Pre-equilibrium solid-phase microextraction of free analyte in complex samples: correction for mass transfer variation from protein binding and matrix tortuosity.
ABSTRACT The accurate measurement of free analyte concentrations within complex sample matrixes by pre-equilibrium solid-phase microextraction (SPME) has proven challenging due to variations in mass uptake kinetics. For the first time, the effects of the sample binding matrix and tortuosity on the kinetics of analyte extraction (from the sample to the SPME fiber) are demonstrated to be quantitatively symmetrical with those of the desorption of preloaded deuterated standards (from the fiber to the sample matrix). Consequently, kinetic calibration methods can be employed to correct for variation in SPME sampling kinetics, facilitating the application of pre-equilibrium SPME within complex sample systems. This approach was applied ex vivo to measure pharmaceuticals in fish muscle tissues, with results consistent with those obtained from equilibrium SPME and microdialysis. The developed method has the inherent advantages of being more accurate, precise, and reproducible, thus providing the framework for applications where rapid measurement of free analyte concentrations (within complicated sample matrixes such as biological tissues, sediment, and surface water) are required.
- SourceAvailable from: James A Noblet[Show abstract] [Hide abstract]
ABSTRACT: The equations governing the use of equilibrium solid-phase microextraction (SPME) for environmental samples with complex heterogeneous matrices were derived in terms of parameters commonly measured or estimated by environmental scientists. Parameterization of the SPME equations allowed for the a priori prediction of SPME performance as a function of analyte and sample properties as well as experimental conditions. A theoretical evaluation of SPME was performed for a broad range of realistic scenarios using calculated equilibrium partitioning parameters and the implications for practical applications were discussed. Potential pitfalls and errors in quantitative measurements were identified, and different approaches to SPME calibration were presented. The concept of an optimum minimum volume for the analysis of heterogeneous environmental samples was presented and fully developed. Data from three previous studies were used to validate the correctness of our theoretical framework; the agreement between the measured relative recoveries of a variety of hydrophobic organic chemicals and theoretical predictions was reasonable. The results of this study highlight the potential for SPME to be a valuable technique for the measurement of hydrophobic organic contaminants in complex environmental samples. The SPME technique appears to be especially well suited for samples with high solids-to-water ratios and/or large sample volumes. Examples of such applications include sediment interstitial water and in situ field measurements, respectively.Environmental Science and Technology 09/2002; 36(15):3385-92. · 5.26 Impact Factor
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ABSTRACT: We study numerically the tortuosity-porosity relation in a microscopic model of a porous medium arranged as a collection of freely overlapping squares. It is demonstrated that the finite-size, slow relaxation and discretization errors, which were ignored in previous studies, may cause significant underestimation of tortuosity. The simple tortuosity calculation method proposed here eliminates the need for using complicated, weighted averages. The numerical results presented here are in good agreement with an empirical relation between tortuosity (T) and porosity (varphi) given by T-1 proportional, variantlnvarphi , that was found by others experimentally in granule packings and sediments. This relation can be also written as T-1 proportional, variantRSvarphi with R and S denoting the hydraulic radius of granules and the specific surface area, respectively. Applicability of these relations appears to be restricted to porous systems of randomly distributed obstacles of equal shape and size.Physical Review E 09/2008; 78(2 Pt 2):026306. · 2.31 Impact Factor
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ABSTRACT: Determination of polymer-water and dissolved organic carbon (DOC)-water distribution coefficients of very hydrophobic chemicals (log K0w > 6) is not straightforward. Poor water solubility of the test compounds complicates the spiking and analysis of actual freely dissolved concentrations. By dosing a system via a PDMS-fiber and monitoring the depletion in the polymer, spiking and analysis of concentrations in the aqueous phase are avoided, and sorption to the polymer and other hydrophobic phases can be determined easily and accurate. In this publication we report the determination of poly(dimethyl-siloxane) (PDMS)-water, and Aldrich humic acid-water distribution coefficients for six PAHs with log K0w values varying from 4.56 to 6.85. The distribution coefficients to a PDMS fiber llog Kf) and the DOC (log KDOC) range from 3.86 to 5.39 and 4.78 to 7.43, respectively. Even for the most hydrophobic compounds, the distribution coefficients show small standard errors (< or = 0.05 log units). Therefore, this method might be applied to determine sorption coefficients of numerous, even more hydrophobic compounds, to humic acids as well as other dissolved hydrophobic matrixes.Environmental Science and Technology 05/2005; 39(10):3736-42. · 5.26 Impact Factor
