial samples; therefore, the referral of specimens to
other laboratories for testing is a common practice that can result
in delays in testing, reporting, and treatment initiation among
patients (141). The average turnaround time for specimens sub-
mitted for mycobacterial testing is often reported to be days to
weeks (142–144).
Historically, bacterial culture remains the most sensitive
method for the detection of M. tuberculosis in clinical specimens
and serves as the starting point for downstream applications, in-
cluding the identification of mycobacteria to the species level and
the determination of antibiotic resistance (142). The identifica-
tion of mycobacteria to the species level cannot be performed with
traditional automated identification systems and instead requires
more complex and labor-intensive molecular assays, including
nucleic acid amplification strategies, molecular probes, high-per-
formance liquid chromatography (HPLC) analysis of mycolic ac-
ids from the bacterial cell wall, or DNA sequencing methods (142,
145–148). Moreover, the general biology of the organism slows
the time to diagnosis due to its requirements for specialized
Clark et al.
566 cmr.asm.org Clinical Microbiology Reviews
growth media, fastidious nature, and exceedingly slow generation
time. Only recently have real-time PCR methods emerged as rou-
tine, practical methods for detection of M. tuberculosis directly
from clinical specimens (149), but rapid detection of other species
from colonies is common, though not all inclusive, via GenProbe
methods (150, 151). The use of MALDI-TOF MS for the identifi-
cation of mycobacteria thus offers an attractive option for labora-
tories both to expand their testing menus and to perform their
own testing in-house in place of sending out specimens for myco-
bacterial identification.
Early investigations into the use of MALDI-TOF MS for the
identification of mycobacteria proved to be successful before the
generation of standardized spectral databases (46, 152, 153). A
preliminary investigation utilizing MALDI-TOF MS for the iden-
tification of six species of Mycobacterium demonstrated that each
species could be unequivocally identified based on their unique
mass-to-charge (m/z) ratios (152). Additionally, biomarkers
thought to be unique to the genus Mycobacterium could also be
identified among tested species. This study also demonstrated that
both whole cells and protein extracts could be used to generate
comparable spectra, thus decreasing the biosafety risks of working
with whole cells. A follow-up to this investigation successfully
demonstrated the potential for the use of MALDI-TOF MS for the
classification of mycobacteria (n ⫽ 16) at the strain level (46). A
larger investigation followed, this time using intact cells for anal-
ysis, and demonstrated that species-specific spectra could be gen-
erated for all but 1 of the 37 isolates tested (153). In each of the
above-mentioned studies, multiple replicates were utilized to
populate a database for the identification of different species of
Mycobacterium at the species and strain levels.
Database refinement is key for identification of Mycobacterium
spp. In a recent study by Lotz et al., the investigators extended a
database population technique to construct a database for analysis
of mycobacteria from commercially available type strains (154).
Importantly, the study also analyzed the ability of the database to
identify mycobacterial strains cultured both on Löwenstein-Jen-
sen (LJ) plates and in mycobacterium growth indicator tube
(MGIT) medium. The database was then challenged with 311 iso-
lates from 31 distinct species of Mycobacterium from LJ plates and
demonstrated 97% concordance with genus and species identifi-
cations and no discordant identifications. Three percent of the
tested strains from LJ plates could not be identified due to insuf-
ficient spectral information. Eighty-two strains were grown in
MGIT broth and analyzed by MALDI-TOF MS. In contrast to LJ
plates, only 77% of samples could be identified by MALDI-TOF
MS using MGIT samples due to insufficient spectra, potentially
due to additives in the MGIT medium. Despite fewer successful
identifications, no discordant results were found by using
MALDI-TOF MS and MGIT medium. Although only one type of
liquid medium was tested, it is important to consider the reduced
capabilities of MALDI-TOF MS using broth cultures, as liquid
medium is preferable to solid medium when isolating mycobac-
teria from direct specimens (155). Lotz et al. reviewed the capa-
bilities of MALDI-TOF MS compared to molecular methods of
mycobacterial identification. The authors noted that MALDI-
TOF MS can distinguish between members of various mycobac-
terial complexes and noted superiority of the mass spectrometry-
based technique compared to nucleic acid probe and DNA strip
methodologies (154).
As commercial databases become available for the identifica-
tion of microorganisms by MALDI-TOF MS, it will become im-
portant to thoroughly evaluate their utility in the clinical setting. It
will also be important to be able to modify or add entries to the
database as required with regard to geographical variation among
strains. A recent study by investigators at the National Institutes of
Health examined the performance of MALDI-TOF MS for iden-
tification of Mycobacterium spp. from protein extracts using an
expanded database of 42 type and reference strains representing
37 species. The Bruker database (v. 3.0.2.0) contained 50 strains
representing only 18 species (156). The constructed database was
then challenged with 104 clinical isolates representing 17 species.
All M. tuberculosis complex (MTC) isolates obtained strong MS
scores and were easily differentiated from nontuberculous myco-
bacteria, but the organisms M. tuberculosis and M. bovis, compris-
ing the MTC, could not be identified to the species level. An earlier
study reported that these organisms could be differentiated at the
species level (152) but utilized a different database containing
fewer strains and a different exaction methodology to make these
species determinations. Other difficulties in species identification
were reported for the identification of genetically similar myco-
bacteria, as these strains often require sequencing of single or mul-
tiple targets to be differentiated. These closely related strains aside,
the rest of the isolates could be easily and accurately identified to
the species level, demonstrating the utility of MALDI-TOF MS
for the identification of mycobacteria in the routine clinical labo-
ratory (156).
The implementation of MALDI-TOF MS in the routine clini-
cal laboratory will provide a powerful and accurate tool to quickly
identify mycobacteria from culture. This implementation will also
change testing algorithms for mycobacteria and provide a mech-
anism for enhanced surveillance and epidemiological data world-
wide. The implementation of MALDI-TOF MS technology will
reduce testing costs for mycobacterial identification, with con-
sumable costs per specimen estimated to be less than $1 per isolate
(156). In sum, these studies demonstrate the feasibility and robust
accuracy associated with MALDI-TOF MS for mycobacterial
identification.
GRAM-NEGATIVE BACTERIA
Gram-negative bacteria are encountered in the clinical laboratory
in all sample types analyzed and are ubiquitous members of the
normal human flora. Saffert et al. analyzed the ability of the
Bruker BioTyper version 2.0 MALDI-TOF MS software to identify
Gram-negative bacilli compared to identifications obtained by us-
ing the BD Phoenix system, using their collection of 440 common
and infrequently encountered bacterial species. There was no
significant difference between the two systems for commonly
encountered species of Gram-negative bacilli; however, the
BioTyper system was better than the Phoenix system for the
identification of infrequently isolated Gram-negative bacilli
(157).
Sample Preparation for Gram-Negative Bacteria
With respect to sample processing for accurate identification and
the analysis of variables potentially influencing MALDI-TOF MS
identification, Ford and Burnham recently reviewed methods
for optimizing routine Gram-negative identification using the
BioTyper system. Using a collection of 208 enteric Gram-negative
organisms and 252 nonfermenting Gram-negative organisms, the
organisms were spotted onto a MALDI plate using either a light or
MALDI-TOF Mass Spectrometry in Clinical Microbiology
July 2013 Volume 26 Number 3 cmr.asm.org 567
heavy smear (correlating to the amount of inoculum) and either
overlaid with 1 l of 100% formic acid or not overlaid, as reported
previously for the processing of Gram-positive organisms (69).
Samples were finally mixed with matrix solution and analyzed by
using the BioTyper 3.0 software (Bruker). These identifications
were compared to those derived phenotypically and to those de-
rived by utilizing a full ethanol-based protein extraction similar to
those necessary for analysis of mycobacteria and Nocardia, again
with 16S rRNA gene sequencing being used as a reference standard
to resolve discrepant results. For enteric organisms, a heavy smear
with an FA overlay provided preferential results compared to a
light smear of FA or to specimens without FA treatment. In con-
trast, heavy smears provided better identifications, but the addi-
tion of FA did not significantly influence MALDI-TOF MS iden-
tification of nonfermenting organisms, allowing the authors to
conclude that in the case of nonfermenting bacilli, FA treatment
was not necessary for optimal identification by MALDI-TOF MS
(158).
The Enterobacteriaceae
The Enterobacteriaceae represent a dynamic group of organisms
encountered in the clinical laboratory that are responsible for a
wide range of pathologies. This broad group of organisms is often
characterized by the ability of the organisms to ferment lactose, as
determined via biochemical testing. MALDI-TOF MS was utilized
by investigators to identify members of this large group of bacteria
and classify them as such while the technique was still in its in-
fancy. Prior to the advent of comprehensive databases that can be
easily queried with acquired spectra, early work using MALDI-
TOF MS for the identification of the Enterobacteriaceae was fo-
cused on the identification of suitable biomarkers for group-level
and genus-level identification. One early study from 1999 using
intact cells lysed by one cycle of freeze-thaw from storage at
⫺20°C examined the use of MALDI-TOF MS to distinguish be-
tween members of this group of organisms: E. coli O157:H7, Kleb-
siella pneumoniae, Salmonella enterica subsp. enterica serovar Ty-
phimurium, Salmonella enterica subsp. enterica serovar Dublin,
and Providencia rettgeri. For these organisms, the authors reported
MS spectral peaks representing family-specific biomarkers for the
Enterobacteriaceae, genus- and species-specific biomarkers for the
two serovars of Salmonella analyzed, and strain-specific biomark-
ers for the two strains of E. coli (159).
In 2005, Pribil and Fenselau used cultures of E. coli, Enterobacter
cloacae, Erwinia herbicola, and Salmonella Typhimurium from the
ATCC and analyzed them by using trypsin-digested whole cells.
Spectra were searched against the NCBInr database using a taxon-
omy restricted to eubacteria. The returned peptide hits consisted
of a number of cell surface-associated outer membrane proteins
(OMPs), leading the authors to suggest that a comparison of
OMPs from the members of the Enterobacteriaceae might lead to a
mechanism for species-specific identification of members of this
group of bacteria (160). Although these first studies were limited
to a small sample size and had restricted diversity with respect to
the genera analyzed, these were important steps toward demon-
strating the utility of MALDI-TOF MS for the identification of
members of the Enterobacteriaceae.
In a study examining the ability of MALDI-TOF MS to differ-
entiate Gram-negative species involved in seafood spoilage,
Böhme et al. reported the creation of a library of mass spectra
associated with the main pathogenic species of Gram-negative
bacteria associated with food spoilage. In this study, a collection of
29 isolates spanning 15 genera, including members of the Entero-
bacteriaceae, were selected for analysis by MALDI-TOF MS. Bac-
terial colonies were harvested and mixed with trifluoroacetic acid
(TFA) and acetonitrile and analyzed by MALDI-TOF MS. The
resultant spectra were added to a library that contained peak data
for peptides in the 2,000- to 10,000-Da range. The spectral peaks
generated could be easily grouped, with members of the Entero-
bacteriaceae generating spectra that could easily be concluded to
be similar, yet differences could be identified, allowing genus- and
species-specific identifications. Of note, spectra derived from
members of the genus Serratia were different from those of other
members of the Enterobacteriaceae. The authors also noted impor-
tant similarities in spectra between organisms that are genetically
closely related as well as organisms found in similar niches (i.e.,
marine environments) (124).
Salmonella spp. Salmonella spp. are important organisms often
associated with food-borne disease and gastrointestinal pathol-
ogy. Detection of Salmonella spp. in the clinical laboratory is a
multistep process often involving multiple selective medium
types, subculture, and serology before a final identification can be
reached. The identification of Salmonella spp. from stool cultures
can take upwards of 2 days when utilizing traditional biochemical
methods. While molecular methods are available, serological pro-
tocols predominate as the method of choice for many laboratories
for serovar determination, further adding to the time to definitive
diagnosis. MALDI-TOF MS has since been utilized to aid in both
the detection and species-level identification of Salmonella.
MALDI-TOF MS was identified early on as an attractive
option for the species and subspecies typing of Salmonella.
Before the widespread use of MALDI-TOF MS for the identifi-
cation of clinical bacterial isolates or the establishment of com-
prehensive databases, Lynn et al. identified genus- and species-
specific biomarkers dedicated specifically to the identification
of Enterobacteriaceae for MALDI-TOF MS identification of
Salmonella, but their study lacked an appropriate system for
complex profile analysis (159). They defined consensus peaks
specific to six Salmonella serovars but found discrepancies with
other studies. Many of these consensus peaks identified by
Lynn et al. were unable to be confirmed by a second group that
performed a similar analysis using members of the genus Sal-
monella, but key differences between the studies (including
differences in the type of mass spectrometer and laser source
utilized) were partially attributed to the inability of the same
consensus spectral peaks to be identified (161). Expanding on
the need for a more defined set of biomarkers for the identification of
the salmonellae, Dieckmann et al. examined variations in housekeep-
ing gene levels among a large collection of Salmonella isolates in order
to generate a more comprehensive phylogenetic classification mech-
anism using whole-cell MALDI-TOF MS (162). Although these pre-
liminary studies utilized nonstandardized methods for the analysis
and generation of their respective mass spectra, they represent some
of the first important steps toward a uniform ability to differentiate
members of the genus Salmonella on species- and serovar-specific
levels.
One of the greatest challenges associated with Salmonella iden-
tification is perhaps not the identification of the organism as a
member of the genus but the further identification to the subspe-
cies level and taxonomy associated with definitive identification.
In a second publication, Dieckmann and Malorny made signifi-
Clark et al.
568 cmr.asm.org Clinical Microbiology Reviews
cant contributions toward the identification of serovar-specific
biomarkers by MALDI-TOF MS utilizing an exhaustive collection
of 913 Salmonella enterica subsp. enterica strains comprising 89
unique serovars and the SAMARIS (release 3.4) database. While
some serovar-specific spectral peaks could be identified, the au-
thors concluded that MALDI-TOF MS would be suitable only for
the rapid screening of isolates, with subsequent serovar identifica-
tion being reliant on traditional serotyping methods for a majority
of strains (163).
While Salmonella enterica serovar Typhi has been essentially
eradicated in the United States, it remains a significant health
concern in many African countries and the developing world. Re-
turning to the issue of Salmonella serovar determination using
MALDI-TOF MS, Kuhns et al. recently evaluated the ability of the
technology to discriminate S. enterica serovar Typhi from other
Salmonella serovars. By using clinical blood culture isolates col-
lected from epidemiological studies and reference strains repre-
senting 160 S. enterica subsp. enterica isolates and 12 serovars,
intact-cell MALDI-TOF MS using the Bruker BioTyper 3.0 data-
base was evaluated and compared to conventional identification
methods. In all cases, Salmonella spp. were readily distinguished
from other members of the Enterobacteriaceae. The authors also
reported their ability to identify biomarkers specific to S. enterica
serovar Typhi compared to spectra generated for other Salmonella
isolates included in their study and showed that the spectra gen-
erated by S. enterica serovar Typhi isolates in this particular col-
lection were significantly different from those of the other serovars
present. Furthermore, the S. enterica serovar Typhi isolates could
be identified based on their respective mass spectral profiles (164).
Well-planned, large-scale studies similar to those performed by
Kuhns et al. and Dieckmann et al. will further enhance the ability
of MALDI-TOF MS to accurately determine subspecies- and se-
rovar-level identifications for members of the genus Salmonella.
Sparbier et al. recently examined the ability of MALDI-TOF
MS to identify S. enterica serovar Typhimurium from spiked stool
specimens obtained from healthy volunteers and from hospital
patients. Samples were treated with formic acid-acetonitrile and
analyzed by using the BioTyper 2.0 software database. Not sur-
prisingly, MALDI-TOF MS was demonstrated to be able to defin-
itively identify Salmonella spp. from spiked samples versus other
bacteria from unspiked controls enriched in selenite enrichment
broth. Importantly, the authors also performed a measurement of
the sensitivity of MALDI-TOF MS for the identification of Salmo-
nella by spiking serially diluted samples of S. enterica serovar Ty-
phimurium into stool and enriching the samples for bacterial
growth. Spiking of samples with 800 CFU or greater followed by
enrichment led to a clear identification of Salmonella spp. by the
software, whereas inoculation of the enrichment broth with ⬎80
CFU led to ambiguous MALDI-TOF MS identifications, likely
due to overgrowth by fecal flora. An examination of this enrich-
ment method followed by MALDI-TOF MS on 4,847 routine
clinical specimens found that of the 108 Salmonella-positive spec-
imens identified by traditional biochemical analysis, MALDI-
TOF MS identified 100 of them correctly 24 h earlier. The 8 spec-
imens missed by MALDI-TOF MS could be identified as
Salmonella positive only after plating of the enrichment medium,
indicating that the bacterial concentration was likely too low to be
detected by MALDI-TOF MS (165).
In sum, the current utility of MALDI-TOF MS for the clinical
diagnosis of Salmonella infections appears to be best exemplified
by the ability of the technology to rapidly identify members of the
genus, in some cases up to 24 h sooner. MALDI-TOF MS fits easily
into the routine workflow associated with Salmonella identifica-
tion but as of now still requires enrichment and supplemental
culture for the most accurate diagnostic results with respect to
specimens containing a low bacterial inoculum. As a tool for sub-
species and serovar typing, MALDI-TOF MS shows significant
promise but will require additional studies and modifications to
existing protocols before the method can be used as a stand-alone
mechanism.
Escherichia coli and Shigella spp. The identification of patho-
genic Escherichia coli and Shigella species is critical and often
challenging for the clinical laboratory because the organisms
are closely related on the genetic level. Growth on sorbitol-
containing MacConkey medium is sometimes used as a prelim-
inary mechanism to differentiate pathogenic species of E. coli
from nonpathogenic species, requiring the use of specialized
media and additional culture time. This method is not defini-
tive for all Shiga-toxin-producing strains, and therefore, addi-
tional reflex testing with serological and molecular methods is
often required.
As early as 2001, the use of MALDI-TOF MS was evaluated for
the identification of pathogenic E. coli and Shigella species. Con-
way et al. reported good identification of E. coli in a preliminary
study in which spectra from 25 clinical isolates were compared to
reference spectra from an in-house database developed for other
members of the Enterobacteriaceae, including Salmonella and Shi-
gella. The authors also undertook exhaustive studies examining
the effects of culture conditions, medium selection, and bio-
marker identification in one of the earliest studies examining the
feasibility of the technology for the identification of this group of
organisms. Finally, the authors reported that cluster analysis of the
spectra generated from these isolates by MALDI-TOF MS allowed
for the construction of a phylogenetic dendrogram, which was
comparable to that generated by molecular methods. At the time,
the authors conceded that the technology was not suitable for
strain-specific identification (166).
A more recent study from the realm of basic proteomic re-
search sought to determine specific biomarkers for E. coli
O157:H7 by using a combination of MALDI-TOF/TOF (tandem
time of flight) and a top-down proteomics approach (167). By
using this approach, six protein biomarkers were able to be iden-
tified, and the associated genes encoding these biomarkers in
strains of different lipopolysaccharide (LPS) and flagellar anti-
genic types were sequenced. A majority of these biomarkers were
determined to be proteins involved in stress responses, with four
of the six proteins containing a signal sequence indicating their
function at the membrane. While these biomarkers were unable to
distinguish between an O157:H7 strain and an O55:H7 strain,
they were suitable for discrimination between an O157:H7 strain
and a nonpathogenic E. coli strain by virtue of a single-amino-acid
change. Subsequently, a second biomarker was also identified as
the HdeB stress chaperone-like protein, which was present in the
mass spectra of the non-O157:H7 isolate but was absent in the
spectra of O157:H7 strains identified (167).
Similarly, Karger et al. sought to use an intact-cell strategy for
the discrimination of Shiga toxin-producing E. coli strains repre-
senting selected serotypes, with mixed results (168). These works
demonstrate the significant sensitivity of mass spectrometry and
its use as a research tool for biomarker discovery; however, in a
MALDI-TOF Mass Spectrometry in Clinical Microbiology
July 2013 Volume 26 Number 3 cmr.asm.org 569
situation similar to that for Salmonella isolates, additional re-
search is warranted to adapt MALDI-TOF/TOF technology to be
suitable for strain-specific identifications of E. coli isolates.
