Download Mass spectrometric analysis of tricarboxylic acid cycle

University of South Bohemia in České Budějovice
Faculty of Science
Mass spectrometric analysis of tricarboxylic acid cycle
metabolites
Bachelor Thesis
Michal Kamenický
Supervisor: RNDr. Petr Šimek CSc.
Guidance: Mgr. Lucie Řimnáčová
České Budějovice 2012
Kamenický, M., 2012: Mass spectrometric analysis of tricarboxylic acid cycle metabolites.
Bc. Thesis, in English. – 33 p., Faculty of Science, University of South Bohemia, České
Budějovice, Czech Republic.
Annotation:
Tricarboxylic acid (TCA) cycle is a complex metabolic hub maintained and coordinated with
other metabolic pathways. Comprehensive determination of key metabolites involved in the
TCA cycle is therefore of great importance in biological and biochemical research. In this study,
two
sample
preparation
approaches
were
examined.
Silylation
and
in
situ
derivatization/extraction with ethyl chloroformate/ethanol/pyridine aqueous medium were
tested. The ethyl chloroformate-based approach has been found as highly perspective.
I hereby declare that I have worked on my bachelor thesis independently and used only the
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I hereby declare that, in accordance with Article 47b of Act No. 111/1998 in the valid wording, I
agree with the publication of my bachelor thesis in full to be kept in the Faculty of Science
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Further, I agree to the electronic publication of the comments of my supervisor and thesis
opponents and the record of the proceedings and results of the thesis defense in accordance with
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Date ...............................
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I
Acknowledgement
I would like to thank RNDr. Petr Šimek CSc. for motivating me and giving me the opportunity
to do this work at the Laboratory of Analytical Biochemistry. Further thanks go to Mgr. Lucie
Řimnáčová and Ing. Helena Zahradníčková Ph.D. for patiently and friendly guiding me through
the practical part of the thesis and also to the whole team for great atmosphere during work. Last
but not least, I want to thank my family, friends and colleagues for supporting me.
This work was financially supported by the Czech Science Foundation, project No. P206/10/240
II
Abstract
Tricarboxylic acid (TCA) cycle is a complex metabolic hub maintained and coordinated with
other metabolic pathways. Altered metabolism in the TCA cycle has serious consequences for
the physiological and metabolic state of each organism and its development. Comprehensive
determination of key metabolites involved in the TCA cycle is therefore of great importance in
biological and biochemical research. In this study, two sample preparation approaches, silylation
and in situ derivatization- extraction with ethyl chloroformate/ethanol/pyridine aqueous medium
were examined for simultaneous gas chromatographic – mass spectrometric analysis of eight
relevant metabolites of the TCA cycle and pyruvic acid. While silylation method was found
laborious and tedious, the latter approach enabled simultaneous GC-MS analysis of eight
metabolites and pyruvate, except unstable oxaloacetate. The arising products provide defined
chromatographic peaks and finger-print electron impact mass spectra enabling the simultaneous
metabolite analysis and their unequivocal identification in less than 15 min. In summary, the
ethyl chloroformate-based approach has been found a method of choice and highly perspective
in future investigations of the TCA cycle in complex biological matrices.
III
Table of Contents
1. Introduction …………………………………………………………………………….……1
1.1. Role of tricarboxylic acid cycle in metabolism………………………………...……1
1.2. How to analyse the intermediates of the TCA cycle……………………………...…4
1.3. Preparation of biological samples with chemical derivatization…………………….4
1.4. Silylation……………………………………………………………………………..5
1.5. Derivatization with alkyl chloroformates……………………………………………6
2. Aim of the thesis…………………………………………………………….…………………8
3. Experimental……………………………………………………………………...……………9
3.1. Reagents and chemicals…………………………………………...…………………9
3.2. Stock solutions……………………………………………………………………….9
3.3. Sample preparation methods…………………………………………………………9
3.3.1. Derivatization with ethyl chloroformate (ECF)………………...………….9
3.3.2. Derivatization with oximation - silylation reagents...……………………10
3.4. Instrumental analysis . .……………………………………………………….……10
3.4.1. GC-MS analysis………………………………..…………………………10
3.4.2. LC-MS analysis…………………………………….…………………….10
3.4.3. GC-MS analysis of the ECF derivatized products……………………….11
3.4.4. LC-MS analysis of the ECF derivatized products……………………….11
3.4.5. GC-MS analysis of the oximation-silylation products. . .…………..……11
4. Results and Discussion…………………………………………………………………….…12
4.1. TCA cycle metabolites derivatized with ECF/EtOH/pyridine/chloroform medium.12
4.1.1. GC-MS investigations……………………………………………………12
4.1.2. LC-MS investigations . .…………………………………..……………..15
4.2. TCA metabolites derivatized with silylation reagents……………………………..17
IV
5. Conclusion………………………………………………………………………...………….19
6. References……………………………………………………………………………………20
7. Appendix 1: Table of analytes………………………………………………..………………23
8. Appendix 2: GC-MS analysis – EI spectra of ECF derivatives……………………………24
9. Appendix 3: LC-MS analysis – ESI positive spectra of ECF derivatives……….………….31
List of Abbreviations
CE
capillary electrophoresis
DCM
dichloromethane
DMF
dimethylformamide
DMSO
dimethyl sulfoxide
ECF
ethyl chloformate
EI
electron impact
ESI
electrospray ionization
EtOH
ethanol
GC
gas chromatography
LC
liquid chromatography
MHA
methylhydroxylamine hydrochloride
MS
mass spectrometry
MTBSTFA
N-tert-Butyldimethylsilyl-N-methyltrifluoroacetamide
MW
molecular weight
RCF
alkyl chloroformate
RT
retention time
TBDMS
tert-Butyldimethylsilyl
TBDMSCl
tert-Butyldimethylchlorosilane
TBDMSIM
1-(tert-Butyldimethylsilyl)imidazole
TCA cycle
tricarboxylic acid cycle
TMS
trimethylsilyl
TMSI
trimethylsilylimidazol
V
1. Introduction
1.1. Role of tricarboxylic acid cycle in metabolism
Tricarboxylic acid (TCA) cycle, also known as citric acid cycle or Krebs cycle, is a central
metabolic hub of the cell, important in energy production and biosynthesis, Fig. 1. It is an
aerobic process and lack of oxygen causes its total or partial inhibition[1]. In prokaryotes the
TCA cycle is located in cytosol, while in eukaryotes the cycle takes place in semi-fluid
mitochondrial matrix. The operation of the cycle is enhanced by association of metabolically
related enzymes into metabolons that facilitate channelling of substrates through selected sets of
enzymes[2]. The semi-fluid character of mitochondrial matrix, folded membranes, proteins, and
RNA and DNA molecules also facilitates kinetic and spatial compartmentation[3].
