Global metabolite analysis of yeast: evaluation of sample preparation methods

Metabolic footprinting as a tool for discriminating between brewing yeasts

The characterization of industrial yeast strains by examining their metabolic footprints (exometabolomes) was investigated and compared to genome-based discriminatory methods. A group of nine industrial brewing yeasts was studied by comparing their metabolic footprints, genetic fingerprints and comparative genomic hybridization profiles. Metabolic footprinting was carried out by both direct injection mass spectrometry (DIMS) and gas chromatography time-of-flight mass spectrometry (GC-TOF-MS), with data analysed by principal components analysis (PCA) and canonical variates analysis (CVA). The genomic profiles of the nine yeasts were compared by PCR-restriction fragment length polymorphism (PCR-RFLP) analysis, genetic fingerprinting using amplified fragment length polymorphism (AFLP) analysis and microarray comparative genome hybridizations (CGH). Metabolomic and genomic analysis comparison of the nine brewing yeasts identified metabolomics as a powerful tool in separating genotypically and phenotypically similar strains. For some strains discrimination not achieved genomically was observed metabolomically.

A transient isotopic labeling methodology for 13C metabolic flux analysis of photoautotrophic microorganisms

Metabolic flux analysis is increasingly recognized as an integral component of systems biology. However, techniques for experimental measurement of system-wide metabolic fluxes in purely photoautotrophic systems (growing on CO(2) as the sole carbon source) have not yet been developed due to the unique problems posed by such systems. In this paper, we demonstrate that an approach that balances positional isotopic distributions transiently is the only route to obtaining system-wide metabolic flux maps for purely autotrophic metabolism. The outlined transient (13)C-MFA methodology enables measurement of fluxes at a metabolic steady-state, while following changes in (13)C-labeling patterns of metabolic intermediates as a function of time, in response to a step-change in (13)C-label input. We use mathematical modeling of the transient isotopic labeling patterns of central intermediates to assess various experimental requirements for photoautotrophic MFA. This includes the need for intracellular metabolite concentration measurements and isotopic labeling measurements as a function of time. We also discuss photobioreactor design and operation in order to measure fluxes under precise environmental conditions. The transient MFA technique can be used to measure and compare fluxes under different conditions of light intensity, nitrogen sources or compare strains with various mutations or gene deletions and additions.

Metabolomics: current state and evolving methodologies and tools

In recent years, metabolomics developed to an accepted and valuable tool in life sciences. Substantial improvements of analytical hardware allow metabolomics to run routinely now. Data are successfully used to investigate genotype-phenotype relations of strains and mutants. Metabolomics facilitates metabolic engineering to optimise mircoorganisms for white biotechnology and spreads to the investigation of biotransformations and cell culture. Metabolomics serves not only as a source of qualitative but also quantitative data of intra-cellular metabolites essential for the model-based description of the metabolic network operating under in vivo conditions. To collect reliable metabolome data sets, culture and sampling conditions, as well as the cells' metabolic state, are crucial. Hence, application of biochemical engineering principles and method standardisation efforts become important. Together with the other more established omics technologies, metabolomics will strengthen its claim to contribute to the detailed understanding of the in vivo function of gene products, biochemical and regulatory networks and, even more ambitious, the mathematical description and simulation of the whole cell in the systems biology approach. This knowledge will allow the construction of designer organisms for process application using biotransformation and fermentative approaches making effective use of single enzymes, whole microbial and even higher cells.

GC/MS analysis of the rat urine for metabonomic research

In this paper, an optimized protocol was established and validated for the metabonomic profiling in rat urine using GC/MS. The urine samples were extracted by methanol after treatment with urease to remove excessive urea, then the resulted supernatant was dried, methoximated, trimethylsilylated, and analyzed by GC/MS. Forty-nine endogenous metabolites were separated and identified in GC/MS chromatogram, of which 26 identified compounds were selected for quantitative analysis to evaluate the linearity, precision, and sensitivity of the method. It showed good linearity between mass spectrometry responses and relative concentrations of the 26 endogenous compounds over the range from 0.063 to 1.000 (v/v, urine/urine+water) and satisfactory reproducibility with intra-day and inter-days precision values all below 15%. The metabonomic profiling method based on GC/MS was successfully applied to urine samples from hyperlipidemia model rats. Obviously, separated clustering of model rats and the control rats were shown by principal components analysis (PCA); time-dependent metabonomic modification was detected as well. It was suggested that metabonomic profiling based on GC/MS be a robust method for urine samples.

Dynamics of the cellular metabolome during human cytomegalovirus infection

Viral replication requires energy and macromolecular precursors derived from the metabolic network of the host cell. Despite this reliance, the effect of viral infection on host cell metabolic composition remains poorly understood. Here we applied liquid chromatography-tandem mass spectrometry to measure the levels of 63 different intracellular metabolites at multiple times after human cytomegalovirus (HCMV) infection of human fibroblasts. Parallel microarray analysis provided complementary data on transcriptional regulation of metabolic pathways. As the infection progressed, the levels of metabolites involved in glycolysis, the citric acid cycle, and pyrimidine nucleotide biosynthesis markedly increased. HCMV-induced transcriptional upregulation of specific glycolytic and citric acid cycle enzymes mirrored the increases in metabolite levels. The peak levels of numerous metabolites during infection far exceeded those observed during normal fibroblast growth or quiescence, demonstrating that HCMV markedly disrupts cellular metabolic homeostasis and institutes its own specific metabolic program.