In addition to the current inability of MALDI-TOF MS to re-
liably distinguish pathogenic from nonpathogenic E. coli isolates,
numerous reports describe the difficulty encountered when trying
to discriminate E. coli from Shigella spp. Differentiation of patho-
genic E. coli strains from Shigella spp. is challenging because of the
close genetic relatedness of the organisms. In some instances, even
molecular analysis, such as 16S rRNA gene sequencing, is unable
to distinguish the organisms. In 2010, He et al. reported that the
BioTyper 2.0 software misidentified 39 Shigella isolates and 3 en-
terohemorrhagic E. coli (EHEC) isolates as E. coli, with the authors
rightfully noting the absence of Shigella sonnei from the database.
Based upon the spectra generated, the authors concluded that re-
dundant ribosomal proteins could not be used to accurately dis-
tinguish Shigella and EHEC from nonpathogenic E. coli (169).
Some investigators concluded that MALDI-TOF MS, at its current
point in development, is inappropriate for the identification of
Shigella species (170) or have implemented supplementary testing
for definitive determinations (171). Additional in-depth analysis
of the spectral output of pathogenic E. coli and Shigella species
isolates will obviously be required for enhanced discrimination
between these organisms.
Proteus spp. In a study of Proteus mirabilis isolates totally or
intermediately resistant to amoxicillin-clavulanic acid, cefoxitin,
cefotaxime, or ceftazidime, MALDI-TOF MS was utilized in com-
parison to repetitive element sequence-based PCR (rep-PCR)
(Diversilab; bioMérieux) for the typing and classification of these
organisms. Colonies were cultured on blood agar and overlaid by
using DHB as a matrix material for MALDI-TOF analysis. The
SARAMIS database was utilized for identification and character-
ization of the P. mirabilis isolates. Among these strains, high levels
of genomic variability were detected by both rep-PCR and
MALDI-TOF MS. Common clustering of strains could be
achieved with rep-PCR and MALDI-TOF MS with some overlap;
however, the authors concluded that a determination as to which
technique was more suited to this type of analysis could not be
elucidated due to the small sample size analyzed by these tech-
niques (172).
Cronobacter spp. Bacteria within the genus Cronobacter are
closely related to members of the genus Enterobacter and are the
causative agents of opportunistic food-borne outbreaks. Using the
SARAMIS database software, Stephan et al. generated a compre-
hensive library of spectra generated by using 54 Cronobacter
strains spanning the six species included in the Cronobacter genus.
Importantly, a number of non-Cronobacter strains were also in-
cluded in the construction of this library, particularly those be-
longing to the closely related genus Enterobacter. The authors used
these 54 strains to determine SuperSpectra for defining this genus.
During library construction, biomarker masses were determined
for protein targets that were Enterobacteriaceae specific, Cronobac-
ter specific, and Cronobacter species specific. Whole cells were uti-
lized without previous protein extractions and analyzed by
MALDI-TOF MS in this study. The generated library was subse-
quently challenged with 36 additional Cronobacter isolates gath-
ered from a field study whose identities were previously confirmed
by PCR and 8 non-Cronobacter isolates. MALDI-TOF MS was able
to derive genus- and species-level identifications for these isolates
or identify them as non-Cronobacter isolates in the case of nontar-
get strains. Cluster analysis was performed by using whole spectra
derived from these Cronobacter isolates, with the resultant den-
drogram strongly resembling dendrograms derived by using mo-
lecular techniques (16S rRNA sequencing, fluorescent amplified
fragment length polymorphism analysis, and ribotyping) (173).
Two studies recently examined the use of MALDI-TOF MS for
the identification of Cronobacter compared to other diagnostic
procedures. Zhu et al. analyzed the ability of MALDI-TOF MS to
identify Cronobacter spp. and closely related members of the En-
terobacteriaceae compared to molecular (16S rRNA sequencing)
and phenotypic (API 32E; bioMérieux) methods of definitive
identification. By using phenotypic approaches, only 22% of iso-
lates could be identified to the species level, 66% of isolates could
be identified on a genus-specific level, and 14% could not be iden-
tified. 16S rRNA gene sequencing and MALDI-TOF MS were able
to distinguish all isolates on the species level, with the mass spec-
trometry-derived identifications being more discriminating
(174). As sequencing methodologies would likely require addi-
tional time due to sequence generation and analysis time along
with time needed for the extraction and processing of DNA,
MALDI-TOF MS represents a logical choice for the analysis of
these types of isolates due to its strong discriminatory power and
rapid analysis time.
Cetinkaya et al. described different findings when analyzing
Cronobacter species isolates by MALDI-TOF MS. Using a very
small sample set of 6 isolates, MALDI-TOF MS was performed
and analyzed by using an in-house database. All strains were iden-
tified as C. sakazakii by MALDI-TOF analysis and as Enterobacter
sakazakii by phenotypic approaches (API 20E and API ID32E), as
Cronobacter sp. is not included in their databases. 16S rRNA and
fusA gene sequencing revealed that three distinct species were
present in this small sample set. The authors concluded that mo-
lecular techniques such as 16S rRNA and fusA gene sequencing
and multilocus sequence typing (MLST) are more reliable mech-
anisms of Cronobacter identification (175); however, the use of an
unverified in-house database often raises questions related to the
robustness and accuracy of the results obtained by their respective
MALDI-TOF analyses (173). Biogrouping analysis among the
same species was possible by using a database created in-house
(176). As comprehensive molecular analysis such as gene sequenc-
ing is not available to a large number of clinical laboratories, nor is
it appropriate for use in situations where rapid identifications are
necessary, a more complete analysis of MALDI-TOF MS for the
identification of species within this sample set of organisms is
warranted prior to drawing conclusions regarding the clinical util-
ity of this technique.
Further demonstrating the discriminatory power of MALDI-
TOF MS for the characterization of Cronobacter, Karamonová et
al. investigated the use of the technique to identify different bio-
groups (biovars) within the C. sakazakii species. A collection of 29
C. sakazakii isolates with biovars previously determined and 5
Enterobacter isolates of various species were processed by using a
whole-cell technique and analyzed by MALDI-TOF MS using the
Bruker BioTyper 2.0 system to verify the genus Cronobacter, and a
specific database was then created in order to analyze members of
each biovar. The database was then challenged with 10 C. sakazakii
isolates of undetermined biovars, which were able to be grouped
into biovars by MALDI-TOF MS. The groupings were confirmed
by biochemical testing, and the authors concluded that MALDI-
Clark et al.
570 cmr.asm.org Clinical Microbiology Reviews
TOF MS was a rapid and acceptable method for the discrimina-
tion of biogroups of bacteria within the same species (176).
Enterobacter cloacae complex. The Enterobacter cloacae com-
plex of organisms is composed of six species of Enterobacter and is
responsible for significant numbers of nosocomial infections. A
number of biochemical and molecular methods were utilized in
an attempt to separate members of this complex of organisms into
single species, but identification to the species level remains diffi-
cult even when using some of the most discriminatory molecular
methods. Pavlovic et al. sought to evaluate the ability of MALDI-
TOF MS to generate species-level identifications from separate
members of this complex of bacteria. The authors utilized
MALDI-TOF MS in conjunction with an in-house-developed
multiplex PCR to determine species-level identifications.
MALDI-TOF MS was found not to be able to identify 11 of 56
isolates determined to be members of the Enterobacter cloacae
complex by biochemical methods, highlighting a shortcoming of
the technology. However, as MALDI-TOF MS was able to deter-
mine species-level identifications for some members of the com-
plex or characterize the isolates as either Enterobacter cloacae or a
member of the Enterobacter cloacae complex, use of dnaJ duplex
real-time PCR in combination with MALDI-TOF MS was sug-
gested for cases where a definitive species-level identification is
necessary (177). It remains to be determined if creation of a
MALDI-TOF MS database compiled with spectra derived exclu-
sively from members of the Enterobacter cloacae complex of or-
ganisms would allow for the identification of species-specific bio-
markers to enhance the resolving power of MALDI-TOF MS
toward rapid species-specific identification of members of the En-
terobacter cloacae complex without the need for additional confir-
matory molecular verification.
Pantoea spp. Members of the genus Pantoea are infrequently
encountered in clinical settings but have been reported as etiolog-
ical agents in sporadic cases. By far the most encountered clinical
species, Pantoea (Enterobacter) agglomerans is often associated
with wound infections, polymicrobial infections, or infections of
immunocompromised patients. A number of commercially avail-
able identification systems have difficulty reaching a determina-
tive identification of Pantoea spp. The overlapping taxonomy of
the Pantoea genus, which is comprised of former members of the
Erwinia and Enterobacter genera, adds further complication.
Rezzonico et al. sought to utilize MALDI-TOF MS to charac-
terize a collection of isolates previously identified as Pantoea spp.
The authors described a current classification scheme in need of
serious overhaul, noting significant inaccuracies with respect to
16S rRNA gene sequence data and the use of outdated classifica-
tion methodologies in the identification of Pantoea spp. The au-
thors used a combination of biochemical (BD Phoenix), molecu-
lar (gyrB and 16S rRNA gene sequencing), and MALDI-TOF MS
approaches to characterize a collection of 73 isolates comprised of
Pantoea spp. and other closely related isolates from the family
Enterobacteriaceae. Whole cells harvested from LB plates were
overlaid with matrix, and the generated spectra were imported
into the SAMARIS database. While gyrB sequencing provided a
more robust discriminatory mechanism than phenotypic meth-
ods, MALDI-TOF MS provided results almost equivalent to those
of gyrB sequencing and was also able to sort strains within the
genus into separate species and clades. The authors continued to
refine their search parameters and concluded that MALDI-TOF
MS was both accurate and suitable for the identification of Pan-
toea spp. but noted that the database would benefit from addi-
tional entries being added to further populate it with entries of
both environmental and clinical interest (178).
Plesiomonas shigelloides. Plesiomonas shigelloides is an uncom-
monly encountered member of the Enterobacteriaceae implicated
in cases of sporadic and epidemic travelers’ diarrhea. The organ-
ism is often isolated from water, soil, and other environmental
sources and represents a challenge to clinical microbiologists due
to familiarity of the organism. The organism is usually identified
by its biochemical profile, with serological and molecular methods
being available as extended options for definitive identification.
MALDI-TOF MS was evaluated for the identification of Plesiomo-
nas spp. from clinical specimens by using whole cells. Seventy-
four isolates were identified as Plesiomonas shigelloides by bio-
chemical methods and serologically typed prior to analysis by
MALDI-TOF MS, with Aeromonas and Shigella isolates being used
as outgroups for comparison. A database was constructed de novo,
and the authors determined that MALDI-TOF MS was suitable for
the identification of Plesiomonas shigelloides, but there was no cor-
relation between the spectral profiles generated and serogrouping
results (179).
Klebsiella/Raoultella spp. Members of the genus Klebsiella are
encapsulated Gram-negative organisms commonly encountered
in the clinical laboratory. K. oxytoca is an important nosocomical
pathogen that is closely related to K. pneumoniae and is phenotyp-
ically distinguished by a positive indole reaction. Members of the
genus Raoultella are closely related to Klebsiella but are infre-
quently isolated from clinical specimens. de Jong et al. evaluated
the use of MALDI-TOF MS to verify isolates identified as K. oxy-
toca by the BD Phoenix system (phenotypic identification) com-
pared to 16S rRNA gene sequencing. Ninety-nine presumptive K.
oxytoca clinical isolates were typed by MALDI-TOF MS using the
Bruker BioTyper 3.0 database. Eight identifications were discor-
dant, with these isolates being identified as members of the genus
Raoultella by MALDI-TOF MS. Indeed, 16S rRNA gene sequenc-
ing identified five of these questionable isolates as Raoultella spp.,
while the additional three were identified as K. oxytoca. Due to the
high level of spectral similarity between many Gram-negative spe-
cies, a 10% difference in the MALDI-TOF score between the best
and second-best results is necessary to accurately determine spe-
cies-level identifications. The authors concluded that applying
this rule to MALDI-TOF MS analysis increases the accuracy of the
technique for the genus-level discrimination of Raoultella from
Klebsiella oxytoca (180).
Yersinia spp. The yersiniae represent a clinically important
group of organisms infrequently encountered in the diagnostic
workup of clinical specimens. The determination of pathogenic
species within this genus is important during routine clinical di-
agnostics, as the identification of Y. pestis is reportable. The use of
MALDI-TOF MS for the broad species-level identification of
members of the yersiniae was investigated by two independent
research groups. In 2010, Lasch et al. developed a spectral database
consisting of Enterobacteriaceae, focusing on members of the ge-
nus Yersinia. As many members of the genus included in the study
represent virulent pathogens, inactivation of the organisms by the
addition of trifluoroacetic acid (TFA) was rightfully performed
prior to matrix overlay and MALDI-TOF MS analysis as well as
liquid chromatography-MALDI tandem mass spectrometry. Im-
portantly, and similar to other studies, the authors described the
presence of Enterobacteriaceae-specific biomarker peaks, which
MALDI-TOF Mass Spectrometry in Clinical Microbiology
July 2013 Volume 26 Number 3 cmr.asm.org 571
can be used to determine, in a general sense, members of this
family of bacteria. Moreover, Yersinia-specific genus- and species-
level peaks were also described. The authors discuss the identifi-
cation of candidate biomarker peaks to discriminate between Y.
pestis and Y. pseudotuberculosis, two clinically relevant and highly
genetically similar organisms with identical 16S rRNA gene se-
quences (181).
Ayyadurai et al. also investigated the use of MALDI-TOF MS
for rapid identification and typing of environmental and clinical
Yersinia isolates using a database constructed from spectra of 39
Yersinia strains representing 12 species and 3 biotypes of Y. pestis.
MALDI-TOF MS and the Bruker BioTyper 2.0 software were able
to identify Y. pestis and Y. enterocolitica isolates using the con-
structed database, in addition to being able to discriminate cor-
rectly between Y. pestis biotypes (182). Thus, MALDI-TOF MS
represents a robust and accurate method for the identification and
characterization of pathogenic and nonpathogenic yersiniae in
addition to providing epidemiological information regarding Y.
pestis biotypes.
One important aspect of analysis that is sometimes overlooked
is the protocols by which pathogenic organisms are inactivated. In
the case of a biosafety level 3 (BSL-3) organism such as Yersinia,it
is important to choose a mechanism of inactivation that will have
a minimal influence on the MALDI-TOF MS spectra generated in
order to garner optimal results. Couderc et al. compared ethanol
and TFA inactivation protocols in parallel with MALDI-TOF MS
to examine which inactivation methodology allowed the most ro-
bust spectra to be obtained for identification. In their study, eth-
anol inactivation yielded spectra of higher quality than spectra
obtained by using TFA extraction. Despite the fact that ethanol
inactivation of the organisms took substantially longer than TFA
inactivation, the authors concluded that it was still compatible for
routine use in the clinical laboratory for accurate identification of
Yersinia spp. (183).
Two Yersinia species, Y. pestis and Y. enterocolitica, have had
additional studies focused on the ability of MALDI-TOF MS to
identify and characterize these organisms. The following sections
will focus on these particular studies, the contribution of MALDI-
TOF MS to the identification and subtyping of Y. enterocolitica
isolates, and the ability of MALDI-TOF MS to discriminate be-
tween the highly related species Y. pestis and Y. pseudotuberculosis.
(i) Yersinia enterocolitica. Y. enterocolitica is an important eti-
ological agent of food-borne infections, with disease being associ-
ated with specific biotypes of the organism. Serological and bio-
chemical analysis can be performed to differentiate different
biotypes within the species, but this testing requires additional
time and cost to the patient, in addition to testing reagents which
might not be compatible with determinative algorithms of non-
specialized laboratories. Stephan et al. used MALDI-TOF MS in
combination with SARAMIS SuperSpectra analysis to identify and
subtype Y. enterocolitica isolates. A collection of yersiniae includ-
ing 19 Y. enterocolitica isolates and representative members of
other species were used to define the SuperSpectra for the different
species of Yersinia as well as the biotypes associated with Y. entero-
colitica isolates. The authors noted that different biotypes of Y.
enterocolitica displayed high levels of spectral similarity, but key
differences in the mass patterns among strains of different bio-
types were observed. In all, 15 genus-identifying, 25 species-iden-
tifying, and 48 biotype-identifying biomarkers were elucidated by
using this analysis. This collection of SuperSpectra was then rig-
orously challenged by using 117 additional Y. enterocolitica clini-
cal isolates of previously defined biotypes using an intact-cell
method. Cells were overlaid with sinapic acid-acetonitrile and
TFA, air dried, and analyzed by MALDI-TOF MS. All 117 strains
were correctly identified to the species level and were assigned
biotypes with 100% correlation to assignments made by tradi-
tional biotyping methods (184).
(ii) Yersinia pestis and Yersinia pseudotuberculosis. The spe-
cies Y. pestis and Y. pseudotuberculosis are highly related and have
recently been proposed to represent two lineages of a single species
rather than two different species. The ability of MALDI-TOF MS
to discriminate between these species was investigated previously
(181), with the study concluding that the technology was able to
accurately identify members of each genus. Wittwer et al. con-
ducted similar experiments using a collection of 61 well-charac-
terized Yersinia species isolates to generate a collection of spectra
using the SARAMIS software package for analysis. Importantly,
the authors reported that by using an unsupervised clustering ap-
proach, MALDI-TOF MS was able to identify all isolates to the
genus level, but 7 of the 11 Y. pestis isolates were identified as Y.
pseudotuberculosis at the species level. Once a supervised classifi-
cation mechanism was utilized by using algorithms derived by the
authors, MALDI-TOF MS was able to accurately distinguish Y.
pseudotuberculosis from Y. pestis isolates (185).
Nonfermenting Gram-Negative Bacteria
A number of studies have focused on the identification of nonfer-
menting Gram-negative bacilli using MALDI-TOF MS methods,
many of which examined strains isolated from cystic fibrosis (CF)
patients. In this section, we review the identification of this group
of bacteria by MALDI-TOF MS, with emphasis on both group-
wide and genus-specific studies (Table 4).
Teramoto et al. reported that MALDI-TOF MS identification
was accurate for Pseudomonas putida isolates, allowing identifica-
tion to the strain level with a cluster analysis and showing a phy-
logeny comparable to that of the DNA gyrase subunit B gene se-
quences (186). Mellmann et al. created a database containing the
spectra of 248 strains of 37 genera of human-pathogenic nonfer-
menting bacteria and used 16S rRNA gene sequencing as a refer-
ence standard for identification. In this study, MALDI-TOF MS
identified 82.5% of 80 clinical isolates to the species level by using
the BioTyper software (58). After improvements, they compared
the MALDI results to results obtained by eight international clin-
ical laboratories and reported accurate identification to the species
level for 98.75% of their isolates (12).
In a comparable study, MADLI-TOF methods accurately iden-
tified 512 clinical isolates and 47 reference strains of nonferment-
ing Gram-negative bacilli (54). In this work, P. aeruginosa, S.
maltophilia, and Alcaligenes (now Achromobacter) xylosoxidans
were correctly identified to the species level, but the Burkholderia
cepacia complex (BCC) isolates were poorly identified. Enrich-
ment of the spectrum database allowed 98% correct identification
of all strains tested at the species level. Discrepancies in these
results were clarified by analysis performed on B. cepacia at ap-
proximately the same time using two data analysis algorithms:
SARAMIS (Shimadzu and AnagnosTec) and BioNumerics (Ap-
plied Maths) (187). The authors accurately identified 65 and 69
out of 75 isolates of Burkholderia spp. to the species level with
SARAMIS and BioNumerics, respectively. In studies not specifi-
cally dedicated to P. aeruginosa and other nonfermenting Gram-
Clark et al.
572 cmr.asm.org Clinical Microbiology Reviews
negative species, identification to the species level was 100% for P.
aeruginosa and ranged from 56.6 to 100% for other species.
More recently, Fernández-Olmos et al. further investigated the
use of MALDI-TOF MS for the identification of nonfermenting
Gram-negative organisms from cystic fibrosis patients. In their
study, the authors utilized a collection of 182 isolates collected
from CF patients and stored over a 15-year period, representing a
wide range of diverse genera, as identified by phenotypic methods.
MALDI-TOF analysis was performed directly on colonies by using
the Bruker BioTyper 2.0 database, with discordant identifications
or nonidentifications being resolved by 16S rRNA gene sequenc-
ing. MALDI-TOF MS was determined to be significantly better for
the identification of this collection of isolates. MALDI-TOF MS
proved to be more discriminatory for members of the genus Ach-
romobacter and Pandoraea, in addition to better identifying spe-
cific members of the Burkholderia cepacia complex of organisms.
