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Introduction: Saccharomyces cerevisiae has been widely used for fermenting food and beverages for over thousands years. Its metabolism together with the substrate composition play an important role in determining the characteristics of the final fermented products. We previously showed that the polyunsaturated fatty acid, linoleic acid, which is present in the grape juice at trace levels, significantly affected the development of aroma compounds of the wines. However, the effect of linoleic acid on the overall cell metabolism of S. cerevisiae is still not clear. Therefore, we aimed to unlock the metabolic response of S. cerevisiae to linoleic acid using metabolomics and isotope labelling experiments., Methods: We cultured the cells on a minimal mineral medium supplementing them with linoleic acid isomers and 13C-linoleic acid. Both intracellular and extracellular metabolite profiles were determined using gas chromatography coupled to mass spectrometry (GC-MS) to investigate which S. cerevisiae pathways were affected by linoleic acid supplementation., Results: The utilisation of linoleic acid by S. cerevisiae had a significant impact on the primary carbon metabolism increasing the glucose consumption and the ethanol production under anaerobic condition. The energetic state of the cell was, therefore, affected and the glycolytic pathway, the TCA cycle and the amino acid production were up-regulated. We also observed that linoleic acid was transported into the cell and converted into other fatty acids affecting their profile even under anaerobic condition., Conclusion: Our data clearly shows that linoleic acid supplementation in growth medium increased glucose consumption and ethanol production by S. cerevisiae under anaerobic condition. We also suggest that S. cerevisiae might be able to perform an alternative anaerobic pathway to β-oxidation, which has not been reported yet.

Background: Quenching in cold buffered methanol at -40 °C has long been the preferred method for sub-second inactivation of cell metabolism during metabolic fingerprinting. However, methanol is known to cause intracellular metabolite leakage of microbial cells, making the distinction between intra- and extracellular metabolites in microbial systems challenging. In this paper, we tested three quenching protocols proposed for microbial cultures: fast filtration, cold buffered methanol and cold glycerol saline., Results: Our results clearly showed that cold glycerol saline quenching resulted in the best recovery of intracellular metabolites in Lactobacillus paracasei subsp. paracasei (L. paracasei). Membrane integrity assayed by propidium iodide revealed that approximately 100 % [Corrected] of the L. paracasei cell membranes were damaged by contact with the cold buffered methanol solution, whilst cold glycerol saline quenching led to minimal cell damage. Due to the nature of the L. paracasei culture, fast filtration took several minutes, which is far from ideal for metabolites with high intracellular turnover rates., Conclusion: The implementation of a reliable, reproducible quenching method is essential within the metabolomics community. Cold glycerol saline prevented leakage of intracellular metabolites, and, thus, allowed more accurate determinations of intracellular metabolite levels.

Motivation: The Automated Mass Spectral Deconvolution and Identification System (AMDIS) is freeware extensively applied in metabolomics. However, datasets processed by AMDIS require extensive data correction, filtering and reshaping to create reliable datasets for further downstream analysis. Performed manually, these processes are laborious and extremely time consuming. Furthermore, manual corrections increase the chance of human error and can introduce additional technical variability to the data. Thus, an automated pipeline for curating GC-MS data is urgently needed., Results: We present the Metab R package designed to automate the pipeline for analysis of metabolomics GC-MS datasets processed by AMDIS., Availability: The Metab package, the AMDIS library and the reference ion library are available at www.metabolomics.auckland.ac.nz/index.php/downloads., Contact: k.ruggiero@auckland.ac.nz.

Motivation: Metabolomics is one of the most recent omics-technologies and uses robust analytical techniques to screen low molecular mass metabolites in biological samples. It has evolved very quickly during the last decade. However, metabolomics datasets are considered highly complex when used to relate metabolite levels to metabolic pathway activity. Despite recent developments in bioinformatics, which have improved the quality of metabolomics data, there is still no straightforward method capable of correlating metabolite level to the activity of different metabolic pathways operating within the cells. Thus, this kind of analysis still depends on extremely laborious and time-consuming processes., Results: Here, we present a new algorithm Pathway Activity Profiling (PAPi) with which we are able to compare metabolic pathway activities from metabolite profiles. The applicability and potential of PAPi was demonstrated using a previously published data from the yeast Saccharomyces cerevisiae. PAPi was able to support the biological interpretations of the previously published observations and, in addition, generated new hypotheses in a straightforward manner. However, PAPi is time consuming to perform manually. Thus, we also present here a new R-software package (PAPi) which implements the PAPi algorithm and facilitates its usage to quickly compare metabolic pathways activities between different experimental conditions. Using the identified metabolites and their respective abundances as input, the PAPi package calculates pathways' Activity Scores, which represents the potential metabolic pathways activities and allows their comparison between conditions. PAPi also performs principal components analysis and analysis of variance or t-test to investigate differences in activity level between experimental conditions. In addition, PAPi generates comparative graphs highlighting up- and down-regulated pathway activity., Availability: These datasets are available in http://www.4shared.com/file/hTWyndYU/extra.html and http://www.4shared.com/file/VbQIIDeu/intra.html. PAPi package is available in: http://www.4shared.com/file/s0uIYWIg/PAPi_10.html, Contact: s.villas-boas@auckland.ac.nz, Supplementary Information: Supplementary data are available at Bioinformatics online.

