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Systematic evaluation of extraction methods for multi-platform based metabotyping: Application to the Fasciola hepatica metabolome Jasmina Saric, Elizabeth J. Want, Urs Duthaler, Matthew Lewis, Jennifer Keiser, John P Schockcor, Gordon A. Ross, Jeremy Kirk Nicholson, Elaine Holmes, and Marina Franco Maggi Tavares Anal. Chem., Just Accepted Manuscript • DOI: 10.1021/ac300586m • Publication Date (Web): 12 Jul 2012 Downloaded from http://pubs.acs.org on July 21, 2012
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Analytical Chemistry
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Systematic evaluation of extraction methods for multi-
2
platform based metabotyping: Application to the
3
Fasciola hepatica metabolome
4 5
Jasmina Saric,† Elizabeth J. Want,† Urs Duthaler,§ Matthew
6
Lewis,† Jennifer Keiser,§ John P. Shockcor, Gordon A. Ross,#
7
Jeremy K. Nicholson,† Elaine Holmes,†,* and Marina F. M.
8
Tavares, †,‡,*
9 10
†
11
Medicine, Imperial College London, Sir Alexander Fleming Building, South
12
Kensington, London SW7 2AZ, U.K.; §Department of Medical Parasitology
13
and Infection Biology, Swiss Tropical and Public Health Institute, CH-4002
14
Basel, Switzerland and University of Basel, CH-4003 Basel, Switzerland;
Biomolecular Medicine, Department of Surgery and Cancer, Faculty of
Pharmaceutical
15
Business
Operations,
Waters
Corporation,
Milford,
16
Massachussetts, U.S.A.; #Agilent Technologies Life Sciences and Chemical
17
Analysis, Lakeside, Cheadle Royal Business Park, Stockport, Cheshire, SK8
18
3GR, U.K.; ‡Institute of Chemistry, University of Sao Paulo, P.O. Box 26077,
19
05513-970, Sao Paulo, SP, Brazil
20 21
*
22
E-mail:
[email protected]; E-mail:
[email protected] To whom correspondence should be addressed:
23
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ABSTRACT
25
Combining data from multiple analytical platforms is essential for
26
comprehensive study of the molecular phenotype (metabotype) of a given
27
biological sample. The metabolite profiles generated are intrinsically
28
dependent on the analytical platforms, each requiring optimization of
29
instrumental parameters, separation conditions and sample extraction to
30
deliver maximal biological information. An in depth evaluation of extraction
31
protocols for characterizing the metabolome of the hepatobiliary fluke Fasciola
32
hepatica using UPLC-MS and CE-MS is presented. The spectrometric
33
methods were characterized by performance and metrics of merit were
34
established including precision, mass accuracy, selectivity, sensitivity and
35
platform stability. Although a core group of molecules was common to all
36
methods, each platform contributed a unique set and 142 metabolites out of
37
14,724 features were identified. A mixture design revealed that 15:59:26
38
chloroform:methanol:water was globally the best composition for metabolite
39
extraction across UPLC-MS and CE-MS platforms accommodating different
40
columns and ionization modes. Despite the general assumption of the
41
necessity of platform-adapted protocols for achieving effective metabotype
42
characterization, we show that an appropriately designed single extraction
43
procedure is able to fit the requirements of all technologies. This may
44
constitute a paradigm shift in developing efficient protocols for high throughput
45
metabolite profiling with more general analytical applicability.
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Analytical Chemistry
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INTRODUCTION
48
Metabolic profiling using mass spectrometry (MS) hyphenated with ultra
49
performance liquid chromatography (UPLC) or gas chromatography (GC) and
50
nuclear magnetic resonance (NMR) spectroscopy have been successfully
51
applied to the characterization of systemic responses of organisms to
52
disease, pharmaceutical intervention and dietary modulation.1,2,3 In such
53
studies, the adequacy of a given analytical platform is typically dependent
54
upon the class of chemical compounds under investigation, the cost of
55
analysis, ease of sample preparation and the requirement for sensitivity,
56
specificity, and robustness. No single method enables complete coverage of
57
the entire metabolic information and increasingly, metabolic profiling studies
58
are adopting more than one analytical platform to augment the number of
59
metabolites identified and therefore enhance the extraction of biological
60
information.