Organisms not identified by MALDI-TOF analysis (defined as a
“no identification” result) included members of the genus Ralsto-
nia, Bordetella petrii, Chryseobacterium, and Sphingobacterium
spiritivorum, which were determined to be due to the absence of
suitable reference spectra within the database (188).
Finally, a comparative analysis of two different MS platforms
and databases was recently performed to evaluate their respective
abilities to identify nonfermenting bacilli from CF patients. Two
hundred isolates were tested by using both the Bruker BioTyper
3.0 software and bioMérieux Vitek-MS (formally SARAMIS data-
base 3.62), using single-spot analysis for the Bruker analysis and
double-spot analysis for the Vitek-MS study. Identifications were
compared to biochemical- and molecular-derived identifications
made previously. 16S rRNA gene sequencing was utilized to re-
solve discordant results. In all, the Bruker system identification
was concordant with reference testing for 72.5% of isolates tested
to the species level of identification, with 3% of isolates being
unable to be identified, but required ethanol and FA extraction
steps more frequently than the Vitek-MS system. The Vitek-MS
system identified 80% of isolates to the species level, with 7% of
isolates not being able to be identified. Both systems were deter-
mined to be better than conventional phenotypic methods for the
identification of organisms within this set of isolates (189).
In the following sections, we review studies dedicated to the
identification of individual species within specific genera con-
tained with the nonfermenting Gram-negative bacilli.
Acinetobacter spp. Prior to the advent of specialized microbial
databases for the identification and analysis of different microbial
genera and species, an analysis of environmental bacteria by Ru-
elle and colleagues demonstrated that MALDI-TOF MS could be
utilized to identify the genus Acinetobacter versus E. coli and Sal-
monella (190). Since that time, the standardization of culture and
MS techniques facilitated significant progress in the characteriza-
tion of Acinetobacter species isolates with MALDI-TOF MS. Three
main types of studies have been undertaken. Studies examining
the antibiotic resistance profiles of these isolates are reviewed else-
where in this article, whereas here we examine works directed
toward the species-level identification of members of the genus in
addition to MALDI-TOF MS-based typing methods to analyze
Acinetobacter baumannii.
Two studies examining the ability of MALDI-TOF MS to dis-
criminate between different species within the genus Acinetobacter
were published. The first, by Šedo et al., sought to determine a
method of sample processing which would enhance MS-mediated
analysis of Acinetobacter spp. (191). The second study, by Álvarez-
Buylla et al., examined the use of the Bruker BioTyper as an alter-
native to molecular methods for the species-specific identification
of Acinetobacter spp. One hundred nine isolates were routinely
identified as Acinetobacter spp. by phenotypic methods (Vitek-2;
bioMérieux). MALDI-TOF MS analysis was performed by using
the Bruker BioTyper 2.0 software, and identifications were com-
pared to rpoB sequencing used in conjunction with PCR to detect
the presence or absence of the bla
OXA-51
-like gene. Importantly,
the authors concluded that MALDI-TOF MS was able to accu-
rately distinguish A. baumannii from other members of Acineto-
bacter spp.; however, using this software version, the technique
was not able to discriminate well among non-A. baumannii iso-
lates compared to rpoB sequencing (192) without elaborating on
the spectra currently available in that version of the BioTyper soft-
ware.
The Acinetobacter baumannii group of organisms is a collec-
tion of three closely related species, A. baumannii, A. pittii, and A.
nosocomialis, which are difficult to resolve by using phenotypic
methods. Espinal et al. investigated the ability of MALDI-TOF MS
to discriminate between these species using the BioTyper 2.0 soft-
ware and an extended database constructed in-house. Strong dis-
crimination between these highly related species was observed,
making MALDI-TOF MS a rapid and attractive alternative to
costly molecular analyses needed for species-level determination
among these isolates ( 193). Finally, Mencacci et al. recognized the
potential of MALDI-TOF MS for real-time detection of pathogens
and chose to analyze the technology for the detection of nosoco-
mial Acinetobacter baumannii outbreaks compared with rep-PCR
(Diversilab). The authors concluded that the technology could be
applicable to real-time evaluation of Acinetobacter baumannii out-
breaks, providing results well before established molecular meth-
ods (194).
Burkholderia cepacia complex. The Burkholderia cepacia com-
plex (BCC) represents a group of closely related, nonfermenting,
Gram-negative rods that are important opportunistic pathogens,
particularly in patients with cystic fibrosis (CF). Members of this
group of bacteria can be isolated from both the environment and
infected patients and can be readily transmitted between CF pa-
tients, resulting in outbreaks (195). Differentiation of the species
contained within the complex is challenging by biochemical anal-
ysis alone, with phylogenetic techniques such as recA 16S rRNA
gene sequencing and MLST predominating for species-specific
analysis of members of the complex (196). Additionally, the large
genomes associated with members of the complex can hinder both
molecular- and phenotypic-based identification (197), and in
some cases, multiple assays are necessary to discern specific spe-
cies. Thus, the implementation of proteome-based identification
is an attractive option for determinative analysis of members of
this complex of bacteria.
A number of recent studies have examined the ability of
MALDI-TOF MS to fill the role of a rapid and automated system
for the species-specific discrimination of members of the B. cepa-
cia complex of organisms (187, 198, 199). In addition to studies
evaluating the technology for the routine identification of bacteria
from CF patients compared to phenotypic methods (200), one of
the first investigations of the technology included an analysis of 75
isolates of BCC or BCC-like organisms and used MALDI-TOF MS
to generate MS spectra analyzed by SARAMIS and BioNumerics
(version 4.5) software. MALDI-TOF MS with cluster analysis pro-
MALDI-TOF Mass Spectrometry in Clinical Microbiology
July 2013 Volume 26 Number 3 cmr.asm.org 573
vided good discrimination between members of the BCC and out-
liers, in addition to phylogenetic analysis of species within the
complex (187).
A second study evaluated two different intact-cell MS methods
for the analysis of spectra for the discrimination of BCC species,
including members of taxon K, representing a relatively new and
loosely important classification of organisms within the BCC
demonstrated to consist of novel species (201). Analyzing 26 ref-
erence and 146 clinical isolates from sputum samples of CF pa-
tients, Minan et al. reported the identification of specific biomark-
ers for the discrimination of members within the BCC from other
nonfermenting Gram-negative rods. Species-level discrimination
using biomarkers visualized by using the in-gel view of the soft-
ware was also described. Clustering analysis also allowed the dis-
crimination of closely related species within the BCC (199).
The most recent study involving the application of MALDI-
TOF MS for the discrimination of members of the BCC from CF
patients was reported by Lambiase et al., who compared MS data
to identifications made by PCR-restriction length polymorphism
(RFLP) analysis of the recA gene. Each of 57 isolates was identified
by phenotypic methods (BD Phoenix with API 20 NE used for
confirmation) and MALDI-TOF MS using the BioTyper version
1.0 software. DNA was also prepared from each sample, and the
recA gene was PCR amplified and subjected to RFLP. Both meth-
ods performed amicably for the identification of isolates to the
species level, with RFLP providing slightly more discriminatory
results in its ability to discriminate between two different lineages
of B. cenocepacia but conversely being more expensive than
MALDI-TOF MS (198).
Burkholderia mallei and Burkholderia pseudomallei. Both
Burkholderia mallei and Burkholderia pseudomallei are closely re-
lated Gram-negative organisms with high pathogenic potential in
animals and humans. B. pseudomallei is the etiological agent of
melioidosis, a condition acquired through the inhalation, inges-
tion, or invasion of the organism, with disease manifesting as ab-
scess formation in internal organs and occasionally as septic
shock. Conversely, B. mallei is the causative agent of equine glan-
ders and infrequently infects humans in areas of endemicity (202).
The organism cannot persist in the environment outside its host,
with both species being facultative intracellular bacteria that are
capable of replication inside epithelial and phagocytic cells (203).
When isolated, both species are considered reportable and repre-
sent virulent and dangerous biosafety level 3 (BSL-3) organisms.
Identification of B. pseudomallei can be difficult in the clinical
laboratory, as both molecular and phenotypic assays may not be
discriminatory enough to differentiate it from closely related spe-
cies, including B. thailandensis (204). Additionally, full analysis
and definitive identification of Burkholderia isolates can take up to
1 week (205).
Lau et al. evaluated the use of MALDI-TOF MS for the identi-
fication of B. pseudomallei using the BioTyper version 3.0 soft-
ware. As reported in this study and elsewhere, the routine database
does not contain reference spectra for select agents, and identifi-
cation would normally require the use of an extended commercial
database available from Bruker (206, 207). In this instance, the
authors supplemented the version 3.0 database with spectra from
B. pseudomallei and the closely related organism B. thailandensis.
MALDI-TOF MS performed well in the accurate identification of
B. pseudomallei, with the authors noting that the inclusion of ad-
ditional validated spectra would enhance the accuracy of identifi-
cation of these and other related species (204).
Two additional studies have examined the identification of
both B. mallei and B. pseudomallei by MALDI-TOF MS, one of
which examined the ability of MALDI-TOF MS to identify these
species both directly from positive blood culture bottles as well as
from plated media by using an in-house library generated from
collected spectra of Burkholderia strains (207). The second study
sought to further evaluate the technology for the identification of
both species, where MALDI-TOF MS was able to accurately dis-
criminate between members of both species after careful selection
of reference spectra. Additionally, the authors reported that
spectra generated from B. mallei exhibited higher levels of ho-
mogeneity than did those from B. pseudomallei, with the type
strain of B. pseudomallei being separated from more recent
isolates of B. pseudomallei. This may be due to genetic modifi-
cation of the type strain due to significant passage or inappro-
priate medium combinations (205). This finding represents a
potential challenge with regard to standardization of specimen
age and levels of manipulation of microbes submitted for
MALDI-TOF MS identification.
Pseudomonas spp. The genus Pseudomonas is perhaps one of
the most complex genera, representing an ever-growing number
of species. Recently, a comparison of MALDI-TOF MS and mul-
tilocus sequence typing (MLST) was performed to evaluate the
ability of MS to accurately identify species of Pseudomonas. A total
of 141 Pseudomonas strains (133 of which were type strains, fur-
ther illustrating the diversity of bacteria included in this genus)
were processed for MALDI-TOF MS and MLST. MS spectra were
obtained and compiled by using SARAMIS software, and a phy-
logram was created to examine the relatedness of the strains in-
cluded in the study. Compared to each other, both MLST and
MALDI-TOF MS allowed for resolution of the included Pseu-
domonas species to the group or subgroup level. The authors con-
cluded that while MLST should be used for more in-depth phylo-
genetic studies, MALDI-TOF MS represents a rapid and viable
option for species-level differentiation and identification in clini-
cal and environmental microbiology settings (208).
Stenotrophomonas maltophilia. The most clinically relevant
species of the genus Stenotrophomonas is S. maltophilia. This organ-
ism is responsible for an increasing number of infections resulting in
diverse clinical presentations such as sepsis, urinary tract infections
(UTIs), and endocarditis. Vasileuskaya-Schulz et al. recently evalu-
ated the use of the MALDI-TOF MS BioTyper system in concert with
multilocus sequence analysis for the analysis of 21 strains belonging
to different species within the genus. Good conformity was observed
between the two techniques, with intra- and interstrain differences
being observed with MALDI-TOF MS spectra generated from these
isolates (209). Additional analysis of members of this group of non-
fermenting bacteria will be important to further examine the discrim-
inatory ability of MALDI-TOF MS for Stenotrophomonas spp.
Fastidious Gram-Negative Bacteria
Fastidious Gram-negative bacteria are a group of microorganisms
that require additional nutritional requirements for their cultiva-
tion. Many of these bacteria are substantial pathogens and signif-
icant concerns for public health. As such, both the MALDI-TOF
MS spectral libraries used to analyze these pathogens and sample
preparation mechanisms associated with these organisms need to
be standardized. As mentioned on numerous occasions through-
Clark et al.
574 cmr.asm.org Clinical Microbiology Reviews
out this review and others, the construction of refined spectral
databases greatly enhances the capacity of MALDI-TOF MS to
provide rapid and accurate species-level identifications for a wide
variety of bacterial pathogens. These spectral databases are usually
constructed from in-house collections of isolates from clinical
material or from established collections which have had signifi-
cant analysis previously performed on them to serve as references
in comparative studies.
Sample preparation methods for MALDI-TOF MS analysis of
fastidious Gram-negative rods, including dangerous bacteria.
Cunningham and Patel raise an excellent point in their recent
publication examining the use of MALDI-TOF MS when analyz-
ing select agents. They point out that while database enhancement
is demonstrated to improve MS performance, access to select
agents is quite limited, and as such, construction of specialized
databases for species such as Francisella tularensis, Burkholderia
pseudomallei, and Brucella spp. would be difficult for most labo-
ratories (206). The BioTyper reference library does not contain
spectra for the identification of select agents; such spectra are con-
tained in the security-relevant library, which can be queried in
tandem with the reference library, as previously reported. The
authors evaluated the MALDI-TOF MS system for the identifica-
tion of 20 isolates representing select agents. Spectra were evalu-
ated by the BioTyper software (version 3.0) with and without the
use of the extended security-relevant library (version 1.0) (206).
Using the BioTyper software alone, 18 isolates returned spectra
with scores of ⬎1.7 but were identified as having “no reliable
identification” due to a lack of references in the database, and 2
Burkholderia pseudomallei isolates returned identifications of
“Burkholderia thailandensis” with scores that would be acceptable
for genus-level identification, along with a comment mentioning
that B. thailandensis is related to B. pseudomallei. The addition of
the security-relevant database resulted in species-level identifica-
tion of five F. tularensis isolates, with two additional F. tularensis
isolates being identified to the genus level. The extended database
was also used to identify Brucella and Burkholderia to the genus
level, with species-level identifications being achieved in some
cases. Importantly, the authors warn that a result of “no reliable
identification” could potentially lead to additional testing of these
problem isolates, increasing the potential for exposure to labora-
tory personnel. Finally, the authors rightfully conclude that for
optimal patient care and laboratory safety, spectra for members of
these genera should be included in the standard BioTyper data-
base, and the direct-colony approach for analysis of Burkholderia,
Francisella, and Brucella species isolates should not be performed
(206).
Drevinek et al. recently evaluated sample preparation methods
for highly dangerous bacteria in an attempt to propose a process-
ing scheme to streamline and ensure safe manipulation of these
organisms for MALDI-TOF MS (195). While direct analysis of
intact cells was proposed for a number of organisms as the optimal
approach for analysis by MALDI-TOF MS, work with BSL-3 or-
ganisms often dictates their inactivation prior to manipulation in
the laboratory to minimize exposure risks. Four different speci-
men preparation methods were analyzed for BSL-3 agents, includ-
ing Bacillus anthracis, Clostridium botulinum, Brucella melitensis,
Burkholderia mallei, Francisella tularensis, Shigella dysenteriae,
Vibrio cholerae, Yersinia pestis, and Legionella pneumophila. Anal-
ysis to determine the most appropriate method focused on differ-
ent aspects of sample preparation and MALDI-TOF MS analysis,
including inactivation of the organism, concentration of protein
obtained from the specimen, and quality and stability of the MS
spectra obtained. Importantly, the authors found that ethanol
pretreatment and the use of formic acid with acetonitrile for pro-
tein extraction, as described by Marklein et al. (210), could be used
as a rapid and universal method for the MALDI-TOF MS process-
ing of these sample types. Additionally, inactivated bacterial ly-
sates in 300 l water and 900 l ethanol were recommended for
interlaboratory evaluations, although the quality and robustness
of spectra obtained from these samples decrease, making strain-
level identifications more difficult over time (49).
Brucella spp. Ferreira et al. used a collection of 131 Brucella
human isolates (Brucella abortus, Brucella melitensis, and Brucella
suis) and obtained 100% identification to the genus level ( 211).
The identification to the species level was not reliable. A spectrum
bank was created from 12 Brucella strains from six species by using
the MALDI BioTyper 2.0 system. Species identification may not
represent a serious limitation for the technology, since some tax-
onomists propose the grouping of classical Brucella species into
one species, as biovars of Brucella melitensis. Others argue that
despite their high level of DNA identity, Brucella species can be
distinguished by distinct biochemical and fatty acid characters as
well as by a marked host range (e.g., B. suis for swine, B. melitensis
for sheep and goats, and B. abortus for cattle) (212). It is reason-
able that identification as Brucella spp. would be useful for clinical
laboratories who will be alerted to handling of the select agent with
proper biosafety precautions according to LRN guidelines.
Since the previous publication, Lista et al. reported the con-
struction of a spectral database to be used for the species-level
identification of Brucella isolates using strains that demonstrate
genetic variation at the species and biovar levels by multilocus
variable-number tandem-repeat analysis (MLVA). This database
was then used to analyze 152 Brucella isolates also preliminarily
characterized by MLVA using the BioTyper 2.0 software. Using
the data analysis parameters reported in their article, the authors
concluded that MALDI-TOF MS could indeed discriminate be-
tween and accurately identify different species and biovars of Bru-
cella (213).
Bartonella spp. Members of the genus Bartonella are zoonotic
bacteria that are becoming increasingly recognized as etiological
agents of human disease. The phenotypic analysis of these organ-
isms is difficult and not well defined due to poor biochemical
reactivity associated with the genus. MALDI-TOF MS has recently
been proposed as a mechanism to determine species-level identi-
fications for members of this genus. Using type strains represent-
ing 17 species of Bartonella, Fournier et al. utilized the BioTyper
software (which did not contain spectra generated from Barto-
nella) for spectral analysis. The generated spectra were then used
to identify an additional 39 isolates. MALDI-TOF MS was able to
correctly provide species-level identifications for all strains tested,
with most generating scores of ⱖ2.0. Moreover, subspecies-level
identifications of B. vinsonii isolates could be determined, in ad-
dition to genotype discrimination between the two genotypes as-
sociated with B. henselae (214).
Francisella spp. For identification of Francisella spp. and Fran-
cisella tularensis, the causative agent of tularemia, the phenotypic
discrimination of closely related, but differently virulent, Franci-
sella tularensis subspecies is difficult and often produces ambigu-
ous results. Seibold et al. reported the testing of reference spectra
from five representative strains of various Francisella spp. and sub-
MALDI-TOF Mass Spectrometry in Clinical Microbiology
July 2013 Volume 26 Number 3 cmr.asm.org 575
species, including F. tularensis, establishing spectral references
and evaluating the capability of MALDI-TOF MS to correctly
identify 45 blind-coded Francisella strains against a database
(215). Identity was confirmed by 23S rRNA sequencing. In this
study, all strains were correctly identified, with both methods
showing perfect agreement at the species level as well as at the
subspecies level. The identification of Francisella strains was re-
producible using replicate testing examining different culture me-
dia, cultivation times, serial passages of the same strain, prepara-
tion protocols, and mass spectrometers. In an additional study,
Muller et al. used MALDI-TOF MS to identify F. tularensis isolates
from a field study involving European brown hares. The authors
reported that isolates generated strong spectra and that MALDI-
TOF MS was able to rapidly identify isolates to the subspecies level
(216).
Haemophilus spp. Members of the genus Haemophilus are
nonmotile bacilli that are identified based on their nutritional
requirements for X and V factors found in blood. Recovery and
identification from culture can be challenging, as most species are
not readily isolated from culture on blood-containing media, of-
ten requiring chocolate agar for their isolation. There are cur-
rently 10 recognized species of Haemophilus, some of which can be
further classified into distinct serotypes that can provide valuable
epidemiological data in outbreak situations by either serological
or molecular methods. Members of the species H. influenzae can
be further separated into biotypes that were historically associated
with disease presentations, antibiotic resistance patterns, and
sources of infection.
MALDI-TOF MS was utilized in the identification and charac-
terization of different members of the genus Haemophilus. Hae-
mophilus species, with an emphasis on Haemophilus ducreyi, were
identified by MALDI-TOF MS (217). Strains of Aggregatibacter
(formerly Actinobacillus) actinomycetemcomitans were also iden-
tified (217). Additional studies demonstrated good genus-level
identification of Haemophilus, Aggregatibacter, Cardiobacterium,
Eikenella, and Kingella (so-called HACEK species) by MALDI-
TOF MS. Couturier et al. tested 103 species of HACEK group
microbes and achieved 93% genus-level identification but only
66% species-level identification with the Bruker database (218).
During a study focusing on the differentiation between H. parah-
aemolyticus and H. paraphrohaemolyticus, a distinct taxon of un-
characterized Haemophilus spp. was described and validated by
16S rRNA gene sequencing as unique. This unique species, now
named Haemophilus sputorum, was additionally confirmed by
MALDI-TOF MS using the BioTyper version 2.0 software due to
the generation of a spectrum unique from those of other bacterial
species analyzed (219).