The oxidation of acetyl-coenzyme A (Ac-CoA) to CO2 is central process in energy metabolism.
It is yielded from catabolism of glucose, fatty acids, and some amino acids. The dominant
source of acetyl-coenzyme A is oxidative decarboxylation of pyruvate catalyzed by pyruvate
dehydrogenase complex (PDH complex) at the end of glycolysis. The acetyl group of the
acetyl-coenzyme A enters the cycle via condensation reaction with oxaloacetate. In the course of
eight oxidation-reduction reactions, the acetyl group is oxidized to two molecules of carbon
dioxide. The carbons in the CO2 molecules are not identical to those entering the cycle in the
form of acetyl group[4]. Energy released at each turn of the cycle is stored in three NADH, one
FADH2 along with one molecule of adenosine triphosphate (ATP). The electrons arising from
the reduced electron carriers are transferred to oxygen and the energy of the electron flow is
fixed in ATP molecules during oxidative phosphorylation. The reactions, metabolites and
products of the TCA cycle are shown in Fig. 1.
1
Fig. 1: Reactions of the TCA cycle. The pink shaded carbon atoms are derived from the acetyl
group of acetyl-coenzyme A. It is impossible to distinguish the carbons in/after succinate,
because symmetry of the molecule. Adapted from [4].
2
The TCA cycle is an amphibolic metabolic pathway: it participates both in catabolic and
anabolic processes. Due to this ambiguity, the cycle serves as source of energy, but also
provides variety of important biosynthetic precursors. For example oxaloacetate is a starting
material for gluconeogenesis and together with α-ketoglutarate also serves as molecular building
block for many amino acids, as well as for purine and pyrimidine nucleotides. Fatty acid
biosynthesis starts via citrate. Succinyl-coenzyme plays an important role in the biosynthesis of
porphyrin rings in heme[4].
The TCA cycle must be maintained and coordinated with other metabolic pathways that enter
and leave this major turntable of the cell metabolism[3, 5]. The processes replenishing
intermediates into the cycle are called anaplerotic reactions (anaplerosis). The opposite process
by which an intermediate in the TCA cycle is removed to prevent its accumulation in the
mitochondrial matrix is called cataplerosis[6].
Reversible carboxylation of pyruvate with CO2 to oxaloacetate is a notable example of
anaplerosis. The reaction is catalysed by pyruvate carboxylase and mostly takes place in liver
and kidney of mammals. During starvation, amino acids also serve as source of energy and
some of them they enter the cycle via the analoplerotic reactions. Under normal conditions,
balance between anaplerosis and cataplerosis facilitates to hold concentrations of intermediates
in the cycle at almost constant level and maintains optimal activity of the cycle[4]. The regulation
of anaplerosis and cataplerosis depends upon the metabolic and physiological stage of the
individual and its specific organs/tissues involved. The importance of the anaplerotic and
catapletoric reactions further underlines their role that both pathways play in the regulation of
glucose, nonessential amino acid and fatty acid metabolism[6, 7].
Observations of the altered metabolism in the TCA cycle and association of anaplerotic and
cataplerotic metabolic pathways has been subjected to intense research, because of key role of
these processes in organism and disease development. Consequently, sensitive and efficient
analytical methods are highly desirable for simultaneous analysis of acidic metabolites involved
in the TCA cycle.
3
1.2. How to analyse the intermediates of the TCA cycle
The intermediates are present at various concentrations in a complex biological matrix, inside
the cell, in the cell tissues or body fluids. The matrix represents a complex, buffered aqueous
biological environment with a number of prospective components involving inorganic ions,
macromolecules such as lipoproteins, proteins, glycans and organels and membrane structures
that may interfere in the metabolite analysis.
Various analytical methods have been investigated for the simultaneous analysis of the
metabolites involved in the TCA cycle at the same time, using an automated electrochemical
analyser[8], enzymatic assay kit available for citrate, isocitrate, succinate, malate, oxaloacetate
and 2-ketoglutarate[9], by liquid chromatography with ultraviolet (UV) detection[10] or
fluorometric detection[11], by ion-exchange chromatography coupled to mass spectrometry (LCMS) [12] by capillary electrophoresis coupled to mass spectrometry (CE-MS)[13,14] and by gas
chromatography coupled to mass spectrometry (GC-MS) upon prior derivatization of analytes
with silylation reagents or alkyl chloroformates. For the simultaneous assay of the acidic
metabolites the GC-MS technique has been most frequently applied. Its sample preparation
always requires a derivatization step involving blockage of protic functional groups[15]. In this
study, GC-MS methodology was preferred for investigations of simultaneous analysis of the
TCA cycle intermediates. For the metabolites investigated in the study see Appendix 1.
1.3. Preparation of biological samples with chemical derivatization
Sample preparation is an essential step prior to analysis of small molecule metabolites in a
complex biological matrix. The preparation usually involves various extraction procedures with
respect to the chemical structure and thus polarity of the targeted analytes. Liquid-liquid
extraction (LLE) and solid phase extraction (SPE) represent most common strategies for these
purposes. However, acidic metabolites of the TCA cycle are small molecules possessing mostly
carboxylic, hydroxyl- and keto- groups that are difficult to analyse simultaneously. With this
respect, an efficient separation system and mass spectrometer as a detector have been most
appropriate, because enable both unequivocal identification as well robust and cost-effective
quantitation of metabolites. In addition to LC-MS[11-12] and CE-MS methods[13-14], GC-MS has
been more accessible technique requiring only a routine instrumentation for analytical
4
measurements of acidic analytes. However, chemical derivatization of acids is an essential step
in this case and relies mainly on silylation[16-18] or derivatization with alkyl chloroformates[19-21].
