Global metabolite analysis of yeast: evaluation of sample preparation methods

Loss of Volatile Metabolites during Concentration of Metabolomic Extracts

Volatile metabolites can be lost during the preanalytical stage of metabolomic analysis. This work is aimed at the experimental and theoretical study of mechanisms of volatile substance evaporation and retention in the residues during the drying of extract solutions. We demonstrate that solvent evaporation leads to the unavoidable loss of nondissociating volatile metabolites with low boiling points and high vapor pressures (such as acetone and ethanol). The retention of dissociating volatile compounds (primarily organic acids RH) during the evaporation depends on the presence of buffer salts in solution, which are responsible for maintaining the neutral pH. An acid remains in the solution as long as it is present predominantly in the dissociated R- state. At the very last stage of solvent evaporation, buffer salts precipitate, forming a solid matrix for metabolite trapping in the residue. At the same time, buffer precipitation leads to a decrease of the solution pH, increase of the portion of RH in associated state, and acceleration of RH volatilization. The RH recovery is thus determined by the competition between the solute volatilization in the associated RH form and metabolite trapping in the solid matrix. The retention of volatile acids in the residue after extract drying can be improved either by adding buffer salts to maintain high pH or by incomplete sample drying.

Screening of Saccharomyces cerevisiae metabolite transporters by 13C isotope substrate labeling

The transportome of Saccharomyces cerevisiae comprises approximately 340 membrane-bound proteins, of which very few are well-characterized. Elucidating transporter proteins' function is essential not only for understanding central cellular processes in metabolite exchange with the external milieu but also for optimizing the production of value-added compounds in microbial cell factories. Here, we describe the application of 13C-labeled stable isotopes and detection by targeted LC-MS/MS as a screening tool for identifying Saccharomyces cerevisiae metabolite transporters. We compare the transport assay's sensitivity, reproducibility, and accuracy in yeast transporter mutant cell lines and Xenopus oocytes. As proof of principle, we analyzed the transport profiles of five yeast amino acid transporters. We first cultured yeast transporter deletion or overexpression mutants on uniformly labeled 13C-glucose and then screened their ability to facilitate the uptake or export of an unlabeled pool of amino acids. Individual transporters were further studied by heterologous expression in Xenopus oocytes, followed by an uptake assay with 13C labeled yeast extract. Uptake assays in Xenopus oocytes showed higher reproducibility and accuracy. Although having lower accuracy, the results from S. cerevisiae indicated the system's potential for initial high-throughput screening for native metabolite transporters. We partially confirmed previously reported substrates for all five amino acid transporters. In addition, we propose broader substrate specificity for two of the transporter proteins. The method presented here demonstrates the application of a comprehensive screening platform for the knowledge expansion of the transporter-substrate relationship for native metabolites in S. cerevisiae.

Endo metabolomic profiling of flor and wine yeasts reveals a positive correlation between intracellular metabolite load and the specific glycolytic flux during wine fermentation

This study explored the intracellular metabolic variations between 17 strains of Saccharomyces cerevisiae belonging to two different genetic populations: flor and wine yeasts, in the context of alcoholic fermentation. These two populations are closely related as they share the same ecological niche but display distinct genetic characteristics. A protocol was developed for intracellular metabolites extraction and 1H-NMR analysis. This methodology allowed us to identify and quantify 21 intracellular metabolites at two different fermentation steps: the exponential and stationary phases. This work provided evidence of significant differences in the abundance of intracellular metabolites, which are strain- and time-dependent, thus revealing complex interactions. Moreover, the differences in abundance appeared to be correlated with life-history traits such as average cell size and specific glycolytic flux, which revealed unsuspected phenotypic correlations between metabolite load and fermentation activity.

Untargeted Metabolomics Reveals Lipid Impairment in the Liver of Adult Zebrafish (Danio rerio) Exposed to Carbendazim

Carbendazim is a systemic fungicide used in several countries, particularly in Brazil. However, studies suggest that it is related to the promotion of tumors, endocrine disruption, and toxicity to organisms, among other effects. As a result, carbendazim is not allowed in the United States, Australia, and some European Union countries. Therefore, further studies are necessary to evaluate its effects, and zebrafish is a model routinely used to provide relevant information regarding the acute and long-term effects of xenobiotics. In this way, zebrafish water tank samples (water samples from aquari containing zebrafish) and liver samples from animals exposed to carbendazim at a concentration of 120 μg/L were analyzed by liquid chromatography coupled to high-resolution mass spectrometry, followed by multivariate and univariate statistical analyses, using the metabolomics approach. Our results suggest impairment of lipid metabolism with a consequent increase in intrahepatic lipids and endocrine disruption. Furthermore, the results suggest two endogenous metabolites as potential biomarkers to determine carbendazim exposure. Finally, the present study showed that it is possible to use zebrafish water tank samples to assess the dysregulation of endogenous metabolites to understand biological effects. Environ Toxicol Chem 2023;42:437-448. © 2022 SETAC.

The effect of root hairs on exudate composition: a comparative non-targeted metabolomics approach

Root exudation is a major pathway of organic carbon input into soils. It affects soil physical properties, element solubility as well as speciation, and impacts the microbial community in the rhizosphere. Root exudates contain a large number of primary and secondary plant metabolites, and the amount and composition are highly variable depending on plant species and developmental stage. Detailed information about exudate composition will allow for a better understanding of exudate-driven rhizosphere processes and their feedback loops. Although non-targeted metabolomics by high-resolution mass spectrometry is an established tool to characterize root exudate composition, the extent and depth of the information obtained depends strongly on the analytical approach applied. Here, two genotypes of Zea mays L., differing in root hair development, were used to compare six mass spectrometric approaches for the analysis of root exudates. Reversed-phase liquid chromatography and hydrophilic interaction liquid chromatography combined with time-of-flight mass spectrometry (LC-TOF-MS), as well as direct infusion Fourier-transform ion cyclotron resonance mass spectrometry (DI-FT-ICR-MS), were applied with positive and negative ionization mode. By using the same statistical workflow, the six approaches resulted in different numbers of detected molecular features, ranging from 176 to 889, with a fraction of 48 to 69% of significant features (fold change between the two genotypes of > 2 and p-value < 0.05). All approaches revealed the same trend between genotypes, namely up-regulation of most metabolites in the root hair defective mutant (rth3). These results were in agreement with the higher total carbon and nitrogen exudation rate of the rth3-mutant as compared to the corresponding wild-type maize (WT). However, only a small fraction of features were commonly found across the different analytical approaches (20-79 features, 13-31% of the rth3-mutant up-regulated molecular formulas), highlighting the need for different mass spectrometric approaches to obtain a more comprehensive view into the composition of root exudates. In summary, 111 rth3-mutant up-regulated compounds (92 different molecular formulas) were detected with at least two different analytical approaches, while no WT up-regulated compound was found by both, LC-TOF-MS and DI-FT-ICR-MS. Zea mays L. exudate features obtained with multiple analytical approaches in our study were matched against the metabolome database of Zea mays L. (KEGG) and revealed 49 putative metabolites based on their molecular formula.