61
Although the
literature is
scattered
with platform-specific
sample
62
preparation procedures,4 there is a paucity of studies reporting the systematic
63
evaluation of sample preparation across multiple platforms.5 Despite the
64
recent technological developments in the field of sample preparation of
65
biofluids,
66
methods,6,7,8,9
67
microextractions12 to the more sophisticated use of molecularly imprinted
68
polymers13 and restricted-access materials,14 sample extraction continues to
69
be a crucial and time consuming step of any analytical method, with important
70
implications on the information recovered and analytical interpretation. This is
spanning
from
liquid-liquid
the or
more
traditional
solid-phase
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protein
precipitation
extractions10,11
and
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particularly true for comprehensive metabolic profiling, where the chemical
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complexity, sample heterogeneity, and wide concentration range of
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endogenous metabolites place a strong demand on the extraction
74
procedure.15 Metabolite losses, matrix effects, artefacts and analytical
75
variability are often inevitable,16 which indicate that the ultimate goal of full
76
characterisation of a metabolome will be a challenging task for many
77
biological samples.
78
To preserve sample integrity, methods with minimal sample treatment are
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desirable and often applicable for liquid biological samples, such as urine or
80
plasma, where simple dilution followed by filtration and/or centrifugation are
81
the norm. However, for solid or semi-solid biological samples, such as faeces
82
and tissues, more elaborate sample preparation procedures are required.
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Tissue extraction is usually performed by cooled homogenisation of tissue
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followed by stepwise addition of reagents and solvents of differing polarities
85
such
86
experimental approaches include the use of automated homogenizers,18,19,20
87
microdialysis tissue sampling,21 and solid-phase extraction with a large variety
88
of sorbents.22
as
perchloric
acid
or
methanol-chloroform
mixtures.17
Other
89
Here we apply a multi-platform strategy for a more comprehensive
90
assessment of the metabolic composition of tissues using the parasitic
91
hepatobiliary trematode Fasciola hepatica as a model system. F. hepatica
92
infects livestock and imposes a considerable economic burden across the
93
globe linked to decreased productivity of the affected animals.23 Due to its
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zoonotic character, fascioliasis has emerged as human infection in the last
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two decades, whereby an estimated 91 million people are at risk. Although
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some host spots of prevalence have been identified, such as Western Europe,
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the Andes, and Egypt, human cases have been reported from as many as 51
98
countries.24 Diseases management is currently suboptimal since diagnosis is
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largely based on microscopic examination of helminth eggs in stool, whereby
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detection capacity is limited in early and light infection. The first line
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therapeutic
102
triclabendazole, whereby resistances have already been reported.25 Metabolic
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characterisation of the fluke may aid in deepening understanding of the
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biochemical communication between parasite and host and may provide
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leads for identifying novel diagnostic markers and drug targets at the
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metabolic level.
intervention is
limited
to
one
main
compound,
namely
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We evaluated the extraction of metabolic information from spectral profiles
108
acquired across five different analytical methods. A quadrupole time-of-flight
109
(Q-ToF) mass analyzer was used for UPLC-MS analysis in combination with
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two different column chemistries, i.e. reversed-phase liquid chromatography
111
(RPLC) using a C18 column and hydrophilic interaction liquid chromatography
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(HILIC), in both positive and negative electrospray ionization modes (ESI+
113
and ESI-, respectively). Capillary electrophoresis (CE) coupled to MS was
114
applied in ESI+ mode only. Additionally, a mixture design was used to define
115
the optimal solvent composition for the global platform combination, and thus
116
to derive a single procedure that can be applied generically for tissue
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extraction across a range of biomedical samples and analytical platforms. In
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addition to providing an optimised and augmented metabolic screening
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capacity, such an approach would also facilitate the mathematical modelling
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across different analytical platforms since the preparation parameters are
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maintained regardless of platform, thereby reducing additional sources of
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variation introduced by differential extraction efficiency of metabolites.26
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MATERIALS AND METHODS
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Materials. Water, acetonitrile, methanol and chloroform (chromatography
126
grade) used in the tissue extractions were obtained from Sigma (Gillingham,
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U.K.) as well as most standards used to confirm the identity of the
128
chromatographic peaks. Cholic acid derivatives were acquired from Steraloids
129
Inc (Newport, RI, U.S.A.) and phospholipids were purchased from Avanti
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Polar Lipids Inc (Alabaster, AL, U.S.A.) (Supplementary Table S-1). Stock
131
standard solutions were prepared at 1 mg/mL in chromatography purity water.