Derivatization was introduced into analytical chemistry to obtain desired product of the analyte
with optimal properties via chemical reaction proceeding between the original sample and a
derivatization reagent. Specific derivatization reactions can be performed before the
chromatographic separation (pre-column), during (on-column) and between the separation and
introduction of analyte into a detector (post-column)[22].
In the field of GC-MS analysis, chemical derivatization enables to increase volatility,
temperature stability a improve separation properties of the analytes. Low volatility is caused
by high molecular weight of the analyte, but more often by the presence of polar protic groups
(-COOH, OH, -NH, and -SH) in the structure resulting in the strong intermolecular interactions
that deteriorate the GC separation process [23, 24].
1.4. Silylation
Acidic metabolites have mostly been treated with the silylation reagents, the most common are
summarized in Table 1.
Silylation is one of the most versatile derivatization techniques used in gas chromatography.
Silyl derivatives are formed according to scheme shown in Fig. 2.
The reaction with trimethylsilyl group was used as example. The –COOH, -OH, -SH, and –NH
groups are the protic target undergoing the derivatization reaction. The arising derivatives
exhibit enhanced volatility and thermal stability. Their polarity is decreased.
Fig. 2: A scheme of the trimethylsilyl derivatization reaction
Nowadays, silylation reagents – donors of the trimethylsilyl (TMS) group and a bulkier
tert-butyldimethylsilyl (TBDMS) group have been used. The derivatives containing bulkier
5
groups are generally more stable, but the lower reactivity is a disadvantage of the reagents
possessing the TBDMS group. Abilities of different functional groups to react with a silylation
reagent
follow
the
order:
alcoholic
hydroxyl > phenolic
hydroxyl > carboxyl
>
amine > amide[23]. The reactivity of a particular reagent toward each compound class is also
influenced by the steric hindrance of their functional groups. The primary alcohol is the most
reactive one, whereas the tertiary alcohol is the least reactive. The order is similar in case of
amines: primary group is silylated much easier than the secondary amine. Unprotected keto
groups form hydrolytically and thermally unstable keto-enol derivatives. In many instances the
keto groups are therefore protected by formation of an oxime or O-alkyloxime[25].
The silylated derivatives are sensitive to hydrolysis and thus residues of water have carefully to
be removed from a sample before the reaction with a silylation reagent. If it is not possible,
excess of the reagent can be added and moisture is removed from the sample by hydrolysis of of
water residues with the silylation reagent. Reagents containing sterically hindered groups such
as TBDMS can alternatively be employed. Silylation reactions are typically carried out in
aprotic solvents such as pyridine, dimethylformamide (DMF), dimethyl sulphoxide (DMSO),
tetrahydrofuran (THF) and acetonitrile. In some cases silylation reagent itself can be used as
suitable solvent[25]. The reaction time is in (minutes - hours) and temperature (25 °C - 100 °C or
higher) of silylation reaction varies depending on the analyte structure and the reactivity of the
reagent.
6
Table 1: List of common derivatization reagents used in GC-MS of acidic metabolites
Silylation reagents
1-(Trimethylsilyl)imidazole (TMSI)
N-tert-Butyldimethylsilyl-N-methyltrifluoroacetamide
(MTBSTFA)
N-tert-Butyldimethylsilyl-N-methyltrifluoroacetamide
+ 1% tert-Butyldimethylchlorosilane,
(MTBSTFA + 1% TBDMSCl)
Derivatization with chloroformates
Ethyl chloroformate (ECF)
Heptafluorobutyl chloroformate (HFBCF)
1.5. Derivatization with alkyl chloroformates
In contrast to silylation, derivatization with alkyl chloroformates (RCF) proceeds directly in an
aqueous medium, in situ[19-21], typically in the presence of the corresponding alcohol and under
pyridine catalysis.
Carboxyl, hydroxyl, thiol and amino groups thus can simultaneously be protected according to
schemes shown in Fig. 2, where reactions with phenol (yielding the carbonate) and glycine
(providing the corresponding ester and carbamate) are used as examples.
7
Fig. 3: Scheme of phenol and glycine derivatization with an alkyl chloroformate (RCF)
The arising derivatives are much less polar and easily extractable into an immiscible organic
phase. Furthermore, the derivatives obtained with alkyl chloroformates are also amenable to
LC-MS analysis[26]. The derivatization reaction is very fast (5 min) and cost effective.
2. Aim of the thesis

to summarized current knowledge about TCA acid cycle

to found suitable method for analysis of metabolites involved in TCA cycle
8
3. Experimental
3.1. Reagents and chemicals
Ethyl chloformate (ECF), dimethylformamide (anhydrous, DMF), pyridine (anhydrous),
methylhydroxylamine hydrochloride (MHA), ammonium formate, potassium hydroxide, and
citric, cis-aconitic, fumaric, isocitric, α-ketoglutaric, malic, oxaloacetic, pyruvic and
hydrochloric (37 %)
Silylation
reagents,
acid were purchased from Sigma Aldrich (Praha, Czech Republic).
trimethylimidazol
(TMSI),
1-(tert-butyldimethylsilyl)imidazole
(TBDMSIM) , N-tert-butyldimethylsilyl-N-methyltrifluoroacetamide (MTBSTFA), and N-tertButyldimethylsilyl-N-methyltrifluoroacetamide
+
1%
tert-butyldimethylchlorosilane
(MTBSTFA + 1 % TBDMSCl), were also supplied by Sigma-Aldrich (Praha, Czech Republic).
Ethanol, dichloromethane (DCM), isooctane, and chloroform were purchased from Merck.
Methanol was purchased from Fisher Scientific (Pardubice, Czech Republic).
3.2. Stock solutions
10 mM (10 µmol/mL) stock aqueous solution of each examined acid was prepared. The solution
containing all examined acids was mixed from the stock solutions to the final concentration
1 mM (1 µmol/mL) of each acid.
3.3. Sample preparation methods
3.3.1. Derivatization with ethyl chloroformate (ECF)
Reactions were carried out in glass tubes 6 × 50 mm without any closures. Aliquot of a sample
stock solution was used and filled up with water to 100 µL. Ethanol - pyridine mixture (75 µL,
4:1, v/v) and the same volume of chloroform – ECF (9:1, v/v) were vortexed with the sample
solution to create emulsion. Then, 75 µL of 1.5 M NaOH were added for pH adjustment and the
content was vortexed. An aliquot of chloroform – ECF (75 µL, 9:1, v/v) was again added,
followed by vortexing and centrifugation. The final mixture was treated with 75 µL of 3 M HCl,
properly mixed and centrifuged.