Optimized Fast Filtration-Based Sampling and Extraction Enables Precise and Absolute Quantification of the Escherichia coli Central Carbon Metabolome

Precise and accurate quantification is a prerequisite for interpretation of targeted metabolomics data, but this task is challenged by the inherent instability of the analytes. The sampling, quenching, extraction, and sample purification conditions required to recover and stabilize metabolites in representative extracts have also been proven highly dependent on species-specific properties. For Escherichia coli, unspecific leakage has been demonstrated for conventional microbial metabolomics sampling protocols. We herein present a fast filtration-based sampling protocol for this widely applied model organism, focusing on pitfalls such as inefficient filtration, selective loss of biomass, matrix contamination, and membrane permeabilization and leakage. We evaluate the effect of and need for removal of extracellular components and demonstrate how residual salts can challenge analytical accuracy of hyphenated mass spectrometric analyses, even when sophisticated correction strategies are applied. Laborious extraction procedures are bypassed by direct extraction in cold acetonitrile:water:methanol (3:5:2, v/v%), ensuring compatibility with sample concentration and thus, any downstream analysis. By applying this protocol, we achieve and demonstrate high precision and low metabolite turnover, and, followingly, minimal perturbation of the inherent metabolic state. This allows us to herein report absolute intracellular concentrations in E. coli and explore its central carbon metabolome at several commonly applied cultivation conditions.

The effects of acetate and glucose on carbon fixation and carbon utilization in mixotrophy of Haematococcus pluvialis

The culture method using sodium acetate and glucose, widely used as organic carbon sources in the mixotrophy of Haematococcus pluvialis, was compared with its autotrophy. In the 12-day culture, mixotrophy using sodium acetate and glucose increased by 40.4% and 77.1%, respectively, compared to autotrophy, but the mechanisms for the increasing biomass were different. The analysis of the mechanism was divided into autotrophic and heterotrophic metabolism. The mixotrophy with glucose increased the biomass by directly supplying the substrate and ATP to the TCA cycle while inhibiting photosynthesis. Gene expressions related to glycolysis and carbon fixation pathway were confirmed in autotrophy and mixotrophy with glucose and acetate. The metabolism predicted in the mixotrophy with acetate and glucose was proposed via autotrophic and heterotrophic metabolism analysis. The mechanism of Haematococcus pluvialis under mixotrophic conditions with high CO₂ concentration was confirmed through this study.

SiMeEx, a simplified method for metabolite extraction of adherent mammalian cells

A reliable method for metabolite extraction is central to mass spectrometry-based metabolomics. However, existing methods are lengthy, mostly due to the step of scraping cells from cell culture vessels, which restricts metabolomics in broader application such as lower cell numbers and high-throughput studies. Here, we present a simplified metabolite extraction (SiMeEx) method, to efficiently and quickly extract metabolites from adherent mammalian cells. Our method excludes the cell scraping step and therefore allows for a more efficient extraction of polar metabolites in less than 30 min per 12-well plate. We demonstrate that SiMeEx achieves the same metabolite recovery as using a standard method containing a scraping step, in various immortalized and primary cells. Omitting cell scraping does not compromise the performance of non-targeted and targeted GC-MS analysis, but enables metabolome analysis of cell culture on smaller well sizes down to 96-well plates. Therefore, SiMeEx demonstrates advantages not only on time and resources, but also on the applicability in high-throughput studies.

Metabolomics and modelling approaches for systems metabolic engineering

Metabolic engineering involves the manipulation of microbes to produce desirable compounds through genetic engineering or synthetic biology approaches. Metabolomics involves the quantitation of intracellular and extracellular metabolites, where mass spectrometry and nuclear magnetic resonance based analytical instrumentation are often used. Here, the experimental designs, sample preparations, metabolite quenching and extraction are essential to the quantitative metabolomics workflow. The resultant metabolomics data can then be used with computational modelling approaches, such as kinetic and constraint-based modelling, to better understand underlying mechanisms and bottlenecks in the synthesis of desired compounds, thereby accelerating research through systems metabolic engineering. Constraint-based models, such as genome scale models, have been used successfully to enhance the yield of desired compounds from engineered microbes, however, unlike kinetic or dynamic models, constraint-based models do not incorporate regulatory effects. Nevertheless, the lack of time-series metabolomic data generation has hindered the usefulness of dynamic models till today. In this review, we show that improvements in automation, dynamic real-time analysis and high throughput workflows can drive the generation of more quality data for dynamic models through time-series metabolomics data generation. Spatial metabolomics also has the potential to be used as a complementary approach to conventional metabolomics, as it provides information on the localization of metabolites. However, more effort must be undertaken to identify metabolites from spatial metabolomics data derived through imaging mass spectrometry, where machine learning approaches could prove useful. On the other hand, single-cell metabolomics has also seen rapid growth, where understanding cell-cell heterogeneity can provide more insights into efficient metabolic engineering of microbes. Moving forward, with potential improvements in automation, dynamic real-time analysis, high throughput workflows, and spatial metabolomics, more data can be produced and studied using machine learning algorithms, in conjunction with dynamic models, to generate qualitative and quantitative predictions to advance metabolic engineering efforts.

Evaluation and optimization of analytical procedure and sample preparation for polar Streptomyces albus J1074 metabolome profiling

Metabolomics is an essential discipline in omics technology that promotes research on the biology of microbial systems. Streptomyces albus J1074 is a model organism used in fundamental research and industrial microbiology. Nevertheless, a comprehensive and standardized method for analyzing the metabolome of S. albus J1074 is yet to be developed. Thus, we comprehensively evaluated and optimized the analytical procedure and sample preparation for profiling polar metabolites using hydrophilic interaction liquid chromatography (HILIC) coupled with high-resolution mass spectrometry (HRMS). We systematically examined the HILIC columns, quenching solutions, sample-to-quenching ratios, and extraction methods. Then, the optimal protocol was used to investigate the dynamic intracellular polar metabolite profile of the engineered S. albus J1074 strains during spinosad (spinosyn A and spinosyn D) fermentation. A total of 3648 compounds were detected, and 83 metabolites were matched to the standards. The intracellular metabolomic profiles of engineered S. albus J1074 strains (ADE-AP and OE3) were detected; furthermore, their metabolomes in different stages were analyzed to reveal the reasons for their differences in their spinosad production, as well as the current metabolic limitation of heterologous spinosad production in S. albus J1074. The HILIC-HRMS method is a valuable tool for investigating polar metabolomes, and provides a reference methodology to study other Streptomyces metabolomes.

