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.     

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.     

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.     

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.     

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.     

An isotope-dilution,GC–MS assay for formate and its application to human and animal metabolism

Formate, a crucial component of one-carbon metabolism, is increasingly recognized as an important intermediate in production and transport of one-carbon units. Unlike tetrahydrofolate-linked intermediates, it is not restricted to the intracellular milieu so that circulating levels of formate can provide insight into cellular events. We report a novel isotope-dilution, GC–MS assay employing derivatization by 2,3,4,5,6-pentafluorobenzyl bromide for the determination of formate in biological samples. This assay is robust and sensitive; it may be applied to the measurement of formate in serum, plasma and urine. We demonstrate how this method may be applied by providing the first characterization of formate levels in a human population; formate levels were higher in males than in females. We also show how this procedure may be applied for the measurement of in vivo kinetics of endogenous formate production in experimental animals.     

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.

     

HPTLC and GC–MS finger-printing of two potential multifunctional siddha tailams: Mathan and maha megarajanga tailam

The Siddha system of medicine is an ancient medical lineage that is practiced primarily in the southern part of India. Siddha system of medicine has been in practice for thousands of years with documented evidence dating back to the 6th century BCE. According to siddha system of medicine’s basic fundamental principle, the human body is made up of 96 thathuvam (primary components), which encompass physical, physiological, psychological, and intellectual aspects. Medicine (marunthu) is classified as a wide range of internal and external medicines. The major components of its medical formulations include plant parts, minerals and animal products. Various methods were carried out for the purification process to eliminate the toxins. Choornam, Guligai, Tailam, Parpam, Chendooram, Kattu, Pasai and Poochu are the most common medicines used in Siddha system of medicine for the treatment of various diseases. The pathophysiological classification of diseases is elaborated in detail in the classical Siddha literature. Siddha system of medicine plays an important role in protecting people from diseases such as COVID-19 by providing immune-protecting and immune-boosting medicines in today's world. Mathan tailam and maha megarajanga tailam are the two unique preparations used widely for various skin diseases including chronic wounds and burns. Scientific validation of both medicines will help in understanding their effectiveness against a typical wound condition. In the present study physio-chemical and phytochemical, HPTLC, and GC–MS analyses were carried out and discussed in detail on the multifunctional properties exhibited in the patient communities.     

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%.     

Optimized GC–MS metabolomics for the analysis of kidney tissue metabolites

Introduction

Metabolomics is a promising approach for discovery of relevant biomarkers in cells, tissues, organs, and biofluids for disease identification and prediction. The field has mostly relied on blood-based biofluids (serum, plasma, urine) as non-invasive sources of samples as surrogates of tissue or organ-specific conditions. However, the tissue specificity of metabolites pose challenges in translating blood metabolic profiles to organ-specific pathophysiological changes, and require further downstream analysis of the metabolites.

Objectives

As part of this project, we aim to develop and optimize an efficient extraction protocol for the analysis of kidney tissue metabolites representative of key primate metabolic pathways.

Methods

Kidney cortex and medulla tissues of a baboon were homogenized and extracted using eight different extraction protocols including methanol/water, dichloromethane/methanol, pure methanol, pure water, water/methanol/chloroform, methanol/chloroform, methanol/acetonitrile/water, and acetonitrile/isopropanol/water. The extracts were analyzed by a two-dimensional gas chromatography time-of-flight mass-spectrometer (2D GC–ToF-MS) platform after methoximation and silylation.

Results

Our analysis quantified 110 shared metabolites in kidney cortex and medulla tissues from hundreds of metabolites found among the eight different solvent extractions spanning low to high polarities. The results revealed that medulla is metabolically richer compared to the cortex. Dichloromethane and methanol mixture (3:1) yielded highest number of metabolites across both the tissue types. Depending on the metabolites of interest, tissue type, and the biological question, different solvents can be used to extract specific groups of metabolites.

Conclusion

This investigation provides insights into selection of extraction solvents for detection of classes of metabolites in renal cortex and medulla, which is fundamentally important for identification of prognostic and diagnostic metabolic kidney biomarkers for future therapeutic applications.

     

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.