Published: April 01, 2011
r2011 American Chemical Society
dx.doi.org/10.1021/ac2004899|Anal. Chem. 2011, 83, 3365–3370
Pre-Equilibrium Solid-Phase Microextraction of Free Analyte
in Complex Samples: Correction for Mass Transfer Variation from
Protein Binding and Matrix Tortuosity
Xu Zhang,†Ken D. Oakes,†Md Ehsanul Hoque,§Di Luong,†Chris D. Metcalfe,§Janusz Pawliszyn,‡and
Mark R. Servos*,†
†Department of Biology and‡Department of Chemistry, University of Waterloo, Ontario N2L 3G1, Canada
§Worsfold Water Quality Center, Trent University, Peterborough, Ontario K9J 7B8, Canada
S Supporting Information
concentration) of a chemical in a biological or environmental
system is often more relevant than the total concentration since
only the free fraction can diffuse through biological membranes
or bind to receptors. Due to its simplicity and ease of imple-
mentation, solid-phase microextraction (SPME) is a widely used
technique for evaluating protein binding,1?3bioavailability,4?6
as pharmaceuticals and organic pollutants.10?12Both the in-
applications are generally predicated on the accurate measure-
however, only equilibrium SPME (E-SPME) has been validated
for its accuracy in monitoring free concentrations.6,10,11,16With
the exception of fast equilibrium sampling of lipid tissue by
poly(dimethylsiloxane) (PDMS) fibers as demonstrated by
P. Mayer’s group,11the long sampling times required to achieve
equilibriumprevent widespread applicationofE-SPMEforlabile
compounds which can be quickly degraded. Furthermore,
the application of E-SPME within highly dynamic systems
where analyte concentrations change rapidly over time is largely
rom a toxicological and/or pharmacological point of view,
the free concentration (i.e., free dissolved or unbound
impractical. In these cases, pre-equilibrium SPME (PE-SPME)
offers distinct advantages due to its better temporal resolution
and short sampling intervals, which allow for the monitoring of
The intrinsic variation in mass transfer kinetics attributable to
the composition and structure of complex environmental and
biological sample systems presents technical challenges limiting
the accuracy of PE-SPME. For example, the presence of proteins
and dissolved organic carbon (DOC) in biological and environ-
mental samples (respectively) may enhance SPME extraction
these binding matrixes.1,18,19Recently, it was observed that the
presence of nanoparticles also facilitated the sampling of water-
borne atrazine;20this phenomenon, termed the “diffusion-layer
effect (DLE)” by Heringa et al., has been widely documented for
SPME,13liquid-phase microextraction (LPME),21and electro-
chemical metal analysis.22,23According to Oomen’s study, the
December 10, 2010
March 17, 2011
ABSTRACT: The accurate measurement of free analyte con-
centrations within complex sample matrixes by pre-equilibrium
solid-phase microextraction (SPME) has proven challenging
due to variations in mass uptake kinetics. For the first time, the
effects of the sample binding matrix and tortuosity on the
kinetics of analyte extraction (from the sample to the SPME
fiber) are demonstrated to be quantitatively symmetrical with
those of the desorption of preloaded deuterated standards
(from the fiber to the sample matrix). Consequently, kinetic
calibration methods can be employed to correct for variation in
SPME sampling kinetics, facilitating the application of pre-
equilibrium SPME within complex sample systems. This ap-
proach was applied ex vivo to measure pharmaceuticals in fish
muscle tissues, with results consistent with those obtained from
equilibrium SPME and microdialysis. The developed method
has theinherent advantagesof beingmore accurate, precise, andreproducible,thus providingtheframework forapplications where
rapid measurement of free analyte concentrations (within complicated sample matrixes such as biological tissues, sediment, and
surface water) are required.
dx.doi.org/10.1021/ac2004899 |Anal. Chem. 2011, 83, 3365–3370
presence of a matrix can enhance analyte extraction as long as
the dissociation kinetics of the matrix-bound species is fast.10
One can imagine that, in a complicated environmental or
biological sample (such as the effluent from a municipal waste-
water treatment plant or a biological tissue/blood sample), there
are frequently potential matrix components meeting Oomen’s
complex samples might be significant, even if the contributions
from individual matrix components are not.
Furthermore, for semisolid biological tissues, structural char-
acteristics such as tortuosity may significantly affect SPME
sampling, though this has yet to be experimentally investigated.
