Chromatographic profiling of Pancharishta at different stages of its development using HPTLC,HPLC, GC–MS and UPLC–MS

Pancharishta is the traditional Ayurvedic polyherbal formulation prepared by decoction of plant materials followed by fermentation for preservation and facilitation of extraction due to the production of alcohol. Since the preparation of pancharishta involves various steps. The aim of the current investigation was to carry out comparative metabolomics profiling at different stages of preparation for the understanding impact of different steps and ingredients. A decoction of 21 plant materials are main components in pancharishta formulations followed by fermentation and addition of other ingredients with or without fermentation yielded eight different formulations. The vacuum concentration of pancharishta samples yielded a semisolid mass of different formulations ranging from 8 to 37% w/v. The HPTLC fingerprinting analysis of samples was carried out in butanol: ethanol: 0.5% v/v ammonia (5:4:0.5, v/v/v). Derivatization with anisaldehyde-sulphuric acid showed the presence of two major peaks at R_f 0.29 and 0.35. The peak at R_f 0.29 is intense in a formulation containing 12 extra plant materials. Quantification of gallic acid, ellagic acid, tannic acid, kaemferol and quercetin were carried out on newly developed HPLC method using acetonitrile and 0.5% v/v formic acid with a gradient elution. A significant difference in their content was found in different formulations. Further, polar and nonpolar metabolites of pancharishtha were analyzed using UPLC–MS and GC–MS, respectively. GC–MS profiling results in the identification of 144 metabolites among them 26 are common metabolites at different stages. The UPLC–MS analysis resulted in the tentative identification of 43 metabolites. The results of UPLC–MS and GC–MS analysis were used for multivariate analysis using XLSTAT. Principal Component Analysis plot distributed all samples into four different clusters with two formulations each.     

GC–MS and GC–MS/MS measurement of the cardiovascular risk factor homoarginine in biological samples

l-Homoarginine (hArg) has recently emerged as a novel cardiovascular risk factor and to herald a poor prognosis in heart failure patients. Here, we report on the development and thorough validation of gas chromatography–mass spectrometry (GC–MS) and gas chromatography–tandem mass spectrometry (GC–MS/MS) methods for the quantitative determination of hArg in biological samples, including human plasma, urine and sputum. For plasma and serum samples, ultrafiltrate (10 µL; cutoff, 10 kDa) was used. For urine samples, native urine (10 µL) was used. For sputum, protein precipitation by acetone was performed. hArg is derivatized to its methyl ester tri(N-pentafluoropropionyl) derivative; de novo synthesized trideutero-methyl ester hArg is used as the internal standard (IS). Alternatively, [guanidino-¹⁵N₂]-arginine can be used as an IS. Quantitative analyses were performed after electron-capture negative-ion chemical ionization by selected-ion monitoring in GC–MS and selected-reaction monitoring in GC–MS/MS. We obtained very similar hArg concentrations by GC–MS and GC–MS/MS, suggesting that GC–MS suffices for accurate and precise quantification of hArg in biological samples. In plasma and serum samples of the same subjects very close hArg concentrations were measured. The plasma-to-serum hArg concentration ratio was determined to be 1.12 ± 0.21 (RSD, 19 %), suggesting that blood anticoagulation is not a major preanalytical concern in hArg analysis. In healthy subjects, the creatinine-corrected urinary excretion of hArg varies considerably (0.18 ± 0.22 µmol/mmol, mean ± SD, n = 19) unlike asymmetric dimethylarginine (ADMA, 2.89 ± 0.89 µmol/mmol). In urine, hArg correlated with ADMA (r = 0.475, P = 0.040); in average, subjects excreted in the urine about 17.5 times more ADMA than hArg. In plasma of healthy humans, the concentration of hArg is of the order of 2 µM. hArg may be a low-abundance constituent of human plasma proteins. The GC–MS and GC-MS/MS methods we report in this article are useful to study the physiology and pathology of hArg in experimental and clinical settings.     