For GC-MS analysis, 50 µl of the sample extract was taken from the bottom organic phase,
transferred into a 1.1 ml autosampler vial and 0,5 µl aliquot was injected into an GC injection
port of the GS-MS spectrometer. Another 30 µL aliquot of the bottom organic layer was
9
transferred into another vial and carefully evaporated to dryness under a mild stream of N2 at
room temperature. The residue was immediately dissolved in 60 µL of a mobile phase and
analysed by LC-MS.
3.3.2 Derivatization with oximation - silylation reagents
The derivatization procedure was performed in thick-wall glass vials with open-top screw caps
and PTFE/Rubber laminated discs (Supelco, Sigma-Aldrich). An aqueous solution of each
sample was evaporated to dryness with a 100 µL dichloromethane by a mild stream of nitrogen.
The portion of DCM was added in excess to facilitate evaporation of moisture from the sample.
The oximation reaction step was performed with 25 µL MHA solution (fresh, 20 mg MHA in
1 mL pyridine) in 30 µL of dried dimethylformamide. The content was mixed and heated at
80°C in an oven for 30 minutes.
The subsequent silylation step was accomplished with addition of 70 µL of dried dimethylformamide and 30 µL of silylation reagent were added to the sample (cooled to room
temperature). The content was vortexed for 5 s. Then the mixture was incubated at 80°C for 30
minutes in an oven and then cooled to room temperature. Finally, 150 µL of isooctane was
added, followed by proper vortexing. After separation of two immiscible layers, the upper
organic layer extract was withdrawn, transferred in an autosampler vial and analysed by
GS-MS.
3.4. Instrumental analysis
3.4.1. GC-MS analysis
GC-MS analysis was performed using programmable temperature vaporizing injector connected
to a ThermoFisher Scientific Trace GC Ultra and Trace DSQ single quadrupole mass
spectrometer equipped with EI ion source (all Thermo Scientific, USA). Xcalibur 2.1 software
(Thermo Scientific, USA) was used for GC-MS system control, data acquisition and data
processing.
3.4.2. LC-MS analysis
LC-MS analysis was carried out on a linear ion trap mass spectrometer LTQ XL (Thermo
Scientifics, USA) equipped with an electrospray ion source and connected to an HTC PAL
10
system autosampler (CTC Analytics, Switzerland) and Rheos Allergo pump (Flux Instruments,
Switzerland). Xcalibur 2.1 software (Thermo Scientific, USA) was used for LC-MS system
control, data acquisition and data processing.
3.4.3. GC-MS analysis of the ECF derivatized products
A 0.5 µL aliquot was injected in the splitless mode (closed for 0.7 min, split flow: 50 mL/min)
and the injector was kept at 250 °C. Properties of the used GC-columns were following:
TR-50MS, 30 m × 0.25 mm i.d., 0.25 µm film thickness (Thermo Scientifics, USA) and
VF-17MS, 30 m × 0.25 mm, i.d. 0.25 µm (Agilent, USA). The oven was held at 45 °C for
1.2 minute, raised at 16 °C/min until 330 °C and held for 2 min. Helium was used as carrier gas
with constant flow rate 1.1 mL/min. The ion source was set to 230 °C and the MS transfer line
was held at 250 °C. Detection employed EI mode in full scan regime (40-500 Da).
3.4.4. LC-MS analysis of the ECF derivatized products
The injection volume was set to 5 µL and a column was kept at 35 °C. LC column Kinetex C18,
150 mm × 2.1 mm, 2.6 µm (Phenomenex) was used to achieved a separation with mobile phase
consisting of methanol (A) and water (B), both enriched with 5 mM ammonium formate. The
gradient elution was as follows: A/B = 0 min : 30/70, 12 min : 100/0. The flow rate was set to
200 µL/min. The following parameters were used for ESI: capillary temperature of 200 °C and
vaporizer temperature of 150 °C, source voltage of 4 kV for positive and of 3 kV for negative
ionization modes, capillary voltage of 40 V for positive ionization mode and – 40 V for negative
ionization mode. Nitrogen was used as the desolvation-declustering gas.
3.4.5. GC-MS analysis of the oximation-silylation products
A 1 µL of the sample extract aliquot was injected in splitless mode (closed for 0.7 min, split
flow: 20 mL/min) and the injector was kept at 220 °C. Properties of the used GC-column were
following: VF-17MS, 30 m × 0.25 mm, i.d. 0.25 µm (Agilent, USA). The oven was held at 40
°C for 1 min, than raised at 5 °C/min until 60 °C and subsequently ramped to 302 °C with rate
12 °C/min and held for 2 min. Helium was used as carrier gas with constant flow rate
1.1 mL/min. The ion source was set to 200 °C and the MS transfer line was held at 250 °C.
Detection employed EI mode in full scan regime (50-750 Da).
11
4. Results and Discussion
4.1. TCA cycle metabolites derivatized with ECF/EtOH/pyridine/chloroform medium
4.1.1. GC-MS investigations
The metabolites were treated with ECF. The derivatized products were extracted into an organic
layer and then separated on a fused capillary column. A typical extracted chromatogram of a
standard mixture obtained by GC-MS analysis is presented in Fig. 4. The retention time and
three most abundant m/z signals of each derivative are summarized in Table 2.