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A HILIC-HRMS method was developed for polar metabolome profiling.

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Sample preparation protocol for Streptomyces albus J1074 intracellular metabolites was studied for the first time.

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This study revealed the possible reasons for different production of spinosad of engineered S. albus J1074 strains.

A targeted metabolomics method for extra- and intracellular metabolite quantification covering the complete monolignol and lignan synthesis pathway

Microbial synthesis of monolignols and lignans from simple substrates is a promising alternative to plant extraction. Bottlenecks and byproduct formation during heterologous production require targeted metabolomics tools for pathway optimization.

In contrast to available fractional methods, we established a comprehensive targeted metabolomics method. It enables the quantification of 17 extra- and intracellular metabolites of the monolignol and lignan pathway, ranging from amino acids to pluviatolide. Several cell disruption methods were compared. Hot water extraction was best suited regarding monolignol and lignan stability as well as extraction efficacy. The method was applied to compare enzymes for alleviating bottlenecks during heterologous monolignol and lignan production in E. coli. Variants of tyrosine ammonia-lyase had a considerable influence on titers of subsequent metabolites. The choice of multicopper oxidase greatly affected the accumulation of lignans. Metabolite titers were monitored during batch fermentation of either monolignol or lignan-producing recombinant E. coli strains, demonstrating the dynamic accumulation of metabolites.

The new method enables efficient time-resolved targeted metabolomics of monolignol- and lignan-producing E. coli. It facilitates bottleneck identification and byproduct quantification, making it a valuable tool for further pathway engineering studies. This method will benefit the bioprocess development of biotransformation or fermentation approaches for microbial lignan production.

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Monolignols and lignans were heterologously produced in Escherichia coli

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A targeted metabolomics method was developed covering 17 out of 20 metabolites.

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Hot water extraction is well suited for intracellular monolignol & lignan analysis.

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Metabolite accumulation identifies bottlenecks and dynamic activity.

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Assessment of pathway activity enables efficient cell factory engineering.

Atrazine Exposure Induces Hepatic Metabolism Disorder in Male Adult Zebrafish

Atrazine (ATZ) is a herbicide used in agricultural production and has been detected in surface water due to its widespread use worldwide. This may pose a threat to the health of aquatic animals. To explore the ATZ−induced hepatic metabolism disorder, male zebrafish were exposed to 300 and 1000 μg/L ATZ for 21 days, respectively. The results revealed that ATZ exposure significantly reduced hepatic triglyceride (TG) levels, while significantly (p < 0.05) increased pyruvate (PYR) and total cholesterol (TC) levels. In addition, the liver sample from the 1000 μg/L ATZ−treated group was used for GC/MS metabolomic analysis. The principal component analysis (PCA) model showed significant separation of the 1000 μg/L ATZ group from the control group, indicating that ATZ exposure altered hepatic metabolism in male adult zebrafish. A total of 29 significantly (p < 0.05) different metabolites were observed and identified in the ATZ−treated group. Moreover, the most disturbed pathways by ATZ were the arginine and proline metabolic pathways, followed by the glutathione metabolic pathway. Three and two metabolites were significantly altered in the arginine and proline metabolic pathways and glutathione metabolic pathway, respectively. Based on these results, we suggested that ATZ was capable of altering liver metabolism in zebrafish and that its ecological risk to aquatic organisms cannot be ignored.

MetHoS: a platform for large-scale processing, storage and analysis of metabolomics data

BACKGROUND

Modern mass spectrometry has revolutionized the detection and analysis of metabolites but likewise, let the data skyrocket with repositories for metabolomics data filling up with thousands of datasets. While there are many software tools for the analysis of individual experiments with a few to dozens of chromatograms, we see a demand for a contemporary software solution capable of processing and analyzing hundreds or even thousands of experiments in an integrative manner with standardized workflows.

RESULTS

Here, we introduce MetHoS as an automated web-based software platform for the processing, storage and analysis of great amounts of mass spectrometry-based metabolomics data sets originating from different metabolomics studies. MetHoS is based on Big Data frameworks to enable parallel processing, distributed storage and distributed analysis of even larger data sets across clusters of computers in a highly scalable manner. It has been designed to allow the processing and analysis of any amount of experiments and samples in an integrative manner. In order to demonstrate the capabilities of MetHoS, thousands of experiments were downloaded from the MetaboLights database and used to perform a large-scale processing, storage and statistical analysis in a proof-of-concept study.

CONCLUSIONS

MetHoS is suitable for large-scale processing, storage and analysis of metabolomics data aiming at untargeted metabolomic analyses. It is freely available at: https://methos.cebitec.uni-bielefeld.de/ . Users interested in analyzing their own data are encouraged to apply for an account.

Metabolomic profiling of Spathaspora passalidarum fermentations reveals mechanisms that overcome hemicellulose hydrolysate inhibitors

Understanding the mechanisms involved in tolerance to inhibitors is the first step in developing robust yeasts for industrial second-generation ethanol (E2G) production. Here, we used ultra-high-performance liquid chromatography tandem mass spectrometry (UHPLC-MS/MS) and MetaboAnalyst 4.0 for analysis of MS data to examine the changes in the metabolic profile of the yeast Spathaspora passalidarum during early fermentation of hemicellulosic hydrolysates containing high or low levels of inhibitors (referred to as control hydrolysate or CH and strategy hydrolysate or SH, respectively). During fermentation of SH, the maximum ethanol production was 16 g L^-1 with a yield of 0.28 g g^-1 and productivity of 0.22 g L^-1 h^-1, whereas maximum ethanol production in CH fermentation was 1.74 g L^-1 with a yield of 0.11 g g^-1 and productivity of 0.01 g L^-1 h^-1. The high level of inhibitors in CH induced complex physiological and biochemical responses related to stress tolerance in S. passalidarum. This yeast converted compounds with aldehyde groups (hydroxymethylfurfural, furfural, 4-hydroxybenzaldehyde, syringaldehyde, and vanillin) into less toxic compounds, and inhibitors were found to reduce cell viability and ethanol production. Intracellularly, high levels of inhibitors altered the energy homeostasis and redox balance, resulting in lower levels of ATP and NADPH, while that of glycolytic, pentose phosphate, and tricarboxylic acid (TCA) cycle pathways were the most affected, being the catabolism of glucogenic amino acids, the main cellular response to inhibitor-induced stress. This metabolomic investigation reveals interesting targets for metabolic engineering of ethanologenic yeast strains tolerant against multiple inhibitors for E2G production. KEY POINTS: • Inhibitors in the hydrolysates affected the yeast's redox balance and energy status. • Inhibitors altered the glycolytic, pentose phosphate, TCA cycle and amino acid pathways. • S. passalidarum converted aldehyde groups into less toxic compounds.