The significant influence of tortuosity and extracellular volume
fraction on mass transfer of ion-selective microelectrode (ISM)
sampling has, however, been well demonstrated.24If tortuosity
affects SPME sampling kinetics in a manner similar to that of
ISM, it would pose challenges for accurately applying PE-SPME
to quantify free concentrations.
Finally, fouling of SPME probes by biological or environ-
mental matrix materials might change their extraction behavior.
Recent evidence suggests a negligible impact of fouling might
reasonably be expected, as illustrated by deployments of PDMS
patible SPME probes offers the possibility of reduced fouling
during sampling, at least within biological applications, but
additional evaluations in other matrixes would be prudent.27
To address these issues and their influence on PE-SPME
accuracy, we provide experimental evidence for the influence of
the binding matrix and sample tortuosity on SPME kinetics.
Accordingly, a PE-SPME approach is proposed to measure free
concentrations by utilizing kinetic calibration to compensate for
variation in SPME sampling kinetics induced by the sample
matrix and/or structure. The kinetic calibration method was
developed on the basis of the symmetric relationship between
absorption of the analyte from the sample matrix to the SPME
fiber and the desorption of preloaded standards from the fiber to
the sample matrix.12The feasibility of the developed approach
was demonstrated by monitoring the free concentration of the
pesticide atrazine (a model hydrophobic compound) and utiliz-
ing bovine serum albumin (BSA) as the binding matrix. This
approach was further evaluated ex vivo by analysis of pharma-
ceuticals and other environmental contaminants in fish epaxial
muscle, with the results validated against established methods
such as E-SPME, equilibriumdialysis(ED),microdialysis (MD),
and solid-phase extraction (SPE).
Chemicals and Materials. Gemfibrozil, atorvastatin, ibupro-
fen, carbamazepine (CBZ), diclofenac, naproxen, and bisphenol
Canada). Fluoxetine (FLX) and lorazepam were obtained from
Cerilliant Corp. (Round Rock, TX). Atrazine was obtained from
Chem Service Inc. (West Chester, PA), while the deuterated
standards of atrazine, atorvastatin, BPA, CBZ, diclofenac, FLX,
Isotopes Inc. (Pointe-Claire, Qu? ebec, Canada). All chemicals
purchased were of the highest possible purity and were used
without further purification. HPLC grade acetic acid (glacial)
and methanol for the HPLC mobile phase were purchased from
Fisher Scientific (Unionville, Ontario, Canada). BSA (molecular
weight 67000) and agar were obtained from Sigma-Aldrich (St.
Louis, MO). The 1 cm biocompatible C18 particle (45 μm)
coated SPME fibers were obtained from Supelco (Bellefonte,
PA) for use with in vitro experiments. The Micro-Equilibrium
dialyzers with 50 μL chambers and regenerated cellulose mem-
brane (25000 molecular weight cutoff) were purchased from
Harvard Apparatus Canada (Saint-Laurent, Qu? ebec, Canada).
The 4 mm CMA/12 microdialysis probes (20000 molecular
weight cutoff) and tubing were purchased from CMA/Micro-
dialysis AB (Stockholm, Sweden).
Extraction Procedure in Model Sample Systems. Two
simplified model systems were used to simulate biological and
environmental samples. BSA solutions in phosphate-buffered
saline (PBS buffer) modeled aqueous samples with an organic
binding matrix, while agarose gel was used to mimic semisolid
samples such as biological tissue that possesses inherent struc-
tural tortuosity. Due to their similar porous structures, agarose
gel has been widely used as a medium to mimic animal tissue in
investigations of diffusion mechanisms.24Time profile experi-
ments were used to determine absorption and desorption
polar and partially ionize at environmental pH values, both
model matrixes were prepared in PBS buffer at a fixed pH value
The first experiment was performed in 2 μg/mL atrazine
solutions containing differing concentrations of BSA (0, 6, and
20 μM) in PBS buffer (pH 7.4), shaken gently overnight
(at 150 rpm on an orbital shaker) to ensure atrazine and BSA
achieved a binding equilibrium prior to the SPME experiment.
The C18 fibers were preloaded with deuterated atrazine in
100 mL of loading solution (100 ng/mL atrazine-d5in PBS
at 150 rpm). The BSA/atrazine solutions were separated into
1.5 mL aliquots in amber GC vials, and SPME fibers were
deployed into the solutions for differing sampling durations
(15 and 30 min and 1, 1.5, 2, 2.5, 3, 3.5, 4, and 5 h). The loss
vials during sample preparation was negligible (<0.5%).