3
100
10
90
80
Relative Abundance
70
8
60
1
50
4
2
40
11
30
5
9
6
7
13
20
10
12
0
4
5
6
7
8
9
10
11
12
13
14
15
Time (min)
Fig. 4: GC-MS chromatogram showing separation of analytes on a TR-50MS column
(ThermoScientific, 30 m × 0.25 mm, 0.25 µm film thickness) after treatment with ECF. 1 =
pyruvic acid, 2 = fumaric acid, 3 = succinic acid, 4 = maleic acid, 5 = α-ketoglutaric acid (1),
6 = α-ketoglutaric acid (2), 7 = citric acid (1), 8 = malic acid, 9 = cis-aconitic acid, 10 = citric
acid (2), 11 = isocitric acid (1), 12 = citric acid (3), 13 = isocitric acid (2)
12
Table 2: GC-MS analysis; retention times and three most abundant m/z signals of detected
analytes after derivatization with ECF.
diagnostic m/z ions (% of rel. abundance)a
Analyte
RT
m/z (100)
m/z
m/z
4.46
43
42 (6)
Pyruvic acid
7.87
127
99 (63)
Fumaric acid
8.04
101
129 (62)
Succinic acid
8.24
99
127 (27)
Maleic acid
10.03
101
129 (51)
α-Ketoglutaric acid (1)
10.27
101
129 (66)
α-Ketoglutaric acid (2)
11.20
157
115 (93)
Citric acid (1)
11.64
71
117 (65)
Malic acid
11.90
112
212 (62)
cis-Aconitic acid
12.17
157
115 (35)
Citric acid (2)
12.56
129
157 (90)
Isocitric acid (1)
13.93
157
115 (57)
Citric acid (3)
14.25
157
129 (87)
Isocitric acid (2)
a
Diagnostic m/z ions suitable for identification involve the most intensive m/z
other 2 fragment ions.
45 (6)
126 (37)
55 (24)
126 (17)
55 (26)
55 (27)
43 (57)
89 (48)
213 (55)
203 (17)
101 (83)
213 (49)
101 (44)
(100 %) and
For the EI spectrum of each particular detected metabolite derivative see Appendix 2.
Pyruvic acid and all organic acids participated in the TCA cycle were clearly detected, except
oxaloacetic acid. The oxaloacetic acid derivative was not detected in the GC-MS
chromatograms although various reaction, extraction, and chromatographic conditions were
examined with freshly prepared aqueous standard solutions. This is not surprising, because the
intermediate is known to be very unstable and easily decarboxylates to pyruvate [10, 16].
Other seven acidic metabolites of the TCA cycle and pyruvic acid provide well defined
derivatization products by their retention and fingerprint-type EI mass spectra. They are also
searchable in commercially available mass spectral libraries such as NIST 2.0 installed on the
used GC-MS spectrometer.
ECF is a highly reactive species, which efficiently esterifies carboxylic group in aqueous
environment in seconds. Nevertheless, in sterically hindered structures, such as citric acid, the
reaction route results in 2-4 products, which were observed on the investigated GC-MS
chromatograms. Thus treatment of citric, isocitric, and α-ketoglutaric acids provided four, three
and two products, respectively. Refer also to Table 2 and also their EI spectra in the Appendix 2.
13
In addition to the supposed tri-, di-esters forms, OH group is converted to the O-ethoxycarbonyl
derivative. The further peaks in the (iso)citric acids represent the derivatives, where the
sterically hindered hydroxyl group is not transformed to carbonate moiety or one of the
neighbouring sterically hindered carboxyl groups remains untouched.
However, the structural elucidation has not definitively been solved yet and will be a subject of
further study. Dehydratation of citric acid to cis-aconitic acid structure was also observed to a
minor extent. The chromatogram of citric acid derivatives is shown in Fig. 5.
14.03
100
90
80
Relative Abundance
70
13.67
60
50
40
30
12.77
20
16.35
10
0
12.5
13.0
13.5
14.0
14.5
15.0
15.5
16.0
16.5
Time (min)
Fig. 5: GC-MS chromatogram of citric acid derivatives; column VF-17MS (30 m × 0.25 mm,
0.25 µm film thickness). 12.77 = citric acid (1), 13.67 = cis-aconitic acid, 14.03 = citric acid (2),
and 16.35 = citric acid (3).
Interestingly, fumaric acid provided two peaks. According to their EI mass spectra, the
intermediate possessing a double bond is isomerized partly into the cis-izomer - maleic acid
14
during the derivatization reaction. The chromatogram of fumaric acid derivatives is shown in
Fig. 6.
8.14
100
90
80
Relative Abundance
70
7.76
60
50
40
30
20
10
7.0
7.1
7.2
7.3
7.4
7.5
7.6
7.7
7.8
Time (min)
7.9
8.0
8.1
8.2
8.3
8.4
8.5
Fig. 6: GC-MS chromatogram of the detected fumaric acid derivatives; column TR-50MS (30 m
× 0.25 mm, 0.25 µm film thickness). 7.76 = fumaric acid, 8.14 = maleic acid
4.1.2. LC-MS investigations
In order to confirm the structures arising from the RCF-mediated reaction, the derivatized
products were also investigated by LC-MS analysis. The hydroxy- and/or oxycarbonyl ethyl
esters of the studied acids are very weak bases and thus not efficient proton acceptors during
electrospray ionization. As a result, only a part of them, particularly those that contain hydroxyl
group or double bond, were ionized with sufficient efficiency. The detected analytes possess
principal [M + NH4]+ signals on LC-MS chromatogram owing to the presence of ammonium
formate buffer in the mobile phase. The LC-MS chromatogram of the detected metabolites is
shown in Fig. 7.
15
7.85
100
90
80
Relative Abundance
70
60
9.52
50
9.22
7.06
40
30
20
10
6.0
6.5
7.0
7.5
8.0
Time (min)
8.5
9.0
9.5
10.0
Fig. 7: LC-MS chromatogram showing separation of analytes on column Kinetex C18 (150
mm × 2.1 mm, 2.6 µm) after treatment with ECF. 7.06 = citric acid (1), 7.85 = malic acid,
9.22 = isocitric acid, 9.52 = cis-acinitic acid, 9.55 = citric acid (2) – coeluted with 9.52. 10 nmol
of each.
Retention times, observed [M + NH4]+ ions and calculated molecular weights (MW) of the
detected analytes are summarized in the Table 3.
Table 3: LC-MS analysis; retention times, observed [M + NH4]+
molecular weight of detected analytes after derivatization with ECF.
Analyte
+
ions and the estimated
RT [min]
[M + NH4]
Citric acid (1)
7.06
294
276
Malic acid
7.85
280
262
Isocitric acid
9.22
366
348
cis-Aconitic acid
9.52
276
258
Citric acid (2)
9.55
366
348
16
MW [Da]
As documented in Table 3, four metabolites of the TCA cycle, citrate, isocitrate, malate and
cis-aconitate were detected by LC-MS with positive electrospray detection. Peaks corresponding
to succinate, oxaloacetate, fumarate, α-ketoglutarate and pyruvate were not observed.
For an ESI positive spectrum of each particular detected metabolite derivative, refer to the
Appendix 3.