This protocol describes an analytical platform for the analysis of intra- and extracellular metabolites of microbial cells (yeast, filamentous fungi and bacteria) using gas chromatography-mass spectrometry (GC-MS). The protocol is subdivided into sampling, sample preparation, chemical derivatization of metabolites, GC-MS analysis and data processing and analysis. This protocol uses two robust quenching methods for microbial cultures, the first of which, cold glycerol-saline quenching, causes reduced leakage of intracellular metabolites, thus allowing a more reliable separation of intra- and extracellular metabolites with simultaneous stopping of cell metabolism. The second, fast filtration, is specifically designed for quenching filamentous micro-organisms. These sampling techniques are combined with an easy sample-preparation procedure and a fast chemical derivatization reaction using methyl chloroformate. This reaction takes place at room temperature, in aqueous medium, and is less prone to matrix effect compared with other derivatizations. This protocol takes an average of 10 d to complete and enables the simultaneous analysis of hundreds of metabolites from the central carbon metabolism (amino and nonamino organic acids, phosphorylated organic acids and fatty acid intermediates) using an in-house MS library and a data analysis pipeline consisting of two free software programs (Automated Mass Deconvolution and Identification System (AMDIS) and R).

The effect of dimethyl sulfoxide (DMSO) on fungal metabolism has not been well studied. This study aimed to evaluate, by metabolomics, the impact of DMSO on the central carbon metabolism of Candida albicans. Biofilms of C. albicans SC5314 were grown on paper discs, using minimum mineral (MM) medium, in a dynamic continuous flow system. The two experimental conditions were control and 0.03% DMSO (v/v). After 72 h of incubation (37 °C), the biofilms were collected and the metabolites were extracted. The extracted metabolites were subjected to gas chromatography–mass spectrometry (GC/MS). The experiment was conducted using five replicates on three independent occasions. The GC/MS analysis identified 88 compounds. Among the 88 compounds, the levels of 27 compounds were markedly different between the two groups. The DMSO group exhibited enhanced levels of putrescine and glutathione and decreased levels of methionine and lysine. Additionally, the DMSO group exhibited alterations in 13 metabolic pathways involved in primary and secondary cellular metabolism. Among the 13 altered pathways, seven were downregulated and six were upregulated in the DMSO group. These results indicated a differential intracellular metabolic profile between the untreated and DMSO-treated biofilms. Hence, DMSO was demonstrated to affect the metabolic pathways of C. albicans. These results suggest that DMSO may influence the results of laboratory tests when it is used as a solvent. Hence, the use of DMSO as a solvent must be carefully considered in drug research, as the effect of the researched drugs may not be reliably translated into clinical practice. [ABSTRACT FROM AUTHOR]