A second experiment utilizing agarose gel (0.8%, 1.6%, and
2.4%) containing 300 ng/mL atrazine evaluated the influence of
as the model sample matrix since the relationship among agar
is well established.28The gel (1.5 cm in thickness) was cast in
previously.29Twenty-four C18 fibers preloaded with deuterated
standards were placed into the gel plate simultaneously and then
removed sequentially after 0.5, 1, 1.5, 2, 3, 4, 5, and 6 h of
Desorption of SPME Fibers and Instrumental Analysis.
Desorption of C18 SPME fibers was conducted in 100 μL of
desorption solution (MeOH (50%) in Nanopure water contain-
ing 0.1% acetic acid and 1 ng/mL lorazepam) for 30 min with
agitation at 150 rpm on an orbital shaker. A subsequent
desorption of previously desorbed fibers confirmed that 99% of
the chemicals were extracted from the fibers during the first
desorption cycle. Lorazepam was used as the injection standard
to calibrate for variations in injected volume by the HPLC
Analytes and the injection standard (lorazepam) were quanti-
fied by LC/MS/MS with an Agilent 1200 HPLC instrument
dx.doi.org/10.1021/ac2004899 |Anal. Chem. 2011, 83, 3365–3370
transitions monitored were (diazepam) 285/154, (fluoxetine) 310/
44, (carbamazepine) 237/195, (ibuprofen) 205/161, (atrazine)
216/174, (atorvastatin)559/440, (naproxen)229/169, (dicl-
ofenac) 294/250, (atorvastatin-d5) 564/445, (ibuprofen-d3) 207/
164, (carbamazepine-d10) 247/204, (diclofenac-d4) 298/217,
([13C1]naproxen-d3) 233/169, (fluoxetine-d5) 315/44, (diaze-
pam-d5) 290/198, (atrazine-d5) 221/179, and (lorazepam)
321.1/274.9. The peak area ratio of the analyte to lorazepam was
used for quantitation. The instrumental response to each analyte
was calibratedusing standardcurves with standards prepared in the
same desorption solution.
In Vitro Application: Measurement of Free Atrazine Con-
centrations in BSASolutions.To demonstrate the feasibility of
the proposed approach in sample systems with a binding matrix,
the concentrations of atrazine inBSAsolutions were determined
using PE-SPME. Atrazineconcentrations weredeterminedusing
preloaded with deuterated standards and the second utilizing
dual blank fibers exposed over differing time durations (5 and 10
min).30For the single-fiber procedure, fibers preloaded with
PBS solutions with 0, 6, and 20 μM BSA equilibrated overnight
prior to SPME analysis) stirred at 600 rpm for 5 min. Afterward,
the fibers were desorbed into 100 μL of desorption solution as
described. For the dual extraction method, two clean fibers were
deployed into the sample simultaneously for 5 and 10 min
intervals, respectively. The calculations supporting both kinetic
To measure free concentrations, the product of KfbVf was
calculated from the equilibrium extraction in PBS standard
solutions,29where the equilibrium extraction for atrazine was
found to be linear up to 2000 ng/mL.
The SPME analysis was validated against both equilibrium
SPME (4 h sampling duration) and ED (detailed procedure
provided in the Supporting Information). Quantification of
atrazine extracted by ED was performed by HPLC/MS/MS on
the basis of the external calibration curve method. A standard
solution series (5?2000 ng/mL) was prepared in PBS buffer,
and 5 μL of each concentration was mixed with 95 μL of
desorption solution for instrumental analysis. In this study, the
dynamic range of analysis for ED was linear up to 5000 ng/mL.
Monitoring of Pharmaceuticals and Environmental Chemi-
cals in Fish Muscle. All fish experiments were performed in
accordance with protocols approved by our institutional Animal
Care Committee (AUP No. 07-16) in the Biology wet-Lab Facility
at the University of Waterloo. An 8 day laboratory exposure was
performed for immature rainbow trout (Oncorhynchus mykiss, n =
19, 22.1 ( 2.3 cm, 107.1 ( 27.1 g). A total of 9 of the 19 fish were
divided into 3 glass aquaria (3 fish/tank) and exposed to fresh well
water spiked with 100 μL of pure methanol (with 2 day static
renewals) containing the analyte mixture (atorvastatin, atrazine,
BPA, carbamazepine, diclofenac, fluoxetine, gemfibrozil, ibuprofen,
3 μg/L. An additional three fish were in a separate tank and were
treated with only methanol as the solvent control, while the seven
remaining fish were held as clean water controls.