     

Baitmet,a computational approach for GC–MS library-driven metabolite profiling

Introduction

Current computational tools for gas chromatography—mass spectrometry (GC–MS) metabolomics profiling do not focus on metabolite identification, that still remains as the entire workflow bottleneck and it relies on manual data reviewing. Metabolomics advent has fostered the development of public metabolite repositories containing mass spectra and retention indices, two orthogonal properties needed for metabolite identification. Such libraries can be used for library-driven compound profiling of large datasets produced in metabolomics, a complementary approach to current GC–MS non-targeted data analysis solutions that can eventually help to assess metabolite identities more efficiently.

Results

This paper introduces Baitmet, an integrated open-source computational tool written in R enclosing a complete workflow to perform high-throughput library-driven GC–MS profiling in complex samples. Baitmet capabilities were assayed in a metabolomics study involving 182 human serum samples where a set of 61 metabolites were profiled given a reference library.

Conclusions

Baitmet allows high-throughput and wide scope interrogation on the metabolic composition of complex samples analyzed using GC–MS via freely available spectral data. Baitmet is freely available at http://CRAN.R-project.org/package=baitmet.

     

Analysis of sugar composition and pesticides using HPLC and GC–MS techniques in honey samples collected from Saudi Arabian markets

Honey is a complex foodstuff found in nature which is used without any processing. Honey has been in use in medicine as well as raw food since ancient times. Essentially, it is a blend of sugars especially fructose and glucose. The objectives of the study were to determine major sugar composition as well as pesticides contamination in honey samples. Further, Hydroxy-methyl-furfuraldehyde (HMF) level was also determined to ascertain the freshness of honey samples. A total of 14 samples were collected from local market and tested for fructose, glucose, sucrose, HMF and organochlorine pesticides using HPLC and GC–MS techniques respectively. The total sugars in the 14 honey samples were found ranging between 50.26 and 74.74 g/100 g of honey. The chromatographic results showed the presence of the sugars like fructose and glucose in all honey samples. The honey sample SH–11 was found to contain the highest amount of fructose (40.63%). On the other hand, the lowest amount of fructose with 29.08% was observed in SH–7. The HPLC analysis also revealed the presence of sucrose in two samples but under the permissible limit. The average ratio of fructose to glucose in these honey samples was 1.3. None of the sample has ratio below 1.0 indicating lesser chances for honey to crystallize on storage. Out of 14 honey samples, 13 samples were found negative for the presence of any of the 63 pesticides tested. Only sample No. 13, was found to contain 15.95 ppb hexachlorobenzene per kilogram of honey. The HMF was not detected in four samples but in remaining samples it was well below the maximum permissible limit. No pesticide and sugar adulteration was observed in any of the honey samples. The honeys collected from Saudi Arabian markets were found to confirm the standards set by the regional and international standardization organization, the GSO and Codex Alimentarius Commission respectively.     

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.     

Potato metabolomics by GC–MS: what are the limiting factors?

Metabolic profiling methods are not ideally suited to the simultaneous analysis of all metabolite classes within a biological sample and must be optimized for maximum applicability. Several factors related to the optimization, validation and limitations of a GC–MS-based metabolic profiling method for potato were examined. A key step is conversion of reducing sugars to methyloximes, and optimum reaction conditions were 50 °C for 4 h. Shorter times or lower temperatures resulted in incomplete oximation whereas longer times and higher temperatures caused hydrolysis of sucrose, the major tuber dissacharide. Metabolite concentration gradients were observed in tuber sections. Glucose, fructose, alanine, methionine, threonine and tyrosine were more concentrated in the interior, whereas asparagine, putrescine, and caffeic and chlorogenic acids were higher in the skin and citrate was concentrated at the tuber’s bud end. These results impact upon choice of sampling strategy, consequently the use of freeze-dried (FD) material from a sampling protocol developed to avoid gradient-induced bias was examined. Using FD material, the method was highly linear and there was little qualitative or quantitative difference in the metabolite composition between fresh and FD material. The short- and long-term repeatability of the method was studied, and the use of reference materials to monitor and to improve data quality is discussed. Ascorbate is an important tuber metabolite that is readily measured by targeted approaches, but can be a problem in metabolic profiling. It was shown for standards and FD potato that ascorbate was largely degraded during oximation, although some survived in FD material. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

GC–MS measurement of biological NG-hydroxy-l-arginine,a stepmotherly investigated endogenous nitric oxide synthase substrate and arginase inhibitor

Amino Acids - l-Arginine is converted by nitric oxide synthase (NOS) to l-citrulline and nitric oxide (NO). NG-Hydroxy-l-arginine (NOHA) is the isolable intermediate of this reaction. NOHA has been...