Metabolomic and elemental analysis of camel and bovine urine by GC–MS and ICP–MS

Recent studies from the author’s laboratory indicated that camel urine possesses antiplatelet activity and anti-cancer activity which is not present in bovine urine. The objective of this study is to compare the volatile and elemental components of bovine and camel urine using GC–MS and ICP–MS analysis. We are interested to know the component that performs these biological activities. The freeze dried urine was dissolved in dichloromethane and then derivatization process followed by using BSTFA for GC–MS analysis. Thirty different compounds were analyzed by the derivatization process in full scan mode. For ICP–MS analysis twenty eight important elements were analyzed in both bovine and camel urine. The results of GC–MS and ICP–MS analysis showed marked difference in the urinary metabolites. GC–MS evaluation of camel urine finds a lot of products of metabolism like benzene propanoic acid derivatives, fatty acid derivatives, amino acid derivatives, sugars, prostaglandins and canavanine. Several research reports reveal the metabolomics studies on camel urine but none of them completely reported the pharmacology related metabolomics. The present data of GC–MS suggest and support the previous studies and activities related to camel urine.     

Preliminary screening of Houttuynia cordata for biological potential and chemical components using TLC and GC–MS analysis

Journal of Plant Biochemistry and Biotechnology - The objective of the study is to ascertain the biological potential and to identify the bioactive compounds of the four crude extract hexane,...     

Identification of bioactive phytochemical from two Punica species using GC–MS and estimation of antioxidant activity of seed extracts

Punica species are medicinally important plants belonging to the family Lythraceae. The pomegranate is widely reported to exhibit antiviral, antioxidant, anticancer, anti-proliferative activities. In the present study the ethanolic extract of the peel seeds of two species of Punica (Punica granatum and Punica protopunica) were subjected to GC–MS analysis. Twenty-one and 14 compounds were identified in P. granatum and P. protopunica peel seeds, respectively. The main chemical constituents in P. granatum-peel seeds were propanoic acid, benzenedicarboxylic acid, methoxypropionic acid and methyl amine. The corresponding constituents of P. protopunica peel seeds were benzenedicarboxylic acid, benzoic acid and propanoic acid. Moreover, the antioxidant effects of the aqueous ethanolic extracts were estimated in vitro. The two tested extracts contained significantly different phenolic and total flavonoid contents in P. granatum than in P. protopunica. Different in vitro methods of antioxidant activity determination produced varying results. In malondialdehyde (MDA), hydrogen peroxide (H₂O₂) scavenging and 1,1-diphenyl-2-picrylhydrazyl (DPPH) assays, the two peel seed extracts exhibited very high antioxidant activities, with higher activity observed for the P. granatum extract.     

Urinary amino acid analysis: A comparison of iTRAQ®–LC–MS/MS,GC–MS,and amino acid analyzer

Urinary amino acid analysis is typically done by cation-exchange chromatography followed by post-column derivatization with ninhydrin and UV detection. This method lacks throughput and specificity. Two recently introduced stable isotope ratio mass spectrometric methods promise to overcome those shortcomings. Using two blinded sets of urine replicates and a certified amino acid standard, we compared the precision and accuracy of gas chromatography/mass spectrometry (GC–MS) and liquid chromatography–tandem mass spectrometry (LC–MS/MS) of propyl chloroformate and iTRAQ^® derivatized amino acids, respectively, to conventional amino acid analysis. The GC–MS method builds on the direct derivatization of amino acids in diluted urine with propyl chloroformate, GC separation and mass spectrometric quantification of derivatives using stable isotope labeled standards. The LC–MS/MS method requires prior urinary protein precipitation followed by labeling of urinary and standard amino acids with iTRAQ^® tags containing different cleavable reporter ions distinguishable by MS/MS fragmentation. Means and standard deviations of percent technical error (%TE) computed for 20 amino acids determined by amino acid analyzer, GC–MS, and iTRAQ^®–LC–MS/MS analyses of 33 duplicate and triplicate urine specimens were 7.27 ± 5.22, 21.18 ± 10.94, and 18.34 ± 14.67, respectively. Corresponding values for 13 amino acids determined in a second batch of 144 urine specimens measured in duplicate or triplicate were 8.39 ± 5.35, 6.23 ± 3.84, and 35.37 ± 29.42. Both GC–MS and iTRAQ^®–LC–MS/MS are suited for high-throughput amino acid analysis, with the former offering at present higher reproducibility and completely automated sample pretreatment, while the latter covers more amino acids and related amines.     