Citric acid derivatives provided two distinct peaks. Their molecular weight deduced from their
ESI spectrum indicates, that all three carboxyl groups in citrate and isocitrate are successfully
esterified. The detected structures of citrate differ in the treatment of hydroxyl, which remains
untreated at citric acid (1) and is carbonated at citrate (2). The proposed structures of the citric
acid (1) and citric acid (2) are shown in Fig. 8.
Fig. 8: Structures corresponding to peaks citric acid (1) and citric acid (2) in Table 2.
4.2. TCA metabolites derivatized with silylation reagents
The TCA metabolites contain mainly carboxy-, hydroxyl- and keto- functional groups and these
groups can be directly treated with silylation reagents [25] in an non-aqueous environment.
Within the study, we investigated reactions of the nine acidic metabolites with the most
common oximation reagent O-methyl-hydroxylamine and four silylation reagents (TMSI,
TBDMSIM, MTBSTFA, MTBSTFA + 1 % TBDMSCl). However, the obtained results were
much less satisfactory than with the RCF derivatization. The sample preparation is tedious,
because water has to be removed prior to the analyte treatment [23, 25]. However, even under
strictly anhydrous conditions, the reaction yields were low or not obtained at all. Importantly,
the reaction process cannot be coupled with liquid-liquid extraction as in the case of the ECF17
mediated derivatization method. Fouling of GC-MS instrumentation with silylation reagents and
much less clean extracts is also a notable disadvantage [19-20, 23].
We tested liquid-liquid extraction of the silylated metabolites from dimethylformamide into an
isooctane environment. Only derivatives of citric, fumaric and succinic acid were detected after
derivatized with MTBSTFA reagent without prior oximation step. Retention times and three
most abundant m/z signals of detected analytes are summarized in the Table 4.
Table 4: GC-MS; silylation reagent: MTBSTFA, oximation step skipped, column: VF-17 MS
(30 m × 0.25 mm, 0.25 µm film thickness)
Analyte
diagnostic m/z ions (% of rel. abundace)
RT [min]
m/z (100)
m/z
m/z
a
Fumaric acid
9.02
147
73 (74)
289 (21)
Succinic acid
9.11
287
73 (90)
147 (31)
Citric acid
14.94
73
591 (32)
23 (17)
a
Diagnostic m/z ions suitable for identification involve the most intensive m/z (100 %) and
other 2 fragment ions.
The failure of the silylation method and its experimented modifications was probably caused by
still present moisture resulting in hydrolysis of silylation reagent and the examined derivatives
of analytes. The reason of positive response of citric, fumaric and succinic acids could be found
in the fact that tendency to decomposition of derivatives is different for each compound[25].
18
5. Conclusion
A series of eight metabolites involved in the TCA cycle (together with pyruvate) was
investigated for simultaneous analysis by GC-MS in aqueous matrices. Two derivatization
procedures were examined; in-situ derivatization with ethyl chloroformate/ethanol/pyridine
aqueous medium coupled with liquid-liquid extraction of the arising derivatives into an
immiscible chloroform layer and silylation with four TMS and TBDMS reagents in non-aqueous
environment.
The developed ECF-mediated derivatization protocol provides well defined products of all
metabolites under the study, except the unstable oxaloacetate. Although citric, isocitric, and
α-ketoglutaric + fumaric acids provided four, three and two respective products, their peaks are
easily separated and can be used for GC-MS simultaneously enabling thus comprehensive
analysis of the intermediates of the TCA cycle.
In addition, four derivatized metabolites were also detected by positive ESI LC-MS analysis.
Despite the modest ionization efficiency, the LC-MS analysis provided important information
about the molecular weight of the prepared RCF derivatives and confirmed the structures of the
derivatives observed by the GC-MS method.
Experiments with silylation procedures showed that this sample preparation procedure is much
more laborious and requires strictly anhydrous conditions for work.
In summary, the developed ECF-mediated derivatization-extraction method has been found
promising for GC-MS analysis of the acidic metabolites and will be applied to future planned
investigations of the TCA cycle in cell cultures and relevant biological matrices.
19
6. References
[1]
Murray R. K., Granner D. K., Rodwell V.W., Mayes P. A.: Harper’s Biochemistry, 23rd
ed., Appleton & Lange, a Publishing division of Prentice-Hall International Inc., East
Norwalk, Connecticut 1993.
[2]
Briere J.J., Favier J., Gimenez-Roqueplo A. P., Rustin P. (2006) Tricarboxylic acid cycle
dysfunction as a cause of human diseases and tumor formation, Am J Physiol Cell Physiol
291: C1114-C1120.
[3]
Rustin P., Bourgeron T., Parfait B., Chretien D., Munnich A., Rotig A. (1997) Inborn
errors of the Krebs cycle: a group of unusual mitochondrial diseases in human. Biochimica
et Biophysica Acta 1391: 185-197
[4]
Nelson D. L., Cox, M. M.: Lehninger Principles of Biochemistry, 5th ed., W. H. Freeman
and Company, New York, 2008
[5]
Krebs H. A., Johnson W. A. (1937) The role of citric acid in the intermediate metabolism
in animal tissues. Enzymologica 4:148-156.
[6]
Oven O. E., Kalhan S. C., Hanson R. W. (2002) The Key Role of Anaplerosis and
Cataplerosis for Citric Acid Cycle Function. The Journal of Biological Chemistry 277:
30409-30412
[7]
Raimundo N., Baysal B. E., Shadel G. S. (2011) Revisiting the TCA cycle: signalling to
tumor formation. Trend in Molecular Medicine 17: 641-649
[8]
Cheng T, Sudderth J, Yang C, Mullen AR, Jin ES, Mates JM (2011), Pyruvate
carboxylase is required for glutamine-independent growth of tumor cells. PNAS 108:
8674-8679.
[9]
Sigma Aldrich, www.sigma-aldrich.com, catalogue technical bulletins to the particular
metabolites. For instance,
http://www.sigmaaldrich.com/etc/medialib/docs/Sigma/Bulletin/1/mak071bul.Par.0001.Fi
le.tmp/mak071bul.pdf.
[10] Haas J.W., Joyce W.F., Shyu Y.J., et al. (1998) Phosphoric acid-modified amino bonded
stationary phase for high-performance liquid-chromatographic chemical class separation.