Precursor Quantitation Methods for Next Generation Food Production

Food is essential for human survival. Nowadays, traditional agriculture faces challenges in balancing the need of sustainable environmental development and the rising food demand caused by an increasing population. In addition, in the emerging of consumers' awareness of health related issues bring a growing trend towards novel nature-based food additives. Synthetic biology, using engineered microbial cell factories for production of various molecules, shows great advantages for generating food alternatives and additives, which not only relieve the pressure laid on tradition agriculture, but also create a new stage in healthy and sustainable food supplement. The biosynthesis of food components (protein, fats, carbohydrates or vitamins) in engineered microbial cells often involves cellular central metabolic pathways, where common precursors are processed into different proteins and products. Quantitation of the precursors provides information of the metabolic flux and intracellular metabolic state, giving guidance for precise pathway engineering. In this review, we summarized the quantitation methods for most cellular biosynthetic precursors, including energy molecules and co-factors involved in redox-reactions. It will also be useful for studies worked on pathway engineering of other microbial-derived metabolites. Finally, advantages and limitations of each method are discussed.

Improved Sample Preparation for Untargeted Metabolomics Profiling of Escherichia coli

Metabolomics is a powerful tool that can systematically describe global changes in the metabolome of microbes, thus improving our understanding of the mechanisms of action of antibiotics and facilitating the development of next-generation antibacterial therapies. However, current sample preparation methods are not efficient or reliable for studying the effects of antibiotics on microbes. In the present study, we reported a novel sample preparation approach using cold methanol/ethylene glycol for quenching Escherichia coli, thus overcoming the loss of intracellular metabolites caused by cell membrane damage. After evaluating the extraction efficiency of several extraction methods, we employed the optimized workflow to profile the metabolome of E. coli exposed to cephalexin. In doing so, we proved the utility of the proposed approach and provided insights into the comprehensive metabolic alterations associated with antibiotic treatment.

IMPORTANCE The emergence and global spread of multidrug-resistant bacteria and genes are a global problem. It is critical to understand the interactions between antibiotics and bacteria and find alternative treatments for infections when we are moving closer to a postantibiotic era. It has been demonstrated that the bacterial metabolic environment plays an important role in the modulation of antibiotic susceptibility and efficacy. In the present study, we proposed a novel metabolomic approach for intracellular metabolite profiling of E. coli, which can be used to investigate the metabolite alterations of bacteria caused by antibiotic treatment. Further understanding of antibiotic-induced perturbations of bacterial metabolism would facilitate the discovery of new therapeutic targets and pathways.

Identification of potential serum metabolic biomarkers for patient with keratoconus using untargeted metabolomics approach

This study aimed to investigate the metabolite differences between patients with keratoconus and control subjects and identify potential serum biomarkers for keratoconus using a non-targeted metabolomics approach. Venous blood samples were obtained from patients with keratoconus (n = 20) as well as from age-, gender- and race-matched control subjects (n = 20). Metabolites extracted from serum were separated and analyzed by liquid chromatography/quadrupole time-of-flight mass spectrometer. Processing of raw data and analysis of the data files was performed using Agilent Mass Hunter Qualitative software. The identified metabolites were subjected to a principal component and hierarchical cluster analysis. Appropriate statistical tests were used to analyze the metabolomic profiling data. Together, the analysis revealed that the dehydroepiandrosterone sulfate from the steroidal hormone synthesis pathway was significantly upregulated in patients with keratoconus (p < 0.05). Also, a combination of eicosanoids from the arachidonic acid pathway, mainly prostaglandin F2α, prostaglandin A2, 16,16-dimethyl prostaglandin E2, and 5-hydroxyeicosatetraenoic acid were collectively up-regulated as a group in keratoconus patients (p < 0.05). On the other hand, glycerophospholipid PS(17:2(9Z,12Z)/20:4(5Z,8Z,11Z,14Z)) was found to be significantly upregulated in the metabolomics profiles of control subjects (p < 0.05). The differently regulated metabolites provide insights into the pathophysiology of keratoconus and could potentially be used as biomarkers for keratoconus to aid in screening for individuals at risk hence, enabling early diagnosis and timely monitoring of disease.

Influence of Extraction Solvent on Nontargeted Metabolomics Analysis of Enrichment Reactor Cultures Performing Enhanced Biological Phosphorus Removal (EBPR)

Metabolome profiling is becoming more commonly used in the study of complex microbial communities and microbiomes; however, to date, little information is available concerning appropriate extraction procedures. We studied the influence of different extraction solvent mixtures on untargeted metabolomics analysis of two continuous culture enrichment communities performing enhanced biological phosphate removal (EBPR), with each enrichment targeting distinct populations of polyphosphate-accumulating organisms (PAOs). We employed one non-polar solvent and up to four polar solvents for extracting metabolites from biomass. In one of the reactor microbial communities, we surveyed both intracellular and extracellular metabolites using the same set of solvents. All samples were analysed using ultra-performance liquid chromatography mass spectrometry (UPLC-MS). UPLC-MS data obtained from polar and non-polar solvents were analysed separately and evaluated using extent of repeatability, overall extraction capacity and the extent of differential abundance between physiological states. Despite both reactors demonstrating the same bioprocess phenotype, the most appropriate extraction method was biomass specific, with methanol: water (50:50 v/v) and methanol: chloroform: water (40:40:20 v/v) being chosen as the most appropriate for each of the two different bioreactors, respectively. Our approach provides new data on the influence of solvent choice on the untargeted surveys of the metabolome of PAO enriched EBPR communities and suggests that metabolome extraction methods need to be carefully tailored to the specific complex microbial community under study.

Metabolomics: small molecules that matter more

Metabolomics, an analytical study with high-throughput profiling, helps to understand interactions within a biological system. Small molecules, called metabolites or metabolomes with the size of <1500 Da, depict the status of a biological system in a different manner. Currently, we are in need to globally analyze the metabolome and the pathways involved in healthy, as well as diseased conditions, for possible therapeutic applications. Metabolome analysis has revealed high-abundance molecules during different conditions such as diet, environmental stress, microbiota, and disease and treatment states. As a result, it is hard to understand the complete and stable network of metabolites of a biological system. This review helps readers know the available techniques to study metabolomics in addition to other major omics such as genomics, transcriptomics, and proteomics. This review also discusses the metabolomics in various pathological conditions and the importance of metabolomics in therapeutic applications.

