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Neuropeptides are a diverse category of signaling molecules in the nervous system regulating a variety of processes including food intake, social behavior, circadian rhythms, learning, and memory. Both the identification and functional characterization of specific neuropeptides are ongoing fields of research. Matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF MS) analysis of nervous tissues from a variety of organisms allows direct detection and identification of neuropeptides. Here, we demonstrate an analysis workflow that allows for the detection of differences in specific neuropeptides amongst a variety of neuropeptides being simultaneously measured. For sample preparation, we describe a straight-forward and rapid (minutes) method where individual adult Drosophila melanogaster brains are analyzed. Using a MATLAB-based data analysis workflow, also compatible with MALDI-TOF mass spectra obtained from other sample preparations and instrumentation, we demonstrate how changes in neuropeptides levels can be detected with this method. Over fifty isotopically resolved ion signals in the peptide mass range are reproducibly observed across experiments. MALDI-TOF MS profile spectra were used to statistically identify distinct relative differences in organ-wide endogenous levels of detected neuropeptides between biological conditions. In particular, three distinct levels of a particular neuropeptide, pigment dispersing factor, were detected by comparing groups of preprocessed spectra obtained from individual brains across three different D. melanogaster strains, each of which express different amounts of this neuropeptide. Using the same sample preparation, MALDI-TOF/TOF tandem mass spectrometry confirmed that at least 14 ion signals observed across experiments are indeed neuropeptides. Among the identified neuropeptides were three products of the neuropeptide-like precursor 1 gene previously not identified in the literature. Using MALDI-TOF MS and preprocessing/statistical analysis, changes in relative levels of a particular neuropeptide in D. melanogaster tissue can be statistically detected amongst a variety of neuropeptides. While the data analysis methods should be compatible with other sample preparations, the presented sample preparation method was sufficient to identify previously unconfirmed D. melanogaster neuropeptides.
Overview of spectra acquired within an experiment where changes in ion signals corresponding to PDF were detectable statistically. A) Total average spectrum used to define peaks detected within an experiment. The isotopic distribution with monoisotopic peak at m/z 1972.0 is shown in inset. Peak bins detected using our described criteria are highlighted in blue. B) Pseudogel view after preprocessing of all spectra acquired in a particular replicate experiment. C) Zoomed in pseudogel view at m/z regions containing the isotopically resolved [M + H]+ of IPNamide (monoisotopic m/z 1653.9, left panel) and the [M + H]+ of PDF (monoisotopic m/z 1972.0, boxed off in orange dashed lines, right panel) and the [M + K]+ of PDF (monoisotopic m/z 2010.0, boxed off in blue dashed lines, right panel). Also seen in right panel is the isotopic distribution with monoisotopic peak at m/z 1991.0 (boxed off in the dashed magenta lines), corresponding to the truncated and amidated variant of NPLP13 (QRAamide). Peaks trailing from this distribution observed in the PDF overexpressing flies likely corresponds to the [M + Na]+ of PDF (monoisotopic m/z 1994.0, marked by an asterisk) which was not resolved enough in the total average spectrum to be detected as a distinct isotopic distribution. D) Averages of preprocessed spectra within experimental conditions at two m/z regions (red = PDF-null, black = WT, blue = PDF overexpressing). The [M + H]+ of IPNamide (left, 95% confidence intervals shown to the left of each peak for clarity), which was found not to vary significantly across conditions (Kruskal-Wallis ANOVA raw p-value = 0.22), is compared with the [M + H]+ of PDF (right), which was detected to be significantly different across the three conditions (Bonferroni-adjusted p-value = 0.0017).
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M E T H O D O L O G Y Open Access
A rapid MALDI-TOF mass spectrometry workflow
for Drosophila melanogaster differential
Joseph P Salisbury
, Kristin J Boggio
, Yun-Wei A Hsu
, Jeniffer Quijada
, Anna Sivachenko
Gabriele Gloeckner
, Paul J Kowalski
, Michael L Easterling
, Michael Rosbash
and Jeffrey N Agar
Background: Neuropeptides are a diverse category of signaling molecules in the nervous system regulating a
variety of processes including food intake, social behavior, circadian rhythms, learning, and memory. Both the
identification and functional characterization of specific neuropeptides are ongoing fields of research.
Matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF MS) analysis of nervous tissues
from a variety of organisms allows direct detection and identification of neuropeptides. Here, we demonstrate an
analysis workflow that allows for the detection of differences in specific neuropeptides amongst a variety of
neuropeptides being simultaneously measured. For sample preparation, we describe a straight-forward and rapid
(minutes) method where individual adult Drosophila melanogaster brains are analyzed. Using a MATLAB-based data
analysis workflow, also compatible with MALDI-TOF mass spectra obtained from other sample preparations and
instrumentation, we demonstrate how changes in neuropeptides levels can be detected with this method.
Results: Over fifty isotopically resolved ion signals in the peptide mass range are reproducibly observed across
experiments. MALDI-TOF MS profile spectra were used to statistically identify distinct relative differences in
organ-wide endogenous levels of detected neuropeptides between biological conditions. In particular, three distinct
levels of a particular neuropeptide, pigment dispersing factor, were detected by comparing groups of preprocessed
spectra obtained from individual brains across three different D. melanogaster strains, each of which express different
amounts of this neuropeptide. Using the same sample preparation, MALDI-TOF/TOF tandem mass spectrometry
confirmed that at least 14 ion signals observed across experiments are indeed neuropeptides. Among the identified
neuropeptides were three products of the neuropeptide-like precursor 1 gene previously not identified in the literature.
Conclusions: Using MALDI-TOF MS and preprocessing/statistical analysis, changes in relative levels of a particular
neuropeptide in D. melanogaster tissue can be statistically detected amongst a variety of neuropeptides. While the data
analysis methods should be compatible with other sample preparations, the presented sample preparation method
was sufficient to identify previously unconfirmed D. melanogaster neuropeptides.
Keywords: Neuropeptidomics, MALDI-TOF, Drosophila melanogaster, Neuropeptides, Pigment dispersing factor,
Tandem mass spectrometry, NPLP1, Neuropeptide-like precursor 1
* Correspondence:
Equal contributors
Depts of Chemistry and Chemical Biology and Pharmaceutical Sciences and
Barnett Institute of Chemical and Biological Analysis, Northeastern University,
140 The Fenway, Boston, MA 02115, USA
Full list of author information is available at the end of the article
© 2013 Salisbury et al.; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative
Commons Attribution License (, which permits unrestricted use, distribution, and
reproduction in any medium, provided the original work is properly cited. The Creative Commons Public Domain Dedication
waiver ( applies to the data made available in this article, unless otherwise
Salisbury et al. Molecular Brain 2013, 6:60
Neuropeptides are a large and diverse class of signaling
molecules that affect numerous processes, including behav-
ior, development, heart rate, metabolism, and reproduction
[1,2]. These peptides, mostly exerting their role by acting
upon G-protein coupled receptors [3], can function as clas-
sical hormones, localized neurohormones [4], at muscles
and glands, and synaptically, where they can modify the
postsynaptic response to classical, fast-acting neurotrans-
mitters [5]. Studies of neuropeptide function that cross a
wide variety of aspects of behavior and development have
been particularly productive in the model organism Dros-
ophila melanogaster [3,6-14], which benefits from excep-
tional genetic manipulation tools developed for the study of
the molecular mechanisms of development and behavior.
In model insects such as D. melanogaster,Apis mellifera
(honeybee), and Tribolium castaneum (red flour beetle),
3040 genes have been consistently identified as encoding
neuropeptides [8,15,16], with each gene product potentially
producing multiple different mature neuropeptides. To
become active, neuropeptides often require multiple
post-translational modifications, such as proteolysis and
amidation, which are difficult to infer from a genome and
necessitate that putative neuropeptides be directly identi-
fied in organisms, often using mass spectrometry-based
methods. Bioinformatics studies have predicted as many
as 156 neuropeptides encoded by 33119 putative neuro-
peptide genes in D. melanogaster, and a total of 76 neuro-
peptides from 21 genes have been detected experimentally
[3,17]. The sensitivity of MS-based methods has allowed
for detection and identification of neuropeptides from
specific nervous system regions and cellular populations
across the developmental lifespan of D. melanogaster
[1,6,7,9,18,19] permitting precise temporal and spatial
localization to be ascribed to various neuropeptides.
While great strides have been made towards compre-
hensive identification of D. melanogaster neuropeptides,
functional characterization is lacking for many. For ex-
ample, the majority of the peptides derived from the
D. melanogaster gene neuropeptide-like precursor 1
(NPLP1) remain orphanedwithout an identified re-
ceptor and/or physiological function [20]. Quantitative
neuropeptidomics provides a discovery tool for ascer-
taining functional significance of neuropeptides, with
goals of monitoring and quantifying changes in levels
of multiple neuropeptides in response to experimental
perturbations such as those eliciting complex behav-
ioral responses. For example, isotope labeling followed
by UPLC-ESI-QTOF has been used to quantify ~50 of
known Apis mellifera brain peptides in the context of
foraging, revealing molecular connections between the
regulation of food intake in individual insects and this
social behavior, as well as distinctions between nectar
and pollen gathering [21]. Isotopic labeling from extracts
using MALDI-TOF MS combined with direct tissue
MALDI imaging has been used to provide complemen-
tary information regarding changes in the expression
of an array of neuropeptides during feeding in both the
brain and pericardial organ of the crab Cancer borealis
[22]. A label-free LC-Orbitrap approach was employed
to analyze extracts from hypothalamus and striatum
from rats, using higher-energy collision dissociation and
electron transfer dissociation fragmentation to identify
more than 1700 endogenous peptides, revealing upregula-
tion of orexigenic and anorexigeneic neuropeptides in ani-
mals fed on a high-fat/high-sucrose diet [23]. Direct access
to quantitative neuropeptidomics techniques, however, is
often limited to laboratories equipped with a considerable
array of specialized instrumentation, reagents, and per-
sonnel, preventing these methods from being more
routinely utilized by those studying D. melanogaster devel-
opment and behavior. Thus, we sought to develop a rapid
method for performing differential expression neuropepti-
domics studies utilizing D. melanogaster that does not re-
quire specialized reagents or advanced MS instrumentation.
Furthermore, we wanted to present a data analysis work-
flow utilizing software that could preprocess and statistically
analyze MS data regardless of instrument manufacturer.