Triptolide derivatives as potential multifunctional anti-Alzheimer agents: Synthesis and structure–activity relationship studies

Owning to the promising neuroprotective profile and the ability to cross the blood–brain barrier, triptolide has attracted extensive attention. Although its limited solubility and toxicity have greatly hindered clinical translation, triptolide has nonetheless emerged as a promising candidate for structure–activity relationship studies for Alzheimer’s disease. In the present study, a series of triptolide analogs were designed and synthesized, and their neuroprotective and anti-neuroinflammatory effects were then tested using a cell culture model. Among the triptolide derivatives tested, a memantine conjugate, compound 8, showed a remarkable neuroprotective effect against Aβ_1–42 toxicity in primary cortical neuron cultures as well as an inhibitory effect against LPS-induced TNF-α production in BV2 cells at a subnanomolar concentration. Our findings provide insight into the different pharmacophores that are responsible for the multifunctional effects of triptolide in the central nervous system. Our study should help in the development of triptolide-based multifunctional anti-Alzheimer drugs.     

Granger causality in integrated GC–MS and LC–MS metabolomics data reveals the interface of primary and secondary metabolism

Metabolomics has emerged as a key technique of modern life sciences in recent years. Two major techniques for metabolomics in the last 10 years are gas chromatography coupled to mass spectrometry (GC–MS) and liquid chromatography coupled to mass spectrometry (LC–MS). Each platform has a specific performance detecting subsets of metabolites. GC–MS in combination with derivatisation has a preference for small polar metabolites covering primary metabolism. In contrast, reversed phase LC–MS covers large hydrophobic metabolites predominant in secondary metabolism. Here, we present an integrative metabolomics platform providing a mean to reveal the interaction of primary and secondary metabolism in plants and other organisms. The strategy combines GC–MS and LC–MS analysis of the same sample, a novel alignment tool MetMAX and a statistical toolbox COVAIN for data integration and linkage of Granger Causality with metabolic modelling. For metabolic modelling we have implemented the combined GC–LC–MS metabolomics data covariance matrix and a stoichiometric matrix of the underlying biochemical reaction network. The changes in biochemical regulation are expressed as differential Jacobian matrices. Applying the Granger causality, a subset of secondary metabolites was detected with significant correlations to primary metabolites such as sugars and amino acids. These metabolic subsets were compiled into a stoichiometric matrix N. Using N the inverse calculation of a differential Jacobian J from metabolomics data was possible. Key points of regulation at the interface of primary and secondary metabolism were identified.     

GC–MS and FTIR Analysis of Chemical Compounds in Ocimum Gratissimum Plant

Biophysics - The plant tissues produce many chemical compounds with potential biological activities. The present study has been carried out to identify the chemical constituents present in the...     

Metabolomic changes in Caenorhabditis elegans lifespan mutants as evident from GC–EI–MS and GC–APCI–TOF–MS profiling

Lifespan mutants of the nematode Caenorhabditis elegans are a much studied aging model, however, aging-related changes at the metabolome level remain largely unexplored. To identify metabolic features connected to mitochondrial dysfunction, a hallmark of aging and age-related disease, we analyzed a short-lived mitochondrial mutant (mev-1(kn1)), a long-lived mutant with enhanced cellular maintenance (ife-2(ok306)) and the novel double mutant ife-2(ok306);mev-1(kn1) which is normal-lived, possibly through attenuation of the metabolic mev-1 phenotype. Metabolomic analysis involved coupled gas chromatography–mass spectrometry with electron ionization (GC–EI–MS) and, in addition, recently introduced GC with soft atmospheric pressure chemical ionization coupled to time-of-flight mass spectrometry (GC–APCI–TOF–MS) to yield complementary mass spectrometric information for enhanced metabolite annotation. Multivariate analysis allowed distinction of mev-1 and ife-2 mutants from the wild type, while suggesting still another, distinct metabolic phenotype for the ife-2;mev-1 double mutant. In mev-1(kn1), disturbed energy metabolism was indicated by upset TCA cycle homeostasis, elevated glycolytic substrate and lactic acid levels as well as depletion of free amino acids pools. Surprisingly, these mitochondrially related changes were retained in the ife-2;mev-1 mutant, as were highly elevated levels of the dipeptide glycylproline indicative of increased collagen catabolism. However, the double mutant reverted mev-1(kn1) changes in uric acid and long-chain fatty alcohol metabolism, two pathways connected to the peroxisomal compartment. Our results are in line with recent evidence for a critical role of this organelle in aging and demonstrate the usefulness of non-targeted metabolomics approaches for detecting complex metabolic changes in the study of mitochondrial dysfunction.     