Generic multicriteria approach to determine the best precipitation agent for removal of biomacromolecules prior to non-targeted metabolic analysis

The removal of biomacromolecules from biofluids decreases the sample complexity and lower electrospray suppression effects. Furthermore, it can increase the analysis sensitivity, precision, and selectivity. Often removal approaches evaluate the model based on a single criterion, like protein removed or response of one of few specific metabolites. In this study, we used a multicriteria approach to test the effect of using the solvents methanol and acetonitrile (organic solvent precipitation), trichloroacetic acid (acidic precipitation) and ammonium sulphate (salting out) to remove biomacromolecules from a downstream recovery process from a bacillus fermentation. The downstream recovery process intermediates were analysed using reversed-phase ultra-high-pressure liquid chromatography with electrospray ionisation and high-resolution time-of-flight mass spectrometry detection. To evaluate the pre-treatment agents the following multicriteria was applied i) practical considerations, ii) total amino acid in the precipitated pellet, iii) putative identification of the molecules removed or created by the different treatments, iv) coherence between high quality extracted ion chromatograms (repeatability of DW-CODA) and v) replicate consistency from principal component analysis score values obtained by using the CHEMometric analysis of sections of Selected Ion Chromatograms (CHEMSIC) method. This study presents a generic workflow to find the best pre-treatment for removing bio-macromolecules from biofluids with a multicriteria approach. In our case, the best protein removal strategy for downstream recovery intermediates was acetonitrile precipitation. This method showed high precision, created few artefact peaks compared to simple sample dilution, and mainly removed small peptides.

Genomic characterization of a diazotrophic microbiota associated with maize aerial root mucilage

A geographically isolated maize landrace cultivated on nitrogen-depleted fields without synthetic fertilizer in the Sierra Mixe region of Oaxaca, Mexico utilizes nitrogen derived from the atmosphere and develops an extensive network of mucilage-secreting aerial roots that harbors a diazotrophic (N2-fixing) microbiota. Targeting these diazotrophs, we selected nearly 600 microbes of a collection obtained from mucilage and confirmed their ability to incorporate heavy nitrogen (15N2) metabolites in vitro. Sequencing their genomes and conducting comparative bioinformatic analyses showed that these genomes had substantial phylogenetic diversity. We examined each diazotroph genome for the presence of nif genes essential to nitrogen fixation (nifHDKENB) and carbohydrate utilization genes relevant to the mucilage polysaccharide digestion. These analyses identified diazotrophs that possessed the canonical nif gene operons, as well as many other operon configurations with concomitant fixation and release of >700 different 15N labeled metabolites. We further demonstrated that many diazotrophs possessed alternative nif gene operons and confirmed their genomic potential to derive chemical energy from mucilage polysaccharide to fuel nitrogen fixation. These results confirm that some diazotrophic bacteria associated with Sierra Mixe maize were capable of incorporating atmospheric nitrogen into their small molecule extracellular metabolites through multiple nif gene configurations while others were able to fix nitrogen without the canonical (nifHDKENB) genes.

An Optimized Dual Extraction Method for the Simultaneous and Accurate Analysis of Polar Metabolites and Lipids Carried out on Single Biological Samples

The functional understanding of metabolic changes requires both a significant investigation into metabolic pathways, as enabled by global metabolomics and lipidomics approaches, and the comprehensive and accurate exploration of specific key pathways. To answer this pivotal challenge, we propose an optimized approach, which combines an efficient sample preparation, aiming to reduce the variability, with a biphasic extraction method, where both the aqueous and organic phases of the same sample are used for mass spectrometry analyses. We demonstrated that this double extraction protocol allows working with one single sample without decreasing the metabolome and lipidome coverage. It enables the targeted analysis of 40 polar metabolites and 82 lipids, together with the absolute quantification of 32 polar metabolites, providing comprehensive coverage and quantitative measurement of the metabolites involved in central carbon energy pathways. With this method, we evidenced modulations of several lipids, amino acids, and energy metabolites in HepaRG cells exposed to fenofibrate, a model hepatic toxicant, and metabolic modulator. This new protocol is particularly relevant for experiments involving limited amounts of biological material and for functional metabolic explorations and is thus of particular interest for studies aiming to decipher the effects and modes of action of metabolic disrupting compounds.

Comprehensive Vitamer Profiling of Folate Mono- and Polyglutamates in Baker's Yeast (Saccharomyces cerevisiae) as a Function of Different Sample Preparation Procedures

Folates are a group of B9 vitamins playing an important role in many metabolic processes such as methylation reactions, nucleotide synthesis or oxidation and reduction processes. However, humans are not able to synthesize folates de novo and thus rely on external sources thereof. Baker's yeast (Saccharomyces cerevisiae) has been shown to produce high amounts of this vitamin but extensive identification of its folate metabolism is still lacking. Therefore, we optimized and compared different sample preparation and purification procedures applying solid phase extraction (SPE). Strong anion exchange (SAX), C18 and hydrophilic-lipophilic-balanced (HLB) materials were tested for their applicability in future metabolomics studies. SAX turned out to be the preferred material for the quantitative purification of folates. Qualification of several folate vitamers was achieved by ultra-high pressure liquid chromatography quadrupole time of flight mass spectrometry (UHPLC-Q-ToF-MS) measurements and quantification was performed by liquid chromatography tandem mass spectrometry (LC-MS/MS) applying stable isotope dilution assays (SIDAs). The oxidation product s-pyrazino-triazine (MeFox) was included into the SIDA method for total folate determination and validation. Applying the best protocol (SAX) in regard to folate recovery, we analyzed 32 different vitamers in different polyglutamate states up to nonaglutamates, of which we could further identify 26 vitamers based on tandem-MS (MS2) spectra. Total folate quantification revealed differences in formyl folate contents depending on the cartridge chemistry used for purification. These are supposedly a result of interconversion reactions occurring during sample preparation due to variation in pH adjustments for the different purification protocols. The occurrence of interconversion and oxidation reactions should be taken into consideration in sample preparation procedures for metabolomics analyses with a focus on folates.