After 8 days of exposure, the fish were humanely euthanized
and dissected with approximately 2 g of dorsal-epaxial muscle
tissue snap frozen in liquid nitrogen subsequent to storage
at ?80 ?C until analysis. PE-SPME and E-SPME measurements
were performed using 1 cm C18 fibers inserted into thawed
muscle samples for durations of either 20 min at room tempera-
ture (24 ?C) or 18 h in a refrigerator (4 ?C). The 18 h sampling
duration was deemed sufficient to achieve equilibrium for all
analytes on the basis of previous static extraction-time profile
experiments conductedat 4?C inPBSbuffer, where the times to
equilibrium were determined as follows: carbamazepine, 9 h;
fluoxetine, 12 h; gemfibrozil, 3 h; ibuprofen, 3 h; atrazine, 10 h;
atorvastatin, 5 h; naproxen, 3 h; diclofenac, 4 h; bisphenol A, 4 h.
The kinetic and external calibration methods employed were
identical to those described previously.26,29?32A further valida-
tion of kinetically calibrated PE-SPME was performed by MD
using a perfusion fluid of PBS buffer (pH 6.9, the same as the pH
value of the fish blood) containing a 30 ng/mL concentration of
each deuterated standard, with a flow rate of 1 μL/min using a
PicoPlus syringe pump from Harvard Apparatus (Holliston,
MA). Dialysates were collected in 20 min intervals and mixed
with 80 μL of desorption solution (80% MeOH in Nanopure
water containing 0.1% acetic acid and 1 ng/mL lorazepam) for
the basis of established retrodialysis theory33by LC/MS/MS
employing the calibration curve method using a series of
standard solutions prepared in PBS buffer. A 20 μL volume of
each perfusate was mixed with 80 μL of desorption solution for
instrumental analysis. In standard solutions, the dynamic range
for both SPME (20 min, 18 h) and MD extracts was linear up to
500 ng/mL. The quantification limits of the 20 min SPME
(signal/noise = 10) were 0.1, 0.05, 0.1, 0.02, 0.05, 0.5, 0.5, 1, and
2 ng/mL for gemfibrozil, CBZ, ibuprofen, atrazine, FLX, diclo-
fenac, naproxen, atorvastatin, and BPA, respectively.
’RESULTS AND DISCUSSION
Symmetry between Desorption and Absorption. The
fundamental principle underlying pre-equilibrium SPME kinetic
calibration is the symmetrical relationship (eq 1) between the
extraction (absorption/adsorption) kinetics (eq 2) and desorp-
tion kinetics (eq 3).34,35
¼ 1 ?Q
n ¼ neð1? e?atÞð2Þ
Q ¼ q0e?at
Alternatively, the symmetry is true if the time constant, a, for the
absorption process is the same as that for desorption. Here n is
t, ne is the amount of analyte in the extraction phase at
equilibrium, n/neis the extraction fraction, Q is the amount of
standard remaining in the extraction phase after exposure to the
sample matrix for sampling time t, q0is the amount of standard
fraction. For both the extraction and desorption processes, the
time constant, a, characterizes the kinetics or speed of the mass
transfer. As n, q0, and Q are known or can be determined, necan
then be readily calculated, thus obtaining the amount of analyte
at equilibrium using pre-equilibrium SPME. Alternatively, necan
also be obtained using two clean fibers exposed in a sampling
system for different pre-equilibrium durations as previously
dx.doi.org/10.1021/ac2004899 |Anal. Chem. 2011, 83, 3365–3370
The symmetry between the absorption of atrazine and the
desorption of atrazine-d5has been demonstrated in samples of
various BSA concentrations and agar tortuosities (Figure 1 and
Table 1). The observed symmetry, regardless of the BSA-
enhanced diffusion layer effect, confirms any accelerated desorp-
tion kinetics of the preloaded standard are exactly compensated
for by a commensurate acceleration in absorption kinetics, thus
validating the principle underlying the use of PE-SPME with
kinetic calibration. Conversely, while increased structural tortu-
osity slowed the absorption and desorption kinetics, the time
constants for desorption in different gel media were again
commensurate and symmetrical with those for absorption, as is
required for kinetic calibration (Table 1). Notably, a symmetric