Here we present a D. melanogaster sample preparation
method that, when analyzed with matrix-assisted laser
desorption/ionization time-of-flight mass spectrometry
(MALDI-TOF MS), reliably detects an abundance of
ions in the peptide mass range, 14 of which we subse-
quently confirmed by MALDI-TOF/TOF tandem mass
spectrometry (MS/MS) to be D. melanogaster neuropep-
tides. Amongst the neuropeptides we identified by MS/
MS fragmentation were three peptides derived from the
NPLP1 gene not identified previously in the literature.
Utilizing a MATLAB-based spectra preprocessing work-
flow, we demonstrate the ability to statistically detect
differences in the expression of a specific neuropeptide,
amongst all the ions we simultaneously observe, without
isotopic labeling using MALDI-TOF MS.
Results and discussion
Straight-forward on-target peptide extraction provided
adequate signal quality for MALDI-TOF MS profiling as
well as targeted MALDI-TOF/TOF MS/MS
We set out to develop a sample preparation strategy for
comparing neuropeptidomes from D. melanogaster that:
could be performed in minutes, thus preserving labile
biomolecules; could detect a large number of ions simul-
taneously, ideally with abundant enough signal to confi-
dently identify using MALDI-TOF/TOF MS/MS; did not
require extensive utilization of specialized reagents or
equipment beyond a standard benchtop MALDI-TOF
MS (at least for detection); and that utilized, ideally, only
a single fly brain as an individual sample for statistical
Salisbury et al. Molecular Brain 2013, 6:60 Page 2 of 15
comparisons. The overall sample preparation we used
consisted of dissection of individual D. melanogaster
brains followed by their direct placement onto a steel
MALDI target, an on-target wash, and matrix applica-
tion. As a dissection medium, a modified dissection sa-
line consisting of 7.5 g/L NaCl, 0.2 g/L KCl, 0.2 g/L
, and 0.1 g/L NaHCO
in MilliQ water (pH 7.2) [6]
was chosen as it yields a high number of detected ion
signals and a relatively low baseline compared with dis-
section solutions with higher concentrations of salts. So-
lutions of fructose [24], Tris, and ammonium bicarbonate
were evaluated as wash steps at various concentrations,
with 100 mM ammonium bicarbonate producing the most
abundant number of ions detected in the peptide mass
range. Included in the detectable peaks with this sample
preparation was m/z 1972.0, which we believed and later
confirmed was the neuropeptide pigment-dispersing factor
(PDF). This relatively low abundance peptide was used in
subsequent experiments (see below) to demonstrate that
known differences in relative levels of neuropeptides could
be detected with this technique. With the ammonium bi-
carbonate wash, however, excess ammonium bicarbonate
on the MALDI target after drying from the wash and sub-
sequent matrix deposition was occasionally observed,
which can interfere with homogenous crystallization of
MALDI matrix and decrease the quality of acquired spec-
tra (~10% of spectra). Alternatively, we found washing by
dipping the brain in ammonium bicarbonate after dissec-
tion, but prior to placement on the MALDI target, as an
alternative to the on-target wash. Data shown in the pro-
filing experiments comparing flies with varying of PDF
were acquired from samples prepared with the on-target
wash, with spectra only acquired from samples that were
not contaminated by excess ammonium bicarbonate.
Finally, various concentrations of 2,5-dihydroxybenzoic
acid (DHB) and α-cyano-4-hydroxycinnamic acid (CHCA)
were tested, ranging from 1050 mg/mL and 510 mg/mL,
respectively, as a matrix for MALDI-MS analysis, with
10 mg/mL CHCA providing the most reliable and highest
quality spectra in terms of number of peaks with signal-to-
noise (S/N) ratios greater than 6. During MS acquisition
we noted that the entire crystalline matrix surface across a
given spotted sample on the target did not yield homoge-
neous spectra. Specifically, both the surface of the brain it-
self and the edges of the MALDI spot yielded poor S/N
ratios, leaving a haloregion of high S/N spectra around
the tissue (Additional file 1: Figure S1), consistent with
what has long been observed in MALDI analyses of bio-
logical peptides from tissue samples [25]. We attempted to
improve homogeneity by trituration of the matrix solution;
by homogenizing the brain on-target using a pipette tip or
pressing with a cover slip; and by using a microcentrifuge
tube homogenizer, but all of these procedures resulted
in reduced S/N spectra. Overall, minimal mechanical
perturbation of the brain was found to be important for
achieving optimal quality spectra from single brains. Spec-
tra of homogenized samples could be improved using a re-
versed phase ZipTip,but this required ~20 brains and
added an additional step. As a result of the lack of MALDI
spot homogeneity, we cannot be sure that peptides from all
regions of the brain are extracted with identical efficiency.
While this might prevent analysis of specific neuropeptides
using this method, our primary goals of being able to detect
simultaneously a variety of neuropeptides from various re-
gions of the brain (as well as determine distinct differences
in the levels of these neuropeptides when making experi-
mental comparisons, with particular focus on PDF, as de-
scribed below) were achieved.
Overall, raw spectra acquired with the final method
yielded spectra with 37 ± 9.6 (mean ± S.D.) isotopically
resolved peak distributions of S/N greater than 6 within
the m/z 9004000 range prior to any preprocessing
1972.0, confirmed in experiments below to correspond
to the monoisotopic [M +H]
of the neuropeptide PDF.
Using the yellow white (yw, henceforth referred to as WT
or wild-type flies) fly strain as a control strain, the PDF
signal from m/z 1972.0 was often detectable in spectra
from individual fly brains, but often only barely distin-
guishable from noise (Figure 1A inset). To demonstrate
this sample preparation technique could be used in a dif-
ferential neuropeptide profiling experiment to statistically
identify differences in neuropeptide-derived ion signals,
including neuropeptide-derived ion signals with low S/N
ratios like PDF, flies expressing varying levels of PDF were
obtained and analyzed. In particular, the pdf
fly strain
[14] (henceforth referred to as PDF-nullflies) was used
as a mutant strain lacking any expression of mature PDF
and flies overexpressing PDF throughout the adult ner-
vous system (referred subsequently in the text as PDF
overexpressingflies) were generated using the GAL4-
UAS binary expression system [26] by crossing the pan-
neuronal elav-GAL4 driver line with a UAS-Drm-pdf line
(see Methods section). Indeed, in spectra from individual
flies, the ion signal corresponding to PDF was never ob-
served in samples from PDF-null flies (Figure 1B), and
was almost always observed with S/N > 6 in spectra from
PDF overexpressing flies (Figure 1C). From this, we deter-
mined an experimental design that would permit changes
in PDF to be statistically identified to validate this sample
preparation method as a means for differential profiling of
Preprocessing of spectra permitted statistical
identification of distinct detection levels of ions
corresponding to neuropeptide PDF
The most accurate methods of MS-based quantification
generally involve the use of isotopologue standards [21].
Salisbury et al. Molecular Brain 2013, 6:60 Page 3 of 15
Relative quantitation of neuropeptide standards can be
achieved over a thousand-fold concentration range on a
MALDI-TOF mass spectrometer using isotopic labeling
after careful selection of appropriate data acquisition pa-
rameters [27]. Our method could be adapted to isotope
dilution using any of the strategies demonstrated to
quantify neuropeptides in single neurons or neuron clus-
ters [28]. However, in the current study, we show it is
also possible to detect several distinct levels of expres-
sion of a neuropeptide in a label-free profiling approach
using preprocessed MALDI-TOF MS spectra acquired
from individual D. melanogaster brains. To achieve this,
MALDI-TOF MS spectra from brains of WT flies were
compared to PDF-null flies and PDF overexpressing flies.
All brains were dissected from flies within a two hour
window centered at Zeitgeber time 2 after entrainment
to a 12:12-hour lightdark cycle at 25°C. Within an ex-
periment, fly brains were analyzed individually, with
multiple fly brains per genotype analyzed to permit stat-
istical analysis of differences observed. Two full experi-
ments were performed in order to further analyze the
experimental reproducibility. In one experiment where
the relative expression levels of PDF were compared, spec-
tra were acquired from 10 WT,7 PDF-null, and 9 PDF
overexpressing D. melanogaster brains. In a second ex-
periment, spectra were acquired from 9 WT, 7 PDF-null,
and 9 PDF overexpressing D. melanogaster brains. Differ-
ences in sample numbers between experiments occurred
due to spectra not being acquired from certain prepared
samples judged to have poor crystallization, potentially
from excess ammonium bicarbonate.
In order to use mass spectra obtained from individual
fly brains for the purposes of differential neuropeptide
expression analysis, a spectra preprocessing workflow
[29] was employed that includes spectrum denoising,
baseline correction, and normalization (see Methods
section for full description of preprocessing). Peaks bins
were then chosen from peaks identified in a total average
spectrum, which was calculated from all spectra (after
preprocessing) acquired across the three conditions
(Figure 2A). Deisotoping criteria was applied in order
to identify isotopically resolved peak distributions from
the peaks detected in the total average spectrum. The
inset of Figure 2A highlights the peak bins that were
considered to be a single isotopomer distribution with
a monoisotopic peak at m/z 1972.0 (i.e. PDF). While
over 300 peaks were identified in the total average
spectra of the two replicate experiments described
here, after applying deisotoping criteria, exactly 57 iso-
topically resolved distributions were identified in either
experiment, with 52 ion masses observed common to
both replicate experiments (Additional file 2: Table S1).
Peak bins corresponding to isotopically resolved ion
signals were used to query across all preprocessed
Figure 1 Representative raw spectra from WT flies and flies
lacking expression of, and overexpressing, PDF. A) Spectra
acquired from WT flies included many well resolved peaks with ion
signal at m/z 1972.0 (inset, [M + H]
of PDF) generally resolvable,
although often with low S/N. B) Spectra acquired from PDF-null flies
were similarly rich in features, but without discernible ion signal at
m/z 1972.0 (inset). C) Spectra acquired from PDF overexpressing flies,
while of overall similar quality to those obtained from WT flies, had
the ion signal at m/z resolved with far greater S/N.