Metabolomics and biomarkers in ocular matrix: beyond ocular diseases

According to the recent report, there are 870 million people suffer from ocular diseases worldwide. The present approaches for diagnosis are morphological examination, imaging examination and immunological examination, regrettably, they lack of sensitivity and difficult to make a definite diagnosis in the early stage. Systemic biology as an effective method has been used in clinical diagnosis and treatment for diseases, especially metabolomics which is more attractive with high sensitivity and accuracy. Although previous researches had been confirmed that endogenous metabolites in the ocular matrix play a crucial role in the progress of diseases related diseases, the standard protocols and systematic summary about the biomarker researches based on ocular matrix has not been established. This review article highlights the pretreatment for ocular matrix and the new biomarkers expressed by the eye diseases, expected to promote the application of biomarkers in the diagnosis and treatment of eye diseases.

Metabolomics analysis of Actinosynnema pretiosum with improved AP-3 production by enhancing UDP-glucose biosynthesis

Ansamitocin P-3 (AP-3) shows strong anticancer effects and has used as a payload for antibody-drug conjugates. Our previous study have shown that although genetically engineered Actinosynnema pretiosum strains with enhanced UDP-glucose (UDPG) biosynthesis displayed improved AP-3 production compared to the wild-type strain, the increase in yield was far from meeting the industrial demand. In this study, comparative metabolomics analysis complemented with quantitative real-time PCR analysis was performed for the wild-type strain and two mutants (OpgmOugp, ΔzwfΔgnd) to identify possible metabolic bottlenecks and non-intuitive targets for further enhancement of AP-3 production. We observed that enhancing intracellular UDPG availability facilitated the accumulation of intracellular N-demethyl-AP-3 and AP-3, where the transporting of them outside the cell still needs to be developed. We also found that the UDPG biosynthesis was closely associated with the availability of fructose in the medium and a suitable fructose feeding strategy could promote the further improvement of AP-3 titer. In addition, pathway abundance analysis revealed that undesired fatty acid accumulation and down-regulation of amino acid metabolism may be unfavorable for ansamitocin biosynthesis in later stage of production. These results indicate that genetic modification of the UDPG biosynthetic pathways may have pleiotropic effects on AP-3 production. Efforts must be made to eliminate these newly identified metabolic bottlenecks to boost AP-3 production in A. pretiosum.

Important Considerations for Sample Collection in Metabolomics Studies with a Special Focus on Applications to Liver Functions

Metabolomics has found numerous applications in the study of liver metabolism in health and disease. Metabolomics studies can be conducted in a variety of biological matrices ranging from easily accessible biofluids such as urine, blood or feces, to organs, tissues or even cells. Sample collection and storage are critical steps for which standard operating procedures must be followed. Inappropriate sample collection or storage can indeed result in high variability, interferences with instrumentation or degradation of metabolites. In this review, we will first highlight important general factors that should be considered when planning sample collection in the study design of metabolomic studies, such as nutritional status and circadian rhythm. Then, we will discuss in more detail the specific procedures that have been described for optimal pre-analytical handling of the most commonly used matrices (urine, blood, feces, tissues and cells).

Extracting and Measuring dNTP Pools in Saccharomyces cerevisiae

Regulation of dNTP pools in an intracellular environment is not only vital for DNA replication but also plays a major role in maintaining genomic stability. Ribonucleotide reductase (RNR) catalyzes the rate-limiting step in dNTP synthesis and altered regulation of RNR leads to imbalanced dNTP pools. Increased dNTP levels are mutagenic and have the potential to interfere with pathways that are involved in DNA replication, repair and DNA damage control. However, the mechanisms through which altered dNTP pools affect these pathways are poorly understood. Nonetheless, altered dNTP pools have been identified in a number of cellular contexts, including cancer. In order to interpret and analyze the effects of altered dNTP pools, we need quantitative information about dNTP pools in different genetic and environmental contexts in vivo. Here we describe a high-throughput fluorescence-based assay that uses a qPCR-based approach to quantify dNTP levels for use with Saccharomyces cerevisiae extracts.

Analysing the impact of the nature of the nitrogen source on the formation of volatile compounds to unravel the aroma metabolism of two non-Saccharomyces strains

Even though non-Saccharomyces yeasts were regarded as spoilage microorganisms for a long time, their abilities to improve and diversify the aromatic profile of wines are now well recognized. Consequently, their use in combination with S. cerevisiae strains during winemaking has attracted substantial attention over the last decade. However, our limited understanding of the metabolism and physiology of these species remains a barrier to promoting efficient exploitation of their full potential. In this study, we further explored the metabolism involved in the production of fermentative volatile compounds of two commercial non-Saccharomyces strains, T. delbrueckii Biodiva™ and M. pulcherrima Flavia®, in comparison with the reference wine yeast S. cerevisiae Lalvin EC1118®. After growing these strains in the presence of 24 different N-compounds, particular attention was paid to the influence of the nitrogen source on the profile of aroma compounds synthesized by these yeasts (higher alcohols and acids, medium-chain fatty acids and their acetate or ethyl esters derivatives). A comprehensive analysis of the dataset showed that these three species were able to produce all the fermentative aromas, regardless of the nitrogen source, demonstrating the key contribution of the central carbon metabolism to the formation of volatile molecules. Nevertheless, we also observed some specific phenotypic traits for each of the strains in their assimilation capacities for the various nitrogen nutrients as well as in their response to the nature of the nitrogen source in terms of the production of volatile molecules. These observations revealed the intricacy and interconnection between the networks involved in nitrogen consumption and aroma production. These differences are likely related to the genetic backgrounds of the strains. Overall, this study expands our understanding of the metabolic processes responsible for the formation of volatile compounds during wine fermentation and their variations according to species and the nature of the nitrogen source. This knowledge provides a new platform for the more efficient exploitation of non-Saccharomyces strains during winemaking, improving the management of the fermentation.

Separation of 13C- and 15N-Isotopologues of Amino Acids with a Primary Amine without Mass Resolution by Means of O-Phthalaldehyde Derivatization and Collision Induced Dissociation

Computational and experimental advances of recent years have culminated in establishing ¹³C-Metabolic Flux Analysis (¹³C-MFA) as a routine methodology to unravel the fluxome. As the acronym suggests, ¹³C-MFA has relied on the relative abundance of ¹³C-isotopes in metabolites for flux inference, most commonly measured by mass spectrometry. In this manuscript we expand the scope of labeling measurements to the case of simultaneous ¹³C- and ¹⁵N-labeling of amino acids. Analytically, the separation of isotopologues of this metabolite class can only be achieved at resolving power beyond 65,000. In this manuscript we harvest an overlooked property of the collision induced dissociation of amino acid adducts to discern ¹³C- and ¹⁵N- isotopologues of amino acids with a primary amine without separating them in the m/z domain.