Simple assay of plasma sevoflurane and its metabolite hexafluoroisopropanol by headspace GC–MS

The anesthetic sevoflurane can now be delivered over periods of up to 48 h using a newly developed medical system, the AnaConDa (anesthetic conserving device). Lack of pharmacokinetic data on sevoflurane and its main metabolite (hexafluoroisopropanol, HFIP) in this indication prompted us to develop a headspace GC–MS method to quantify the two substances. The only previously published method for assaying the two substances could not be adapted to our study since it uses expensive and rarely employed system components together with toxic carbon disulfide as a dilution solvent. The method developed is straightforward and uses the relatively non-toxic solvent undecane as dilution solvent and chloroform as internal standard. The method is linear for a concentration range of 1–150 μg/ml, and presents high accuracy and precision. LOD and LOQ are 0.2 and 1 μg/ml, with a short analysis time (7.6 min for a single analysis). The method was applied to determine the plasma levels of sevoflurane and HFIP in six patients under 48-h anesthetic sedation delivered via the AnaConDa system. Average sevoflurane and HFIP concentrations plateaued at 75 and 4 μg/ml, respectively. Sevoflurane quickly tailed off after inhalation was stopped, and HFIP levels remained low.     

Use of chemical ionization for GC–MS metabolite profiling

Metabolite profiling is commonly performed by GC–MS of methoximated trimethylsilyl derivatives. The popularity of this technique owes much to the robust, library searchable spectra produced by electron ionization (EI). However, due to extensive fragmentation, EI spectra of trimethylsilyl derivatives are commonly dominated by trimethylsilyl fragments (e.g. m/z 73 and 147) and higher m/z fragment ions with structural information are at low abundance. Consequently different metabolites can have similar EI spectra, and this presents problems for identification of “unknowns” and the detection and deconvolution of overlapping peaks. The aim of this work is to explore use of positive chemical ionization (CI) as an adjunct to EI for GC–MS metabolite profiling. Two reagent gases differing in proton affinity (CH₄ and NH₃) were used to analyse 111 metabolite standards and extracts from plant samples. NH₃-CI mass spectra were simple and generally dominated by [MH]⁺ and/or the adduct [M+NH₄]⁺. For the 111 metabolite standards, m/z 73 and 147 were less than 3% of basepeak in NH₃-CI and less than 30% of basepeak in CH₄-CI. With CH₄-CI, [MH]⁺ was generally present but at lower relative abundance than for NH₃-CI. CH₄-CI spectra were commonly dominated by losses of CH₄ [M+1-16]⁺, 1–3 TMSOH [M+1-nx90]⁺, and combinations of CH₄ and TMSOH losses [M+1-nx90-16]⁺. CH₄-CI and NH₃-CI mass spectra are presented for 111 common metabolites, and CI is used with real samples to help identify overlapping peaks and aid identification via determination of the pseudomolecular ion with NH₃-CI and structural information with CH₄-CI.

     

Use of chemical ionization for GC–MS metabolite profiling

Metabolite profiling is commonly performed by GC–MS of methoximated trimethylsilyl derivatives. The popularity of this technique owes much to the robust, library searchable spectra produced by electron ionization (EI). However, due to extensive fragmentation, EI spectra of trimethylsilyl derivatives are commonly dominated by trimethylsilyl fragments (e.g. m/z 73 and 147) and higher m/z fragment ions with structural information are at low abundance. Consequently different metabolites can have similar EI spectra, and this presents problems for identification of “unknowns” and the detection and deconvolution of overlapping peaks. The aim of this work is to explore use of positive chemical ionization (CI) as an adjunct to EI for GC–MS metabolite profiling. Two reagent gases differing in proton affinity (CH₄ and NH₃) were used to analyse 111 metabolite standards and extracts from plant samples. NH₃-CI mass spectra were simple and generally dominated by [MH]⁺ and/or the adduct [M+NH₄]⁺. For the 111 metabolite standards, m/z 73 and 147 were less than 3% of basepeak in NH₃-CI and less than 30% of basepeak in CH₄-CI. With CH₄-CI, [MH]⁺ was generally present but at lower relative abundance than for NH₃-CI. CH₄-CI spectra were commonly dominated by losses of CH₄ [M+1-16]⁺, 1–3 TMSOH [M+1-nx90]⁺, and combinations of CH₄ and TMSOH losses [M+1-nx90-16]⁺. CH₄-CI and NH₃-CI mass spectra are presented for 111 common metabolites, and CI is used with real samples to help identify overlapping peaks and aid identification via determination of the pseudomolecular ion with NH₃-CI and structural information with CH₄-CI.     