Salisbury et al. Molecular Brain 2013, 6:60 Page 4 of 15
Figure 2 Overview of spectra acquired within an experiment where changes in ion signals corresponding to PDF were detectable
statistically. A) Total average spectrum used to define peaks detected within an experiment. The isotopic distribution with monoisotopic peak at
m/z 1972.0 is shown in inset. Peak bins detected using our described criteria are highlighted in blue. B) Pseudogel view after preprocessing of all
spectra acquired in a particular replicate experiment. C) Zoomed in pseudogel view at m/z regions containing the isotopically resolved [M + H]
of IPNamide (monoisotopic m/z 1653.9, left panel) and the [M + H]
of PDF (monoisotopic m/z 1972.0, boxed off in orange dashed lines, right
panel) and the [M + K]
of PDF (monoisotopic m/z 2010.0, boxed off in blue dashed lines, right panel). Also seen in right panel is the isotopic
distribution with monoisotopic peak at m/z 1991.0 (boxed off in the dashed magenta lines), corresponding to the truncated and amidated
variant of NPLP13 (QRAamide). Peaks trailing from this distribution observed in the PDF overexpressing flies likely corresponds to the [M + Na]
PDF (monoisotopic m/z 1994.0, marked by an asterisk) which was not resolved enough in the total average spectrum to be detected as a distinct
isotopic distribution. D) Averages of preprocessed spectra within experimental conditions at two m/z regions (red = PDF-null, black = WT, blue = PDF
overexpressing). The [M + H]
of IPNamide (left, 95% confidence intervals shown to the left of each peak for clarity), which was found not to vary
significantly across conditions (Kruskal-Wallis ANOVA raw p-value = 0.22), is compared with the [M + H]
of PDF (right), which was detected
to be significantly different across the three conditions (Bonferroni-adjusted p-value = 0.0017).
Salisbury et al. Molecular Brain 2013, 6:60 Page 5 of 15
spectra (Figure 2B). From this, a value for every ion sig-
nal isotopically resolved in the total average spectrum
was assigned in the individual sample spectra regardless
of whether that signal was detectable in any particular
sample spectrum. Identifying ion signals in a total aver-
age spectrum, as opposed to individual spectra, may re-
duce the sensitivity of feature detection. For example,
ion signals only detectable in a particular set of samples
might be averaged outin the total average spectrum.
However, by using a common set of peak bins across all
spectra, some value can be established for every ion sig-
nal for the purpose of statistical comparisons, avoiding a
missing valueproblem for peaks not otherwise detect-
ablein a given spectrum. Summed deisotoped intensities
were then compared with the non-parametric Kruskal-
Wallis analysis of variance (ANOVA) test (α=0.01). We
adjusted for multiple comparisons using the straight-
forward and conservative Bonferroni correction.
In the experiment comparing spectra from individual
brains of 10 WT,7 PDF-null, and 9 PDF overexpressing
D. melanogaster, there was sufficient power to detect
three significant differences between groups, including
the distributions with monoisotopic peaks at m/z
1972.0 (Bonferroni-adjusted p-value = 0.0017, confirmed
by MALDI-TOF/TOF MS/MS to be the [M + H]
PDF), m/z 2010.0 (Bonferroni-adjusted p-value = 0.0014,
inferred to be the [M + K]
of PDF), and m/z 1203.6
(Bonferroni-adjusted p-value = 0.0099, m/z currently
unassigned). Post-hoc analysis of the PDF species con-
firmed the difference was significant between all three
groups, with levels increasing in the logical order (Tukeys
least significant difference procedure, α=0.05). Figure 2C
and D illustrate differences in ion signals corresponding to
PDF compared to ion signal that did not vary significantly,
m/z 1653.9 (Raw p-value = 0.22, subsequently identified as
the [M + H]
of IPNamide). Post-hoc analysis of m/z
1203.6 suggested detection of this isotope distribution was
significantly reduced in the PDF overexpressing condition.
In the second full profiling experiment performed, spectra
were acquired from 9 WT, 7 PDF-null, and 9 PDF
overexpressing flies, with only two isotope distribu-
tions being significantly different, the [M + H]
of PDF
(Bonferroni-adjusted p-value = 0.0097) and the [M + K]
of PDF (Bonferroni-adjusted p-value = 0.0043). The
significance of the difference in the unidentified m/z
1203.6 was not replicated in this experiment (Bonfer-
roni-adjusted p-value = 0.1142, see Additional file 2:
Table S1 for full results of statistics from both experi-
ments). Post-hoc analysis of the PDF isotope distribu-
tions in this experiment again confirmed that PDF was
detected at distinct levels across the three conditions
in the expected order.
To further evaluate the general reproducibility of
this method, the correlation between intensities of
isotopically resolved ion signals detected in both experi-
ments was examined. Focusing specifically on the four-
teen ion signals later confirmed by MS/MS to be
neuropeptides (see next subsection), the correlation be-
tween replicates of the mean intensities of these signals
within the WT condition was high, with R
= 0.969
(Pearson correlation, Figure 3). In the other two experi-
mental conditions, the correlation between experiments
was still generally high, with R
= 0.894 for the PDF-null
condition and R
= 0.871 for the PDF overexpressing
condition (Additional file 2: Table S2). Expanding this
analysis out to all 52 isotopically resolved signals ob-
served in both experiments, the correlation was gener-
ally high in each condition, with R
= 0.957 for the
WT condition, R
= 0.848 for the PDF-null condition,
and R
= 0.914 for the PDF overexpressing condition
(Additional file 2: Table S3).
Neuropeptide PDF was potentially detected as both an
[M + H]
at m/z 1972.0 and an [M + K]
at m/z 2010.0
(as well as a [M + Na]
at m/z 1994.0, which was not full
resolved in the total average spectrum but is clearly
present in the PDF overexpressing condition, marked by
an asterisk in Figure 2). While both the [M + H]
[M + K]
were found to be reproducibly significantly dif-
ferent between the three genotypes examined, the ratio
of the relative intensities of these two forms of PDF ions
Figure 3 Comparison of mean preprocessed ion intensities and
95% confidence intervals between replicate experiments of
WT flies for the fourteen isotope distributions identified by
MALDI-TOF/TOF MS/MS to be neuropeptides. Linear regression
between the mean values of the fourteen isotope distributions gave an
= 0.969. The dashed red line shows where mean intensity values
should be had they been identical between the two repeat experiments.
The dashed purple and blue lines show where the log
ratio between
two conditions would be 1 or 2, respectively. 95% confidence intervals
in either experiment generally were within 1 log
Salisbury et al. Molecular Brain 2013, 6:60 Page 6 of 15
were not necessarily consistent across an experiment. In
particular, we evaluated the correlation between the in-
tensities of the [M + H]
and [M + K]
of neuropeptide
PDF within experiments (Additional file 2: Table S4). In
the second experiment, there was a high correlation be-
tween the [M + H]
and [M + K]
of neuropeptide PDF in
both the WT and PDF overexpressing conditions (R
0.957 and 0.951, respectively). There was no correlation
between the [M + H]
and [M + K]
signals in the PDF-
null samples from the second experiment (R
=0.022) as
would be expected given there should be no actual PDF
signal in those samples. In the first experiment, however,
while there remained a strong correlation between
the [M + H]
and [M + K]
signals in the WT samples
= 0.802), there was very low correlation between
the [M + H]
and [M + K]
within the PDF overex-
pressing samples (R
= 0.110), suggesting that perhaps
residual potassium was unevenly distributed amongst
samples in this experiment. Despite this inconsistency
in the relative abundance of the potassium adduct of
PDF compared with the [M + H]
, the differences in
PDF levels between genotypes examined in this ex-
periment were substantial enough to be detected whether
either ionized form of PDF was considered. However, as
this is a potentially confounding source of variability, it
is important to consider whether detected changes in
ion signal may be due shifts to different adduct ions,
potentially from biases introduced during sample prep-
aration such as inconsistent washing with ammonium
MS/MS analyses confirm many ions detected are
neuropeptide including three novel identifications
After utilizing MALDI-TOF MS profiling to identify dif-
ferences in particular ions, the next logical step would
be to identify what those ions are, preferably without
additional sample preparation. Indeed, MALDI-TOF/
TOF MS/MS data obtained using this sample prepar-
ation permitted identification of multiple neuropep-
tides, including PDF (Figure 4, Table 1). This was reassuring
given that one concern might have been that the ions we ob-
served were not in fact neuropeptides, but rather, for
Figure 4 MS/MS-based identification of PDF, CAP-3, SIFamide, and a novel NPLP1-derived peptide, NPLP1-2 (DPK peptide), from single
fly brains. MS/MS major peak assignments and corresponding sequence tags for: A,PDF;B,CAP-3;C, SIFamide; D, NPLP1-2 (DPK). Light blue
asterisk denotes the precursor ion. y-type ions are shown in dark blue. b- and a-type ions shown in red. Iminium ions are shown in green
and denoted by the one letter symbol of their respective amino acid followed by an asterisk. Internal fragments (b-y) are shown in green
and denoted by their amino acid sequence. Similar results were obtained in duplicate and triplicate analyses.
Salisbury et al. Molecular Brain 2013, 6:60 Page 7 of 15
example, proteolytic fragments from abundant pro-
teins. The rapidity of this sample preparation, preserv-
ing labile biomolecules, may be one reason we do not
have this problem. In-source/post-source decay could
also yield ions that obscure neuropeptide detection.
Thus far, however, none of the 14 molecular ions ana-
lyzed by MS/MS appear to result from the breakdown
of larger molecules during MS analysis.
Among identifications obtained were three previously
predicted but unconfirmed peptides originating from the
neuropeptide-like precursor 1 gene (NPLP1, Figure 5).
Included in these identifications were two variants of the
predicted NPLP1-3, without and without a C-terminal
GAE (with the peptide lacking GAE being C-terminally
amidated), and a peptide corresponding to the pre-
dicted NPLP1-2 but with a C-terminal lysine intact
(NIATMARLQSAPSTHRDPK, or following previous
convention, DPK peptide for short). It is possible the una-
midated, glycine-extended NPLP1-3 (NVAAVARYNSQH-
GHIQRAGAE) is a precursor to the truncated and
amidated variant (NVAAVARYNSQHGHIQRAa, or
QRAamide), which may be the functional form of this
peptide [31,32]. Four other peptides derived from
NPLP1 have been detected previously [1,7,33]. We also
identify three of these, IPNamide, MTYamide, and
VQQ, using MS/MS and tentatively assigned the fourth,
APK peptide (measured monoisotopic m/z 1423.814/the-
oretical 1423.827). While the VQQ peptide of NPLP1
(NPLP1-4) has been identified as a ligand for receptor
guanylate cyclase Gyc76C, serving a role in modulating
the innate immune IMD pathway in response to salt stress
[20], precise functions for the remaining NPLP1-derived
Table 1 Peaks observed in MALDI-TOF MS profile spectra confirmed to be neuropeptides by MALDI-TOF/TOF MS/MS
Obs. m/z
(Calc. m/z)
(UniProtKB Entry name)
Peptide name Peptide sequence Previous ref.