Journal of Chromatography 457: 215-226
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[11] Kubota K., Fukushima T., Reiko Y., et al. (2005) Development of an HPLC-fluorescence
determination method for carboxylic acid related to the tricarboxzlic acid czcle as a
metabolome tool. Biomedical Chromatography 19: 788-795
[12] McKinnon W., Pentecost C., Gwyn A. L., et al. (2007) Elevation of anions in
exercise-induced acidosis: a study by ion-exchange chromatography/mass spectrometry.
Biomedical Chromatography 22: 301-305
[13] Hirayama A, Kami K, Sugimoto M, Sugawara M, et al. (2009) Quantitative Metabolome
Profiling of Colon and Stomach Cancer Microenvironment by Capillary Electrophoresis
Time-of-Flight Mass Spectrometry, Cancer Research 69: 4918-4925
[14] Soga T, Ohashi Y, Ueno Y, et al. (2003) Quantitative metgabolomic analysis using capillary
electrophoresis mass spectrometry. Journal of Proteome Research 2: 488-494
[15] Kitson F.G., Larsen B.S., McEwen C.N., Gas Chromatography and Mass Spectrometry. A
Practical Guide. Academic Press, New York 1996
[16] Büscher J.M., Czernik D., Ewald J.C., Sauer U., Zamboni N., (2009) Cross-platform
comparison of methods for quantitative metabolomics of primary metabolism. Analytical
Chemistry 81: 2135-2143
[17] Makoto O., Nishiumi S., Tomoo Y., Shiomi Y., (2011) GC/MS-based profiling of amino
acids and TCA cycle/related molecules in ulcerative colitis. Inflamm. Res. 60: 831-840
[18] Koek M.M., Muilwijk B., van der Werf M.J., Hankemeier T., (2006) Microbial
metabolomics with gas chromatography/mass spectrometry. Analytical Chemistry 78:
1272-1281
[19] Hušek P., Šimek P., (2006) Alkyl chloroformates in sample derivatization strategies for
GC analysis, Review on a decade use of the reagents as esterifying agents. Current
Pharmaceut. Analysis, 2: 23-43.
[20] Šimek P., Hušek, P., Zahradníčková, H. (2008), Simultaneous analysis of biomarkers
related to folate and cobalamin status in serum by gas chromatography – mass
spectrometry. Anal Chem, 80: 5776-5782.
[21] Koštál V., Šimek P., Zahradničková, H., Cimlová, J., Štětina T. (2012), Conversion of a
chill susceptible fruit fly larva to a freeze tolerant organism. PNAS 109: 3270-3274. DOI:
10.1073/pnas.1119986109.
[22] Christian G. D., Analytical Chemistry, 6th ed., Wiley, New York 2004
[23] Knapp D. R., Handbook of analytical derivatization reactions, Wiley, New York 1979
21
[24] Clayden J., Organic chemistry, 2nd ed., Oxford. Univ. Press, Oxford 2012
[25] Blau K., Halket J., Handbook of derivatives for chromatography, 2nd ed., Wiley, New
York 1993
[26] Cimlová J, Kružberská P., Hušek, P. and Šimek, P. (2012), Coupled in situ derivatization–
liquid liquid extraction as a sample preparation strategy for quantitative determination of
urinary biomarker prolyl-4-hydroxyproline by liquid chromatography – tandem mass
spectrometry. J Mass Spectrom 47: 294-302. DOI:10.1002/jms.2952
22
7. Appendix 1: Table of analytes
Table 5: Analytes and their molecular weights, chmical formulas and structures
Name
MW [Da]
Chemical Formula
Chemical Structure
Pyruvic acid
88.06
C3H4O3
Fumaric acid
116.07
C4H4O4
Succinic acid
118.09
C4H6O4
Oxaloacetic acid
132.07
C4H4O5
Malic acid
134.09
C4H6O5
α-ketoglutaric acid
146.10
C5H6O5
cis-Aconitic acid
174.11
C6H6O6
Citric acid
192.12
C6H8O7
Isocitric acid
192.12
C6H8O7
23
8. Appendix 2: GC-MS analysis – EI spectra of ECF derivatives
43
100
90
O
80
O
Relative Abundance
70
60
O
50
40
30
20
52
10
51
61
78
68
0
40
60
80 90
80
111
116
100
125
139
120
154
140
168
160
191 197
180
213
200
228
220
242 252 258
240
260
277 284
280
300
300
317
320
334 342 350
340
360
m/z
Fig. 9: GC-MS analysis, ECF derivatization, EI spectrum - pyruvic acid
127
100
O
90
O
80
Relative Abundance
70
99
O
60
O
50
40
126
30
55
20
54
71
45
10
40
100
128
52
0
82
53
81
98
72
56 70 80 83 97
60
80
125
117
143
101
100
129
120
140
146 157 169
160
186 193
180
207
200
m/z
222
220
240 246 259 273 280
240
260
292 302 316 323 333
280
Fig. 10: GC-MS analysis, ECF derivatization, EI spectrum - fumaric acid
24
300
320
345 353
340
360
101
100
O
90
80
O
O
Relative Abundance
70
129
60
O
50
40
30
55 73
128
20
45
56
102
74
10
100
57
60 72
54
0
40
60
75
82 83
80
130
99
103
100
127
120
131
147
148 163 174
140
160
193
180
210 218
200
m/z
220
234 240 246 260 268
240
260
282 292 302 310
280
300
327 332 347 357
320
340
360
Fig. 11: GC-MS analysis, ECF derivatization, EI spectrum – succinic acid
99
100
90
O
O
80
O
O
Relative Abundance
70
60
50
40
30
127
20
10
126
100
54
45
55
53
0
40
82
71
72
56 69 80
60
80
128
98
97
101
100
125
124
120
129
143
145 154
140
160
172
190 197 207
180
200
m/z
223
220
240
240
259
260
271
283
301
280
300
318 328
320
340 345 358
340
360
Fig. 13: GC-MS analysis, ECF derivatization, EI spectrum - maleic acid (from fumaric acid)