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Working solutions used in the identification and MS/MS fragmentation studies
133
were prepared at 0.010 to 0.050 mg/mL.
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Sample preparation. Fresh cattle livers were obtained from an abattoir in
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Basel and live F. hepatica worms were recovered from the bile ducts at the
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Swiss Tropical and Public Health Institute (Basel, Switzerland). Worms were
137
snap frozen and forwarded on dry ice to Imperial College London and kept at -
138
40°C.
139
For characterization of the F. hepatica metabolome and for assessment of
140
the methods performance, two batches of six individual flukes (~80 mg each)
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obtained from two different livers were thawed and weighed. Each worm was
142
placed into a separate 2 mL plastic tube containing 500 mg of 1 mm diameter
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zirconia beads (Stratech Scientific Ltd, U.K.). One mL of 80% methanol, which
144
was cooled down previously to 4°C, was added to each tube. The tubes were
145
processed in a tissue homogenizer (Precellys 24, Peqlab Ltd., UK) in two 30 s
146
cycles of 6,000 rpm, subsequently centrifuged for 5 min at 18,894 g and the
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supernatants transferred into Eppendorf tubes placed on ice. The extraction
148
procedure was repeated once by adding 500 µL cold methanol to the
149
remaining pellet in each tube, followed by homogenization and centrifugation
150
as described above. Both supernatants were combined and divided in
151
different aliquots for spectral assessment, i.e. equal aliquots of 100 µL for
152
UPLC-MS and CE-MS analysis, and the remaining was retained as a backup.
153
The extracts were dried overnight in a speedvac (Eppendorf concentrator
154
plus, Eppendorf UK Ltd, Cambridge, U.K.) at 45°C, under vacuum and
155
rotational speed of 1,400 rpm (the g-force varies according to the position of
156
the tubes in the rotors between 130 and 250 g). Dried extracts were stored at
157
-40°C prior to UPLC-MS and CE-MS analysis.
158
In order to evaluate the optimal solvent extraction condition to suit multiple
159
analytical platforms a mixture design study was performed. A total of 13 F.
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hepatica worms (~400 mg total) were ground together in liquid nitrogen using
161
a mortar and pestle. Samples of the ground tissue (~30 mg) were transferred
162
into separate Eppendorf tubes and 1 mL of a given proportion of cooled
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solvent/solution (4°C) was added to the tissue as follows: (1) = 1000A, (2) =
164
1000B, (3) = 100B + 900C, (4) = 500A + 500B, (5) = 500A + 500C, (6) = 500B
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+ 500C, (7) = 750A + 250B, (8) = 250A + 750B, (9) = 250B + 750C, (10) =
166
700A + 150B + 150C, (11) = 150A + 700B + 150C, (12) = 150A + 150B +
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700C, and (13) = 333A + 333B + 333C, where A = 80% methanol, B = 20%
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methanol and C = pure chloroform. Samples were vortexed for 1 min,
169
centrifuged (18,894 g; 5 min) and the upper aqueous phases were transferred
170
into new separate Eppendorf tubes. The same amount of the solvent mixture
171
was added to the remaining pelleted biomass and the extraction procedure
172
repeated. The aqueous phase was again harvested and combined with the
173
previous extract into a single Eppendorf tube. Final volumes were 2 mL after
174
addition of 80% methanol. The samples were vortexed again and divided into
175
equal aliquots of 200 µL each for UPLC-MS, CE-MS analysis and a backup
176
sample. The aqueous extracts were dried overnight at 45°C under vacuum.