relationship between extraction and desorption has previously
been observed in diverse matrixes, including 5% acetonitrile
aqueous solutions, PBS buffer (pH 7.4), river water, white wine,
and plasma and blood samples. These symmetries were assessed
using various SPME fiber materials, such as polypyrrole, carbow-
ax/templated resin, carbon tape, and C18-bonded silica for
different target compounds, including pharmaceuticals and
Precision and Accuracy of the Proposed Approach in
Model Systems. To validate our corrections for mass transfer
variation induced by binding matrixes, measured free analyte
concentrations derived using kinetically calibrated PE-SPME
approaches were evaluated against established E-SPME and
equilibrium dialysis methods (Table 2). Both the accuracy and
precision of the single-fiber PE-SPME method were comparable
to those of E-SPME and ED. While the dual-fiber PE-SPME
demonstrated acceptable accuracy, it exhibited higher relative
variation (23?29%) than the single-fiber method (16?20%),
due to interfiber variation (5?12%) which contributed to the
overall variation of the approach. Despite the higher variability
inherent to the dual-fiber approach, in circumstances when
deuterated standards for the analyte of interest are not available,
the dual-fiber method may of necessity be the only acceptable
The traditional calibration curve method, when employed to
was incapable of accurately measuring free concentrations. For
example, free atrazine concentrations in 6 and 20 μM BSA
solutions were overestimated by roughly 40% and 90%, respec-
tively. In contrast, atrazine in PBS buffer only yielded accurate
PE-SPME concentration estimates when quantitated by the
traditional calibration curve method, estimates consistent with
those calibrated by the two kinetic calibrations. The reason for
BSA enhanced the SPME extraction kinetics, the extracted
atrazine was overcorrected to higher concentration estimates
by a calibration curve generated in standard solutions free of any
binding matrixes (and consequently devoid of any enhanced
mass transfer kinetics). The extent of the overestimation can be
overestimation ð%Þ ¼Cmeasured?Creal
where Cmeasuredis the measured free concentration using the
calibration curve, Crealis the real concentration (the free con-
centration obtained by the established method, E-SPME),
and amatrixand abufferare the time constants in samples with and
without binding matrixes, respectively. The disparity between
Table 1. Symmetric SPME Extraction (Absorption/Ad-
sorption) and Desorption Time Constants for Atrazine, CBZ,
and FLX Agar Gel Media (n = 3)
a value for extraction (h?1)a value for desorption (h?1)
(%) atrazineCBZFLX atrazineCBZ FLX
3.1(0.4 1.3(0.2 2.1(0.3 3.0( 0.3 1.2(0.3 2.3(0.5
1.6(0.2 1.4 (0.2 1.5(0.2 1.4(0.3
1.3(0.1 0.9(0.1 1.0(0.2 1.2(0.3 0.8 (0.2 1.1(0.1
0.8(0.1 0.8(0.2 0.7 (0.1 0.9(0.2
Table 2. Free Atrazine Concentrations (ng/mL) Measured in BSA Solutions Using the PE-SPME Approach Calibrated by Two
Kinetic Calibration Methods (Single Fiber Preloaded with Atrazine-d5, Dual Blank Fiber) as Well as the Traditional Calibration
BSA concn (μM)single loadeddual blankcalibration curvecalibration curvecalibration curve
in parentheses (n = 5).
Table 3. Free Pharmaceutical Concentrations in Rainbow
Trout Dorsal-Epaxial Muscle (ng/g) Following 8 Days of
Exposure to the Analyte Mixture (n = 9)a
analytePE-SPME (20 min) E-SPME (18 h)MD
aNo analyte signal was detected from the solvent control (n = 3) and
fresh water control fish (n = 7) by each of the three methods. ND = not
detectable. NR = notreported due to huge variations in FLX concentra-
0.12 ( 0.02
0.25 ( 0.05
1.25 ( 0.4
6.48 ( 0.3
0.15 ( 0.05
0.14 ( 0.05
0.13 ( 0.01
0.22 ( 0.05
1.18 ( 0.3
6.95 ( 0.8
0.12 ( 0.04
0.13 ( 0.03
0.12 ( 0.03
0.27 ( 0.04
1.20 ( 0.4
0.16 ( 0.05
0.12 ( 0.02
dx.doi.org/10.1021/ac2004899 |Anal. Chem. 2011, 83, 3365–3370
free concentration estimates obtained by traditional calibration
curves and those from kinetic calibration demonstrates the
feasibility of eq 4.