Nontypeable H. influenzae causes a number of serious etiolo-
gies, including pneumonia, meningitis, and sinus and ear infec-
tions. Microbiological identification of this particular serotype of
H. influenzae is difficult, as it is phenotypically similar to H. hae-
molyticus, a species that is not usually associated with serious in-
fections. Several molecular techniques, such as gene-specific PCR
and sequence analysis of outer membrane protein genes, have
proven to be unsuitable for definitive discrimination between
these two species, with multilocus sequence typing (MLST) pro-
viding good discrimination. Zhu et al. recently utilized MALDI-
TOF MS using the BioTyper version 2.0 software to discriminate
between these species. Rightfully noting that the commercial da-
tabase contained only 10 H. influenzae reference spectra, the au-
thors constructed an in-house version with additional spectra de-
rived from 10 nontypeable H. influenzae and H. haemolyticus
isolates and then evaluated the database against 42 nontypeable H.
influenzae and 10 H. haemolyticus isolates. The authors concluded
MALDI-TOF MS, using the extended database constructed in-
house, was an excellent method for differentiating these two
closely related organisms (220).
Vibrio spp. The use of MALDI-TOF MS for the characteriza-
tion of Vibrio species was investigated. MALDI-TOF MS also ac-
curately identified 67 isolates of Vibrio spp. from 16 different spe-
cies to the species level and discriminated between closely related
species, such as Aeromonas spp., Photobacterium damselae, and
Grimontia hollisae (221). In another study, 20 strains of Vibrio
parahaemolyticus were successfully identified to the species level
from nine different species of Vibrio (222). In a survey of 30 envi-
ronmental isolates from wastewater sources, MALDI-TOF MS
was successfully used to identify closely related Vibrio species us-
ing the BioTyper software (223).
Aeromonas spp. In two independent studies, 32 isolates of
Aeromonas from 17 different species and 34 out of 52 environ-
mental isolates of Aeromonas spp. were correctly identified (224,
225). In a more recent examination of 171 Aeromonas isolates
representing type strains and clinical and environmental isolates,
the Bruker BioTyper version 2.0 software was evaluated for genus-
and species-level identifications. MALDI-TOF MS was able to
determine genus-level identification with 100% accuracy and spe-
cies-level identifications with 90% (clinical isolates), 93.9% (envi-
ronmental isolates), and 90.6% (type strains) accuracies (226).
Benagli et al. described difficulties in determining the taxo-
nomic standing of some isolates of Aeromonas spp. using pheno-
typic methods and described the development of a database for
the rapid characterization of such isolates. Despite complex and
evolving taxonomy within the genus, gene sequencing and other
time-consuming and labor-intensive molecular methods have
predominated when attempting specific identification of Aeromo-
nas isolates. Using SARAMIS, the authors assembled a database
containing information from 94 Aeromonas isolates and gener-
ated SuperSpectra to provide identifications for 11 different spe-
cies, and these identifications were compared to results from gyrB
sequencing and generated useful data regarding Aeromonas tax-
onomy. The representative database was then used to characterize
741 strains of Aeromonas, with 93% of these isolates being identi-
fied successfully and with unidentified isolates not having ade-
quate spectra represented in the database (227).
Campylobacter spp. Members of the Campylobacter genus have
also been studied by MALDI-TOF MS and represent one of the
earliest genera to be evaluated for species-level identification by
the technology. In 1999, Winkler et al. published findings of a
study of the direct analysis of Campylobacter and Helicobacter us-
ing methanol-inactivated isolates. The study determined that
MALDI-TOF MS could be used to differentiate between the two
genera as well as related members of different species through the
identification of specific spectral peaks corresponding to bio-
markers (228). Subsequent studies (229, 230) further examined
the ability of MALDI-TOF MS to provide rapid and accurate spe-
cies-level identifications for members of the genus, with encour-
aging results.
More recent attempts to identify and characterize Campylobac-
ter isolates have also been successful. After constructing a spectral
database using the BioTyper 1.1 software package, Alispahic et al.
Clark et al.
576 cmr.asm.org Clinical Microbiology Reviews
reported 100% identification to the species level for 144 clinical
isolates of Campylobacter spp. and the related genera Arcobacter
and Helicobacter. Additionally, it was noticed that mass spectral
fingerprints obtained from thermophilic Campylobacter species
(C. jejuni, C. coli, and C. lari) were distinct from nonthermophilic
species (C. fetus and C. hyointestinalis)(231), potentially provid-
ing preliminary targets for biomarker analysis for more discrimi-
natory typing methods using MALDI-TOF MS. Interestingly, the
choice of medium used for cultivation of Campylobacter (in addi-
tion to Helicobacter and Arcobacter) in this study proved to have
bearing on MS spectral integrity, as bacteria grown on modified
charcoal-cefoperazone-deoxycholate agar generated poor spectral
output. As this agar is routinely used for the identification of Cam-
pylobacter spp., additional culturing on supplemental agar may be
necessary prior to definitive identification by MALDI-TOF.
In a rigorous study by Bessède et al., 1,003 successive Campy-
lobacter-like strains from the French National Reference Center
for Campylobacter and Helicobacter were analyzed by MALDI-
TOF MS, with these identifications being compared to those made
by using phenotypic and molecular methods, including real-time
PCR. The Bruker BioTyper 2.0 software package was utilized to
analyze the spectra collected from these isolates. Compared with
molecular methods, MALDI-TOF MS provided similar results,
with the exception of a notable discrepancy in the misidentifica-
tion of four isolates of C. jejuni as either C. coli or C. fetus with
identification scores of ⬎2. Four of the cultures analyzed were
determined to contain a mixture of organisms, for which MALDI-
TOF MS was not able to identify each of the organisms present
(232).
Finally, a comparison between routine clinical diagnostic
methods relying on biochemical profiling/molecular typing and
MALDI-TOF MS was undertaken by Martiny et al. This compar-
ative study examined the ability of the API Campy (bioMérieux)
biochemical-based assay, the Vitek-2 system using the Neisseria-
Haemophilus card, and MALDI-TOF MS using the Bruker Bio-
Typer database to identify 224 clinical and 10 reference isolates
representing Campylobacter, Helicobacter, and Arcobacter. For C.
coli and C. jejuni isolates, MALDI-TOF MS correctly identified
100% of these strains, with an overall sensitivity of 98.3% for all
isolates tested. In addition to significantly outperforming the
other methods with respect to identification of isolates at the spe-
cies level, MALDI-TOF MS did not require any additional testing
for the identification of these isolates, in contrast to the pheno-
typic identification systems. The authors concluded that MALDI-
TOF MS should be the method of choice for the routine identifi-
cation of these organisms (233).
Helicobacter spp. In comparison with Campylobacter, few stud-
ies have specifically evaluated MALDI-TOF MS for the character-
ization of Helicobacter species. Winkler et al. previously reported
that members of the genus Helicobacter could be differentiated
from Campylobacter by MALDI-TOF MS and that species within
the genus could be differentiated from each other (228). In a study
involving Neisseria gonorrhoeae (described below) and H. pylori,it
was reported that due to high intraspecies diversity accumulated
among a collection of 2 reference and 22 clinical strains of H.
pylori, the use of MALDI-TOF MS for the identification of H.
pylori appeared difficult (234). However, Alispahic et al. later con-
firmed the use of MALDI-TOF MS for the identification of Heli-
cobacter pullorum and H. pametensis using the BioTyper software
(231), indicating that perhaps species-specific discrimination be-
tween members of this genus was possible.
Preliminary cluster analysis was able to determine some level of
relatedness between these 24 isolates, indicating the potential for
strain-specific analysis of H. pylori isolates (234). These studies
were expanded in a 2010 publication examining the application of
MALDI-TOF MS for the species-specific identification of H. pylori
(235). Using a collection of 2 reference strains and 17 clinical
isolates, MALDI-TOF MS analysis was performed with the Bruker
BioTyper 2.0 software. Despite significant differences observed in
MALDI spectra analyzed both in this study and previously, the
BioTyper database identified all isolates tested as H. pylori. Thus,
MALDI-TOF MS was deemed suitable for the identification of H.
pylori, even in the case of an organism which exhibits high levels of
genetic plasticity (234, 235).
Neisseria spp. Commercial databases for the identification of
Neisseria species isolates have also been undertaken. By using
BioTyper software, members of Neisseria spp. were accurately
identified, with 100% correct identification of 57 strains of Neis-
seria spp., including 29 Neisseria meningitidis and 13 Neisseria gon-
orrhoeae strains. No differences in the spectra were observed be-
tween different serogroups, leaving no evidence to support the use
of MADLI-TOF MS for epidemiological serotyping purposes
(236). Strains of N. gonorrhoeae were successfully identified by
MALDI-TOF MS by a comparison of selected peaks in the ob-
tained spectra without using any software for comparison (217).
With respect to intraspecies analysis, the variable combination
of the mass-to-charge (m/z) ratios of three ribosomal proteins was
utilized to group strains into one of four groups in an analysis of
278 N. gonorrhoeae isolates (234). Additionally, Lowe et al. re-
ported that the detection of a single-nucleotide polymorphism
within the fumC gene could be utilized to differentiate a hyper-
virulent ET-15 lineage of N. meningitidis from other isolates by
using MALDI-TOF MS (237). Thus, while few studies were con-
ducted to assess the ability of MALDI-TOF MS to definitively
characterize strains of Neisseria, MALDI-TOF MS has exhibited
promise toward the intraspecies analysis of this group of diverse
bacteria.
Moraxella catarrhalis. Currently, no definitive studies exam-
ining the typing of M. catarrhalis isolates have been undertaken
using commercially available MS databases. Schaller et al. re-
ported the description of two distinct 16S rRNA gene types of M.
catarrhalis and information regarding the profiling of OMPs by
MALDI-TOF MS. In their analysis, a collection of 18 characterized
M. catarrhalis isolates was utilized for analysis by an intact-cell
approach. Results were compared to 16S rRNA typing methods,
which classified the isolates into either RNA type 1, 2, or 3, which
have strong associations with specific OMPs expressed by differ-
ent M. catarrhalis strains. Strains belonging to rRNA type 2 or 3
exhibit a decreased or lack of expression of certain OMPs, which
represent potential vaccine candidates. Thus, M. catarrhalis iso-
lates can be broadly classified into two distinct groups. The au-
thors found agreement between results of MALDI-TOF MS and
16S rRNA typing methods in 15 of the 18 cases, with the 3 discrep-
ant isolates being misclassified within 16S rRNA groups 2 and 3.
Additionally, it was determined that each 16S rRNA group differ-
entially expressed additional OMPs (238). Although preliminary,
this study demonstrated the usefulness of MALDI-TOF MS for
typing of M. catarrhalis isolates, which could provide useful infor-
MALDI-TOF Mass Spectrometry in Clinical Microbiology
July 2013 Volume 26 Number 3 cmr.asm.org 577
mation for future epidemiological studies and in outbreak situa-
tions.
Legionella spp. Moliner et al. were one of the first groups to
evaluate MALDI-TOF MS for the identification of Legionella spp.
Noting that the early version of the Bruker database used in this
study contained only a few entries for Legionella spp. (one spec-
trum per species), the authors analyzed representative strains of all
Legionella species recognized at the time, including members of
the same species but different serogroups, and constructed their
own database in order to more robustly analyze members of the
genus. Spectra were obtained for all strains tested, and no differ-
ences were observed between members of the same species be-
longing to different serogroups. The assembled database was then
evaluated by using 237 additional isolates. MALDI-TOF MS was
found to be a good method for discrimination at the strain level,
particularly for L. pneumophila isolates, but as observed during the
construction of the database, serogroup-specific identification
was not possible (239).
In a subsequent study, the ability of MALDI-TOF MS to iden-
tify and group Legionella isolates was compared to that of mip
(macrophage infectivity poteniator) gene phylogenetic analysis
utilizing SARAMIS software. Using a collection of 453 clinical and
environmental samples representing 38 species of Legionella, Gaia
et al. used 216 of these isolates to construct a Legionella-specific
database of SuperSpectra and the remaining 237 isolates to evalu-
ate that database. MALDI-TOF MS identifications were compared
to identifications derived by mip sequence analysis and agglutina-
tion assays for Legionella species identification. Assembled den-
drograms revealed good correlation between mip analysis and
MALDI-TOF MS to determine relatedness between members of
the genus. All but two isolates could be identified to the species
level by MALDI-TOF MS. The authors concluded that by using
their constructed database, spectral differences between members
of the same genus could be identified; however, identification and
classification of strains into different serogroups were still not pos-
sible (240).
Fujinami et al. addressed the question of further examining
intraspecies differences in MALDI-TOF MS spectra between dif-
ferent L. pneumophila strains. Using 23 reference L. pneumophila
strains as references, mass spectra were generated and analyzed by
using the Bruker BioTyper version 1.1 software and compared to
results from PFGE analysis for phylogenetic classification of iso-
lates. PFGE analysis revealed a strong association between the geo-
graphical location of strain acquisition and organism relatedness,
a finding also observed in the MALDI-TOF MS clustering of or-
ganisms (241).
Svarrer and Uldum evaluated the ability of MALDI-TOF MS to
identify species other than L. pneumophila from samples of both
clinical and environmental origins. In their study, 33 isolates of
nonpneumophila Legionella species were obtained from respira-
tory patients, and 42 isolates were obtained from environmental
origins. All isolates were identified to the species level by mip se-
quencing and subsequently processed for MALDI-TOF MS anal-
ysis with the Bruker BioTyper 2.0 software. Isolates yielding dis-
crepant identifications were analyzed by 16 rRNA gene
sequencing. Here the authors reported that 3 of the 33 clinical
isolates had scores of ⬍2.0, yielding an overall sensitivity of 90.6%;
however, these isolates were identified correctly to the species level
compared with mip sequencing. Thirty-four of the 42 environ-
mental isolates were correctly identified by MALDI-TOF MS to
the species level, and 8 isolates yielded identification scores of
⬍2.0, with these isolates being either not represented or repre-
sented by only a single spectrum in the database (242).
Thus, MALDI-TOF MS represents an accurate method for the
species-level identification of Legionella species, with the level of
accuracy being strongly dependent upon the number of species-
specific spectra populating the database. Many of the authors of
the above-mentioned reviews call for databases with expanded
numbers of Legionella-specific entries to more accurately discrim-
inate between different species within the genus. However, sero-
group-level determinations are still not possible using this tech-
nology.
ANAEROBIC BACTERIA
The MALDI-TOF method has special importance in routine iden-
tification of pathogens that require long incubation times for iso-
lation and are biochemically inactive, such as anaerobic bacteria.
MALDI-TOF MS has also been utilized to evaluate subsets of an-
aerobic microorganisms isolated from defined biological niches.
The applicability of this method for routine identification of im-
portant human-pathogenic anaerobic bacteria was evaluated by
Shah et al., who showed that through the use of intact-cell
MALDI-TOF MS, Porphyromonas strains could be differentiated
(243). Nagy et al. reported 97% accuracy at the species level for
277 isolates and 9 species of Bacteroides (244). Stîngu et al. ana-
lyzed 84 strains of oral anaerobic bacteria in a study designed to
streamline the identification of microbes from patients with peri-
odontal disease. A database was created, and analysis of results
revealed identifications consistent with phenotypic and 16S rRNA
gene sequencing data. The technology was able to differentiate
between two species of Prevotella, P. intermedia and P. nigrescens,
a task which would usually be relegated to costly and time-con-
suming 16S rRNA gene analysis (245).
Nagy et al. tested 283 clinically relevant anaerobic isolates and
compared the results derived from the MALDI BioTyper 3.0 soft-
ware to conventional identification. In this study, 218 (77%) of
283 isolates were identified to the species level when a log score of
⬎2.0 was used as a cutoff, 31 isolates (10.95%) were identified to
the genus level (log score of 1.7 to 2.0), and 34 (12%) produced a
nonreliable identification (log score of ⬍1.7). Of 31 isolates with a
log score of 1.7 to 2.0, a total of 24 isolates were noted to have the
same species name as that determined by classical identification.
For the 44 discordant results, 16S rRNA gene sequencing con-
firmed the MALDI-TOF MS identification in 41 cases, leaving 3
isolates (0.7%) that were misidentified by MALDI-TOF MS (246).
In a 2011 article, La Scola et al. surveyed the ability of MALDI-
TOF MS to identify anaerobic microorganisms isolated from a
large clinical laboratory (247). Culture isolates from positive
blood culture bottles and other clinical specimens were subcul-
tured and grown in an anaerobic chamber. In contrast to other
studies, MALDI-TOF MS was utilized for the routine identifica-
tion of anaerobic isolates, with colonies not able to be identified by
MS methods being identified by 16S rRNA gene sequencing. Of
the 554 isolates tested, MALDI-TOF MS was able to identify 61%
of them, with the authors highlighting genus- and species-specific
trends likely due to a combination of the quality and number of
spectra available in the MALDI-TOF MS database. Of the 212
remaining isolates, 95% were able to be identified to the species
level by 16S rRNA gene sequencing. The authors concluded that
16S rRNA gene sequencing represents a strong technique to com-
Clark et al.
578 cmr.asm.org Clinical Microbiology Reviews
plement MALDI-TOF MS for the identifications of anaerobic bac-
teria, with MS technologies likely to be implemented as the pri-
mary determinative method in the future as the technology
continues to develop (247). It is also important to emphasize that
the ability of MALDI-TOF MS to identify anaerobic species cur-
rently is not as robust as it is for the routine species-level identifi-
cation of other groups of bacteria; therefore, the use of additional
confirmatory testing will likely be necessary for some time to
come.
In a series of evaluations of MALDI-TOF MS technology from
the same group, Veloo et al. examined 79 clinical isolates repre-
senting 19 anaerobic genera by comparing the Bruker and Shi-
madzu systems with 16S rRNA sequencing, achieving correct
identifications to the genus level for 61% and 71% of isolates and
to the species level for 51% and 61% of isolates, respectively.
When species not present in the database were excluded, correct
identification was achieved for 75% of isolates with the Bruker
system, versus 76.7% for the Shimadzu system (248), leading the
authors to conclude that database optimization was necessary. In
a subsequent evaluation of the technology for the identification of
Gram-positive anaerobic cocci, the authors used a specialized da-
tabase constructed in-house and compared these identifications
to those of 16S rRNA gene sequencing. MALDI-TOF MS per-
formed well, identifying 96 of 107 clinical isolates (249). Finally, in
an excellent review from the same year, the authors again highlight
the importance of expanded databases for the identification of
anaerobic bacteria (250).
More recently, the use of MALDI-TOF MS for the routine
identification of anaerobic bacteria from clinical specimens was
evaluated and compared to 16S rRNA gene sequencing by using
the Bruker BioTyper v2.0 software. Following the accurate iden-
tification of reference strains, 152 clinical isolates were analyzed.
MALDI-TOF MS correctly identified 130 (86%) isolates when the
threshold for confident identification was lowered from ⬎2.0 to
⬎1.8 and when an expanded database and protein extracts rather
than whole cells were utilized (251). This report demonstrated
higher levels of correct identifications than those reported in pre-
vious studies due to the fact that the authors rigorously optimized
both their analysis and identification protocols. Thus, sample
preparation and depth of the database to be utilized are important
considerations when utilizing MALDI-TOF MS for the identifica-
tion of anaerobic organisms.
Comparisons between different MALDI-TOF MS systems for
the identification of anaerobic microbes have also been under-
taken. Justesen et al. used both the Bruker BioTyper version 3.1
and SARAMIS software to examine 290 clinically relevant anaer-
obic isolates compared to 16S rRNA gene sequencing and re-
ported that the Bruker system generated more correct identifica-
tions at the species level but also more incorrect identifications
overall (252). This study also highlights important questions re-
garding database content and expansion and rightfully proposed
that cutoff values associated with a confident identification may
need to be adjusted on a genus- and species-specific basis. Of the
isolates that could not be reliably identified, a large proportion of
them belonged to the group of metronidazole-resistant Gram-
positive rods, despite spectra being available for members of these
groups within the system database. The authors concluded that
this either could represent an issue with species diversity, which
could be solved with database optimization, or could be due to a
biological issue with these species, which may result in the need for
an optimized extraction protocol for MALDI-TOF MS analysis of
these organisms (252).