Untargeted GC–MS investigation of serum metabolomics of coronary artery disease patients

Recent advances in metabolomics provide tools to investigate human metabolome in order to establish new parameters to study different approaches towards diagnostics, diseases and their treatment. The present study focused on the untargeted identification of metabolites in serum of patients with coronary artery disease who were under treatment at the time of sample collection. AUCs (Area Under the Curves) from different peaks were considered for the analysis and comparison purposes. The metabolome was studied using GC–MS (Gas Chromatography Mass Spectrometry) and the metabolites were identified with NIST (The National Institute of Standards and Technology) and Wiley library matches. A total of 17 metabolites were identified and focused on to compare with the metabolome of healthy individuals. T test analysis found significant differences in alanine, malonic acid, ribitol, D-glucose, mannose (P < 0.001), acetohydroxamic acid, N-carboxyglycine, and aminobutyrate (P < 0.05). Principal Component Analysis of serum metabolites data found three components out of 17 metabolites; RC1 (Acetohydroxamic acid, alanine, D-glucose, malonic acid, mannose, N-carboxy glycine and ribitol), RC2 (Heptadecanoic acid, hexadecanoic acid, octadecanoic acid and Trans-9-octadecanoic acid), RC3 (Aminobutyrate, D-sorbit, gamma lactone, valine, benzene propanoic acid and lactic acid). No correlation was found among the components.     

Comparison of derivatization and chromatographic methods for GC–MS analysis of amino acid enantiomers in physiological samples

GC–MS analysis of fluorinated and non-fluorinated chloroformate and anhydride derivatives of amino acid (AA) enantiomers on two different chiral columns was compared for the direct quantification of free l- and d-AAs in human serum and urine in a single analytical run. Best sensitivity was achieved with pentafluoropropionic anhydride/heptafluorobutanol derivatives separated on a Chirasil-l-Val column. However, the occurrence of racemization during derivatization precluded accurate quantification of AA enantiomers. Derivatization with methyl chloroformate/methanol and separation on an Rt-γDEXsa column did not exhibit racemization and yielded ten baseline separated racemates of proteinogenic AAs with resolution values greater than 2.4. However, protein and peptide hydrolysis occurred in serum and urine during the highly exothermal derivatization reaction under alkaline conditions. Removing serum proteins by precipitation before derivatization and performing the reaction at neutral pH enabled the determination of accurate free AA enantiomer concentrations. Accuracy of quantification was validated by an established nonchiral GC–MS method for AA analysis. Reliable quantification was achieved using stable-isotope labeled l-AAs as internal standards. Limits of detection (LOD) and lower limits of quantification (LLOQ) for the d-AAs were in the range of 3.2–446 nM and 0.031–1.95 μM, respectively. Relative standard deviations (N = 6) for the measurement of AAs in urine and serum ranged from 0.49–11.10% to 0.70–3.87%, respectively. The method was applied to the analysis of urine from 19 patients with renal insufficiency. In comparison to healthy probands, D-ratios of Ala, Val, Pro, Thr, Asp, and Asn were significantly increased.     

Chemical compositions by using LC–MS/MS and GC–MS and antioxidant activities of methanolic extracts from leaf and flower parts of Scabiosa columbaria subsp. columbaria var. columbaria L.

The members of the Scabiosa genus are one of the traditional medicinal plants used in the treatment of many diseases, in particular the treatment of scabies. In this study, it was aimed to determine antioxidant activities and chemical composition of methanolic extracts of leaves and flowers of Scabiosa columbaria subsp. columbaria var. columbaria. The phenolic contents of both parts of the plant were analyzed by LC–MS/MS. A total of 6 phenolic compounds were determined and chlorogenic acid was the major compound in both flower and leaf parts of the plants, with 5936.052 µg/g and 8021.666 µg/g, respectively. 6 different methods were used to determine the antioxidant activity of the plant parts. Both leaf and flower parts of the plant showed high antioxidant activity in all tested methods and the antioxidant activity values of the leaf part were measured higher than those of the flower part for four tests. The methanol extracts of the plant parts was analyzed with GC–MS and number of the essential oil compounds in the leaf and flower parts were determined as 17 and 13, respectively. Linalool compound was also found to be common in both parts of the plant. The major compounds of the essential oils were identified as 4-Octadecenal (30.01%) in the flower and carvone (35.44%) in the leaf. In addition, terpene derivatives was determined as 90.32% of the highest essential oil group in the leaf, while this value was determined as 1.42% in the flower. For the flower, aromatics were determined as the main component group with 21.31%.     