SNPF_DROME RLRF peptide 2 R.SPSLRLRFa.G [1,2,9,18,19,30]
FMRF_DROME DPKQDFMRFamide (FMRFamide 2) R.DPKQDFMRFa.G [1,2,7,9,19,30]
NEMS_DROME Dromyosuppressin (TDVDHVFLRFamide) R.TDVDHVFLRFa.G [1,2,7,9,18,19,30]
Q59E62_DROME SIFamide (IFa-1) A.AYRKPPFNGSIFa.G [1,2,9,18,19]
T.GPSASSGLWFGPRLa.G [1,2,9,19,30]
NPLP1_DROME MTYamide peptide
R.YIGSLARAGGLMTYa.G [1,2,7,9,18,19]
R.NVGTLARDFQLPIPNa.G [1,2,7,9,18,19,30]
Listed are D. melanogaster neuropeptides identified in this study. The final three listings are believed to be novel. Reported observed m/zs are the average of the
m/zs observed between the two replicate experiments MALDI-TOF MS exp eriments described. A ll obs erved m/zs listed were determined to be monoisotopic
[M + H]
s of listed neuropeptides based on the calculated monoisotopic [M + H]
(shown in parenthes es below observed m/z). Truncated peptides are denoted
by superscripts showing amino acids present from the annotated peptide sequence (i.e. NPLP1-3
is missing the final three residues o f th e an notated NPL P1-3
sequence, also shown). Peptide sequences include pre- and post- cleavage residues separated from sequences by a period. C-terminal amidation is denoted
by an aat end of the peptide sequence. Abbreviations are listed in Table 2legend. *m/z 925.481 likely corresponds to the convolution of PDNFMRFamide
(monoisotopic [M + H]
= 925.435) and Drostatin-3 (Ast-A3, monoisotopic [M + H]
= 925.489, see Table 2), which were detected as separate peaks with
MALDI-FTICR-MS (Figure 6), hence the comparatively larger m/z error.
Salisbury et al. Molecular Brain 2013, 6:60 Page 8 of 15
peptides are unknown. The ability to monitor and detect
changes in these peptides in response to various D. mela-
nogaster experimental paradigms will hopefully provide
insight into their potential significance.
Curiously, m/z 925.481, determined by MALDI-TOF/
TOF MS/MS to be PDNFMRFamide (monoisotopic
[M + H]
= 925.435) was of a slightly higher mass error
(50 ppm) compared with other identified peaks (aver-
age mass error = 4 ppm). Subsequent analysis with
MALDI-Fourier transform ion cyclotron resonance
(FTICR) MS, which has substantially higher resolving
power compared with MALDI-TOF MS, confirmed this
peak was actually a convolution of PDNFMRFamide and a
peak tentatively assigned as Drostatin-3 (Ast-A3, mono-
isotopic [M + H]
= 925.489, Figure 6), hence the com-
paratively larger m/z error. Including Drostatin-3, 30
additional molecular ions observed in at least some
MALDI-TOF profiling spectra have been tentatively
assigned by mass matching to be neuropeptides (Table 2).
Of these 30 molecular ions, 19 were abundant enough to
be detected (using our stringent deisotoping criteria) in
both experiments presented here. This implies that per-
haps at least 63% of the molecular ions detected in our
MALDI-TOF MS profiling experiments are neuropeptides
[(14 neuropeptides detected in both experiments identi-
fied with MS/MS + 19 additional peaks detected in both
experiments tentatively assigned to neuropeptides)/52 iso-
topically resolved ion signals detected in both experi-
ments], suggesting this method is highly specific for this
type of biomolecule.
We acknowledge the rigor of isotopic labeling-based ap-
proaches to quantitative mass spectrometry and are
Figure 5 NPLP1 sequence with peptides identified in this study
and/or previously. In blue are three peptides (MTYamide, IPNamide
and VQQ), which were identified both previously and in this study
with MALDI-TOF/TOF MS/MS. In purple are the regions containing
three novel molecules we detected and identified. One peptide we
identified corresponded to the predicted NPLP1-2, which we detected
with an intact C-terminal lysine (DPK peptide), marked Kin red. Also
identified were two distinct peptides corresponding to the predicted
NPLP1-3, with (GAE) and without (QRAamide) a C-terminal GAE
sequence marked in red. The NPLP1-3 variant without the GAE
fragment was observed to be amidated (QRAamide). We also detected
and tentatively assigned, but not identified by fragmentation, an ion
mass corresponding to the peptide outlined in orange, which has
been reported with (as APK peptide) and without (as NAP peptide) a
C-terminal K (marked in red). Our tentative assignment corresponded
to the peptide with C-terminal K intact. Dibasic residue cleavage sites
are shown underlined and bolded. Additional peptides that have been
predicted but not identified are not explicitly highlighted.
Figure 6 High resolution MALDI-FTICR MS resolves neuropeptides
PDNFMRFamide and Drostatin-3 (Ast-A3), convoluted in MALDI-TOF
mass spectra. Through the use of MALDI-FTICR MS, we were able
to resolve m/z 925.481 from the MALDI-TOF MS (top) as being the
convolution of two neuropeptides. PDNFMRFamide, identified by
MALDI-TOF/TOF MS/MS fragmentation, was observed in MALDI-FTICR MS
(bottom) as 925.43564 (theoretical monoisotopic [M + H]
= 925.43594).
A second peak at m/z 925.49004 was tentatively assigned to correspond
to Drostatin-3 (Ast-A3, calculated [M + H]
= 925.48994).
Salisbury et al. Molecular Brain 2013, 6:60 Page 9 of 15
Table 2 Peaks observed in MALDI-TOF MS profile spectra tentatively assigned to known neuropeptides by mass
Obs. m/z
(Calc. m/z)
(UniProtKB Entry name)
Peptide name Peptide sequence Previous ref.
(FMRFamide 9)
R.SDNFMRFa.G [1,2,7,9,30]
ALLS_DROME Drostatin-3 (Ast-A3) R.SRPYSFGLa.G [1,2,7,9,18]
ALLS_DROME Drostatin-1 (Ast-A1) R.VERYAFGLa.G [9,18]
R.KPMRLRWa.G [18,19]
SNPF_DROME RLRF peptide 2 R.SPSLRLRFa.G [1,2,9,18,19,30]
CP2B_DROME CAP-2 (CAPA-2) K.ASGLVAFPRVa.G [1,2,7,9,30]
FMRF_DROME TPAEDFMRFamide (FMRFamide 7) R.TPAEDFMRFa.G [1,2,7,9,19,30]
CORZ_DROME Corazonin
T.FQYSRGWTNa.G [1,2,30]
AKH_DROME AKH Peptide (+ C-term GK) C.pQLTFSPDWGK.R [9,19,30]
DSK_DROME Drosulfakinin-1 (DSK-1) R.FDDYGHMRFa.G [9,19]
MIP_DROME Drostatin-B5 (Ast-B4) R.DQWQKLHGGWa.G [1,2,7,18,19]
ALLS_DROME Drostatin-4 (Ast-A4) R.TTRPQPFNFGLa.G [1,2,7,9,18,19]
SNPF_DROME RLRF peptide 1 K.AQRSPSLRLRFa.G [9,18,30]
CORZ_DROME Corazonin (Crz Peptide) G.pQTFQYSRGWTNa.G [1,2,7,9,19,30]
NPLP1_DROME NAP peptide (+ C-term K)
T.GPSASSGLWFGPRLa.G [1,2,9,19,30]
MIP_DROME Drostatin-B3 (Ast-B3) R.RQAQGWNKFRGAWa.G [9,18,19]
Salisbury et al. Molecular Brain 2013, 6:60 Page 10 of 15
aware of confounds inherent to MALDI MS-based
quantification (i.e. differences in ionization efficiency
of analytes, ion suppression effects, etc.). These not-
withstanding, there are numerous examples of label-free
MALDI-TOF MS-based methods providing informative
semi-quantitative results [34-36]. Indeed, MALDI-TOF
MS neuropeptide peak detection alone has been sufficient
to distinguish particular cell types and tissues in Drosoph-
ila [6,19]. Given the benefits of MALDI-TOF MS in terms
of relative instrument expense and maintenance, as well
as the ease of sample preparation and data acquisition,
MALDI-TOF MS, even in instances when isotopic label-
ing is prohibitive, can serve as a valuable discovery tool,
particularly when discovery of relatively more pronounced
differences is an acceptable achievement (as opposed to
absolute quantification). Here we present a rapid, label-
free MALDI-TOF MS-based method and data analysis
workflow that permits detection of differences in specific
neuropeptides amongst a panel being monitored, using
individual D. melanogaster brains as sample points.
The described MATLAB-based preprocessing work-
flow and statistical analysis is compatible with other
MALDI-TOF MS sample preparation techniques, in-
cluding those previously described by other groups
that have obtained spectra of excellent quality using
other D. melanogaster tissues, including more specific
D. melanogaster brain regions such as the antennal
lobe [18] and individual cells [6]. The relatively straight-
forward sample preparation method described here was
sufficient to enable both detection of distinct levels of
neuropeptide expression, as well as identify previously un-
confirmed neuropeptides. Similar to other discovery-based
methodologies, we strongly recommend differences in ion
intensities detected with the described technique be vali-
dated by an independent method (such as more quantita-
tive MS and/or immuno-based methods). However, we
believe this validation effort is worth the additional time
given the relative ease of the initial discovery procedure.
Fly stocks
D. melanogaster were reared on standard medium and
raised under 12:12-hour lightdark conditions at 25°C.
Flies were dissected between one to three hours after
lights-on (two hour window centered at Zeitgeber time
2) when PDF expression levels are high [37]. The pan-
neuronal elav-GAL4 driver line was Bloomington stock
#8760 (Bloomington Drosophila Stock Center at Indiana
University, Bloomington, IN, USA).
Generation of UAS-Drm-pdf transgenic flies
Full-length D. melanogaster pdf-cDNA (Drm-pdf-cDNA)
was kindly provided by Jeffrey C. Hall [38] and initially
cloned into the pBluescript II SK (+/) vector. To gener-
ate the UAS-Drm-pdf construct, the Drm-pdf-cDNA was
then subcloned into the appropriate sites of the polylin-
ker of the pUAST vector [26]. The pUAST vector con-
tains a P-element for which the transposase gene has
been replaced by the sequences of the GAL4-specific
UAS, the hsp70 TATA-box, the mini-white gene and the
SV40 polyadenylation signal. The construct has been
confirmed by direct sequencing using vector specific
primers. Transgenic flies were generated by germline
transformation following standard protocols. Briefly, the
pUAST-Drm-pdf-cDNA construct and the transposase
gene-containing helper plastmid pUChsΠΔ2-3 [39] were
co-injected into Drosophila w
embryos using stand-
ard injection protocols. Two homozygous transgenic fly
lines with different chromosomal localization of the con-
struct (line no. 77: III chromosome) were obtained.