MALDI-TOF MS Sample Preparation for Identification of
Anaerobic Bacteria
Specific protocols for sample preparation for the analysis of an-
aerobic bacteria have also been investigated. Fournier et al. com-
pared three preanalytical processing methods for MALDI-TOF
MS analysis of anaerobic bacteria: direct smear of intact cells and
chemical extraction (253). Two hundred thirty-eight consecutive
clinical isolates previously identified by conventional phenotypic
methods were used, with both chemical extraction and direct-
colony analysis being performed following 48 h of growth by MS
and the BioTyper version 3.0 software. The authors concluded
that there was no significant difference in the numbers of species-
level identifications derived between direct-smear and chemical
extraction after adjusting the acceptable cutoff score to 1.7, as
others have suggested for the identification of anaerobic bacteria.
Moreover, some isolates which were not able to be identified fol-
lowing chemical extraction were able to be identified by using
direct-smear methods, arguing that in some cases, protein extrac-
tion may be detrimental to optimal spectral generation (253).
Similar to published work examining protein extraction for
yeast and corynebacteria from the same group (254), Schmitt et al.
continued their evaluation of an on-plate method of FA extraction
for MALDI-TOF MS identification of anaerobic bacteria. Bacte-
rial isolates were smeared directly onto the MALDI plate, with 1 l
of 70% FA being directly deposited onto the smear. The samples
were subsequently overlaid with matrix and analyzed by MALDI-
TOF MS. Samples were analyzed with the Bruker BioTyper ver-
sion 3.0 software, with manufacturer-recommended cutoff log
score values being used for genus- and species-level determina-
tions. Identifications determined by MALDI-TOF MS were com-
pared to identifications derived from phenotypic methods, with
discrepant samples being resolved by 16S rRNA gene sequencing.
Of the 253 isolates included in the study, the BioTyper correctly
identified 232 (91.7%) to the genus level and 179 (70.8%) to the
species level, with expansion of the database being suggested as a
mechanism to improve species-level identifications (255).
Propionibacterium spp.
Propionibacteria represent a significant diagnostic challenge for
the clinical microbiology laboratory due to their slow-growing
nature and reduced biochemical activity. Despite past challenges
with routine identification, the use of MALDI-TOF MS was inves-
tigated for the phylogenetic analysis of isolates of Propionibacte-
rium acnes (256). P. acnes classification is based upon the presence
of different phylotypes present within the genus, as identified by
differences in cell wall sugars, carbohydrate fermentation tests,
molecular analysis, and serological methods. Some of these ge-
netic groups were clearly more associated with disease than others.
The authors used MALDI-TOF MS to evaluate the ability of MS-
based methods to rapidly classify P. acnes isolates into distinct
phylotypes compared to MLST. In total, 12 reference and 49 clin-
ical strains were analyzed. Of note, samples processed for MALDI-
TOF MS were processed by using ethanol precipitation and formic
acid prior to MALDI-TOF MS and analysis by the Bruker Bio-
Typer 3.0 software and database. The MS platform was able to
accurately discriminate P. acnes from other Propionibacterium
spp. tested. In an evaluation of culture conditions, the authors
MALDI-TOF Mass Spectrometry in Clinical Microbiology
July 2013 Volume 26 Number 3 cmr.asm.org 579
found that P. acnes was able to be accurately identified to the
species level following 24 h of incubation when only relatively little
biomass (pinpoint colonies) was available. MALDI-TOF MS was
able to group the collection of isolates tested into distinct phylo-
types, with more discriminatory MLST methods grouping the iso-
lates into 28 different sequence types. However, considering ad-
vantages in time to result and relative assay costs, MALDI-TOF
MS represents an attractive mechanism for discrimination be-
tween the main phylotypes of P. acnes (256).
Bacteroides spp.
The species-level identification of members of the Bacteroides ge-
nus is important, as the species of the isolate encountered can have
a substantial bearing on the antibiotic resistance profile of that
particular isolate. As such, a number of species-specific investiga-
tions using MALDI-TOF MS on members the genus Bacteroides
have been undertaken. Nagy et al. utilized a collection of 277
clinical isolates characterized by phenotypic methods includ-
ing RapID 32A and API20 ANA (bioMérieux) (244). Proteins
were additionally extracted and analyzed by MALDI-TOF MS
using the BioTyper 2.0 software package. Discrepant identifi-
cations between the MS and phenotypic methods were resolved
by 16S rRNA gene sequence analysis. All but 7 isolates gener-
ated scores of ⱖ2.0. Of the 270 isolates identified, 23 were
discrepant with biochemical testing, and 11 of these isolates
were analyzed by 16S rRNA gene sequencing. The MALDI-TOF
MS identification matched the 16S rRNA sequencing identifi-
cation in 10 out of the 11 cases, with the 11th isolate being
identified as B. vulgatus by MALDI-TOF MS, but a reliable
species identification could not be determined by 16S rRNA
gene sequencing. Additionally, biomarker peaks for rapid and
accurate discrimination between subtypes of B. fragilis could be
identified and were reproducible (244).
A subsequent study of 193 B. fragilis group isolates previously
identified by RapID 32A (bioMérieux) was undertaken by Cul-
ebras et al. with the goal to further evaluate MALDI-TOF MS with
the Bruker BioTyper 2.0 software for the routine identification of
Bacteroides spp. (257). When 16S rRNA gene sequencing was used
as a reference, MALDI-TOF MS correctly identified 168 (87%)
isolates to the species level, whereas the phenotypic method iden-
tified 101 (52%). Misidentifications or no identifications by
MALDI-TOF MS were consistent with an absence of spectra from
the database or with new or closely related species (257). Thus, as
with other groups of bacteria analyzed, database expansion could
aid in the species-level identification of Bacteroides spp. and per-
haps enhance MALDI-TOF MS performance such that more dis-
criminatory types of analysis could be performed, such as group-
ing of subspecies typing and antibiotic resistance determination
among clinical isolates.
Clostridium spp.
Members of the genus Clostridium are very diverse and medically
important. In a preliminary analysis, Grosse-Herrenthey et al.
evaluated the use of MALDI-TOF MS for the identification of
members of the genus Clostridium (258). Sixty-four strains repre-
senting 31 distinct species were analyzed with the Bruker BioTyper
version 1.1 software. Cells were harvested from plated medium,
resuspended in 80% TFA for 5 min to inactivate spores, and then
processed for MALDI-TOF MS analysis. A spectral database was
compiled and used to analyze a set of clinical isolates from the
genus. Media used for bacterial cultivation had minimal bearing
on the spectra produced in this study, whereas the spores’ pres-
ence had more of an impact, leading the investigators to use
younger cultures in their analysis to minimize spectral interfer-
ence. The robustness and accuracy of the spectra generated al-
lowed phylogenetic analysis of the genus, in addition to enhancing
the ability of MALDI-TOF MS to provide species-level identifica-
tions for a collection of clostridial clinical isolates. In this early
study, MALDI-TOF MS provided a rapid and efficient method for
determining species-level identifications of members of the genus
Clostridium using a dedicated database (258).
Clostridium difficile is a worldwide problem, often causing large
nosocomial outbreaks of antibiotic-associated diarrhea in health
care settings (259), with disease being mediated by the use of sev-
eral important virulence determinants (260). A number of typing
methodologies were used to examine genetic lineages of C. difficile
associated with outbreaks, including ribotyping, PFGE, MLST,
and restriction enzyme analysis (REA). Ribotyping represents an
analysis of the sizes of fragments generated by PCR, constituting
intragenic spacer regions between conserved genes. These PCR
fragments are visualized via gel or capillary electrophoresis to gen-
erate a pattern that can then be compared to patterns from other
strains, resulting in a classification scheme.
Recently, the SARAMIS MALDI-TOF MS system was evaluated
as a tool to discern different ribotypes among isolates of C. difficile
(261). Direct cells from 24-h cultures were deposited onto the
MALDI-TOF MS plate, and matrix solution was applied. A recog-
nized collection of isolates (ECDC-Brazier) encompassing 25 dif-
ferent ribotypes of C. difficile was used to generate a dedicated
database using derived SuperSpectra. By using this method, four
specific ribotypes were identified, including ribotype 027 (NAP1),
which is associated with epidemic outbreaks of C. difficile. A col-
lection of 355 PCR-ribotyped clinical isolates was tested against
the database. Using parameters determined in-house for database
matching, all ribotype 001 isolates (n ⫽ 248), all ribotype 027
isolates (n ⫽ 7), and 6 of 7 ribotype 126/078 isolates could not be
further separated due to high levels of similarity. Importantly, the
authors concluded that this method may represent a mechanism
for the rapid identification and characterization of C. difficile iso-
lates in the future, but more complete databases encompassing a
wider variety of ribotypes, including isolates from diverse geo-
graphical locations, will be needed to assess MALDI-TOF MS ca-
pabilities of discriminating between closely related strains (261).
FUNGI: YEASTS
The rapid analysis of fungi by MALDI-TOF MS has the potential
to revolutionize medical mycology. Identification of fungi in the
clinical laboratory is most traditionally associated with the use of
selective or differential media in addition to both manual and
automated biochemical identification systems. By implementing a
rapid system which functions on a universal platform for the de-
finitive identification of fungal specimens, significant reductions
in time to diagnosis and laboratory costs could be realized, in
addition to benefits with respect to patient care.
An appropriate drug regimen with antifungal treatment is a
critical component to successfully cure serious fungal infections,
but targeted therapy is difficult. It requires several days for growth
and identification by conventional biochemical and morphologi-
cal approaches, and the results may sometimes be inconclusive.
Species-specific susceptibility patterns can help clinicians make
Clark et al.
580 cmr.asm.org Clinical Microbiology Reviews
therapeutic decisions, but determination of antifungal suscepti-
bility can take weeks in some cases. Protein content and expres-
sion levels of fungal isolates may be affected by growth states and
mycological life cycles; therefore, standardization of medium and
growth phase will be important when using MS technology for
evaluation of therapeutics. Still, MALDI-TOF MS holds the
promise of significantly accelerating these processes, substantially
improving fungal diagnostics and patient treatment.
For 138 common and 103 archived strains of yeast, MALDI-
TOF MS was compared to phenotypic testing for yeast identifica-
tion, with 96.3% and 84.5% accurate species-level identifications
(spectral scores, ⱖ1.8) for common and archived strains, respec-
tively. The authors additionally performed a cost analysis to de-
termine if MALDI-TOF MS was financially competitive with
other rapid identification systems for fungal identification, deter-
mining that operating costs were lower than those of most con-
ventional and molecular testing systems in terms of reagent costs
and hands-on time required for sample processing (262).
Putignani et al. analyzed spectra by the Bruker BioTyper soft-
ware from 303 clinical isolates using standard pattern matching.
Identifications were compared to identifications by a reference
biochemical-based system (Vitek-2), and when results were dis-
cordant, BioTyper identifications were verified with genotyping
identifications obtained by sequencing of the 25S-28S rRNA hy-
pervariable D2 region. Of the 26 discordant results, only 5 ap-
peared to be real once further determinative testing was per-
formed. The BioTyper showed high analytical performance and
was able to discriminate patterns for strain typing of some species
(263).
The Bruker BioTyper has the most publications describing
yeast identification by MALDI-TOF MS. In perhaps the largest
analysis published to date, a diverse collection of 1,192 yeast and
yeast-like isolates was tested by Bader et al., who compared Bio-
Typer and SARAMIS databases to a classical differentiation
scheme based on microscopic and biochemical characteristics.
For 95.1% of the isolates, all three methods produced the correct
species identification, with improved identification noted for both
MALDI-TOF MS systems. Closely related species, such as Candida
orthopsilosis, C. metapsilosis, and C. parapsilosis or Candida
glabrata and C. bracarensis, could be resolved by both MALDI-
TOF MS systems but not by the biochemical methods (264).
Yeast Sample Preparation for MALDI-TOF MS
In a manner similar to bacterial studies, the preanalytical steps
associated with processing of fungi were previously investigated.
Theel et al. evaluated an FA-based on-plate method for the
MALDI-TOF MS-based identification of fungi from the clinical
laboratory. In total, 90 clinical yeast isolates were analyzed by di-
rectly smearing a small amount of biomass onto a MALDI plate
and overlaying the smear with 1 l 70% FA, followed by drying
and addition of matrix. MALDI-TOF MS analysis was performed
with the Bruker BioTyper 3.0 database, and a log score of 1.7 or
higher was accepted for a species-level identification. MS identifi-
cations were compared to those derived by standard phenotypic
methods, with discrepant results being resolved by 28S rRNA gene
sequencing. Eighty-six of 90 (95.6%) isolates were identified to the
genus level, and 73/90 (81.1%) were identified to the species level,
with a single misidentification being reported. Finally, in compar-
ison to a commonly used ethanol-based extraction method de-
scribed as being more time-consuming and requiring additional
consumables, the direct on-plate method performed better for
species-level identification of clinical yeast isolates (254). A second
comparison of this modified method determined that the modi-
fied method was suitable for rapid identification of yeast isolates;
however, the log score values for fungal identification needed to be
lowered to accommodate the lower spectral scores generated by
using this method (265).
The age and amount of fungal culture, a second aspect of pre-
analytical processing of yeast for MALDI-TOF MS analysis, have
also been investigated by Goyer et al. The authors determined that
only a single colony of yeast isolated from CHROMAgar needed
be isolated to provide accurate identification of yeast isolates, in-
stead of five colonies, which had been reported elsewhere (210).
Forty-eight-hour and 72-h cultures were also compared to deter-
mine if culture age had a bearing on identification. No significant
difference was found when using 48- or 72-h cultures. Good iden-
tification was also achieved by using 24-h cultures, but this
method was deemed not suitable for routine practice, as 48 h is
necessary for full color development with chromogenic medium
in order to accurately detect fungal mixtures (38).
In the following sections, we review the literature pertaining
to the identification of specific groups of fungal pathogens by
MALDI-TOF MS.
Candida spp.
Candida species infections are a major health problem worldwide.
The epidemiology of candidemia has substantially changed over
the last decades with the emergence of individual species formerly
classified into the nonalbicans Candida species group, known for
variability in susceptibility to antifungals and typically isolated
from those most unlikely to battle the infection, the immunocom-
promised and other compromised subpopulations. This inherent
variability highlights the need for the proper identification of Can-
dida spp. to enhance regional choices for prophylaxis and empir-
ical treatment and to further characterize the epidemiology of
infections. For example, recent studies of Candida species out-
breaks showed an increased incidence of bloodstream infections
in neonatal intensive care units (NICUs) caused by C. parapsilosis.
Species-specific differentiation of two closely related yeasts, Can-
dida albicans and C. dubliniensis, is important to better under-
stand the epidemiology and virulence of C. dubliniensis.
MALDI-TOF MS shows its potential for the rapid identification
of C. albicans and related species. In a study by Pinto et al.,
MALDI-TOF MS was performed on a 264-strain library com-
posed of clinical and reference strains. Discordant and unreliable
identifications were resolved by sequencing of the internal tran-
scribed spacer (ITS) region of the rRNA gene cluster. In this anal-
ysis, 20 (67%; 16 species) and 24 (80%) of 30 reference strains
were identified to the species (spectral score, ⱖ2.0) and genus
(score, ⱖ1.70) levels, respectively. Of clinical isolates, 140/167
(84%) strains were correctly identified with scores of ⱖ2.0, and
160/167 (96%) strains were correctly identified with scores of
ⱖ1.70; among Candida spp. (n ⫽ 148), correct species assignment
with scores of ⱖ2.0, and ⱖ1.70 were obtained for 86% and 96% of
isolates, respectively (versus 76.4% correct assignments by bio-
chemical methods). MALDI-TOF MS identified uncommon Can-
dida spp., differentiated C. parapsilosis from C. orthopsilosis and C.
metapsilosis, and distinguished between C. glabrata, C. nivariensis,
and C. bracarensis. Yeasts with scores of ⬍1.70 included 4/12
MALDI-TOF Mass Spectrometry in Clinical Microbiology
July 2013 Volume 26 Number 3 cmr.asm.org 581
Cryptococcus neoformans isolates. When protein extraction was
used, there were no misidentifications in the data set (266).
A total of 18 type collection strains and 267 recent clinical iso-
lates (Candida [n ⫽ 250], Cryptococcus, Saccharomyces, Tricho-
sporon, Geotrichum, Pichia, and Blastoschizomyces spp.) were iden-
tified by BioTyper analysis. The results were compared with those
obtained by conventional phenotyping and biochemical tests in-
cluding the API ID 32C system (bioMérieux) and other biochem-
ical tests. After complementation of the database, with species
identification from 26S rRNA gene sequencing, accurate species
identification by MALDI-TOF MS was achieved for all isolates. In
contrast, the API ID 32C biochemical diagnostic system identified
244 isolates (210).
Discrimination between C. albicans and C. dubliniensis is pos-
sible by using MS methods, as demonstrated by analysis of refer-
ence strains from type culture collections and other well-charac-
terized isolates. The spectra of C. albicans and C. dubliniensis easily
differentiated species, and further study revealed that each species
consists of several clades, which could be distinguished by
MALDI-TOF MS (267).
Dermatological yeast isolates were tested by Seyfarth et al. using
MALDI-TOF MS, the API ID 32C system, and sequencing of the
ITS regions of ribosomal DNA. The accuracy of MALDI-TOF MS
compared to the results derived from ITS sequence analysis was
94%, whereas API ID 32C was accurate for only 84.3% of the
isolates. Species tested included C. albicans (41.9%), C. parapsilo-
sis (20.3%), C. glabrata (10.8%), and C. krusei (6 isolates) (8.1%).
Rarely isolated yeasts, including C. colliculosa, C. famata, C. guil-
liermondii, C. lusitaniae, and C. tropicalis, as well as Geotrichum
candidum, Rhodotorula mucilaginosa, and Trichosporon mucoides
were also correctly identified. For the API ID system, C. krusei was
incorrectly identified as C. inconspicua/C. norvegensis, Candida
tropicalis,orGeotrichum capitatum. In contrast, all C. krusei
strains were correctly identified with discriminatory power com-
paratively similar to that of ITS sequence analysis (268).
Similar to the BioTyper, accurate results were observed by using
the Confidence Axima system (Shimadzu) with Shimadzu
Launchpad software and the SARAMIS database (AnagnosTec
GmbH). Nonalbicans Candida spp. (n ⫽ 73) isolated from non-
invasive samples were tested by using the Vitek-2 systems YST and
API CAUX, identifying 67 yeast isolates to the species level and 6
to the genus level. Discrepancies were resolved by SeptiFast Light-
Cycler multiplex PCR, C. glabrata-specific PCR, and enzymatic
digestion (269).
For the Andromas system, the accuracy for identification of
Candida spp. is also quite high. Using the Andromas software and
MALDI-TOF MS, Bille et al. analyzed 162 yeast isolates and found
96.3% accuracy for the first acquisition of spectra and 98.8% ac-
curacy after a second acquisition (53).
After constructing an in-house database (270), Marklein et al.
used the BioTyper system to identify 267 clinical isolates and 18
collection strains of yeast and yeast-like fungi (210). Candida spp.
were correctly identified for 240/250 (96%) clinical isolates on the
first attempt, with no false-positive results. Investigation of the
discrepancies between biochemical MALDI-TOF MS identifica-
tions by 26S rRNA gene sequencing resulted in 100% identifica-
tion to the species level. The same procedure used for identifica-
tion of the 17 clinical isolates of yeast-like fungi identified 100% of
isolates to the species level.
Stevenson et al. reported accurate identification of 194 clinical
isolates after implementation of a database containing 109 type
and reference strains of yeasts from 44 different species. Correct
identification to the species level with a score of ⱖ1.8 was obtained
for 192 (99%) isolates (271). Finally, in the largest set of yeasts ever
tested for analysis of MALDI-TOF MS performance for identifi-
cation, Bader et al. tested two systems, BioTyper and SARAMIS
(264). Twenty-one species, representing 1,148 isolates of yeast,
were tested, with large sample sizes for C. albicans, C. glabrata, C.
parapsilosis, and C. tropicalis and fewer samples for other Candida
and non-Candida species. The results obtained with these two
systems were comparable, with identification rates at the species
level of ⱖ99% for isolates that were represented in the respective
databases. Both methods each misidentified two single isolates
absent from the respective databases as a wrong species, while the
biochemical approach (ID 32C; bioMérieux) misidentified 30 iso-
lates as a wrong species, instead of reporting them as “unknown.”