177
The organic phase was collected and stored at -40°C but was not analyzed
178
further here, since the aqueous phase gave information relating to both the
179
low molecular weight components and lipids.
180
The dried aliquots for UPLC-MS and CE-MS were dissolved in 200 µL of
181
50% methanol and 20% methanol, respectively, vortexed for 20 s and
182
subsequently sonicated for 5 min. A volume of 120 µL was transferred either
183
into the wells of a 96-well plate (Waters, Hertfordshire, U.K.) for UPLC-MS or
184
to the CE-MS sample vials (Agilent Technologies UK Ltd, Edinburgh, U.K.). A
185
quality control (QC) sample pool was prepared by mixing 5 µL of each
186
aqueous extract sample in a separate Eppendorf tube. At the beginning of
187
each of the chromatographic/electrophoretic runs, 5 injections from the QC
188
sample pool were made; further QC injections were made after every 5
189
samples throughout the run, in order to assess repeatability and platform
190
stability.
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Instrumentation and data acquisition. All extracts were analyzed on a
192
UPLC system (UPLC Acquity, Waters Ltd., Elstree, U.K.) coupled online via
193
electrospray ionization to a Q-ToF Premier mass spectrometer (Waters MS
194
Technologies Ltd., Manchester, U.K.) using both a Waters Acquity UPLC BEH
195
C18 column (1.8 µm, 2.1 x 100 mm) at 50°C and a Waters Acquity HILIC BEH
196
column (1.7 µm, 2.1 x 100 mm) at 40°C, operated under gradient elution, as
197
follows. For C18: A = 0.1% formic acid in water, B = 0.1% formic acid in
198
methanol, under flow rate of 0.4 mL/min. Gradient elution: 0-2 min, 99.9%
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A:0.10% B; 6 min, 75% A:25% B; 10 min, 20% A:80% B, 12 min, 10% A:90%
200
B, 21-23 min, 0.10% A:99.9% B, 24-26 min: 99.9% A:0.10% B. For HILIC: A
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= 95% acetonitrile: 5% 200 mmol/L ammonium acetate, containing a total of
202
0.1% formic acid; B = 50% acetonitrile: 50% 20 mmol/L ammonium acetate,
203
containing a total of 0.1% formic acid, under flow rate of 1.4 mL/min. Strong
204
wash solvent was 5% acetonitrile whereas the weak wash solvent was 95%
205
acetonitrile. Gradient elution: 0-1 min, 99% A:1% B; 12 min, 100% B; 12.1-15
206
min, 99% A:1% B.
207
Other chromatographic conditions common to both modes include the
208
temperature of the autosampler compartment (4°C), the injection volume (5
209
µL) and the injection loop option (partial loop with needle overfill). Capillary
210
voltage was 3,200 V (positive ionization) and 2,400 V (negative ionization),
211
and the sample cone voltage was maintained at 35 V. The desolvation
212
temperature was set to 350°C and the source temperature to 120°C, and
213
cone gas flow and desolvation gas flow were maintained at 25 L/h and 900
214
L/h, respectively. The Q-ToF Premier was operated in V optics mode, with a
215
data acquisition rate of 0.2 s and a 0.01 s interscan delay. Leucine enkephalin
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(m/z 556.2771) was used as lockmass whereby a solution of 200 pg/µL in
217
50% acetonitrile was infused into the instrument at a rate of 3 µL/min via an
218
auxiliary sprayer. Data were collected in centroid mode with a scan range of
219
50 – 1000 m/z, with lockmass scans collected every 15 s and averaged over 3
220
scans to perform mass correction.