25
101
100
90
80
Relative Abundance
70
60
129
50
40
30
55
73
20
10
45
56
54
0
40
57
74
69
60
83
80
100
97
102
103
100
157
128 130
131
126
120
156 158 169
140
160
180
192 201 209 222
200
m/z
220
241 247
240
260
260
279 285
280
305 315
300
320
333
350 356
340
360
Fig. 14: GC-MS analysis, ECF derivatization, EI spectrum – α-ketoglutaric acid (1), the exact
structure of the derivative undefined
101
100
90
80
129
Relative Abundance
70
60
50
40
30
55 56
73
20
10
45
57
54
100 102
74
99 103
83
72
130
128
157
158
165
0
40
60
80
100
120
140
160
191
180
212 218
200
m/z
220
240 251 260
240
260
276 290 300
280
300
320 331
320
346 353
340
360
Fig. 15: GC-MS analysis, ECF derivatization, EI spectrum – α-ketoglutaric acid (2), the exact
structure of the derivative undefined
26
157
100
115
90
80
Relative Abundance
70
43
60
50
40
30
69
20
114
86
139
129
85
10
0
87
45
56 68
60 70
47
74
60
40
185
158
116
91
110
80
143
117
100
120
155
140
167
160
184 186 196 208
180
200
m/z
223 237 243
220
240
259
280 287
260
280
302 309
300
328 336
320
348 355
340
360
Fig. 16: GC-MS analysis, ECF derivatization, EI spectrum – citric acid (1), the exact structure
of the derivative undefined
71
100
O
90
80
O
Relative Abundance
70
O
O
117
O
60
O
89
50
O
40
30
43
44
55 75
127
99
20
145
116
101
10
144
47
60
54
61
88
87
0
40
60
80
115
104
100
142
120
140
190
173
128
90
146
172
160
217
189 191
180
200
m/z
216 218
220
235
240
257 262
260
275 284
280
Fig. 17: GC-MS analysis, ECF derivatization, EI spectrum – malic acid
27
301
300
317 325 333
320
348
340
359
360
112
100
O
O
90
O
80
O
O
O
Relative Abundance
70
212
139
60
213
50
84
167
40
138 140
30
111
156
20
184
157
185
67
10
113
69
43
85
57
53
128
94
65
95
71
141
214
168
114
155
169
0
40
60
80
100
120
140
160
211
210
186
187
180
200
m/z
215 229
220
242
240
258 261
260
287
280
299
318
334 345
300
320
340
357
360
Fig. 18: GC-MS analysis, ECF derivatization, EI spectrum – cis-aconitic acid
157
100
90
80
O
Relative Abundance
70
O
O
60
O
O
O
OH
50
40
115
30
20
203
43
10
87
56 60
61
55
0
40
60
69
111
84 88
70
89 102
80
100
158
129
116
120
139
155 159
140
160
168
185
180
202 204 213
200
m/z
220
231
243
240
256 267 277
260
293 299
280
Fig. 19: GC-MS analysis, ECF derivatization, EI spectrum – citric acid (2)
28
300
315
331 341 348 359
320
340
360
129
100
157
90
101
80
Relative Abundance
70
60
55
50
85
40
83
30
158
20
73
57
113
130
45
10
54
0
40
82
60
80
185
128
86 99
88
68
58
127
100
120
159
156
131
140
160
184 186
180
202 206
200
m/z
228
220
240
252 259 273 285 293 301
240
260
280
316
300
327 332
320
340
Fig. 20: GC-MS analysis, ECF derivatization, EI spectrum – isocitric acid (1), the exact
structure of the derivative undefined
157
100
90
O
O
O
O
80
Relative Abundance
70
O
O
O
60
115
O
50
O
213
40
185
30
43
139
20
158
85
113
69
10
49
0
40
82
46
88
67
60
81
78
80
167
141
111
130
203
156
116
89
100
184 187
172
154
103
120
140
160
180
214
200
m/z
220
259
230
252
240
268
260
283 299 303
280
Fig. 21: GC-MS analysis, ECF derivatization, EI spectrum – citric acid (3)
29
300
319 327
320
350 356
340
360
356
360
157
100
O
129
90
O
O
80
O
O
70
O
O
60
O
50
O
101
40
30
185
84
55
83 85
57 73
20
128
112 127
113
45
189
139
156
99
10
47
141
167
213
201
158
111
89
68 71
58
203 212
173
155
82
98
190
0
40
60
80
100
120
140
160
229
231
184
180
200
m/z
214
227
232
220
240
303
302
259
275
257
281 290 304 313
270
260
280
300
Fig. 22: GC-MS analysis, ECF derivatization, EI spectrum – isocitric acid (2)
30
320
333
340
352 358
360
9. Appendix 3: LC-MS analysis – ESI positive spectra of ECF derivatives
+
[M+NH4 ]
294
100
90
80
70
Relative Abundance
O
O
O
60
O
O
50
O
OH
40
30
20
10
264
0
100
120
140
160
180
200
220
240
260
277
280
300
320
340
360
380
400
380
400
m/z
Fig. 23: LC-MS analysis, ECF derivatization, ESI positive spectrum – citric acid (1)
+
[M+NH4 ]
280
100
90
80
O
70
Relative Abundance
O
O
O
60
O
O
50
O
40
30
20
10
263
163
0
100
120
140
160
180
200
220
240
260
280
300
320
340
360
m/z
Fig. 24: LC-MS analysis, ECF derivatization, ESI positive spectrum – malic acid
31
+
[M+NH4 ]
366
100
90
O
80
O
O
70
Relative Abundance
O
O
60
O
50
O
O
O
40
30
20
10
349
0
100
120
160
140
180
200
220
240
260
280
300
320
340
360
380
400
380
400
m/z
Fig. 25: LC-MS analysis, ECF derivatization, ESI positive spectrum – isocitric acid
+
[M+NH4 ]
276
100
90
80
O
O
70
Relative Abundance
O
O
O
O
60
50
40
259
30
20
10
213
0
100
120
140
160
180
200
220
240
260
280
300
320
340
360
m/z
Fig. 26: LC-MS analysis, ECF derivatization, ESI positive spectrum – cis-aconitic acid (1)
32
100
90
80
O
O
O
O
Relative Abundance
70
60
O
O
O
50
O
O
40
30
[M+NH4 ]+
366
20
10
0
100
318
260
349
120
140
160
180
200
220
240
260
280
300
320
340
360
m/z
Fig. 27: LC-MS analysis, ECF derivatization, ESI positive spectrum – citric acid (2)
33
380
400