In contrast, the success rate for classical identification techniques
was 96.7%. Closely related species (e.g., Candida orthopsilosis, C.
metapsilosis, and C. parapsilosis or Candida glabrata and C. braca-
rensis) were resolved by both MALDI-TOF MS systems but not by
the biochemical approach.
Cryptococcus spp.
The Cryptococcus neoformans-C. gattii species complex comprises
two sibling species that are divided into eight major molecular
types that differ in host range, epidemiology, virulence, antifungal
susceptibility, and geographic distribution. Protein extracts ob-
tained from 164 C. neoformans-C. gattii isolates by the formic acid
extraction method were tested, including four interspecies hy-
brids. The mass spectra correctly identified 100% of isolates,
grouped each isolate according to the currently recognized species
C. neoformans and C. gattii, and detected potential hybrids. In
addition, all isolates were clearly separated according to their ma-
jor molecular type (272). In another study, Stevenson et al. used
Bruker Daltonics MALDI BioTyper software and created a spec-
tral database library for 109 type and reference strains of yeast (44
species in 8 genera). The database was 99.0% accurate for 194
clinical isolates (23 species in 6 genera) (271).
Compared to molecular-based methods, MALDI-TOF MS
fares very well. Kaleta et al. evaluated identification of yeast to the
species level with both the Ibis T5000 PCR-ESI-MS and the Bruker
MALDI BioTyper 2.0 platforms, versus Vitek-2 analysis as the
reference standard identification. PCR-ESI-MS and MALDI-TOF
MS were equivalent in their abilities to characterize yeast with
respect to the reference standard (23). Compared to DNA se-
quence analysis, MALDI-TOF MS correctly identified 100% of
Cryptococcus species, distinguishing the notable pathogens C. neo-
formans and C. gattii. Identification was greatly enhanced by sup-
plementing a commercial spectral library with additional entries
to account for subspecies variability (273).
FILAMENTOUS FUNGI AND MOLDS
Delayed and incorrect diagnoses are potential risk factors leading
to high mortality rates due to invasive aspergillosis and other sys-
temic fungal infections. Because of variability of growth patterns
and difficulty obtaining a standardized inoculum, mold identifi-
cation proves to be more difficult than identification of bacteria
and yeast. Phenotypic identification of molds requires experi-
enced and skilled mycologists, who are not available to all labora-
tories, while molecular methods experience limitations with re-
Clark et al.
582 cmr.asm.org Clinical Microbiology Reviews
spect to difficulties associated with lysis and PCR inhibition of
mold specimens (274). Moreover, phenotypic identification is
slow and labor-intensive, with many species being phenotypically
similar but genotypically distinct or different in their propensity
to cause disease (275). Therefore, a rapid mechanism requiring
minimal sample preparation and analysis by the technician for the
identification of these organisms is appealing. MALDI-TOF MS
has been evaluated to potentially fill this niche (reviewed here and
in reference 276). Initial yet promising reports are available; how-
ever, more optimization will need to occur before the breadth of
clinical mold infection diagnoses can be accomplished by using
this technology.
A number of studies have examined the ability of MALDI-TOF
MS to identify molds, and here we highlight those which have
focused on mold identification in a general sense. Cassagne et al.
examined a number of sample preparation conditions (discussed
below) prior to their construction of a dedicated spectral library
for the identification of clinical mold isolates using 143 reference
spectra. Clinical testing of 177 sequential isolates using the con-
structed database followed, with MALDI-TOF MS-derived iden-
tifications being compared to phenotypic identifications. 28S
rRNA gene sequencing was used to resolve discrepant samples.
MALDI-TOF MS correctly identified 87% (154/177) of isolates,
with a 12% (21/177) failure rate for species not included in the
reference library, and two misidentifications (274).
In an evaluation of the ability of the technology to identify
molds, Lau et al. also constructed a MALDI-TOF MS database
(named the NIH Mold Database) to facilitate the identification of
clinical isolates. This database was comprised of spectra from 249
reference isolates and members of the collection of the ATCC.
When challenged with spectra from a collection of 421 clinical
isolates, the NIH Mold Database provided acceptable species-level
identification for 88.9% (370/421) of isolates tested. Importantly,
when the isolates were tested by using the Bruker BioTyper library
(version 3.1) alone, only 3 (0.7%) isolates were identified, high-
lighting the need for database expansion for the identification of
clinical mold isolates. No isolates were misidentified by MALDI-
TOF MS. Implementation of the database has improved labora-
tory efficiency and turnaround time in the experience of the au-
thors, and the database could be made available to other
laboratories for subsequent evaluations (275).
Mold Sample Preparation for MALDI-TOF MS
Sample preparation methods for MALDI-TOF MS analysis of
fungal hyphae and spores have been investigated. Cassagne et al.
evaluated five methods for the preparation of samples from this
material, using various combinations of culture conditions (agar
versus broth), ethanol and no ethanol treatments, heat treat-
ments, and mechanical lysis procedures to determine the method
which yielded the best results. Following these procedures, extrac-
tion with FA was performed, and the sample was analyzed by
MALDI-TOF MS. Following rigorous statistical analysis of spectra
and evaluation of the amount of labor necessary to complete the
procedure, a protocol was elucidated, which was easily performed
and provided robust results. Fungi were cultivated on a Sab-
ouraud gentamicin-chloramphenicol agar plate for 72 h at 27°C
and then extracted with FA following incubation in ethanol. Ace-
tonitrile was added, and the mixture was centrifuged, with the
resulting supernatant being analyzed by MALDI-TOF MS (274).
Lau et al. reported a mechanical lysis method for the prepara-
tion of samples from mold specimens for MALDI-TOF MS anal-
ysis. In their study, a small piece of mold isolate was resuspended
in ethanol and zirconia-silica beads, emulsified thoroughly, and
vortexed. Following centrifugation, the supernatant was removed,
and the remaining pellet was resuspended in 70% FA, vortexed a
second time, and centrifuged. The resulting supernatant was then
either analyzed immediately or stored for up to 1 week at ⫺20°C
for subsequent analysis by MALDI-TOF MS (275). Both methods
worked well for the investigators in their respective studies, and
both protocols will add value toward the future standardization of
sample preparation methods for mold specimens. Irrespective of
which method(s) is chosen in the future, the use of a biosafety
cabinet during sample processing and the minimization of aero-
sols will be important considerations during protocol selection to
ensure the safety of laboratory personnel working in close prox-
imity.
Aspergillus spp.
MALDI-TOF MS-based identification of Aspergillus has been un-
dertaken in the context of both clinical evaluations of the technol-
ogy in a routine setting as well as focused studies evaluating the
technology for species- and strain-level identifications. In a clini-
cal evaluation of the Vitek-MS system, Iriart et al. compared the
performance of the Vitek-MS system to those of both routine
laboratory techniques and Vitek-2. The Vitek-MS system per-
formed well in the identification of yeasts and a limited number of
Aspergillus spp. (93.2% correct identifications) (277). Bille et al.
reported a similar overall identification rate for Aspergillus spp. of
98.4% (63/64) in their study using the Andromas strategy (53).
In an analysis of Aspergillus, Fusarium, and Mucorales, De Caro-
lis reported the construction of a specific database dedicated to the
identification of members of these fungal classifications by using a
collection of 55 reference strains and the BioTyper 2.0 software.
The database was challenged with 103 blind-coded isolates to de-
termine discriminatory ability. Excluding isolates that were not
contained in the database, MALDI-TOF MS successfully identi-
fied 96.8% (91/94) of isolates to the species level (278). When
examining invasive Aspergillus isolates, Pan et al. reported that
more of the differential spectral peaks were present at the second
stage of sporulation, which contains differentiated structures,
than at the first stage, which is comprised primarily of vegetative
hyphae (279). Finally, Hettick et al. used MALDI-TOF MS to de-
rive spectra for 12 species of Aspergillus and five different strains of
A. flavus. Classification of each species and strain of Aspergillus
tested was accomplished with 100% accuracy in their analysis
(280).
Fusarium spp.
Fusarium spp. are significant pathogens, causing infection pri-
marily in immunocompromised patients. Identification of these
species is important for patient management, but conventional
identification strategies can be difficult due to phenotypic poly-
morphism. Aspects of MALDI-TOF MS analysis have been inves-
tigated for Fusarium, including preanalytical sample preparation
(281, 282). Marinach-Patrice et al. studied 62 Fusarium strains
representing nine species. Molecular identification using tef1 gene
sequencing was the reference standard compared to MALDI-TOF
MS. The most frequently isolated species, including F. solani, F.
oxysporum, F. verticillioides, F. proliferatum, and F. dimerum, were
tested, with MALDI-TOF MS correctly identifying 57/61 strains.
MALDI-TOF Mass Spectrometry in Clinical Microbiology
July 2013 Volume 26 Number 3 cmr.asm.org 583
Four species not represented in the MS database were not identi-
fied. MALDI-TOF MS yielded results within 1 h, demonstrating
its utility for identification of Fusarium spp. (283).
Dermatophytes
Dermatophytes are keratinophilic fungi that cause superficial in-
fections in humans by infecting nails, hair, and the stratum cor-
neum, the outermost layer of the epidermis (284). Dermatophyte
taxonomy is complex and has undergone recent revision with the
advent of more sophisticated molecular assays for identification as
well as genomic characterization. Molecular analysis is the gold
standard for identification of these fungi at the species level (285).
Phenotypic identifications are based upon growth on selective
media, colony morphology, and microscopic observation of
conidia (286). A number of studies have been dedicated to the
identification and characterization of these fungi by MALDI-TOF
MS. Erhard et al. were the first to evaluate MALDI-TOF MS spe-
cifically with the aim of identifying species causing onychomyco-
sis and tinea pedis with an early version of the SARAMIS database.
Although the sample size was small, distinct differences in gener-
ated spectra could be identified, and results of MALDI-TOF MS
identification were consistent with the reference standard (se-
quencing) for identification (287).
Theel et al. reported the use of the Bruker BioTyper version 3.0
for identification of dermatophyte species compared to 28S rRNA
gene sequencing. Performance of the BioTyper database was com-
pared using an unmodified version and a version supplemented
with in-house-generated dermatophyte spectra. For optimal per-
formance of MALDI-TOF MS for dermatophyte identification in
this study, supplementation of the commercial library was neces-
sary, as was reducing the log score cutoff values for genus-level
(from ⱖ1.7 to ⱖ1.5) and species-level (from ⱖ2toⱖ1.7) identi-
fications, as has been reported for other fungi and the identifica-
tion of bacteria directly from patient specimens (286).
Work from Alshawa and colleagues described the generation of
their own spectral database for dermatophyte identification, con-
structed from 50 reference strains comprising 12 dermatophyte
species and 2 species of Neoscytalidium, and its subsequent evalu-
ation using a collection of 381 clinical isolates. MALDI-TOF MS
was performed, and spectral evaluation was undertaken by using
the Andromas system. Samples were harvested and resuspended
in FA prior to analysis, reflecting a relatively simple method com-
pared to those reported by other studies highlighted in this sec-
tion. Compared to conventional methods, MALDI-TOF MS iden-
tified 331 of 360 (91.9%) dermatophyte isolates and 18 of 21
(85.7%) Neoscytalidium isolates tested. The authors concluded
that MALDI-TOF MS could replace conventional methods of der-
matophyte identification in the near future in both routine and
specialized diagnostic laboratories (288).
Nenoff et al. reported a recent substantial study in which the
authors analyzed 285 isolates comprising 21 different species from
the genera Trichophyton, Microsporum, Epidermophyton, and Ar-
throderma using MALDI-TOF MS and the SARAMIS system as
well as gene sequencing following the construction of an in-house
database. Identifications derived by using conventional algo-
rithms matched MS-derived identifications in 78.2% of cases. Im-
portantly, MALDI-TOF MS matched identifications derived by
gene sequencing in 99.3% (283/285) of cases, demonstrating the
high level of accuracy the MS system using the in-house database
(289) as well as the need for a rapid and accurate mechanism of
dermatophyte identification to enhance conventional mecha-
nisms.
Pseudallescheria-Scedosporium Complex
Members of the Pseudallescheria-Scedosporium complex (PSC) are
commonly associated with opportunistic mold infections in both
immunocompetent and immunocompromised patients. These
molds present a significant diagnostic challenge, as they cannot be
distinguished from other filamentous fungi by histological exam-
ination alone, and rapid identification is necessary due to their
poor response to certain antifungal agents (290). Twenty-two PSC
reference strains and three clinical isolates were tested by using
MALDI-TOF MS and the BioTyper software (Bruker). MS iden-
tification was stable after the fungi were subcultured over a
1-month period. While neither culture medium (Sabouraud ver-
sus malt extract) nor protein extraction methods (FA versus TFA)
significantly influenced the quality of the MS identifications, iden-
tification was considerably enhanced between days 3 and 6 of in-
cubation. Further analysis is necessary to evaluate the ability of
MALDI-TOF MS to discriminate between recently identified spe-
cies within the Pseudallescheria boydii group of organisms (291).
Penicillium spp.
Hettick et al. used MALDI-TOF MS to identify 12 species within
the genus Penicillium. Analysis of undisrupted cells generated
consistently poorer spectra, so a disruption protocol was utilized.
Conidia and spores were collected from cultures, resuspended in
TFA-acetonitrile with glass beads, vortexed, and centrifuged, with
the resulting supernatant being used for MALDI-TOF MS analy-
sis. Although a small collection of isolates was utilized and spectral
analysis was done in-house without the aid of standardized soft-
ware, Penicillium species within this collection were able to be
discriminated to the species level with 100% accuracy (292).
Lichtheimia spp.
The genus Lichtheimia is separated into five species, with only
three (L. corymbifera, L. ramosa, and L. ornata) being associated
with clinical disease (293). These organisms are saprophytic fungi
that inhabit soil and decaying plant matter, which can cause rela-
tively rare yet dramatic infections requiring medical intervention
in immunocompromised patients (294). Schrödl et al. recently
utilized MALDI-TOF MS to identify members of the genus Lich-
theimia. Samples were prepared by using a combination of ethanol
inactivation, freeze-thawing, and FA extraction prior to matrix
overlay. MALDI-TOF MS identifications were compared to those
derived by rRNA gene sequencing. A spectral database was con-
structed by using 12 strains of Lichtheimia and seven related gen-
era, which was subsequently challenged with 34 additional clinical
and environmental isolates. MALDI-TOF MS was able to identify
the Lichtheimia genus in 100% of cases and was also able to dis-
criminate specific species within the genus for 32 out of 34 isolates
(295).
Extended Testing of Fungal Isolates by MALDI-TOF MS:
Antifungals and Epidemiology
Recently, MALDI-TOF MS profiling of fungal isolates has been
taken in exciting new directions beyond standard microbial iden-
tification. Although in its infancy, antifungal testing using
MALDI-TOF MS is a possibility. MALDI-TOF MS was evaluated
for testing susceptibility to caspofungin of wild-type and fks mu-
Clark et al.
584 cmr.asm.org Clinical Microbiology Reviews
tant isolates of Candida spp. Caspofungin functions by inhibition
of the synthesis of cell wall components of medically important
fungi, including Candida spp. and Aspergillus spp. (296), with mu-
tations in fks genes conferring reduced susceptibility to echino-
candin antifungals, including caspofungin (297). Complete essen-
tial agreement was observed with the CLSI reference method, with
categorical agreement for 94.1% of the Candida spp. Thus,
MALDI-TOF MS is a reliable and accurate method to detect fun-
gal isolates with reduced caspofungin susceptibility (278).
Epidemiological testing of fungal isolates has also been investi-
gated using MALDI-TOF MS. Strain typing of yeast was at-
tempted when 19 strains of C. parapsilosis isolated from blood
cultures of neonates were genotyped by the amplification of eight
simple sequence repeat (SSR) markers and by MALDI-TOF MS.
Both methods were rapid and effective in highlighting identical
strains and studying microevolutionary changes in the yeast pop-
ulation (298). Further investigations are warranted prior to using
MALDI-TOF MS for outbreak investigations or rapid antifungal
susceptibility testing of yeast isolates; however, these preliminary
investigations provide promising results and highlight the diverse
utility of the technology.
USE OF MALDI-TOF MS IN EPIDEMIOLOGY
Although rapid and accurate microbial identification by MALDI-
TOF MS will be what primarily attracts laboratories to mass spec-
trometry-based analysis methods, the potential for MALDI-TOF
MS to provide critical epidemiological data cannot be under-
stated. One of the great challenges faced by clinical laboratory
scientists (CLSs), infection prevention practitioners, clinicians,
and public health laboratories is determining strain-specific data
for representative taxonomy of clinical isolates in outbreak situa-
tions. In some specific cases (i.e., Salmonella spp. and Streptococcus
spp.), microbial typing is particularly challenging and often re-
quires additional time-consuming second-stage testing in order to
correctly determine serotype, subspecies, or other taxonomic clas-
sifications. This challenge can be further confounded when the
specific implications of a serotype or subspecies in the context of
an infection is ambiguous.
Due to their complexity, many strain typing methods require a
specialized laboratory test method and additional instrumental or
material demands. Therefore, these analyses are not routinely per-
formed in every laboratory, resulting in an increased amount of
“send-out” testing and delays in investigation of hospital-associ-
ated infections and outbreaks. This can result in delayed time to
detection, loss of important epidemiological data, increased test-
ing costs, and potentially inaccurate or inconsistent results. These
minute but important details may be performed in real time on
clinical specimens by the CLS in the laboratory of origin. Having
this information readily available will assist physicians, nurses,
pharmacists, infection control personnel, and local and state au-
thorities in treating and tracking infectious microbes and their
associated epidemiology.
Much of the strain typing research has been completed in ap-
plied research settings outside the clinical laboratory, using spe-
cialized databases constructed through the analysis of expanded
sample collections of isolates consisting primarily of a specific
group of organisms, genus, or species. The ability of MALDI-TOF
MS to discriminate between these highly related organisms, as
demonstrated in these studies, has profound implications for the
clinical microbiology laboratory. As databases used for the spe-
cies- and strain-specific identification of organisms mature, a sec-
ond tier of epidemiological capabilities may emerge, using the
same or similar MALDI-TOF MS instrumentation as that used for
microbial identification. The implementation of an instrument
into the clinical laboratory workflow that can not only identify
microorganisms but also provide rapid and accurate epidemio-
logical data about identified clinical isolates has the potential to
expand the role of the microbiology laboratory beyond microbial
diagnostics and further refine critical roles in hospital infection
control, national surveillance of microbial outbreaks, and biode-
fense.
While the use of MALDI-TOF MS for strain typing is still in its
infancy, the advantages that this type of data could provide to both
hospital and public health officials are profound. As microbes
continue to change at the genetic level and evolve new mecha-
nisms for infection and resistance to antibiotics, the microbiology
laboratory must too evolve, implementing new mechanisms for
increased accuracy, speed, and sensitivity for the identification
and characterization of pathogenic microbes.
MS IDENTIFICATION OF BACTERIA DIRECTLY FROM PATIENT
SPECIMENS
While MALDI-TOF MS has been extensively evaluated as a uni-
versal platform for the proteomic analysis and identification of
bacteria and yeasts from culture media, the technology is also
being exploited to analyze patient specimens directly, completely
bypassing the need for culture by detecting the presence or ab-
sence of pathogens in the clinical specimen proper. This type of
direct analysis proved impossible before the advent of molecular
analysis (Fig. 4).
Due to its exquisite sensitivity, MALDI-TOF MS provides an
attractive mechanism to be used either in place of or in concert
with PCR-based strategies for direct detection of pathogens from
clinical material, as no amplification of the target material is re-
quired. The ability of both molecular and proteomic approaches
to identify targets in these types of samples can also be enhanced
by preliminary processing of these samples, removing some of the
elements (proteins, nucleic acids, and cellular debris, etc.) that can
inhibit analysis. In this section, we review the current knowledge
regarding the testing of patient specimens directly in conjunction
with MALDI-TOF MS.