221
CE-MS
analysis
was
performed
on
an
Agilent
7100
capillary
222
electrophoresis system coupled to an Agilent 6224 Accurate-Mass time-of-
223
flight mass spectrometer (Agilent Technologies, Waldbronn, Germany) by
224
means of a coaxial spray needle configured to an electrospray ionization
225
source. A fused-silica capillary (Composite Metal Services, Hallow, U.K.) with
226
dimensions 50 µm internal diameter, 375 µm outer diameter and 65 cm total
227
length was used as separation device for the positive ionization mode. New
228
fused-silica capillaries were conditioned for 30 min with 1 mol/L NaOH at 1
229
bar pressure followed by 10 min deionized water and 30 min background
230
electrolyte (BGE) composed of 0.80 mol/L formic acid at pH 1.8 containing
231
20% methanol. Before analysis, the capillary was conditioned by pressure
232
flushes (925 bar) of 1 mol/L NaOH (10 min), 0.10 mol/L NaOH (10 min),
233
deionized water (10 min) and BGE (30 min) at 25 °C. In both cases the
234
capillary was conditioned with the distal end outside of the MS source.
235
Between runs the BGE vials were replenished to a height of 1.5 cm and the
236
capillary was flushed with BGE for 5 min. At the end of the day the capillary
237
was pressure flushed with deionized water (10 min), methanol (10 min) and
238
air (10 min). Samples were injected hydrodynamically (50 mbar for 10 s)
239
followed by injection of BGE (50 mbar, 5 s). The CE system was operated
240
under constant voltage of +30 kV and the cartridge was thermostatized at
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25°C. A sheath liquid (SHL) composed of 70% methanol containing 0.5%
242
formic acid was delivered at a flow rate of 4 µL/min via a 1:100 splitter
243
connected to an isocratic pump (1260 Infinity Series, Agilent Technologies)
244
running at 400 µL/min. The nebulizer was set to 10 psig at 0.5 min after
245
injection and a flow of heated dry nitrogen gas (150 °C) was maintained at 10
246
L/min. Transfer capillary voltage was 4500 V, the fragmentor was set to 120
247
V, skimmer to 65 V and ion guide octapole to 750 V. The CE unit was
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operated by the 3D-CE ChemStation Rev B.04.03 software and MS data were
249
acquired by the MassHunter WorkStation Acquisition B.02.01 in centroid
250
mode with a data acquisition rate of 5 spectra per second. Purine
251
(C5H4N4; [M+H]+ 121.05087) and HP921 (hexakis (2,2,3,3,-tetrafluoropropoxy)
252
phosphazine; CAS No.: 58943-98-9; C18H18O6N3P3F24; [M+H]+ 922.00980)
253
were used as reference masses whereby a solution containing 10 mL water,
254
90 mL methanol, 100 µL formic acid, 1600 µL of 5 mmol/L purine and 600 µL
255
of 2.5 mmol/L phosphazine derivative listed above (HP 0921) were infused
256
directly into the ion source. The reference mass spectra were collected
257
simultaneously with the analytical data and used for accurate mass correction.
258
Data processing and peak identification. The raw data files derived from
259
UPLC-MS and CE-MS acquisition were preprocessed using the publically
260
available XCMS software (version 1.24.1).27 Isotope peaks, fragments and
261
adducts were treated as separate features. For the dataset containing the
262
extracts from individual flukes, the samples were grouped according to the
263
liver they were extracted from, whereby QC samples were treated as a
264
separate group. Default settings were employed in XCMS with the exception
265
of width of overlapping m/z slices used for creating peak density
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chromatograms and grouping peaks across samples (mzwid=0.025),
267
bandwidth for the grouping performed after retention time correction (bw=10
268
s) and the degree of smoothing for local polynomial regression fitting
269
(span=0.3). A table of time aligned detected features containing the retention
270
times, m/z ratio and intensities of each sample was then obtained. Median
271
normalization was performed using an in-house developed R script (Dr. K.