D. melanogaster brain dissection and on-target extraction
Flies were dissected in a modified insect dissection saline
(NaCl 7.5 g/L, KCl 0.2 g/L, CaCl
0.2 g/L, NaHCO
0.1 g/L; pH 7.2) [6] and a single dissected fly brain was
transferred with non-locking forceps (Dumont Tweezers
#5, 11 cm, 0.025 × 0.005 mm tip, World Precision
Table 2 Peaks observed in MALDI-TOF MS profile spectra tentatively assigned to known neuropeptides by mass
matching (Continued)
DSK_DROME Drosulfakinin-2 (DSK-2) R.GGDDQFDDYGHMRFa.G [9]
LCK_DROME Leucokinin (DLK) R.NSVVLGKKQRFHSWGa.G [1,2,7,9,19,30]
Ion masses observed to be isotopically resolved in both replicate experiments are underlined and bolded. As in Table 1, these reported observed m/zs are the
average of the m/zs observed between the two replicate MALDI-TOF MS profiling experiments described. Truncated peptides are denoted by superscripts
showing amino acids present from the annotated peptide sequence as described in Table 1. Peptide sequences include pre- and post- cleavage residues separated
from sequences by a period. *All observed m/zs listed are predicted to be monoisotopic [M + H]
s of listed neuropeptides based on the calculated monoisotopic
[M + H]
(shown in parentheses below observed m/z) with the exceptions of m/z of m/z 996.572 and 1452.736 are [M + Na]
sandm/z 2009.982 is an [M + K]
C-terminal amidation is denoted by a, N-terminal pyroglutamation is denoted by p. Abbreviations: Ast allatostatin, AKH adipokinetic hormone,
CAP - Cardioacceleratory peptide, NPLP1 - Neuropeptide-like precursor 1, PDF - Pigment-dispersing factor, sNPF-Small neuropeptide F, TK - Tachykinin-related peptide.
Salisbury et al. Molecular Brain 2013, 6:60 Page 11 of 15
Instruments) to a stainless steel MALDI target. Excess
dissecting saline was removed during the transfer of the
brain. While the brain was still on the forceps, the for-
ceps were touched about 2 mm from the fly brain in
the void space between the two arms of the forceps,
using a KimWipepaper (Kimberly-Clark Worldwide,
Inc.), which wicked away excess liquid. An on-target
wash of 1.0 μL of 100 mM ammonium bicarbonate was
performed using a pipettor to add and aspirate the solu-
tion. 0.5 μL of 10 mg/mL CHCA in 50% (v/v) acetonitrile,
0.1% (v/v) formic acid was then directly pipetted onto the
brain and allowed to dry before MALDI-MS analysis.
MALDI-TOF MS analysis of single dissected fly brains
Mass spectra were acquired on a microflex MALDI-TOF
mass spectrometer (Bruker Daltonics Inc., Billerica, MA)
equipped with a 337 nm N
laser. Positive ion mass
spectrawereacquiredfrom500m/z 4000 m/z in
reflectron mode. The acceleration voltage was set at
20 kV and the pulsed-ion extraction was set at 200 ns.
One thousand laser shots were acquired for each spectrum.
External mass calibration was achieved using a standard
peptide mixture of Angiotensin I and II, Substance P, Renin
Substrate, and ACTH (Bruker Daltonics Inc.). The exter-
nally calibrated mass accuracy of the instrument was ap-
proximately 100 parts-per-million (ppm) at m/z 1500.
MALDI-TOF/TOF MS/MS analysis for identification of
detected peptides from single brain on-target extraction
sample preparation
Fragmentation spectra were acquired in LIFT mode on
an autoflex III and an ultraflex III MALDI-TOF/TOF
mass spectrometer (Bruker Daltonics Inc., Billerica, MA).
MS spectra were acquired in positive ion and reflectron
modes. For MS/MS analysis, the source acceleration volt-
age was set to 8.0 kV and the reflectron voltage was set to
29.5 kV. Mass spectra were acquired with approximately
3000 laser shots summed in 200 to 400 shot increments.
External mass calibration was achieved using a standard
peptide mixture of Angiotensin I and II, Substance P,
Renin Substrate, and ACTH (Bruker Daltonics Inc.). The
external calibration mass accuracy of the instrument was
approximately 20 ppm in MS mode and <400 ppm in
LIFT (MS/MS) mode. MS/MS spectra were not internally
calibrated. All spectra were processed with FlexAnalysis
software (Bruker Daltonics Inc.).
Individual fly brain MALDI-TOF MS profiling data processing
and statistical analysis
For preprocessing and statistical comparison of the rela-
tive abundance of PDF from MALDI-TOF profile spec-
tra, all spectra obtained were first realigned by internal
calibration using a mass list of neuropeptides we identi-
fied with MALDI-TOF/TOF MS/MS that were typically
observed in our profile spectra. Internally calibrated
spectra were exported to a plain text, two-column (m/z
sampling points and corresponding intensities) ASCII
format so they could be loaded into MATLAB 2013a
(Mathworks, Natick, MA, USA). The msresample func-
tion in the MATLAB Bioinformatics Toolbox was used
to resample internally calibrated spectra to a uniformly-
spaced common set of m/z axis values.
Spectra from the two repeat experiments were analyzed
separately. Spectra were denoised [40] in MATLAB using
the undecimated discrete wavelet transform (UDWT)
found in the Rice Wavelet Toolbox (http://www.dsp.ece. with a Daubechiesscaling fil-
ter of length 8, soft thresholding applied, and the thresh-
olding of low pass components enabled. Spectra were
then baseline subtracted using the msbackadj function in
the MATLAB Bioinformatics Toolbox with the default
settings for this function. A total average spectrum of the
denoised/baseline-subtracted spectra across all analyzed
samples (including across conditions) within an experi-
mental repeat was calculated. The total average spectrum
was then normalized to its greatest value (i.e. the base
peak). The mspeaks function from the MATLAB Bioinfor-
matics Toolbox was then used to identify peaks from the
total average spectrum, with the HeightFilter option of the
mspeaks function set to 0.01, so that only local maxima
of the total average spectrum with intensity greater than
1% of the total average spectrums base peak are identified
as peaks. When applying the mspeaks function, the left
and right m/z locations of the full width at half height
(FWHH) limits for each identified peak in the total aver-
age spectrum was specified to be returned. These values
were used to establish peak bins.
Individual denoised and baseline-subtracted spectra
were additionally normalized by dividing each point in
the spectrum by the sum of all intensities in the
spectrum after denoising and baseline subtraction (i.e. a
total ion current normalization, although we avoid the
term here to specify total area under the spectrum is taken
after denoising and baseline-subtraction). Peak bins from
the total average spectrum were used to query across each
spectrum being analyzed, with the maximum value in
each peak bin returned for each spectrum. This reduced
the set of all spectra being processed into a single n× m
matrix, the entries of one dimension representing the n
peaks found by mspeaks and the entries of the second di-
mension corresponding to the m spectra being analyzed.
Intensity values taken from certain peak bins were fur-
ther added together by combining peak bins that corre-
sponded to isotope distributions of the same singly
charged ion. Criteria for combining peak bins corre-
sponding to the same isotope distribution required that
at least three peaks be detected with centroided m/zs
differing by 1 ± 0.03, with the peak corresponding to the
Salisbury et al. Molecular Brain 2013, 6:60 Page 12 of 15
monoisotopic peak in a distribution being the most
abundant ion mass in the total average spectrum for dis-
tributions less than 1700 m/z and the second peak in a
distribution always having to be more abundant than the
third and fourth peak in the total average spectrum.
Series of peaks meeting this criteria were assigned as
isotopically resolved.
Non-parametric statistical analysis (Kruskal-Wallis one-
way ANOVA) was performed in MATLAB, comparing
the sum of the maximum intensities of isotopically re-
solved distributions in each spectrum across the three
fly strains being analyzed. The p-value obtained from
Kruskal-Wallis one-way ANOVA for each isotopically
resolved distribution was adjusted using a simple
Bonferroni correction based on the total number of
isotope distributions being statistically compared so
that a significance level of α=0.01 could be used des-
pite multiple comparisons. Tukeys least significant dif-
ference procedure (α=0.05)wasusedasapost-hoc
analysis to evaluate differences between conditions of
isotopically resolved peaks found to be significantly
different in the ANOVA analysis.
MALDI-TOF MS/MS data processing for neuropeptide
MALDI-TOF/TOF MS/MS fragmentation spectra were
exported to the FlexAnalysis software for batch prepro-
cessing consisting of top-hat baseline subtraction;
smoothing with four, width 0.15 m/z, Savitzky-Golay cy-
cles; and peak picking using the SNAP algorithm with
averagine molecular composition. All MS/MS spectra were
combined and exported from FlexAnalysis as a single Mas-
cot (Matrix Science Inc., London, England) generic file
(*.mgf). The mgf file was submitted to an in-house
Mascot server (version 2.2.07) for putative peptide identi-
fication using a 0.15 Da cutoff for precursor and a 0.5 Da
cutoff for MS/MS peaks. Spectra were searched against
the SwissProt 56.0 database with taxonomy specified as
Drosophila (including 5357 protein sequences). Parame-
ters for the Mascot search included enzyme specified as
none, and variable modifications (C-terminal amidation,
N-terminal pyroglutamic acid modification, methionine
oxidation, and tyrosine sulfation) were considered. FlexA-
nalysis preprocessed MS/MS data were also moved to the
BioTools software program (Bruker Daltonics Inc.) for
manual confirmation of Mascots peptide assignments. A
putative ID was considered confirmed when at least 3
consecutive b- or y-ions were observed, and in addition,
the majority of MS/MS peaks were assigned. Although
Mascot is tuned for protein-, not peptide-level identifica-
tion (its significance scores at the peptide level are conser-
vative), further confirmation came from the Mascot
scoring algorithm in the form of a peptide score, peptide
rank, and expectation value. For example, 13 of the 14
manually confirmed peptide identifications were also the
highest ranking peptide from the Mascot search, and
six of the 14 manually assigned peptides had Mascot
Scores in the statistically significant range for protein
MALDI-Fourier transform ion cyclotron resonance
(FTICR)-MS was performed on an Apex Qe ultra 7
Tesla MALDI-FT-ICR mass spectrometer (Bruker
Daltonics Inc., Billerica, MA). Mass spectra were col-
lected in positive ion mode. The external mass accur-
acy of the instrument was approximately 20 ppm.