Real Sample Application: Environmental Organic Chemi-
cals in Fish Muscle. Quantitative analysis of pharmaceuticals in
semisolid tissues using PE-SPME is challenging due to the
simultaneous influences of both the binding matrix and tortuos-
ity, each moderating mass-uptake kinetics in a simultaneous, yet
opposing manner. Kinetically calibrated PE-SPME compensates
for the extraction-enhancing effects ofthe binding matrix,as well
as the impeding effects of tortuosity. Here, we demonstrate the
feasibility of this approach through the measurement of pharma-
ceuticals in fish muscle.
to identify in fish and their exposure water, six compounds
(ibuprofen, gemfibrozil, atrazine, CBZ, FLX, and diclofenac)
MD obtained consistent results for five of the six compounds:
FLX was too hydrophobic (log Kow= 4.65, pKa= 10.1) to be
accurately and reproducibly extracted by the polar perfusate
(PBS buffer, pH 6.9).17In general, the measured free concentra-
tions reflected the bioconcentration potential of each target
analyte and were consistent with previous studies.38?42More
importantly, the consistency of the data obtained with the
three methods support our hypothesis that the kinetically
calibrated PE-SPME could be used to compensate for the mass
transfer variations from sample matrixes and deliver accurate
measurement of free analyte concentrations in complex sample
While the present study demonstrates the necessity and
importance of kinetic calibration to ensure the accuracy of PE-
SPME quantitative analysis, we are aware that deuterated stan-
dards, if available, are often prohibitively expensive, especially if
large numbers of analytes and their degradation products are
to be considered. In light of such challenges, development of a
kinetic calibration approach based on regular (nonisotopic)
analytical standards is under way in our group.43
The composition and structure of sample systems can exert a
profound influence on sampling kinetics, making accurate PE-
SPME quantitation challenging. The current work compensates
for variations in mass transfer produced by the presence of a
sample binding matrix and/or structural tortuosity. As a result,
this technique for fast PE-SPME analysis of free analyte con-
centrations can be utilized in biological tissues and complicated
environmental samples (such as surface water with dissolved
organic matter and suspending particulates). The principles
underlying this work can be readily extrapolated to similar
sampling techniques such as semipermeable membrane devices
(SPMDs), LPME, biosensors, and MD due to comparable mass
transfer physics that also govern SPME sampling.
available free of charge via the Internet at http://pubs.acs.org.
ED procedure. Thismaterial is
*Phone: (519) 888-4567, ext. 36034. E-mail: mservos@
This work has been supported by the Ontario Ministry of
Research & Innovation Post-Doctoral Fellowship Program, the
Natural Sciences and Engineering Research Council of Canada,
the Canadian Water Network, and the Canada Research Chairs
(1) Vaes, W. H. J.; Ramos, E. U.; Verhaar, H. J. M.; Seinen, W.;
Hermens, J. L. M. Anal. Chem. 1996, 68, 4463–4467.
Figure1. Verificationofthesymmetrybetweenextraction(absorption) ofatrazinefromtheBSAsolutionstoC18-coated SPMEfibersanddesorption
of preloaded standards from the fiber to the sample solutions (n = 6, RSDs 10?15%). Absorption and desorption (D) profiles were obtained in PBS
solutions with different BSA concentrations (0, 6, and 20 μM).
dx.doi.org/10.1021/ac2004899 |Anal. Chem. 2011, 83, 3365–3370
(2) Yuan, H.; Pawliszyn, J. Anal. Chem. 2001, 73, 4410–4416.
(3) Heringa, M. B.; Pastor, D.; Algra, J.; Vaes, W. H. J.; Hermens,
J. L. M. Anal. Chem. 2002, 74, 5993–5997.
(4) van der Wal, L.; Jager, T.; Fleuren, R. H. L. J.; Barendregt, A.;
Sinnige, T. L.; van Gestel, C. A. M.; Hermens, J. L. M. Environ. Sci.
Technol. 2004, 38, 4842–4848.
(5) Hu, X.; Liu, J.; Zhou, Q.; Lu, S.; Liu, R.; Cui, L.; Yin, D.; Mayer,
P.; Jiang, G. Chemosphere 2010, 80, 693–700.
(6) Mayer, P.; Tor€ ang, L.; Glæsner, N.; J€ onsson, J.Å. Anal. Chem.
2009, 81, 1536–1542.
(7) Zeng, E. Y.; Noblet, J. A. Environ. Sci. Technol. 2002,
Sci. Technol. 2005, 39, 3736–3742.
(9) Pino, V.; Ayala, J. H.; Gonzalez, V.; Afonso, A. M. Anal. Chem.
2004, 76, 4572–4578.
(10) Oomen, A. G.; Mayer, P.; Tolls, J. Anal. Chem. 2000,
(11) Jahnke, A.; Mayer, P.; Broman, D.; McLachlan, M. S. Chemo-
sphere 2009, 77, 764–770.