Influence of Drying Method on NMR-Based Metabolic Profiling of Human Cell Lines

Metabolic profiling of cell line and tissue extracts involves sample processing that includes a drying step prior to re-dissolving the cell or tissue extracts in a buffer for analysis by GC/LC-MS or NMR. Two of the most commonly used drying techniques are centrifugal evaporation under vacuum (SpeedVac) and lyophilization. Here, NMR spectroscopy was used to determine how the metabolic profiles of hydrophilic extracts of three human pancreatic cancer cell lines, MiaPaCa-2, Panc-1 and AsPC-1, were influenced by the choice of drying technique. In each of the three cell lines, 40-50 metabolites were identified as having statistically significant differences in abundance in redissolved extract samples depending on the drying technique used during sample preparation. In addition to these differences, some metabolites were only present in the lyophilized samples, for example, n-methyl-α-aminoisobutyric acid, n-methylnicotimamide, sarcosine and 3-hydroxyisovaleric acid, whereas some metabolites were only present in SpeedVac dried samples, for example, trimethylamine. This research demonstrates that the choice of drying technique used during the preparation of samples of human cell lines or tissue extracts can significantly influence the observed metabolome, making it important to carefully consider the selection of a drying method prior to preparation of such samples for metabolic profiling.

Optimized sampling protocol for mass spectrometry-based metabolomics in Streptomyces

In quantitative metabolomics studies, the most crucial step was arresting snapshots of all interesting metabolites. However, the procedure customized for Streptomyces was so rare that most studies consulted the procedure from other bacteria even yeast, leading to inaccurate and unreliable metabolomics analysis. In this study, a base solution (acetone: ethanol = 1:1, mol/mol) was added to a quenching solution to keep the integrity of the cell membrane. Based on the molar transition energy (ET) of the organic solvents, five solutions were used to carry out the quenching procedures. These were acetone, isoamylol, propanol, methanol, and 60% (v/v) methanol. To the best of our knowledge, this is the first report which has utilized a quenching solution with ET values. Three procedures were also adopted for extraction. These were boiling, freezing–thawing, and grinding ethanol. Following the analysis of the mass balance, amino acids, organic acids, phosphate sugars, and sugar alcohols were measured using gas chromatography with an isotope dilution mass spectrometry. It was found that using isoamylol with a base solution (5:1, v/v) as a quenching solution and that freezing–thawing in liquid nitrogen within 50% (v/v) methanol as an extracting procedure were the best pairing for the quantitative metabolomics of Streptomyces ZYJ-6, and resulted in average recoveries of close to 100%. The concentration of intracellular metabolites obtained from this new quenching solution was between two and ten times higher than that from 60% (v/v) methanol, which until now has been the most commonly used solution. Our findings are the first systematic quantitative metabolomics tools for Streptomyces ZYJ-6 and, therefore, will be important references for research in fields such as 13C based metabolic flux analysis, multi-omic research and genome-scale metabolic model establishment, as well as for other Streptomyces.

Efficiency of three intracellular extraction methods in the determination of metabolites related to tryptophan and tyrosine in winemaking yeast's metabolism by LC-HRMS

Yeast nitrogen metabolism produces metabolites, whose origin in wines has scarcely been studied, with an important biological and organoleptic role. The present work focuses on comparing three intracellular extraction methods in order to elucidate efficiency of extraction while measuring the effect of temperature upon the integrity of the compounds related to the metabolism of tryptophan and tyrosine by yeast. Two UHPLC/HRMS methods to measure 16 metabolites were developed and validated. The validation provided optimum values of LOD (7.4·10^-6 to 0.1 μg L^-1), of LOQ (2·10^-5 to 0.02 μg L^-1) of precision (11-0.5% RSD) and repeatability (12-0.5% RSD). The removal of interfering molecules enabled matrix effects to be kept at low levels. The results pointed out that the low-temperature methods were more effective, providing better precision for 16 metabolites. The high-temperature extraction method may yield false enhanced compounds concentrations since they originate in cell wall macromolecules degradation.

Yeast Systems Biology: Model Organism and Cell Factory

For thousands of years, the yeast Saccharomyces cerevisiae (S. cerevisiae) has served as a cell factory for the production of bread, beer, and wine. In more recent years, this yeast has also served as a cell factory for producing many different fuels, chemicals, food ingredients, and pharmaceuticals. S. cerevisiae, however, has also served as a very important model organism for studying eukaryal biology, and even today many new discoveries, important for the treatment of human diseases, are made using this yeast as a model organism. Here a brief review of the use of S. cerevisiae as a model organism for studying eukaryal biology, its use as a cell factory, and how advances in systems biology underpin developments in both these areas, is provided.

Extraction of Extracellular Matrix in Static and Dynamic Candida Biofilms Using Cation Exchange Resin and Untargeted Analysis of Matrix Metabolites by Ultra-High-Performance Liquid Chromatography-Tandem Quadrupole Time-of-Flight Mass Spectrometry (UPLC-Q-TOF-MS)

Fungal infections caused by Candida albicans poses a great threat to human health. The ability of biofilm formation is believed to be associated with resistance-related Candida infections. Currently, knowledge on extracellular matrix (EM) of C. albicans biofilm is limited. In this study, we introduced ion exchange resin, i.e., cation exchange resin (CER) and anion exchange resin (AER), in EM extraction of C. albicans biofilm as well as several non-albicans Candida (NAC) biofilms under static and dynamic states in combination with vortexing and ultrasonication (VU). The metabolites extracted from the dynamic C. albicans biofilm matrix using the CER-VU and VU were identified with ultra-high-performance liquid chromatography-tandem quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MS) via untargeted filtration. Compared with other physical and chemical extraction methods, CER-VU was demonstrated to be an ideal approach with high-yield acquisitions of EM constituents including proteins, triglycerides and carbohydrates and low-level damages on fungal cell viability and integrity. The untargeted MS analysis further showed the high efficacy of CER-VU, as a large quantity of metabolites (217 versus 198) was matched comprising a great number of lipids, carbohydrates, amino acids, nucleic acids and their derivatives together with a high involvement of signaling pathways compared with the VU alone. However, combining the results from both the CER-VU and VU methods could generate more metabolites. In summary, the EM analysis of the dynamic C. albicans biofilm expands our understanding upon a comprehensive depiction of matrix components and provides another effective approach for EM extraction.