After internal calibration, mass accuracy ranged from
02 ppm with a mean value of 0.5 ppm. Mass calibra-
tion was achieved using a standard peptide mixture of
Angiotensin I and II, Substance P, Renin Substrate, and
ACTH (Bruker Daltonics Inc.). Spectra were processed
with DataAnalysis software (Bruker Daltonics Inc.).
Additional file
Additional file 1: Figure S1. On-target extraction provides spectra
with greater signal-to-noise and more peaks from the region surrounding
the tissue, as opposed to acquiring spectra directly from the tissue.
A) Acquiring spectra from directly over the deposited D. melanogaster
brain (shown at the center of the crosshair encircled in red) did not
provide quality spectra reliably. Rather, the region outside the red circle,
which made up the visible matrix spot encircled approximately in orange,
was where the best signal was obtained. B) Shows the same regions
encircled with the crosshairs positioned over an area representative of a
region that provides high and varied ion signal in the peptide
mass range.
Additional file 2: Table S1. This file contains supporting material,
including the following tables. A complete list of isotopically resolved ion
masses detected in either experiment (with neuropeptide assignments
when possible), intensity means with standard deviations calculated
within each group for each of these ion masses, and the adjusted p-values
from Kruskal-Wallis ANOVA. Table S2. Correlation between experiments of
fourteen neuropeptides confirmed by MS/MS fragmentation. Table S3.
Correl ation between experiments of all isotopically resolved ion signals
observed in both experiments. Table S4. Correlation between [M + H]
and [ M + K]
of neuropeptide PDF within experimental conditions for both
repeat experiments. Format: XLSX (Excel Spreadsheet); Size: 45 KB.
MS: Mass spectrometry; MS/MS: Tandem mass spectrometry;
MALDI: Matrix-assisted laser desorption/ionization; TOF: Time-of-flight;
ppm: Part-per-million; FTICR: Fourier transform ion cyclotron resonance;
PDF: Neuropeptide pigment-dispersing factor; NPLP1: Neuropeptide-like
precursor 1; α-CHCA: α-cyano-4-hydroxycinnamic acid.
Competing interests
The authors declare that they have no competing interests.
JNA and MR designed the experiment; KJB and YAH performed the
experiments, with further contributions by JQ and AS; GG contributed the
UAS-Drm-pdf line. PJK and MLE assisted with instrumentation. JNA, KJB, and
JPS analyzed the data, prepared the figures, and wrote the manuscript. All
authors have read and given approval to the final version of the manuscript.
Salisbury et al. Molecular Brain 2013, 6:60 Page 13 of 15
This work was supported by the Department of Defense (contract
W81XWH-04-0158) and Howard Hughes Medical Institute to M.R.; Amyotrophic
Lateral Sclerosis Association (grant 1856) to J.N.A.; and Y.A.H. was supported in
part by the National Institutes of Health (T32NS7292). We would like to thank
Sergei Dikler and Jane-Marie K owasl ki from Bruker Daltonics, Inc. for their
support and insight. We would like to thank Yuhua Shang for initial help
with experiments and dissection.
Author details
Department of Biology, Brandeis University, Waltham, MA 02453, USA.
Department of Chemistry and Volen Center for Complex Systems, Brandeis
University, Waltham, MA 02453, USA.
Howard Hughes Medical Institute,
National Center for Behavioral Genomics, and Department of Biology,
Brandeis University, Waltham, MA 02451, USA.
Depts of Chemistry and
Chemical Biology and Pharmaceutical Sciences and Barnett Institute of
Chemical and Biological Analysis, Northeastern University, 140 The Fenway,
Boston, MA 02115, USA.
Institute of Zoology, Department of Developmental
Biology, University of Regensburg, Regensburg 93040, Germany.
Daltonics Inc., Billerica, MA 01821, USA.
Current Address: Department of
Neurology, University of Massachusetts Medical School, Worcester, MA
01655, USA.
Current Address: Center for Integrative Brain Research, Seattle
Childrens Research Institute, Seattle, WA 98105, USA.
Received: 16 October 2013 Accepted: 20 December 2013
Published: 27 December 2013
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Cite this article as: Salisbury et al.:A rapid MALDI-TOF mass
spectrometry workflow for Drosophila melanogaster differential
neuropeptidomics. Molecular Brain 2013 6:60.
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Salisbury et al. Molecular Brain 2013, 6:60 Page 15 of 15
... MS-based approaches have been previously applied for the detection and identification of neuropeptides from homogenized cells in different developmental lifespans of D. melanogaster [27,[29][30][31][32]. A combination of ToF-SIMS (time-of-flight secondary ion MS) and SEM (scanning electron microscopy) imaging studies on fruit fly brains have recently described the distribution of various intact lipids, including the stimulant drug methylphenidate [33,34]. Using SIMS it was possible to image with a pixel size of 3 μm, but the mass resolution was not sufficient to identify compounds. ...
... All neuropeptides were assigned based on accurate mass and on identifications described in other studies of D. melanogaster. [33]. Nine of those were allatostatins and tachykinin-like peptides. ...
The pomace fly or fruit fly Drosophila melanogaster is known as a cost-effective model organism widely used to study neurological diseases and metabolite-related diseases. Among these metabolites, lipids play important roles in energy homeostasis, metabolism, membrane structure, and signaling. Although the Drosophila lipidome has been described in previous studies, there is only a little information on the localization and distribution of the various lipid classes and species in the fly. In this work, high-resolution atmospheric pressure scanning microprobe matrix-assisted laser desorption/ionization (AP-SMALDI) mass spectrometry imaging was performed in order to determine the spatially resolved distribution of metabolites of D. melanogaster, with a focus on the tissue-specific characteristic regional distributions of identified compounds from 20 μm thick cryosections of the fly. We identified and characterized the anatomical distribution of a total of 97 lipids, 62 of them identified as glycerophospholipids and sphingolipids and 35 of them as glycerolipids, in three biological replicates of the fly with a consistent anatomical distribution using 2,5-dihydroxybenzoic acid (DHB) as a matrix for soft ionization in positive-ion mode with a pixel size of 5–10 μm. Furthermore, we used para-nitroaniline as a matrix for both the positive- and negative-ion mode, enabling the identification of 89 deprotonated lipids in negative-ion mode. Among them, 48 have been identified in both positive- (protonated) and negative-ion (deprotonated) mode within the mass accuracy of ±3 ppm. All ion images were separated according to their localization principally into head, posterior region and whole body of the fly. The spatial identity especially of Drosophila brain metabolites, including lipids, small metabolites and neuropeptides, will provide the possibility of studying neurodegenerative diseases. Therefore, we additionally mapped the distribution of neuropeptides in coronal Drosophila brain sections. Furthermore, several lipophilic male- and female-specific sex pheromones were identified, differentiated, and characterized according to their typical distribution pattern in mated and virgin flies. We report on an efficient method for the preparation of improved tissue sections after ethanol dehydration and 5% carboxymethylcellulose and gelatin embedding, capable of maintaining the tissue integrity of the whole fly, which was a challenge due to the hard cuticle and heterogeneous tissue types of this insect. Moreover, our instrumentation with a high spatial resolution, mass resolution and mass accuracy combined with on-tissue MS/MS imaging overcomes common limitations typically observed with low resolution mass spectrometric imaging, such as insufficient spatial resolution which cannot deliver precise and detailed information from the internal organ-specific tissues, and uncertainties of generated signals based on low mass accuracy and resolution. By using DHB, our approach allowed the identification of protonated, sodiated and potassiated lipid species within a mass accuracy of ±1 ppm and lipophilic pheromones within ±3 ppm with a spatial resolution set up within 5–15 μm at a high detection sensitivity of the instrumentation.
... Neuroendocrine tissue and select types of neuronal populations often contain high local concentrations of neuropeptides and thus are suitable for direct analysis either by matrixassisted laser desorption/ionization (MALDI) MS profiling [33] or MALDI MS imaging (MSI) with minimal sample manipulation [34][35][36][37][38]. Mass spectrometers with standard or interchangeable MALDI ion sources usually have MS/MS capabilities, which allow automatic or manual sequencing of peptides in solid tissue samples [39,40]. MALDI MSI has an added benefit of being capable of mapping peptides to specific loci within the tissue section [34,38]. ...
... Recently, differential comparisons have been used to probe unknown mechanisms in the physiological response to environmental [51], developmental [60] or pharmacological perturbation [31,61,62], disease states [36,[63][64][65], phenotypes [39,66], or even various sample preparation methods crucial for successful neuropeptide detection [67,68]. It is safe to say that relative or differential MS quantitation has already become routine due to the availability of commercial reagents, sensitive analytical instrumentation, and software. ...
The discovery of neuropeptides as signaling molecules with paracrine or hormonal regulatory functions has led to trailblazing advances in physiology and fostered the characterization of numerous neuropeptide-binding G protein-coupled receptors (GPCRs) as potential drug targets. The impact on human health has been tremendous: approximately 30% of commercial drugs act via the GPCR pathway. However, about 25% of the GPCRs encoded by the mammalian genome still lack their pharmacological identity. Searching for the orphan GPCR endogenous ligands that are likely to be neuropeptides has proved to be a formidable task. Here we describe the mass spectrometry (MS)-based technologies and experimental strategies that have been successful in achieving high-throughput characterization of endogenous peptides in nervous and endocrine systems. Copyright © 2015 Elsevier Ltd. All rights reserved.
... The NPLP1 precursor of D. melanogaster contains a number of neuropeptide sequences with potential amidation motifs but the sequences show little sequence similarity among themselves (Figure 5d-III). Mass spectra of type #9 cells (Figure 5d-II) confirmed the presence of all NPLP1 peptides identified before in comprehensive peptidomic analyses of the Drosophila CNS [14,30,45,46]. In addition, an ion signal mass-identical to a further peptide (YPPFHTWGTPPRITALH-OH) was observed. ...
Neuropeptides are structurally highly diverse messenger molecules that act as regulators of many physiological processes such as development, metabolism, reproduction or behavior in general. Differentiation of neuropeptidergic cells often corresponds with the presence of the transcription factor DIMMED. In the central nervous system of the fruit fly Drosophila melanogaster, DIMMED commonly occurs in neuroendocrine neurons that release peptides as neurohormones but also in interneurons with complex branching patterns. Fly strains with green fluorescence protein (GFP)-expressing dimmed cells make it possible to systematically analyze the processed neuropeptides in these cells. In this study, we mapped individual GFP-expressing neurons of adult D. melanogaster from the dimmed (c929)>GFP line. Using single cell mass spectrometry, we analyzed 10 types of dimmed neurons from the brain/gnathal ganglion. These cells included neuroendocrine cells with projection into the retrocerebral complex but also a number of large interneurons. Resulting mass spectra not only provided comprehensive data regarding mature products from 13 neuropeptide precursors but also evidence for the cellular co-localization of neuropeptides from different neuropeptide genes. The results can be implemented in a neuroanatomical map of the D. melanogaster brain.