(12) Chen, Y.; Pawliszyn, J. Anal. Chem. 2004, 76, 5807–5815.
(13) Heringa, M. B.; Hermens, J. L. M. TrAC, Trends Anal. Chem.
2003, 22, 575–587.
2004, 129, 1137–1142.
(15) Bondarenko, S.; Gan, J. Environ. Sci. Technol. 2009,
(16) Heringa, M. B.; Hogevonder, C.; Busser, F.; Hermens, J. L. M.
J. Chromatogr., B 2006, 834, 35–41.
(17) Zhang, X.; Oakes, K.; Luong, D.; Wen, J. Z.; Metcalfe, C. D.;
Pawliszyn, J.; Servos, M. R. Anal. Chem. 2010, 82, 9492–9499.
(18) Kramer, N. I.; van Eijkeren, J. C. H.; Hermens, J. L. M. Anal.
Chem. 2007, 79, 6941–6948.
(19) Mayer, P.; Karlson, U.; Christensen, P. S.; Johnsen, A. R.;
Trapp, S. Environ. Sci. Technol. 2005, 39, 6123–6129.
(21) Jeannot, M. A.; Cantwell, F. F. Anal. Chem. 1997,
(22) van Leeuwen, H. P. Environ. Sci. Technol. 1999, 33, 3743–3748.
(23) van Leeuwen, H. P.; Town, R.M.; Buffle, J.; Cleven, R.F. M. J.;
Davison, W.; Puy,J.; vanRiemsdijk, W.H.; Sigg, L. Environ. Sci.Technol.
2005, 39, 8545–8556.
(24) Nicholson, C.; Phillips, J. M. J. Physiol. 1981, 321, 225–257.
Environ. Sci. Technol. 2010, 44, 3417–3422.
(27) Vuckovic, D.; Shirey, R.; Chen, Y.; Sidisky, L.; Aurand, C.;
Stenerson, K.; Pawliszyn, J. Anal. Chim. Acta 2009, 638, 175–185.
(28) Matyka, M.; Khalili, A.; Koza, Z. Phys. Rev. E 2008, 78,
(29) Zhang, X.; Cai, J.; Oakes, K.; Breton, F.; Servos, M.; Pawliszyn,
J. Anal. Chem. 2009, 81, 7349–7356.
(30) Ouyang, G.; Cai, J.; Zhang, X.; Li, H.; Pawliszyn, J. J. Sep. Sci.
2008, 31, 1167–1172.
(31) Zhang, X.; Cudjoe, E.; Vuckovic, D.; Pawliszyn, J. J. Chroma-
togr., A 2009, 1216, 7505–7509.
(32) Menacherry, S.; Hubert, W.; Justice, J. B., Jr. Anal. Chem. 2002,
(33) Zhou, S. N.; Oakes, K. D.; Servos, M. R.; Pawliszyn, J. Environ.
Sci. Technol. 2008, 42, 6073–6079.
(34) Ai, J. Anal. Chem. 1997, 69, 1230–1236.
(35) Birch, H.; Gouliarmou, V.; L€ utzhøft, Hans-C. H.; Mikkelsen,
P. S.; Mayer, P. Anal. Chem. 2010, 82, 1142–1146.
Chem. 2007, 79, 1221–1230.
(37) Zhou, S. N.; Zhao, W.; Pawliszyn, J. Anal. Chem. 2008, 80,
(38) Daughton, C. G.; Ternes, T. A. Environ. Health Perspect. 1999,
107 (Suppl. 6), 907–938.
(39) Metcalfe, C. D.; Koenig, B. G.; Bennie, O. T.; Servos, M;
Ternes, T. A.; Hirsch, R. Environ. Toxicol. Chem. 2003, 22, 2872–2880.
Anal. Chem. 2007, 79, 3155–3163.
(41) Brooks, B. W.; Chambliss, C. K.; Stanley, J. K.; Ramirez, A. J.;
Banks, K. E.; Johnson, R. D.; Lewis, R. J. Environ. Toxicol. Chem. 2005,
(42) Schwaiger, J.; Ferling,H.; Mallow, U.; Wintermayr, H.; Negele,
R. D. Aquat. Toxicol. 2004, 68, 141–150.
(43) Zhang, X.; Oakes, K.; Luong, D.; Metcalfe, C. D.; Pawliszyn, J.;
Servos, M. R. Anal. Chem. 2011, 83, 2371–2377.