Evaluation of metabolome sample preparation and extraction methodologies for oleaginous filamentous fungi Mortierella alpina

INTRODUCTION

Metabolomics has been successfully applied to guide the rational engineering of industrial strains and improve the performance of bioprocesses. Mortierella alpina has traditionally been one of the most popular industrial strains for the production of polyunsaturated fatty acids. However, a systematic comparison and optimisation of the metabolomic analysis methods of M. alpina has not yet been reported.

OBJECTIVE

We sought to identify potential weaknesses that are important for accurate metabolomic analysis. We also aimed to determine an efficient sample preparation protocol for metabolomics studies in the oleaginous filamentous fungus M. alpina.

METHODS

In this study, using GC-MS, we evaluated three sample preparation protocols and five solvent mixtures by assessment of the metabolite profile differences, the sum of peak intensities and the reproducibility of metabolite quantification.

RESULTS

The freeze-dried biomass had better reproducibility and recovery than fresh biomass for metabolite extraction and data normalisation that is part of a metabolomics analysis of filamentous fungi M. alpina. Methanol:water (1:1) was superior for the profiling of metabolites in oleaginous fungi M. alpina. The unbiased metabolite profiling difference between the growth phase and lipids synthesis phase revealed that the degradation of amino acids were critical nodes for the efficient synthesis of lipids in M. alpina.

CONCLUSION

The use of freeze-dried biomass for metabolite extraction and data normalisation was more efficient at measuring the active state of the intracellular metabolites in M. alpina. We recommend extracting the intracellular metabolites with methanol:water (1:1). An important role of amino acid oxidation in the nitrogen limitation-mediated lipid accumulation was found.

Gas Chromatography-Mass Spectrometry Microbial Metabolomics for Applications in Strain Optimization

Metabolomics is the systems-scale measurement of biochemical intermediates in biological systems; by virtue of its deep and broad study of metabolism, it has great potential for applications in metabolic engineering. While a number of the analytical techniques used widely in metabolomics are familiar to metabolic engineers performing post hoc analyses of product titers, the requirements for accurately capturing metabolism at a systems scale rather than just measuring a single secreted product are much more complicated. Nonetheless, metabolomics (which is still not widely available as an affordable consumer service like many molecular biology services) is within reach of many properly equipped metabolic engineering groups. To this end, we present a detailed metabolomics protocol with application to strain optimization. Specifically, we focus on characterizing metabolism in the yeast Saccharomyces cerevisiae using gas chromatography coupled to mass spectrometry. The measurement of metabolic intermediates that results from such approaches has the potential to enable more informed and rational efforts towards pathway engineering and strain optimization.

Metabolomic Studies of Live Single Cancer Stem Cells Using Mass Spectrometry

Cancer stem cells (CSCs) are rare types of cells responsible for tumor development, relapse, and metastasis. However, current research in CSC biology is largely limited by the difficulty of obtaining sufficient CSCs. Single-cell analysis techniques are promising tools for CSC-related studies. Here, we used the Single-probe mass spectrometry (MS) technique to investigate the metabolic features of live colorectal CSCs at the single-cell level. Experimental data were analyzed using statistical analysis methods, including the t-test and partial least squares discriminant analysis. Our results indicate that the overall metabolic profiles of CSCs are distinct from non-stem cancer cells (NSCCs). Specifically, we demonstrated that tricarboxylic acid (TCA) cycle metabolites are more abundant in CSCs compared to NSCCs, indicating their major energy production pathways are different. Moreover, CSCs have relatively higher levels of unsaturated lipids. Inhibiting the activities of stearoyl-CoA desaturase-1 (SCD1), nuclear factor κB (NF-κB), and aldehyde dehydrogenases (ALDH1A1) in CSCs significantly reduced the abundances of unsaturated lipids and hindered the formation of spheroids, resulting in reduced stemness of CSCs. Our techniques and experimental protocols can be potentially used for metabolomic studies of other CSCs and rare types of cells and provide a new approach to discovering functional biomarkers as therapeutic targets.

Saccharomyces cerevisiae adapted to grow in the presence of low-dose rapamycin exhibit altered amino acid metabolism

BACKGROUND

Rapamycin is a potent inhibitor of the highly conserved TOR kinase, the nutrient-sensitive controller of growth and aging. It has been utilised as a chemotherapeutic agent due to its anti-proliferative properties and as an immunosuppressive drug, and is also known to extend lifespan in a range of eukaryotes from yeast to mammals. However, the mechanisms through which eukaryotic cells adapt to sustained exposure to rapamycin have not yet been thoroughly investigated.

METHODS

Here, S. cerevisiae response to long-term rapamycin exposure was investigated by identifying the physiological, transcriptomic and metabolic differences observed for yeast populations inoculated into low-dose rapamycin-containing environment. The effect of oxygen availability and acidity of extracellular environment on this response was further deliberated by controlling or monitoring the dissolved oxygen level and pH of the culture.

RESULTS

Yeast populations grown in the presence of rapamycin reached higher cell densities complemented by an increase in their chronological lifespan, and these physiological adaptations were associated with a rewiring of the amino acid metabolism, particularly that of arginine. The ability to synthesise amino acids emerges as the key factor leading to the major mechanistic differences between mammalian and microbial TOR signalling pathways in relation to nutrient recognition.

CONCLUSION

Oxygen levels and extracellular acidity of the culture were observed to conjointly affect yeast populations, virtually acting as coupled physiological effectors; cells were best adapted when maximal oxygenation of the culture was maintained in slightly acidic pH, any deviation necessitated more extensive readjustment to additional stress factors.

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.

Targeted Metabolomics of Xylose-Fermenting Yeasts Based on Mass Spectrometry

Mass spectrometry is a sensitive and selective analytical technique that enables detection and quantitation of low abundance compounds in a complex sample matrix. Targeted metabolomics allows for quantitative analysis of metabolites, providing kinetic information of production and consumption rates, an essential step to investigate microbial metabolism. Here, we describe a targeted metabolomics protocol for yeast samples, from sample preparation to mass spectrometry analysis, which enables the identification of metabolic fluxes after xylose consumption. Sample preparation methods were optimized for quenching of yeast metabolism followed by intracellular metabolite extraction, using cold methanol and boiling ethanol protocols. Ultrahigh performance liquid chromatography tandem mass spectrometry (UHPLC-MS/MS) methods using ion pair chromatography (IPC) and hydrophilic interaction liquid chromatography (HILIC) allowed for the quantitation of 18 metabolites involved in central carbon metabolism (glycolysis, pentose phosphate pathway, and tricarboxylic acid cycle). The protocol here described was successfully applied to quantify metabolites in Scheffersomyces stipitis, Spathaspora passalidarum, Spathaspora arborariae, and Candida tenuis samples after xylose consumption.