... Furthermore, discriminating between peptides and "noise" (e.g. random fragments) is extremely challenging, with even the best high-throughput protein expression methods such as tandem MS (MS/MS (Angel et al., 2012)) requiring special tweaking and is limited to the detection of known, highly expressed proteins (Akhtar et al., 2012;Salisbury et al., 2013;Vogel and Marcotte, 2008;Kim et al., 2011;Craft et al., 2013). Often, if a short protein is not already a known candidate, it will not be found (Lubec and Afjehi-Sadat, 2007). ...
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Systematic identification of protein function is a key problem in current biology. Most traditional methods fail to identify functionally equivalent proteins if they lack similar sequences, structural data or extensive manual annotations. In this thesis, I focused on feature engineering and machine learning methods for identifying diverse classes of proteins that share functional relatedness but little sequence or structural similarity, notably, Neuropeptide Precursors (NPPs). I aim to identify functional protein classes solely using unannotated protein primary sequences from any organism. This thesis focuses on feature representations of whole protein sequences, sequence derived engineered features, their extraction, frameworks for their usage by machine learning (ML) models, and the application of ML models to biological tasks, focusing on high level protein functions. I implemented the ideas of feature engineering to develop a platform (called NeuroPID) that extracts meaningful features for classification of overlooked NPPs. The platform allows mass discovery of new NPs and NPPs. It was expanded as a webserver. I expanded our approach towards other challenging protein classes. This is implemented as a novel bioinformatics toolkit called ProFET (Protein Feature Engineering Toolkit). ProFET extracts hundreds of biophysical and sequence derived attributes, allowing the application of machine learning methods to proteins. ProFET was applied on many protein benchmark datasets with state of the art performance. The success of ProFET applies to a wide range of high-level functions such as metagenomic analysis, subcellular localization, structure and unique functional properties (e.g. thermophiles, nucleic acid binding). These methods and frameworks represent a valuable resource for using ML and data science methods on proteins.
... The observation of common signals, or the search for distinguishing signals, in other words the search of biomarker signals, has been based on the comparison of mass spectra, and it has been used to classify patients' samples [1,[3][4][5], to distinguish microorganisms and animal species [6][7][8][9], to detect specific neuropeptides [10]. As these studies demonstrate, the collection of large number of spectra, and their analysis by averaging of replicates and the comparison of the average spectra, is a common practice that represents a field of development for bioinformatics tools. ...
Full-text available
Mass spectrometry (MS) is producing high volumes of data supporting oncological sciences, especially for translational research. Most of related elaborations can be carried out by combining existing tools at different levels, but little is currently available for the automation of the fundamental steps. For the analysis of MALDI/TOF spectra, a number of pre-processing steps are required, including joining of isotopic abundances for a given molecular species, normalization of signals against an internal standard, background noise removal, averaging multiple spectra from the same sample, and aligning spectra from different samples. In this paper, we present Geena 2, a public software tool for the automated execution of these pre-processing steps for MALDI/TOF spectra. Geena 2 has been developed in a Linux-Apache-MySQL-PHP web development environment, with scripts in PHP and Perl. Input and output are managed as simple formats that can be consumed by any database system and spreadsheet software. Input data may also be stored in a MySQL database. Processing methods are based on original heuristic algorithms which are introduced in the paper. Three simple and intuitive web interfaces are available: the Standard Search Interface, which allows a complete control over all parameters, the Bright Search Interface, which leaves to the user the possibility to tune parameters for alignment of spectra, and the Quick Search Interface, which limits the number of parameters to a minimum by using default values for the majority of parameters. Geena 2 has been utilized, in conjunction with a statistical analysis tool, in three published experimental works: a proteomic study on the effects of long-term cryopreservation on the low molecular weight fraction of serum proteome, and two retrospective serum proteomic studies, one on the risk of developing breat cancer in patients affected by gross cystic disease of the breast (GCDB) and the other for the identification of a predictor of breast cancer mortality following breast cancer surgery, whose results were validated by ELISA, a completely alternative method. Geena 2 is a public tool for the automated pre-processing of MS data originated by MALDI/TOF instruments, with a simple and intuitive web interface. It is now under active development for the inclusion of further filtering options and for the adoption of standard formats for MS spectra.
... Based on the present research, it is hypothesised that LK and DH 44 interact, and that furthermore, they act in a feedback loop to regulate the release of each other. In order to explore the validity of this model, a peptidomics approach could be used to evaluate changes in LK and DH 44 levels in circulation following conditional RNAi knockdown of each peptide (Brockmann et al 2009, Predel et al 2004, Salisbury et al 2013, Schoofs & Baggerman 2003. ...
Full-text available
Insects are highly successful and their large numbers lead to economic loss through crop damage and disease transmission. Insecticides provide a valuable tool for control of insect populations. However, as resistance is increasing to existing products, new modes of action are required for the development of novel products. Understanding of the biological mechanisms underlying stress resistance in insects may provide insight into new potential insecticide targets. Malpighian tubules are critical for epithelial fluid transport and xenobiotic tolerance in insects. The function of Malpighian tubules in desiccation stress tolerance was explored by examining changes in gene expression, protein levels, fluid transport rates, and metabolism following stress exposure. The results indicate a reduction in secretion rate during desiccation that is reflected in accumulation of metabolites that are normally processed and excreted by the tubules. Moreover, the involvement of Drosophila melanogaster diuretic hormones corticotrophin releasing factor-like (DH44) and leucokinin (LK) were examined using genetic manipulations based on the GAL4-UAS system. Highly selective manipulation of the DH44-producing neurons via knockdown of DH44 and neuronal ablation indicates that suppression of DH44 signalling contributes to desiccation tolerance. This result is supported by the finding that knockdown of DH44 receptor 2 in the Malpighian tubule principal cells improves survival during desiccation stress. Previous work suggests the possibility of interaction between LK and DH44 signalling as LK receptor (LKR) is colocalised to the DH44 neurons. This hypothesis is supported by the results of this study as selective knockdown of LKR and DH44 in the DH44 neurons produced opposing effects on desiccation tolerance. Moreover, knockdown of DH44 in the DH44 neurons or ablation of these neurons resulted in significantly decreased LKR expression in the Malpighian tubules. Finally, a novel role for the Malpighian tubules in starvation tolerance was uncovered by the study, with LKR gene expression increasing significantly following starvation. Knockdowns of either DH44-R2 or LKR in the Malpighian tubules significantly impaired starvation tolerance. Here, a mechanism for this role of renal epithelia in starvation tolerance is proposed.
... Myriad software solutions for label-free experiments, most of which are designed for proteomic studies, are currently available on the market (83)(84)(85)(86). Total ion current normalization (87,88) as well as normalization to internal standards [e.g., bovine serum albumin (BSA) peptides] (3, 89) are two widely accepted and simple approaches. Several statistical, mathematical methods have been evaluated on endogenous peptide samples (90,91). ...
Neuropeptides are important mediators in the functionality of the brain and other neurological organs. Because neuropeptides exist in a wide range of concentrations, appropriate characterization methods are needed to provide dynamic, chemical, and spatial information. Mass spectrometry and compatible tools have been a popular choice in analyzing neuropeptides. There have been several advances and challenges, both of which are the focus of this review. Discussions range from sample collection to bioinformatic tools, although avenues such as quantitation and imaging are included. Further development of the presented methods for neuropeptidomic mass spectrometric analysis is inevitable, which will lead to a further understanding of the complex interplay of neuropeptides and other signaling molecules in the nervous system. Expected final online publication date for the Annual Review of Analytical Chemistry Volume 8 is June 15, 2015. Please see for revised estimates.
Due to their involvement in numerous biochemical pathways, neuropeptides have been the focus of many recent research studies. Unfortunately, classic analytical methods, such as western blots and enzyme‐linked immunosorbent assays, are extremely limited in terms of global investigations, leading researchers to search for more advanced techniques capable of probing the entire neuropeptidome of an organism. With recent technological advances, mass spectrometry (MS) has provided methodology to gain global knowledge of a neuropeptidome on a spatial, temporal, and quantitative level. This review will cover key considerations for the analysis of neuropeptides by MS, including sample preparation strategies, instrumental advances for identification, structural characterization, and imaging; insightful functional studies; and newly developed absolute and relative quantitation strategies. While many discoveries have been made with MS, the methodology is still in its infancy. Many of the current challenges and areas that need development will also be highlighted in this review.
Conserved across vertebrates, the habenular nuclei are a pair of small symmetrical structures in the epithalamus. The nuclei functionally link the forebrain and midbrain by receiving input from and projecting to several brain regions. Each habenular nucleus comprises two major asymmetrical subnuclei, the medial and lateral habenula. These subnuclei are associated with different physiological processes and disorders, such as depression, nicotine addiction, and encoding aversive stimuli or omitting expected rewarding stimuli. Elucidating the functions of the habenular nuclei at the molecular level requires knowledge of their neuropeptide complement. In this work, three mass spectrometry (MS) techniques – liquid chromatography (LC) coupled to Orbitrap tandem MS (MS/MS), LC coupled to Fourier transform (FT)-ion cyclotron resonance (ICR) MS/MS, and matrix-assisted laser desorption/ionization (MALDI) FT-ICR MS – were used to uncover the neuropeptide profiles of the medial and lateral rodent habenula. With the assistance of tissue stabilization and bioinformatics, a total of 262 and 177 neuropeptides produced from 27 and 20 prohormones were detected and identified from the medial and lateral habenula regions, respectively. Among these neuropeptides, 136 were exclusively found in the medial habenula, and 51 were exclusively expressed in the lateral habenula. Additionally, novel sites of sulfation, a rare post-translational modification, on the secretogranin I prohormone are identified. The results demonstrate that these two small brain nuclei have a rich and differentiated peptide repertoire, with this information enabling a range of follow-up studies.