The development of new tools for assessing the health of cultured shellfish larvae is crucial for aquaculture industries to develop and refine hatchery methodologies. We established a large-volume ecotoxicology/health stressor trial, exposing mussel (Perna canaliculus) embryos to copper in the presence of ethylenediaminetetraacetic acid (EDTA). GC/MS-based metabolomics was applied to identify potential biomarkers for monitoring embryonic/larval health and to characterise mechanisms of metal toxicity. Cellular viability, developmental abnormalities, larval behaviour, mortality, and a targeted analysis of proteins involved in the regulation of reactive oxygen species were simultaneously evaluated to provide a complementary framework for interpretative purposes and authenticate the metabolomics data. Trace metal analysis and speciation modelling verified EDTA as an effective copper chelator. Toxicity thresholds for P. canaliculus were low, with 10% developmental abnormalities in D-stage larvae being recorded upon exposure to 1.10 μg·L−1 bioavailable copper for 66 h. Sublethal levels of bioavailable copper (0.04 and 1.10 μg·L−1) caused coordinated fluctuations in metabolite profiles, which were dependent on development stage, treatment level, and exposure duration. Larvae appeared to successfully employ various mechanisms involving the biosynthesis of antioxidants and a restructuring of energy-related metabolism to alleviate the toxic effects of copper on cells and developing tissues. These results suggest that regulation of trace metal-induced toxicity is tightly linked with metabolism during the early ontogenic development of marine mussels. Lethal-level bioavailable copper (50.3 μg·L−1) caused severe metabolic dysregulation after 3 h of exposure, which worsened with time, substantially delayed embryonic development, induced critical oxidative damage, initiated the apoptotic pathway, and resulted in cell/organism death shortly after 18 h of exposure. Metabolite profiling is a useful approach to (1) assess the health status of marine invertebrate embryos and larvae, (2) detect early warning biomarkers for trace metal contamination, and (3) identify novel regulatory mechanisms of copper-induced toxicity. [ABSTRACT FROM AUTHOR]

Introduction: Technological advances in the area of analytical chemistry and the development of state-of-the-art analytical instrumentation have allowed for a shift in the focus from a previously strict targeted approach towards the approach adopted in metabolomics, the essence of which is non-targeted providing an unbiased analysis of metabolites in biological samples. Metabolite profiling methods have served their purpose in providing descriptive information about biological systems through qualitative and relative semi-quantitative data. However, quantitative characterization of a system cannot be fully accomplished without using absolute metabolite concentrations, an area which is lacking in most current metabolomics platforms. Objectives: The objective of this work was to develop a calibration-curve free method for quantitation of amino and non-amino organic acids in biological samples. Methods: We developed a novel calibration curve-free GC-MS method based on isotope-coded derivatization for absolute non-targeted quantification of polar metabolites. A new R-based package MetabQ was created for automated data processing of GC-MS data files performing data extraction and calculation of absolute metabolite values. The new method requires metabolite response factors which should be calculated only once for each equipment, and was validated for metabolite quantification of different biological matrices. Results: The method showed high reproducibility and accuracy, and does not require the use of calibration curves using standards to be analyzed in parallel with every sample batch. However, there is a small group of metabolites where their quantification required additional steps of correction due to their chemical instability. The introduced R package significantly increased the throughput in the data analysis process, extensively reducing the time required to perform the task manually. Conclusion: Our novel approach gives the potential to identify and quantify hundreds of metabolites, far exceeding the capabilities of any absolute quantitative targeted metabolite analysis, limited only by the size of the mass spectral library. [ABSTRACT FROM AUTHOR]

The article discusses the study which determines whether maternal hair was link with the development of gestational diabetes mellitus (GDM) through investigating the metabolome of maternal hair. The study analyzed hair samples from about 94 pregnant women from China whose hair were deconvulated through Automated Mass Spectral Deconvolution and Identification System (AMDIS). Result shows that a total of 30 metabolites were identified through a in-house mass spectral library.

Current early pregnancy screening tools to identify women at risk of developing gestational diabetes mellitus lack both specificity and sensitivity. As a result, the foetus and mother are often subjected to insult during disease progression, prior to diagnosis and treatment in later pregnancy. Metabolomics is an analytical approach, which allows for appraisal of small molecular mass compounds in a biofluid. The aim of this pilot study was to investigate the relationship between the early gestation serum metabolite profile and the subsequent development of gestational diabetes mellitus in the search for early pregnancy biomarkers and potential metabolic mechanisms. Our nested case-control study analysed maternal serum at 20 weeks' gestation, obtained from the New Zealand cohort of the Screening for Pregnancy Endpoints study. Metabolomic profiling was performed using gas chromatography coupled to mass spectrometry, and metabolites were identified using R software and an in-house mass spectral library. Statistical analysis was performed using SPSS version 21.0. Forty-eight metabolites were identified in the serum samples. Itaconic acid ( P = 0.0003), with a false discovery rate of 0.012, was found to be significantly more abundant in women who subsequently developed gestational diabetes mellitus, when compared to controls with uncomplicated pregnancies. The current pilot study found that itaconic acid may have potential as a novel biomarker in early pregnancy to predict the subsequent development of gestational diabetes mellitus. However, the findings from this pilot study require validation with a larger, diverse population before translation into the clinical setting. [ABSTRACT FROM AUTHOR]