Urine
Proteomic profiling of human urine has been utilized for quite
some time to identify disease-specific biomarkers, and previous
analysis has demonstrated that a number of factors, including
storage time, pH, and the number of freeze-thaw cycles, influ-
enced analysis. Prior to the use of MALDI-TOF MS for the diag-
nosis of urinary tract infections (UTIs), the presence of blood and
bacteria in the urine was known to interfere with urinary pro-
teomic analysis, specifically altering key peptide mass signals in
the sample (299). Additional studies similarly suggested that bac-
terial overgrowth of the urine could hamper proteomic analysis
and recommended that samples be centrifuged and stored imme-
diately at 4°C and have boric acid or NaN
3
added to prevent bac-
teria from overgrowing (300). It remains to be seen which speci-
men handling conditions are necessary for optimal identification
of bacteria in urinary samples, as higher bacterial burdens within
the specimen could potentially simplify the detection of the bac-
MALDI-TOF Mass Spectrometry in Clinical Microbiology
July 2013 Volume 26 Number 3 cmr.asm.org 585
FIG 4 Current position of MALDI-TOF MS in the workflow of the clinical microbiology laboratory, including the current options for analysis of bacteria directly
from patient specimens. The MALDI-TOF MS instrument fits easily into the clinical microbiology workflow, occupying the position once held by instruments
for automated phenotypic-based identifications (blue arrows). Evaluated mechanisms for the processing of samples directly from patient specimens are included
(hatched red arrows), as are options for the use of traditional (green arrows) and MALDI-TOF MS (hatched green arrows) mechanisms. Finally, results are
imported into the laboratory information system from the MADLI-TOF MS instrument or other instruments and reported to physicians and pharmacists as
indicated. BAL, bronchoalveolar lavage.
Clark et al.
586 cmr.asm.org Clinical Microbiology Reviews
teria in urine samples at the expense of the rest of the urinary
proteome.
One of the first studies to directly compare MALDI-TOF MS to
conventional methods of bacterial identification in urine speci-
mens concluded that MALDI-TOF MS was a promising method
for this type of analysis following differential centrifugation. Low-
speed centrifugation was utilized to remove leukocytes, followed
by high-speed centrifugation to collect bacteria in the sample, and
these intact cells were analyzed by MALDI-TOF MS. In an analysis
of 269 samples detected as positive by urine particle analysis (urine
microscopy), 20 were positive in the screening device and negative
by both culture and MALDI-TOF MS analysis using the Bruker
BioTyper 2.0 database. Two hundred twenty of these samples
showed high levels of bacterial growth ( ⬎10
5
CFU/ml), and iden-
tifications for this group were consistent at the genus level in 204
(92.7%) cases and consistent at the species level in 202 (91.8%)
cases compared to identifications made by standard methods
(Wider MIC/ID [Microscan] and Vitek-2 [bioMérieux]). The au-
thors concluded that MALDI-TOF MS provided good identifica-
tion from urine, particularly in cases where Gram-negative bacte-
ria were present at high levels (301). A second study by the same
group further addressed the issue of sample preparation with re-
spect to direct urine samples prior to MALDI-TOF MS analysis.
Ferreira et al. reported that following differential centrifugation to
remove cell debris and leukocytes, ethanol precipitation of pro-
teins followed by formic acid and acetonitrile resuspension of pro-
teins significantly improved the performance of MALDI-TOF MS
for the identification of urinary pathogens compared to the intact-
cell method, as previously reported, leading to the reporting of
analytical results within minutes (138, 301).
An additional study by Kohling et al. investigated the ability of
MALDI-TOF MS to identify bacteria directly from urine speci-
mens and compared the accuracy of this method to identifications
derived by either phenotypic (Vitek-2, API, and Microscan Walk
Away) or molecular (long-chain fatty acid pattern analysis by gas
chromatography) methods. Although a smaller sample set than
those used in studies discussed above in this section (n ⫽ 107), the
authors similarly determined that MALDI-TOF MS was a reliable
methodology for detection of bacteria directly from urinary spec-
imens. Additionally, the authors concluded that this reliability was
applicable to samples with bacterial densities as low as 10
3
CFU/ml
(302).
The most recent studies to date regarding the direct analysis of
urinary specimens were aimed at incorporating MALDI-TOF MS
into the laboratory workflow in conjunction with the urinalysis
section of the clinical laboratory. In a comprehensive study by
Wang et al., urine flow cytometry was utilized as a prescreening
method to eliminate negative samples. Samples determined to be
positive for the presence of bacteria (⬎10
5
CFU/ml) by flow cy-
tometry were processed for MALDI-TOF MS for bacterial identi-
fication. Samples were differentially centrifuged to remove leuko-
cytes from the suspension, followed by high-speed centrifugation
to pellet bacteria. The bacterial pellet isolated from the aqueous
urine was subsequently treated with formic acid and acetonitrile,
and extracted proteins were analyzed by MALDI-TOF MS (Bio-
Typer database) for bacterial identification. These identifications
were compared to identifications derived from cultured bacteria
by using phenotypic methods (Vitek-2), with discrepant identifi-
cations being resolved by 16S rRNA sequencing. Of the 1,456 sam-
ples from patients with UTI symptoms included in the study, 932
(64%) were determined to be negative for the presence of bacteria.
The correct result (no bacteria present or correct bacterial identi-
fication) was obtained for 1,381 of the 1,456 cases (94.8%).
Among the 430 positive samples, 8 were found to be discrepant
between the MALDI-TOF MS and the Vitek-2 results, and all 8
identifications by MALDI-TOF MS were confirmed by 16S rRNA
gene sequencing (303).
It is clear that MALDI-TOF MS has the potential to be used with
great success for the direct identification of bacteria in urine sam-
ples, potentially negating the need for urine culture in compli-
cated cases. However, while tremendous work has been dedicated
to the direct analysis of urine specimens by MALDI-TOF MS,
there are number of questions remaining to be examined. Both
Ferreria et al. and Wang et al. reported that MALDI-TOF MS
could not accurately identify mixed bacteria present in urinary
specimens (138, 303). It remains to be determined if improve-
ments to the respective databases will allow the accurate identifi-
cation of mixed bacteria in urinary specimens. Additionally, no
standardized methodology is currently available regarding the
processing of specimens prior to analysis by MALDI-TOF MS.
Simple protein extraction (i.e., formic acid or ethanol-acetoni-
trile) is demonstrated to be cost-effective and fast and significantly
enhances the ability of MALDI-TOF MS to correctly identify bac-
teria from urine specimens, which would be a reasonable step to
include in a standardization of processing methods prior to
MALDI-TOF MS analysis. Moreover, many clinical laboratories
are already performing urine flow cytometry, with urine cultures
often being submitted for reflex testing following a positive mi-
croscopic observation. There is a possibility that MALDI-TOF MS
could be added to the testing menu and performed following a
positive urine microscopic test, as described previously (303). Ir-
respective of future standardization in the specimen-processing
workflow, MALDI-TOF MS currently represents a robust and ac-
curate technology for the identification and characterization of
single bacterial species present in direct urine specimens.
Cerebrospinal Fluid
Similar to urine, cerebrospinal fluid (CSF) has been used for pro-
teomic profiling for the diagnosis of disease. The presence or ab-
sence of specific proteins in patient CSF was used as a biomarker
for a number of neurological disorders. Bacterial meningitis rep-
resents one of the most serious and clinically significant manifes-
tations of bacterial infection and represents a situation where fast
and accurate detection of the offending bacterial agent is para-
mount. Currently, the detection of bacterial pathogens responsi-
ble for meningitis is accomplished via Gram staining of the CSF
and looking for the presence of bacteria. Samples generating neg-
ative smears are cultured to rule out the presence of circulating
bacteria, while patients with positive cultures are treated immedi-
ately with broad-spectrum antibiotics based upon the Gram stain
result until a definitive identification can be reached and targeted
antimicrobial therapy can be administered.
While CSF can be analyzed by MALDI-TOF MS, there are very
few reports in the literature describing the use of MALDI-TOF MS
for the direct identification of bacteria from CSF. One such report
describes the diagnosis of pneumococcal meningitis in a 46-year-
old man (304). Following sample acquisition, the CSF was pro-
cessed in a manner similar to that discussed above for urine sam-
ples: low-speed centrifugation to remove leukocytes followed by
high-speed centrifugation to pellet bacteria. The pelleted debris
MALDI-TOF Mass Spectrometry in Clinical Microbiology
July 2013 Volume 26 Number 3 cmr.asm.org 587
was then solubilized in formic acid-acetonitrile as described
above, centrifuged, and analyzed by MALDI-TOF MS using the
BioTyper 2.0 database. The identification generated by MALDI-
TOF MS analysis was interpreted as being valid species-level iden-
tification following manual manipulation of the data, although
the automatic analysis would have allowed for only a statistically
confident genus-level identification. Irrespective of the genus or
species level of identification, the use of this technique in combi-
nation with Gram stain and traditional bacterial culture could
represent an important turning point in the diagnosis of bacterial
meningitis, increasing sensitivity and decreasing time to diagnosis
and allowing for targeted and aggressive antibiotic therapy for a
patient population that is critically ill. This is an application of
MALDI-TOF MS that warrants significant further investigation.
Identification of Bacteria Directly from Blood Cultures
Direct identification of bacteria and yeast from blood culture bot-
tle broth is a promising option for MADLI-TOF methods with the
potential to speed the identification process (305, 306). After pre-
processing of the blood culture broth to limit interference from
blood cells and hemoglobin and to concentrate the microbes pres-
ent, the procedure is similar to that used for testing of bacterial
colonies.
Identification by MALDI-TOF MS depends on an adequate
concentration of the inoculum (56). Experiments using S. aureus
and Escherichia coli spiked into blood culture broth indicate that
bacteria can be successfully identified from 10
7
CFU/ml of organ-
isms when the median CFU in a positive blood culture broth is 10
8
CFU/ml (307). The problem with inoculum size is worsened for
bacteria with poor spectral quality, such as streptococci (112).
There is concern that mixed infections would be impossible to
identify; therefore, Gram staining would still be required to miti-
gate that risk. Contrary to most protocols that try to identify in-
fection in blood culture broth as soon as growth is detected by the
automated system (65, 306), some authors have proposed to
maintain positive vials for 3 to 10 h at room temperature to allow
for storage and transport if required (308).
A variety of different protocols have been reported to accurately
identify the microorganisms present in positive blood culture
broth; however, a lack of standardized protocols and the use of
different software for mass analysis and different blood culture
bottles make it difficult to compare the performances of the dif-
ferent methods. One study reported that protocols using extrac-
tion are more effective than the intact-cell method (138). Bact/
Alert bottles without charcoal were tested, and the authors
reported accurate identification with a quick preparation proce-
dure (56); however, preliminary tests performed on Bact/Alert
vials with charcoal (309) produced poorer results than those ob-
tained by using Bactec vials, probably due to the presence of char-
coal.
In the first large published study of blood culture broth testing,
584 positive blood cultures were tested, and 562 contained a
unique bacterial species (306). Two extraction protocols were
used, and good results were reported for Gram-negative bacteria
at the species level. In the same study, Gram-positive bacteria were
poorly identified, with only 37 to 67% being identified to the spe-
cies level. To accommodate errors in MALDI-TOF identification
when mixed cultures were observed, Gram staining was recom-
mended to optimize detection of mixed species.
In a study by Prod’hom et al., identification to the species level
was obtained for only 79% of 122 positive blood cultures, and
identification problems were observed for streptococci and staph-
ylococci. S. epidermidis was identified only 26% of the time (65).
Some microorganisms, such as Klebsiella pneumoniae and Haemo-
philus influenzae, were not accurately identified, suggesting a spe-
cific problem for testing of encapsulated microorganisms.
Stevenson et al. used the BioTyper software to test 212 positive
cultures, and correct identification was obtained at the species
level with scores of ⱖ1.9 for 138 (65%) isolates and at the genus
level with scores of ⱖ1.7 for 162 (76%) isolates (308). The eight
isolates of S. mitis led to the inaccurate results, being identified as
S. pneumoniae. Among 373 monomicrobial-positive blood cul-
ture bottles, correct identification was achieved for 98% of them at
the species level; however, the authors included an additional test
for S. pneumoniae identification to differentiate it from S. mitis.In
addition, they reported 100% identification of the 11 Candida
albicans samples.
Christner et al. reported accurate identification to the species
level (95% of 277 samples). Of 15 nonidentified isolates, 3 were
bacteria for which spectra were not present in the database (307).
In a recent study, the authors confirmed that MALDI-TOF MS
accurately identified, in most cases, one of the species present in a
polymicrobial vial and achieved excellent identification at the spe-
cies level (90% of 497 monomicrobial samples) (307). Ferroni et
al. described the only study reporting good results for blood cul-
ture bottles with polymicrobial infections; however, this study
uniquely used an Andromas-specific database (56). Problems
with identification of S. mitis and with polymicrobial vials were
still described with this database.
Vlek et al. reported that the implementation of MALDI-TOF
MS in the laboratory has resulted in significant improvements to
patient care when used for the analysis of positive blood cultures.
In their trial, MALDI-TOF MS with Bruker BioTyper version 2.0
software was performed on blood culture broths. This reduced the
time to result by 28.8 h and increased the proportion of patients
receiving targeted antimicrobials within 24 h of the receipt of the
sample by 11.3% (310).
Recently, results of the first study to compare two different MS
platforms for the identification of microorganisms directly from
positive blood cultures were published. Chen et al. compared the
Vitek-MS (bioMérieux) system to the Bruker BioTyper version
3.0 for the identification of microorganisms from 202 positive
Bactec bottles. Sample processing was performed with the Bruker
SepsiTyper kit according to the manufacturer’s instructions.
Identifications by the MS system were compared to identifications
derived from 16S rRNA gene sequencing and phenotypic (Vi-
tek-2) methods. The BioTyper system was able to make a higher
number of accurate identifications to the species level than the
Vitek-MS system and demonstrated better performance than Vi-
tek-MS with regard to Gram-positive bacteria at the genus and
species levels. Both systems performed poorly when analyzing
polymicrobial specimens (311).
Identification of Yeast Directly from Blood Culture Broth
The identification of yeast isolates directly from positive blood
culture broth has also been evaluated by a number of groups. Two
studies with a limited number of isolates, 20 and 18, respectively,
demonstrated that the identification of yeasts is possible when
using sample aliquots removed directly from blood culture bottles
(56, 138); however, accuracy varied widely between these two
Clark et al.
588 cmr.asm.org Clinical Microbiology Reviews
studies, with correct identification levels of 5 and 100%, respec-
tively. It is likely that the different protocols, software, and data-
bases used to perform data analysis explain this discrepancy (23).
In addition, Kaleta et al. described accurate characterization of
yeast colonies isolated from blood cultures using the Bruker
MALDI BioTyper 2.0 (MALDI-TOF MS) compared to direct
identification with the Ibis T5000 PCR-ESI-MS system (23).
In 2010, an evaluation of species-level identification of Candida
isolates from positive blood culture broth was reported. Marin-
ach-Patrice et al. spiked blood culture bottles with different Can-
dida species. The authors noted that a direct identification from
the positive bottle would allow bypass of subculture and subse-
quent identification steps, allowing results to be obtained up to 3
days sooner. Extraction protocols were optimized by using SDS
and ethanol, and MS spectra were analyzed for each of the differ-
ent species of Candida utilized in that study, C. glabrata, C. krusei,
C. lusitaniae, C. parapsilosis, and C. tropicalis, with verifiable dif-
ferences between the generated spectra observed. The method was
tested on one routine positive blood culture from a patient, with
correct identification being provided (312), allowing the authors
to conclude that the method for the direct identification of Can-
dida species from blood culture bottles using MALDI-TOF MS
was a rapid and accurate mechanism that could lower costs and
hasten appropriate antifungal therapy.
Finally, Spanu et al. evaluated the Bruker BioTyper version 2.0
software for rapid identification of Candida species causing
bloodstream infections in a large routine setting. Similar to previ-
ous reports, preliminary testing using ATCC isolates yielded 100%
accuracy when determining species-level identifications. Polyfun-
gal isolates that were analyzed were unable to be reliably identified,
a drawback that many users noted with polybacterial infections as
well. Although identification of isolates directly from blood cul-
ture bottles generated log score values that were consistently lower
than those for identification of isolates from plated media, the
software performed well compared to traditional culture-based
identifications (187/195 [95.9% concordant for C. albicans] and
128/148 [86.5% concordant for nonalbicans Candida isolates]).
Perhaps most importantly, 80% of the positive blood cultures in-
cluded in the study were reported to be positive ⱕ24 h after sam-
ple entry, allowing in many cases species-level identifications to be
reported to physicians within 24 h after blood draw (313).
Extraction Methods for Identification of Microbes Directly
from Blood Culture Bottles
Similar to bacterial identifications, the standardization of meth-
ods for the extraction of proteins from blood culture bottles will
need refinement prior to the widespread utilization of MALDI-
TOF MS for direct blood culture analysis. A number of reports
have identified that preanalytical steps can greatly influence the
quality of spectra derived from sample processing; however, in
this case, in addition to the type of organism(s) present, the sam-
ple itself can pose difficult challenges when trying to identify the
bacteria or yeast contained within. Components from human
blood can cause interference or generation of noisy spectra by
MALDI-TOF MS when analyzing blood culture specimens di-
rectly (271). Prior to the availability of a commercial kit for the
processing of specimens directly, the technology was evaluated by
using a number of in-house methods (65, 138, 306, 314).
Bruker has made significant steps in standardizing the method
of sample extraction with the introduction of the SepsiTyper kit
for direct analysis of bacteria from positive blood culture broth
samples. In the first analysis of the SepsiTyper kit, an analysis of
507 mono- and polymicrobial blood cultures was undertaken to
investigate the utility of the kit prior to MALDI-TOF MS. More
Gram-negative organisms were accurately identified than Gram-
positive organisms, with significant difficulties being reported for
the identification of anaerobic bacteria, alpha-hemolytic strepto-
cocci, and polymicrobial mixtures and with ongoing technical de-
velopment aiming toward addressing these issues (314). A num-
ber of comparative evaluations of in-house methods and the
SepsiTyper kit soon followed (315–319).
Following the initial description of the SepsiTyper kit, Buchan
et al. sought to evaluate the performance of the kit in combination
with MALDI-TOF MS for the identification of blood culture iso-
lates using standard MS parameters. One hundred sixty-four iso-
lates composed of Gram-positive, Gram-negative, and fungal he-
matopathogens were analyzed. The MALDI-TOF MS system with
preanalytical preparation by the SepsiTyper system was able to
identify 85.5% of isolates directly from blood culture. Gram-neg-
ative bacteria still provided better log scores than Gram-positive
bacteria, but genus and species concordance was comparable with
the reference methods (Vitek-2 and Phoenix) for both groups.
Fourteen polymicrobial blood cultures were also evaluated, with
the MALDI-TOF MS system identifying at least one organism
with high confidence in nine blood cultures. However, no blood
cultures containing yeast generated acceptable scores by using
standard MS parameters (320).
In a smaller study, Lagacé-Wiens et al. evaluated the SepsiTyper
system in tandem with the BioTyper for the identification of bac-
teria from blood culture bottles and also included a thorough
analysis of turnaround time and laboratory costs associated with
the testing. Limitations similar to those previously documented by
other groups were also reported here with respect to identification
of Gram-positive organisms (alpha-hemolytic streptococci) and
polymicrobial cultures. A mean reduction in turnaround time of
34.3 h was reported compared to conventional analysis where no
additional microbial testing was necessary, and an estimated
26.5-h reduction was reported where some additional character-
ization of the organism was necessary prior to final identification.
With the cost of the SepsiTyper kit being found to be comparable
to that of commercial panels, laboratories using primarily com-
mercial panels were determined to see a marginal change in oper-
ating costs, whereas laboratories using in-house panels were likely
to see an increase in costs per sample with MALDI-TOF MS. These
costs might be offset by the use of MALDI-TOF MS in other areas
of the microbiology laboratory aside from blood culture analysis
(321).
Nonnemann et al. also evaluated the SepsiTyper for routine
use in the diagnostic laboratory but included 19 bottles that
were spiked with fungi in their study. Decreasing the log score
cutoff to 1.5 increased the number of species-level identifica-
tions for both Gram-positive and Gram-negative blood cul-
tures; however, the number of fungal cultures identified re-
mained the same at both cutoff values. Seventy-seven percent
of fungal isolates were identified to the species level by MALDI-
TOF MS using the SepsiTyper kit for preanalytical processing
(322). Adjustment of the log score cutoff value to 1.5 improves
identification of bacteria directly from blood culture, as re-
ported elsewhere (318).