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Neuropeptides are essential cell-to-cell signaling molecules that influence diverse regulatory and behavioral functions within biological systems. Differing in their amino acid sequences and post-translational modifications, hundreds of neuropeptides are produced via a series of enzymatic processing steps, and their levels vary with location, time, and physiological condition. Due to their wide range of endogenous concentrations and inherent chemical complexity, using mass spectrometry (MS) to accurately quantify changes in peptide levels can be challenging. Here we evaluate three different MS systems for their ability to accurately measure neuropeptide levels: capillary liquid chromatography-electrospray ionization-ion trap (CapLC-ESI-IT) MS, ultraperformance liquid chromatography-electrospray ionization-quadrupole-time-of-flight (UPLC-LC-ESI-Q-TOF) MS, and matrix-assisted laser desorption/ionization-time-of-flight (MALDI-TOF) MS. Specifically, eight sample mixtures composed of five neuropeptide standards, with four technical replicates of each, were labeled with H(4)/D(4)-succinic anhydride, followed by relative peptide quantitation using the three MS platforms. For these samples, the CapLC-ESI-IT MS platform offered the most robust ability to accurately quantify peptides over a concentration range of 1200-fold, although it required larger sample sizes than the other two platforms. Both the UPLC-ESI-Q-TOF MS and the MALDI-TOF MS systems had lower limits of quantification, with the MALDI-TOF having the lowest. By implementing several data acquisition schemes and optimizing the data analysis approaches, we were able to accurately quantify peptides over a three orders of magnitude concentration range using either the UPLC or MALDI-TOF platforms. Overall these results increase our understanding of both the capabilities and limits of using MS-based approaches to measure peptides.
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The development of powerful analytical techniques for specific molecular characterization of neural cell types is of central relevance in neuroscience research for elucidating cellular functions in the central nervous system (CNS). This study examines the use of differential protein expression profiling of mammalian neural cells using direct analysis by means of matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS). MALDI-MS analysis is rapid, sensitive, robust, and specific for large biomolecules in complex matrices. Here, we describe a newly developed and straightforward methodology for direct characterization of rodent CNS glial cells using MALDI-MS-based intact cell mass spectrometry (ICMS). This molecular phenotyping approach enables monitoring of cell growth stages, (stem) cell differentiation, as well as probing cellular responses towards different stimulations. Glial cells were separated into pure astroglial, microglial, and oligodendroglial cell cultures. The intact cell suspensions were then analyzed directly by MALDI-TOF-MS, resulting in characteristic mass spectra profiles that discriminated glial cell types using principal component analysis. Complementary proteomic experiments revealed the identity of these signature proteins that were predominantly expressed in the different glial cell types, including histone H4 for oligodendrocytes and S100-A10 for astrocytes. MALDI imaging MS was performed, and signature masses were employed as molecular tracers for prediction of oligodendroglial and astroglial localization in brain tissue. The different cell type specific protein distributions in tissue were validated using immunohistochemistry. ICMS of intact neuroglia is a simple and straightforward approach for characterization and discrimination of different cell types with molecular specificity.
Neuropeptides are widespread signal molecules that display a great chemical and functional diversity. Predictions of neuropeptide cleavage from precursor proteins are not always correct, and thus, biochemical identification is essential. Single-cell analysis is valuable to identify peptides processed from a single precursor, but also to determine coexpression of further neuropeptides from other precursors. We have developed an approach to isolate single identified neurons from the fruit fly Drosophila melanogaster for mass spectrometric analysis. By using Gal4 promoter lines to drive green fluorescent protein under UAS control, we identified specific peptidergic neurons. These neurons were isolated singly under a fluorescence microscope and subjected to MALDI-TOF mass spectrometry. Two Gal4 lines were used here to identify pigment-dispersing factor (PDF) and hugin-expressing neurons. We found that the large PDF expressing clock neurons only give rise to a single peptide, PDF. The three different classes of hugin expressing neurons all display the same mass signal, identical to pyrokinin-2. The other peptide predicted from the hugin precursor, hugin gamma, was not detected in any of the cells. Single-cell peptidomics is a powerful tool in Drosophila neuroscience since Gal4 drivers can be produced for all known neuropeptide genes and thus provide detailed information about neuropeptide complements in neurons of interest.
Neuropeptides are intercellular signal transmitters that play key roles in modulation of many behavioral and physiological processes. Neuropeptide signaling in several nuclei in the hypothalamus contributes to the control of food intake. Additionally, food intake regulation involves neuropeptide signaling in the reward circuitry in the striatum. Here, we analyze neuropeptides extracted from hypothalamus and striatum from rats in four differentially treated dietary groups including a high-fat/high-sucrose diet, mimicking diet-induced obesity. We employ high-resolution tandem mass spectrometry using HCD and ETD fragmentation for sensitive identification of more than 1700 unique endogenous peptides including virtually all key neuropeptides known to be involved in food intake regulation. Label-free quantification of differential neuropeptide expression revealed comparable upregulation of orexigenic and anorexigenic neuropeptides in rats that were fed on a high-fat/high-sucrose diet.
Receptorguanylate cyclases (rGCs) modulate diverse physiological processes including mammalian cardiovascular function and insect eclosion. The Drosophila genome encodes several receptor and receptor-like GCs, but no ligand for any Drosophila rGC has yet been identified. By screening peptide libraries in Drosophila S2 cells, the Drosophila peptide NPLP1-VQQ (NLGALKSSPVHGVQQ) was shown to be a ligand for the rGC, Gyc76C (CG42636, previously CG8742, l(3)76BDl, DrGC-1). In the adult fly, expression of Gyc76C is highest in immune and stress-sensing epithelial tissues, including Malpighian tubules and midgut; and NPLP1-VQQ stimulates fluid transport and increases cGMP content in tubules. cGMP signaling is known to modulate the activity of the IMD innate immune pathway in tubules via activation and nuclear translocation of the NF-kB orthologue, Relish, resulting in increased anti-microbial peptide (AMP) gene expression; and so NPLP1-VQQ might act in immune/stress responses. Indeed, NPLP1-VQQ induces nuclear translocation of Relish in intact tubules and increases expression of the anti-microbial peptide gene, diptericin. Targeted Gyc76C RNAi to tubule principal cells inhibited both NPLP1-VQQ-induced Relish translocation and diptericin expression. Relish translocation and increased AMP gene expression also occurs in tubules in response to dietary salt stress. Gyc76C also modulates organismal survival to salt stress – ablation of Gyc76C expression in only tubule principal cells prevents Relish translocation, reduces diptericin expression, and reduces organismal survival in response to salt stress. Thus, the principal-cell localized NPLP1-VQQ/Gyc76C cGMP pathway acts to signal environmental (salt) stress to the whole organism.
The mechanisms by which circadian pacemaker systems transmit timing information to control behavior are largely unknown. Here, we define two critical features of that mechanism in Drosophila. We first describe animals mutant for the pdf neuropeptide gene, which is expressed by most of the candidate pacemakers (LNv neurons). Next, we describe animals in which pdf neurons were selectively ablated. Both sets of animals produced similar behavioral phenotypes. Both sets entrained to light, but both were largely arrhythmic under constant conditions. A minority of each pdf variant exhibited weak to moderate free-running rhythmicity. These results confirm the assignment of LNv neurons as the principal circadian pacemakers controlling daily locomotion in Drosophila. They also implicate PDF as the principal circadian transmitter.
Repeated exposure to amphetamine (AMPH) induces long-lasting behavioral changes, referred to as sensitization, that are accompanied by various neuroadaptations in the brain. To investigate the chemical changes that occur during behavioral sensitization, we applied a comparative proteomics approach to screen for neuropeptide changes in a rodent model of AMPH-induced sensitization. By measuring peptide profiles with matrix-assisted laser desorption/ionization time-of-flight mass spectrometry and comparing signal intensities using principal component analysis and variance statistics, subsets of peptides are found with significant differences in the dorsal striatum, nucleus accumbens, and medial prefrontal cortex of AMPH-sensitized male Sprague-Dawley rats. These biomarker peptides, identified in follow-up analyses using liquid chromatography and tandem mass spectrometry, suggest that behavioral sensitization to AMPH is associated with complex chemical adaptations that regulate energy/metabolism, neurotransmission, apoptosis, neuroprotection, and neuritogenesis, as well as cytoskeleton integrity and neuronal morphology. Our data contribute to a growing number of reports showing that in addition to the mesolimbic dopamine system, which is the best known signaling pathway involved with reinforcing the effect of psychostimulants, concomitant chemical changes in other pathways and in neuronal organization may play a part in the overall effect of chronic AMPH exposure on behavior.
The larval ring gland and adult corpus allatum (CA) of Drosophila melanogaster produce at least three sesquiterpenoid products: methyl farnesoate (MF), juvenile hormone III (JHIII), and JHIII bisepoxide (JHB(3)). Our understanding of neuropeptide regulation of sesquiterpenoid biosynthesis in D. melanogaster has been hampered by uncertainty over the biosynthetic pathway and the sites of action of regulators. As an approach to defining the neuropeptide regulators, we have used in vivo gene-specific silencing (RNAi). D. melanogaster strains containing an inducible UAS-RNAi construct made to either PheGlyLeu-NH(2)-allatostatin (FGLa/AST) and its cognate receptors Dar-1 and Dar-2 or PISCF-allatostatin (PISCF/AST) or its cognate receptors Drostar-1 or Drostar-2 were expressed in vivo. MF, JHIII and JHB(3) production was measured in ring glands of 3rd instars or corpora allata (CA) of adult females using the radiochemical assay. Reduction in FGLa/AST and Dar-1 or Dar-2 mRNA levels had no effect on MF, JHIII, or JHB(3) production in larvae or adults. Inhibition of Drostar-1 expression resulted in a significant decrease in MF and JHB(3) production in 3rd instars with little effect on JHIII biosynthesis. In contrast, inhibition of Drostar-1 in adult females led to a significant increase in MF and JHIII production. Inhibition of Drostar-2 also reduced MF biosynthesis in 3rd instars. In adults, inhibition of Drostar-2 led to a significant increase in MF and JHIII production but showed no effect on JHB(3). PISCF/AST had no effect on sesquiterpenoid biosynthesis when incubated with 3rd instar ring glands but was stimulatory when incubated with adult glands. Inhibition of short neuropeptide F (sNPF) expression by RNAi or application of sNPF to ring glands had no effect on MF, JHIII, or JHB3 biosynthesis in larvae or adults. Reduction in the neuropeptide Y receptor (NepYr) or neuropeptide F receptor (NPF-R) inhibited JHIII and JHB(3) production in 3rd instars but only reduction in NepYr resulted in JHB(3) reduction in adults.
even-skipped represses wingless and transforms cells that would normally secrete naked cuticle into denticle secreting cells. The GAL4 system can thus be used to study regulatory interactions during embryonic devel- opment. In adults, targeted expression can be used to generate dominant phenotypes for use in genetic screens. We have directed expression of an activated form of the Dras2 protein, resulting in dominant eye and wing defects that can be used in screens to identify other members of the Dras2 signal transduction path- way. SUMMARY