Farnesol is a quorum-sensing molecule ( QSM) produced, and sensed, by the polymorphic fungus, Candida albicans. This cell-to-cell communication molecule is known to suppress the hyphal formation of C. albicans at high cell density. Despite many studies investigating the signalling mechanisms by which QSMs influence the morphogenesis of C. albicans, the downstream metabolic effect of these signalling pathways in response to farnesol-mediated morphogenesis remains obscure. Here, we have used metabolomics to investigate the metabolic response of C. albicans upon exposure to farnesol under hyphae-inducing conditions. We have found a general up-regulation of central carbon metabolic pathways when hyphal formation was suppressed by farnesol evidenced by a considerably larger number of central carbon metabolic intermediates detected under this condition at an overall lower intracellular level. By combining the metabolic profiles from farnesol-exposed cells with previous metabolomics data for C. albicans undergoing morphogenesis, we have identified several metabolic pathways that are likely to be associated with the morphogenetic process of C. albicans, as well as metabolic pathways such as those involved in lipid metabolism that appeared to be specifically affected by farnesol. Therefore, our results provide important new insights into the metabolic role of farnesol in C. albicans metabolism. [ABSTRACT FROM AUTHOR]

Abstract: Glyoxylate biosynthesis in Saccharomyces cerevisiae is traditionally mainly ascribed to the reaction catalyzed by isocitrate lyase (Icl), which converts isocitrate to glyoxylate and succinate. However, Icl is generally reported to be repressed by glucose and yet glyoxylate is detected at high levels in S. cerevisiae extracts during cultivation on glucose. In bacteria there is an alternative pathway for glyoxylate biosynthesis that involves a direct oxidation of glycine. Therefore, we investigated the glycine metabolism in S. cerevisiae coupling metabolomics data and 13C-isotope-labeling analysis of two reference strains and a mutant with a deletion in a gene encoding an alanine:glyoxylate aminotransferase. The strains were cultivated on minimal medium containing glucose or galactose, and 13C-glycine as sole nitrogen source. Glyoxylate presented 13C-labeling in all cultivation conditions. Furthermore, glyoxylate seemed to be converted to 2-oxovalerate, an unusual metabolite in S. cerevisiae. 2-Oxovalerate can possibly be converted to 2-oxoisovalerate, a key precursor in the biosynthesis of branched-chain amino acids. Hence, we propose a new pathway for glycine catabolism and glyoxylate biosynthesis in S. cerevisiae that seems not to be repressed by glucose and is active under both aerobic and anaerobic conditions. This work demonstrates the great potential of coupling metabolomics data and isotope-labeling analysis for pathway reconstructions. [Copyright &y& Elsevier]

Abstract: Candida albicans is a polymorphic fungus that has the ability to rapidly switch between yeast and filamentous forms. The morphological transition appears to be a critical virulence factor of this fungus. Recent studies have elucidated the signal transduction pathways and quorum sensing molecules that affect the morphological transition of C. albicans. The metabolic mechanisms that recognize, and respond to, such signaling molecules and promote the morphological changes at a system level, however, remain unknown. Here we review the metabolic basis of C. albicans morphogenesis and we discuss the role of primary metabolic pathways and quorum sensing molecules in the morphogenetic process. We have reconstructed, in silico, the central carbon metabolism and sterol biosynthesis of C. albicans based on its genome sequence, highlighting the metabolic pathways associated with the dimorphic transition and virulence as well as pathways involved in the biosynthesis of important quorum sensing molecules. [Copyright &y& Elsevier]

Early lifestages of the Pacific oyster ( Crassostrea gigas ) are highly susceptible to infection by OsHV-1 μVar, but little information exists regarding metabolic or pathophysiological responses of larval hosts. Using a metabolomics approach, we identified a range of metabolic and immunological responses in oyster larvae exposed to OsHV-1 μVar; some of which have not previously been reported in molluscs. Multivariate analyses of entire metabolite profiles were able to separate infected from non-infected larvae. Correlation analysis revealed the presence of major perturbations in the underlying biochemical networks and secondary pathway analysis of functionally-related metabolites identified a number of prospective pathways differentially regulated in virus-exposed larvae. These results provide new insights into the pathogenic mechanisms of OsHV-1 infection in oyster larvae, which may be applied to develop disease mitigation strategies and/or as new phenotypic information for selective breeding programmes aiming to enhance viral resistance. [ABSTRACT FROM AUTHOR]