272
Veselkov,
273
normalization. Output tables containing information on the average retention
274
time and average m/z were also prepared as data input of an in-house
275
developed MATLAB script (Dr. P. Masson, Imperial College London) that
276
allowed searching of candidate metabolites in an in-house built UPLC-MS
277
database within specified errors; in this work 0.05 Da for m/z and 1 min for
278
retention time were used to start with. A set of candidate compounds was
279
then generated as a first pass and errors on the m/z and retention time
280
assignments were provided for each compound. Compounds with m/z and
281
retention time differing by more than 20 ppm and 0.5 min, respectively, were
282
disregarded. Eventually, a mass chromatogram of the corresponding
283
authentic standard and the sample were acquired and the peak submitted to
284
fragmentation in a MS/MS experiment. If the fragmentation pattern of both
285
standard and sample peak matched, the peak was then assigned to the
286
alleged compound with improved reliability.
Imperial
College
London),28
followed
by
tissue
weight
287
288
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RESULTS AND DISCUSSION
290
Analytical Platform Selectivity for F. hepatica Metabolites. MS has the
291
necessary sensitivity to assess low abundance molecular species in biological
292
matrices. When combined with appropriately designed extraction methods
293
and any gas or liquid based separation technique, MS is capable of analyzing
294
a plethora of metabolites of different chemical classes. Moreover, the variety
295
of separation modes, ionization schemes and mass analyzers qualifies the
296
use of hyphenated MS platforms as a resourceful approach to metabolic
297
profiling.29,30,31,32
298
We compared individual F. hepatica extracts at 80% methanol prepared
299
from flukes obtained from 2 different cow livers using analytical conditions and
300
instrumental parameters provided in previous work for UPLC-MS,18,33 and a
301
method developed specifically for CE-MS.
302
Typical base peak mass chromatograms acquired using ESI+ and ESI-,
303
respectively, on the C18 column are depicted in Figures 1A and S-1A. As
304
expected, many polar components exhibited poor retention, co-eluting close
305
to the column dead volume. Therefore, assignments for peaks eluting by less
306
than 0.94 min (k22). A polyethylene glycol peak envelope (~8 min) was observed in
329
the mass chromatogram but was also detected in the pure water and
330
therefore attributed to contamination.
331
Similar features were observed in the negative ionization C18 mass
332
chromatogram of Figure S-1A. In addition to phenylalanine and tryptophan, a
333
few carboxylic acids (methylmalonic and pantothenic acids), adenosine
334
monophosphate (AMP) and inosine compose the early eluting polar
335
compounds, whereas in the cholic acid region, deoxycholic acid was further
336
detected. Similar compounds were identified in the phospholipid region for
337
both positive and negative ionization modes, although the monosubstituted
338
glycerophosphocholine derivatives exhibited much higher ionization yields in
339
negative ion mode when compared to the disubstituted phosphatidylcholine
340
homologs, in direct contrast to the observation made from the positive
341
ionization mode data.
342
As the results of Figures 1A and S-1A testify, the choice of C18 columns for
343
UPLC-MS studies allows immediate visualisation of nonpolar and moderately
344
polar compounds. However, its use discriminates instantly against highly polar
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compounds. Recently, HILIC has been offered as a powerful alternative to
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compensate for the poor RPLC retention of highly polar compounds,
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ubiquitous components of many biological fluids.34,35,36 HILIC is a form of
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normal-phase liquid chromatography (NPLC) in the sense that uses polar
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stationary phases, usually water-rich layers immobilized onto silica particles.
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However, unlike NPLC, HILIC employs aqueous mobile phases; during
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Analytical Chemistry
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gradient elution, the polarity is increased from a low organic content to a high
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water content mobile-phase in order to promote the elution of polar
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compounds. HILIC columns have found application in numerous areas,
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including metabolic profiling of various pathologies, but as yet a systematic
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evaluation of their performance as a metabolic profiling tool is lacking.37,38
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Typical base peak mass chromatograms are shown in Figures 1B and S-
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1B, acquired under positive and negative ionization modes, respectively, on
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the HILIC column. In the positive ionization mode (Figure 1B), prominent
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peaks from a few quaternary ammonium compounds (choline and betaine)
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and proline (a cyclic aminoacid) were bracketed by moderately retained
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phospholipids (4