Functional redundancy of the two 5-hydroxylases in monolignol biosynthesis of Populus trichocarpa: LC–MS/MS based protein quantification and metabolic flux analysis

Flowering plants have syringyl and guaiacyl subunits in lignin in contrast to the guaiacyl lignin in gymnosperms. The biosynthesis of syringyl subunits is initiated by coniferaldehyde 5-hydroxylase (CAld5H). In Populus trichocarpa there are two closely related CAld5H enzymes (PtrCAld5H1 and PtrCAld5H2) associated with lignin biosynthesis during wood formation. We used yeast recombinant PtrCAld5H1 and PtrCAld5H2 proteins to carry out Michaelis-Menten and inhibition kinetics with LC-MS/MS based absolute protein quantification. CAld5H, a monooxygenase, requires a cytochrome P450 reductase (CPR) as an electron donor. We cloned and expressed three P. trichocarpa CPRs in yeast and show that all are active with both CAld5Hs. The kinetic analysis shows both CAld5Hs have essentially the same biochemical functions. When both CAld5Hs are coexpressed in the same yeast membranes, the resulting enzyme activities are additive, suggesting functional redundancy and independence of these two enzymes. Simulated reaction flux based on Michaelis-Menten kinetics and inhibition kinetics confirmed the redundancy and independence. Subcellular localization of both CAld5Hs as sGFP fusion proteins expressed in P. trichocarpa differentiating xylem protoplasts indicate that they are endoplasmic reticulum resident proteins. These results imply that during wood formation, 5-hydroxylation in monolignol biosynthesis of P. trichocarpa requires the combined metabolic flux of these two CAld5Hs to maintain adequate biosynthesis of syringyl lignin. The combination of genetic analysis, absolute protein quantitation-based enzyme kinetics, homologous CPR specificity, SNP characterization, and ER localization provides a more rigorous basis for a comprehensive systems understanding of 5-hydroxylation in lignin biosynthesis.     

Evaluation of bioactive flavonols and ent-kaurenes in the 2,4-dichlorophenoxyacetic acid-induced calli of Senegalia nigrescens using FTIR and GC–MS

Journal of Plant Biochemistry and Biotechnology - The increasing demand for plant-derived pharmacologically active compounds calls for sustainable alternative sources and conservation of medicinal...     

Review of recent developments in GC–MS approaches to metabolomics-based research

Background

Metabolomics aims to identify the changes in endogenous metabolites of biological systems in response to intrinsic and extrinsic factors. This is accomplished through untargeted, semi-targeted and targeted based approaches. Untargeted and semi-targeted methods are typically applied in hypothesis-generating investigations (aimed at measuring as many metabolites as possible), while targeted approaches analyze a relatively smaller subset of biochemically important and relevant metabolites. Regardless of approach, it is well recognized amongst the metabolomics community that gas chromatography-mass spectrometry (GC–MS) is one of the most efficient, reproducible and well used analytical platforms for metabolomics research. This is due to the robust, reproducible and selective nature of the technique, as well as the large number of well-established libraries of both commercial and ‘in house’ metabolite databases available.

Aim of review

This review provides an overview of developments in GC–MS based metabolomics applications, with a focus on sample preparation and preservation techniques. A number of chemical derivatization (in-time, in-liner, offline and microwave assisted) techniques are also discussed. Electron impact ionization and a summary of alternate mass analyzers are highlighted, along with a number of recently reported new GC columns suited for metabolomics. Lastly, multidimensional GC–MS and its application in environmental and biomedical research is presented, along with the importance of bioinformatics.

Key scientific concepts of review

The purpose of this review is to both highlight and provide an update on GC–MS analytical techniques that are common in metabolomics studies. Specific emphasis is given to the key steps within the GC–MS workflow that those new to this field need to be aware of and the common pitfalls that should be looked out for when starting in this area.