Significantly less information is available to describe standard-
MALDI-TOF Mass Spectrometry in Clinical Microbiology
July 2013 Volume 26 Number 3 cmr.asm.org 589
ization of preparatory methods for pathogenic yeast isolates re-
covered from blood culture. In an analysis of randomly selected
clinical samples, Yan et al. evaluated the SepsiTyper sample-pro-
cessing system in conjunction with the BioTyper version 2.0 soft-
ware for the analysis of yeast species directly from blood speci-
mens. The SepsiTyper kit was adapted for use with yeast
specimens, and MALDI-TOF MS-derived identifications were
compared to phenotypic identifications (germ tube, urease, and
API 20C AUX), with 23S rRNA gene sequencing being used to
resolve discrepant identifications. In all, 42 cultures were ana-
lyzed, which included C. albicans, C. parapsilosis, C. tropicalis, and
one isolate of Cryptococcus neoformans, with all samples yielding
correct species-level identifications. The MALDI-TOF MS identi-
fications derived directly from blood samples did not change
when plated cultures from the same blood culture bottle were
analyzed by MALDI-TOF MS. Moreover, the entire procedure
(including time for specimen extraction) was reportedly com-
pleted in an hour (323).
The analysis of bacteria and fungi directly from blood spec-
imens shows promise for drastically improving the time to re-
sult and allowing faster implementation of targeted therapy for
patients with sepsis. These technologies will continue to de-
velop to allow greater sensitivity and discrimination among
bacteria, particular Gram-positive species, and yeast. Contin-
ued evaluation of MALDI-TOF MS by clinicians and labora-
tory personnel will aid in the development and adaptation of
the technology.
MS IDENTIFICATION OF ANTIMICROBIAL RESISTANCE
In addition to the accurate identification of bacteria in clinical
material, another critical responsibility of the clinical microbiol-
ogy laboratory is to determine antibiotic susceptibilities of organ-
isms and to report these findings to both physicians and pharma-
cists for the implementation of targeted antimicrobial therapy.
Mechanisms used for the determination of antimicrobial suscep-
tibilities can vary depending upon the type of organism in ques-
tion but can include culture-based methods such as Kirby-Bauer
disc diffusion testing, Etests, selective growth media, and broth
microdilution analysis. Additionally, many automated technolo-
gies used for the phenotypic identification of bacteria, including
the Vitek-2 (bioMérieux) and the Phoenix (Becton, Dickinson)
systems, also function to determine antimicrobial susceptibilities.
The drawback of these technologies is the increased time to result
associated with them. Rapid testing mechanisms for commonly
encountered resistant organisms (i.e., MRSA) were developed as
well, including agglutination and enzyme immunoassay (EIA)
testing, but are limited to a small number of bacterial species.
What is not currently available is a universal platform for the rapid
determination of antimicrobial resistance covering an extended
spectrum of bacterial genera that can be implemented into the
workflow of the clinical laboratory.
Detection of Resistance to Beta-Lactam Antibiotics in
Enteric and Nonfermenting Gram-Negative Rods
As MALDI-TOF MS gains acceptance as an improvement over
most phenotypic methods utilized for bacterial identification, its
exquisite sensitivity with regard to the type of molecules that can
be detected during the analysis of bacterial samples is evolving. It
is no wonder that a number of investigators have sought to adapt
the technology for the identification of bacterial proteins associ-
ated with antimicrobial resistance: laboratorians are anxious to
have antimicrobial assays run in parallel with bacterial identifica-
tion. The speed of MALDI-TOF MS identification will no doubt
be helpful for treatment of some microbes that have clearly delin-
eated antibiograms; however, for many microbes, no clearly de-
fined antimicrobial changes will be possible without rapid and
parallel detection of genetic or phenotypic recognition of antimi-
crobial resistance. Although in its early stages, several publications
are summarized and describe the successful use of MALDI-TOF
MS for discriminating antibiotic-resistant bacterial strains. While
a comprehensive description of the use of MALDI-TOF MS for
the identification of microbes in the clinical laboratory is expertly
reviewed elsewhere (324) and is outside the scope of this review,
we will instead highlight some of the uses of MALDI-TOF MS for
the detection of different groups of clinically important antibiot-
ic-resistant bacteria.
Due to the heavy use of cephalosporin antibiotics worldwide,
the spread of Enterobacteriaceae capable of producing extended-
spectrum beta-lactamases (ESBLs) is a cause for concern. With the
exception of carbapenems, ESBL-producing organisms are resis-
tant to cephalosporins, and as such, strains capable of producing
carbapenemase enzymes are closely monitored (325). As MALDI-
TOF MS is demonstrated to be a sensitive method for the analysis
of cellular products from bacteria, it makes sense that it could
potentially be used to characterize products of antibiotic resis-
tance mechanisms. This may be accomplished by observations
based simply on the change of molecular mass of antibiotic com-
pounds due to their alteration as a mechanism of resistance (i.e.,
beta-lactam antibiotics and beta-lactamase production).
In 2007, Camara and Hays used MALDI-TOF MS to discrimi-
nate between ampicillin-resistant and -sensitive strains of E. coli
by MALDI-TOF MS. While largely a control study of MS sensitiv-
ity, their investigation demonstrated that the technology could
identify the presence of the beta-lactamase enzyme in spectra gen-
erated from protein extracts obtained from broth-grown cultures
(326). Since then, a number of additional studies were undertaken
to investigate beta-lactam resistance among bacteria, albeit focus-
ing more on the fate of the antibiotic (hydrolysis and degradation,
etc.) than on the physical presence of the resistance determinant.
Sparbier et al. detected hydrolysis of the beta-lactam ring after a
few hours of incubation by detecting a mass shift of ⫹18 Da.
Different enterobacteria were screened for resistance to ampicil-
lin, piperacillin, cefotaxime, ceftazidime, ertapenem, imipenem,
and meropenem (327). Similar studies have also been performed
to examine carbapenemase activity in enteric organisms and
members of the genus Pseudomonas, with good results and rapid
turnaround times reported to be as quick as 1 to 4 h following the
initiation of testing (328, 329).
Carbapenem-Resistant Acinetobacter baumannii
Carbapenem-resistant Acinetobacter baumannii is a concern for
clinicians, as it drastically limits options for antibiotic interven-
tion (330). Kempf et al. analyzed 63 well-characterized carbap-
enem-resistant A. baumannii strains for carbapenemase produc-
tion using a 4-h preincubation with imipenem, centrifugation,
and MALDI-TOF assessment of supernatant for imipenem me-
tabolite-specific peaks. In addition, 43 non-carbapenemase-pro-
ducing strains and 43 control strains (7 carbapenem-resistant and
36 carbapenem-sensitive strains) were studied. For this strain set
of clinical isolates, sensitivity and specificity were 100.0% (331).
Clark et al.
590 cmr.asm.org Clinical Microbiology Reviews
Another method used meropenem and this approach was success-
fully validated on 108 carbapenemase-producing members of the
Enterobacteriaceae, 2 NDM-1-producing A. baumannii isolates,
and 35 carbapenem-resistant enterobacteria producing no car-
bapenemase (332).
Results of rapid MALDI-TOF MS analysis for the detection of
carbapenemase activity are promising, and investigators have be-
gun to establish standardized procedures for the identification of
antibiotic resistance among isolates in a similar manner to what
has been done for routine bacterial identification. Recently, iso-
lates of A. baumannii identified by rpoB sequencing were included
in a study to standardize a sample-processing workflow for the
determination of carbapenem resistance by MALDI-TOF MS.
MICs of imipenem and meropenem were determined, and
MALDI-TOF MS was performed by using samples treated with
four different concentrations of imipenem diluted in three differ-
ent testing solutions with and without the addition of SDS. Com-
parison of the peaks generated by MALDI-TOF MS to the spec-
trum of imipenem allowed for the selection of peaks that could be
related to antibiotic hydrolysis. A standard protocol was derived, 1
mg/ml imipenem with 2.5 ⫻ 10
10
CFU/ml inoculum incubated at
35°C for 1 h with shaking (500 rpm) and then validated against A.
baumannii isolates that produced different types of carbapen-
emases (333).
Carbapenem-Resistant Klebsiella spp.
The spread of carbapenem-resistant Klebsiella spp. is of significant
concern to health care practitioners, as K. pneumoniae is known to
be a significant cause of nosocomial infections and a reservoir for
the accumulation and dissemination of antibiotic resistance de-
terminants among endogenous bacteria (334). Recently, MALDI-
TOF MS was evaluated for the detection of carbapenem resistance
among strains of Klebsiella spp.
Porins serve as channels at the Gram-negative outer membrane
that allow the diffusion of molecules (including beta-lactam anti-
biotics) into the cell. The loss or reduced expression of specific
outer membrane proteins (OMPs) is implicated as a mechanism
for carbapenem resistance. One of these OMPs, OmpK36, has
been identified as a major membrane porin of K. pneumoniae
(335). Porin analysis of bacterial isolates is often relegated to
specialized laboratories, with analysis being labor-intensive and
requiring techniques not found in most routine clinical microbi-
ology laboratories (typically SDS-PAGE). In a study of eight car-
bapenem-resistant K. pneumoniae isolates and one K. oxytoca iso-
late, loss of OmpK36 was investigated by using MALDI-TOF MS.
Strains previously determined to be deficient in OmpK36 were
identified and compared to strains that were known to express the
protein, although more robust analysis will be necessary to vali-
date this method (336).
Carbapenem-Resistant Bacteroides fragilis
Resistance to carbapenem antibiotics in B. fragilis strains is medi-
ated through the carriage and expression of the cfiA gene, which
produces an imipenem-hydrolyzing metallo--lactamase (337).
Using a number of molecular techniques, including MLST and
ribotyping, B. fragilis strains characterized as cfiA positive or neg-
ative were found to belong to two genotypically distinct groups
(338). Due to the ability of MALDI-TOF MS to be able to discrim-
inate between strains of bacteria that are closely related, a number
of studies have examined the ability of the technology to differen-
tiate strains that are cfiA positive from those that are cfiA negative.
A study by Wybo et al. determined that MALDI-TOF MS pro-
vided a suitable mechanism to distinguish between cfiA-positive
and -negative B. fragilis isolates. Cluster analysis of B. fragilis clin-
ical isolates clearly delineated these two groups, and this delinea-
tion was found not to be dependent upon the presence or absence
of a single spectral peak (338). Nagy et al. reported similar results
with a set of 40 clinical isolates. Using a subset of 12 of these
isolates with known cfiA status, the authors compared these results
to spectra derived from 28 B. fragilis isolates of unknown cfiA
status. The two groups of B. fragilis were again clearly separated by
MALDI-TOF MS spectral analysis (339), suggesting that MALDI-
TOF MS may be a useful tool for the rapid identification of these
resistant bacteria.
MRSA and Vancomycin-Intermediate Staphylococcus aureus
Some investigations into the ability of MALDI-TOF MS to rapidly
identify methicillin-resistant isolates of S. aureus within in the
context of bacterial identification and lineage determination have
been described elsewhere in this review (83, 85). Here we describe
additional studies examining the characterization of resistant iso-
lates, including vancomycin intermediately resistant S. aureus
(VISA) strains.
An examination of the use of MALDI-TOF MS for the identifi-
cation of biomarkers that could be used to rapidly identify hospi-
tal-acquired MRSA (HA-MRSA), community-acquired MRSA
(CA-MRSA), heterogeneous VISA (hVISA), and VISA was per-
formed with a collection of reference and clinical isolates by using
ethanol-extracted proteins for analysis. Following optimization of
bacterial culture and MS procedures, spectra were analyzed for the
identification of specific biomarkers that could be used to discrim-
inate between HA-MRSA and CA-MRSA isolates. Relationships
between the generated spectra and SCCmec types of the strains
could be discerned, with the peptide profiles from SCCmec types I
to III differing from the profiles from SCCmec types IV and V.
Two distinct spectral peaks belonging to members of the phenol-
soluble modulin family of proteins were reported, which could
potentially be used to differentiate between HA-MRSA and CA-
MRSA strains following bacterial identification. Additional peaks
were also identified in hVISA and VISA strains belonging to pro-
cessed forms of acyl carrier protein, which could potentially be
useful for determination of vancomycin resistance in S. aureus
isolates by MALDI-TOF MS (340).
Wolters et al. established a method of typing MRSA isolates
using MALDI-TOF MS analysis for the most abundant HA-
MRSA strains. A total of 85 MRSA strains belonging to the five
major HA-MRSA clonal complexes (CCs) were analyzed in the
course of the study, with 25 being utilized for preliminary spectral
analysis and the remaining 60 being used for downstream evalu-
ation of the derived method. Unique spectral peaks obtained from
the 25 preliminary isolates were identified and used to classify the
remaining 60 isolates. Fifteen different groups were identified by
MALDI-TOF analysis and had good concordance with CC group-
ings, as determined by spa typing. The authors used FA extraction
of proteins in order to streamline their method into most labora-
tory MS workflows, and results could be provided for up to 19
isolates in 2.5 h (88).
In a similar investigation regarding the use of MALDI-TOF MS
for characterizing specific lineages of S. aureus, Josten et al. chose
to examine peptides identified in the MS spectra of S. aureus and
MALDI-TOF Mass Spectrometry in Clinical Microbiology
July 2013 Volume 26 Number 3 cmr.asm.org 591
MRSA isolates that exhibited mass shifts in order to evaluate the
technology for lineage-specific identification. MRSA isolates
could be differentiated into specific CCs, as could MSSA isolates.
The method was then tested by using 33 isolates from an outbreak.
MALDI-TOF MS could identify the CC associated with a majority
of isolates responsible for the outbreak and delineate between dif-
ferent outliers within this collection that were not associated with
the outbreak of MSSA and borderline oxacillin-resistant S. aureus
(BORSA) (341).
Each of the above-mentioned studies demonstrates the strong
discriminatory power that MALDI-TOF/MS exhibits for identifi-
cation and characterization of drug-resistant S. aureus. Because of
these findings, further research should be aimed at enhancing
these studies with more streamlined methods and evaluating de-
termined typing schemes with large collections of geographically
diverse isolates from HA-MRSA and CA-MRSA lineages with the
ultimate goal of realizing a real-time typing method using
MALDI-TOF MS instrumentation for use in the clinical labora-
tory.
Vancomycin-Resistant Enterococcus
Glycopeptide antibiotics are used as a cornerstone for the treat-
ment of severe or resistant Gram-positive infections. Vancomy-
cin-resistant enterococci pose a significant burden to health care
systems worldwide. The acquisition of resistance genes and the
protein components that they encode was proposed to be a poten-
tial mechanism whereby vancomycin-resistant enterococci could
be differentiated from vancomycin-sensitive isolates by MALDI-
TOF MS. In fact, MALDI-TOF MS was demonstrated to be able to
rapidly and accurately discriminate vanB-positive Enterococcus
faecium isolates from susceptible strains, in addition to examining
relatedness between strains during an outbreak situation (342).
Extension of such rigorous analysis could be beneficial, especially
when considering organisms that rely on similar mechanisms for
glycopeptide resistance.
FUTURE VIEW AND IMPLICATIONS
Although some of the methods described here are currently still
restricted to clinical research laboratories and large reference lab-
oratories, the potential of these testing algorithms to move into
routine clinical microbiology and public health laboratories seems
imminent. The implementation of MALDI-TOF MS in the rou-
tine clinical laboratory will provide a powerful and accurate tool
to quickly identify bacteria, mycobacteria, fungi, and Nocardia
from culture. Further improvements in specimen processing of
blood culture broth and urine will be required prior to implemen-
tation in clinical laboratories that will be faced with the challenge
of selecting between MALDI-TOF methods and emerging molec-
ular methods to identify bacteria from broth or directly from spec-
imens. Improvements to spectral databases and analysis software
should optimize the use of MALDI-TOF methods and should re-
duce the turnaround time for identification of nearly all microbes.
In the future, mass spectrometers will be linked with automated
antimicrobial susceptibility systems, thus allowing partial or com-
plete automation of routine microbial characterization. The first
generation of this automation, the BD Kiestra system, is available
from Becton Dickinson. Integration of MALDI-TOF analysis
should greatly impact the current processes used in clinical micro-
biology laboratories. Additionally, research dedicated to adapting
MALDI-TOF MS technology to the direct analysis of patient spec-
imens shows promise and may eliminate the need for culture in
some cases, thus streamlining diagnostic analysis, which could
result in shorter hospital stays, improved prognoses, and de-
creased financial burden to both the hospital and patient. Rapid
and accurate identification of microorganisms directly from clin-
ical specimens is becoming an expectation for clinical laborato-
ries, essential for optimal diagnosis and treatment of patients with
infections, and MALDI-TOF technology may support these ef-
forts in the future, but direct-from-specimen testing methods are
not currently available.
As the number of studies examining the accuracy and applica-
bility of MALDI-TOF MS in routine clinical situations continues
to grow, so too will publications examining the financial and clin-
ical benefits of implementing this rapid technology. An exemplary
study by Tan et al. prospectively examined the implementation of
MALDI-TOF MS in terms of time to identification in a specimen-
based, bench-to-bench approach. This facilitated the real-time
evaluation of the technology within the clinical workflow and al-
lowed direct evaluation of instrument performance compared
with traditional methodologies. Reduced laboratory costs and
time to results were reported when using MALDI-TOF MS for
routine testing. This study should serve as a model for future in-
vestigations regarding the implementation of MALDI-TOF MS in
different laboratories and evaluations of associated benefits and
drawbacks (171).
Newer determinative technologies are constantly evolving for
clinical microbiology laboratories, aiding the evolution of the mi-
crobiology laboratory from one of the slowest of all laboratory
services to one that is a plastic and dynamic entity able to directly
influence patient outcomes with speed and robust accuracy. As we
usher in an era of improved response and higher expectation of
accuracy, clinical laboratories are consistently striving to extend
the capabilities of these new methods, often in partnership with
developmental scientists, resulting in novel technologies, such as
MALDI-TOF MS, which should shape and define the diagnostic
landscape for years.
ACKNOWLEDGMENTS
We thank Kevin A. Lewis for assistance with generation and rendering of
figures and Linda Hilbert, Nina Nguyen, and Natalie Whitfield for critical
reading of the manuscript.
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Andrew E. Clark, M.S., is a Ph.D. student in the
Department of Veterinary Science and Micro-
biology at the University of Arizona, Tucson,
AZ. He is a microbiologist with interests in ap-
plied clinical, diagnostic, and molecular micro-
biology. He has worked extensively in both clin-
ical and basic research laboratories, with special
interest in the development and evaluation of
molecular techniques for the diagnosis and
characterization of bacterial infections. His cur-
rent research is directed toward understanding
the molecular events leading to Clostridium difficile colonization and the
interplay between pathogen and subsequent host immune responses.
Erin J. Kaleta, Ph.D., received her bachelor’s
degree in biochemistry from Cedar Crest Col-
lege and doctorate in chemistry from the Uni-
versity of Arizona. She is currently a clinical
chemistry fellow in the Department of Labora-
tory Medicine and Pathology at the Mayo
Clinic. She has been involved in a diverse range
of mass spectrometry research for about 10
years, having worked in clinical microbiology as
well as analytical chemistry, clinical chemistry,
and proteomics.
Amit Arora, M.D., is currently pursuing his
master’s of science (M.S.) in Epidemiology at
the Mel and Enid Zukerman College of Public
Health at the University of Arizona (UA). He
completed his medical education in India,
where he also served as the lead facilitator and
analyst for multiple phase I and II clinical trials
for various respiratory diseases. As an M.S. can-
didate, Dr. Arora is currently collaborating with
researchers at the UA BIO5 Institute on
genomic analysis of quantitative traits among
type II diabetic patients. His further research interests lie in analytical meth-
ods in bioinformatics and high-throughput genomic and quantitative pro-
teomics.
Clark et al.
602 cmr.asm.org Clinical Microbiology Reviews
Donna M. Wolk, M.H.A., Ph.D., D(ABMM), is
an Associate Professor at the Arizona Health
Science Center and a Clinical Research Scholar
at the University of Arizona’s BIO5 Institute,
which houses her clinical and translational re-
search efforts in the Infectious Disease Research
Core Laboratory. She currently serves as the
System Director of Clinical Microbiology at
Geisinger Health System in Danville, PA, and as
a principal investigator at the Weis Center for
Research. Her translational research efforts fo-
cus on evaluation of new technology for infectious disease diagnostics, thus
her interest in mass spectrometry as a tool in clinical microbiology. She
received her Ph.D. in Pathobiology at the University of Arizona and rejoined
the faculty in 2001, after completing a postdoctoral Medical and Public
Health Microbiology Laboratory fellowship at Mayo Clinic in Rochester,
MN. She is a Diplomate of the American Board of Medical Microbiology
(ABMM) and earned a master’s degree in Health Administration.
MALDI-TOF Mass Spectrometry in Clinical Microbiology
July 2013 Volume 26 Number 3 cmr.asm.org 603