Viruses are parasites. They depend on the biochemical infrastructure of host cells to grow. A key element of the infrastructure provided by the host cell is its metabolic machinery, which viruses rely upon to provide the energy and building blocks necessary for their replication. The way in which viruses interact with host cell metabolism remains, however, poorly understood. The authors have used an advanced measurement technique, liquid chromatography-mass spectrometry, to quantitate directly the levels of a large number of metabolic compounds (energy molecules and biochemical building blocks) during cytomegalovirus infection of cultured human cells. They find that viral infection leads to dramatic increases in the levels of many metabolites and that these increases substantially exceed those associated with normal transitions of cells between resting and growing states. In several cases, enhanced metabolite levels induced by the virus coincide with an apparent increase in host cell production of the machinery (enzymes) involved in making those metabolites. This work represents the first comprehensive characterization of the metabolic environment of virally infected cells and identifies a number of profound metabolic effects of the virus, some of which may eventually prove fruitful targets for antiviral therapy.

Cellular metabolomics of Escherchia coli

Escherichia coli is among the simplest and best-understood free-living organisms. It has served as a valuable model for numerous biological processes, including cellular metabolism. Just as E. coli stood at the front of the genomic revolution, it is playing a leading role in the development of cellular metabolomics: the study of the complete metabolic contents of cells, including their dynamic concentration changes and fluxes. This review briefly describes the essentials of cellular metabolomics and its fundamental differentiation from biomarker metabolomics and lipidomics. Key technologies for metabolite quantitation from E. coli are described, with a focus on those involving mass spectrometry. In particular emphasis is given to the cell handling and sample preparation steps required for collecting data of high biological reliability, such as fast metabolome quenching. Future challenges, both in terms of data collection and application of the data to obtain a comprehensive understanding of metabolic dynamics, are discussed.

Quantitative analysis of sulfur-related metabolites during cadmium stress response in yeast by capillary electrophoresis–mass spectrometry

The objective of this research is to establish an evaluation system of metabolites by capillary electrophoresis-mass spectrometry (CE-MS) in response to chemical stress using the unicellular genome model, yeast (Saccharomyces cerevisiae strain S288C). A method previously reported by Soga et al. was modified and validated for the determination of sulfur-related metabolites, 23 cationic metabolites, in yeast extract. A mixture of 5 mM formic acid in 50% (v/v) 2-propanol was used for the sheath liquid to improve the detection sensitivity. Moreover, washing of CE capillary with 0.1M ammonia solution between successive runs enhanced the reproducibility. After analytical validation, the method was applied to the metabolomic analysis of yeast cells in response to cadmium (Cd) stress. Under Cd exposure, some interesting observations were obtained, particularly the depletion of glycine and the strong accumulation of L-gamma-glutamylcysteine in yeast cells.

Revised procedures for yeast metabolites extraction: application to a glucose pulse to carbon-limited yeast cultures, which reveals a transient activation of the purine salvage pathway

In this study we have revised our original procedure of yeast metabolites extraction. We showed that: (a) less than 5% of intracellular metabolites leaks out during the step of rapid arrest of cellular metabolism by quenching yeast cells into a 60% methanol solution kept at -40 degrees C; and (b) with a few exception, the stability of metabolites were not altered during the 3 min boiling procedure in a buffered ethanol solution. However, there was a loss of external added metabolites of 5-30%, depending on the type of metabolites. This was mainly attributable to their retention on cellular debris after ethanol treatment, which prevented centrifugation of the cellular extracts before evaporation of ethanol. We further simplified our previous high-performance ionic chromatography (HPIC) techniques for easier, more reliable and robust quantitative measurements of organic acids, sugar phosphates and sugar nucleotides, and extended these techniques to purine and pyrimidine bases, using a variable wavelength detector set at 220 and 260 nm in tandem with a pulsed electrochemical or suppressed conductivity detector. These protocols were successfully applied to a glucose pulse to carbon-limited yeast cultures on purines metabolism. This study showed that glucose induced a fast activation of the purine salvage pathway, as indicated by a transient drop of ATP and ADP with a concomitant rise of IMP and inosine. This metabolic perturbation was accompanied by a rapid increase in the activity of the ISN1-encoded specific IMP-5'-nucleotidase. The mechanism of this activation remains to be determined.

Central carbon metabolism of Saccharomyces cerevisiae in anaerobic, oxygen-limited and fully aerobic steady-state conditions and following a shift to anaerobic conditions

Saccharomyces cerevisiae CEN.PK113-1A was grown in glucose-limited chemostat culture with 0%, 0.5%, 1.0%, 2.8% or 20.9% O2 in the inlet gas (D=0.10 h(-1), pH 5, 30 degrees C) to determine the effects of oxygen on 17 metabolites and 69 genes related to central carbon metabolism. The concentrations of tricarboxylic acid cycle (TCA) metabolites and all glycolytic metabolites except 2-phosphoglycerate+3-phosphoglycerate and phosphoenolpyruvate were higher in anaerobic than in fully aerobic conditions. Provision of only 0.5-1% O2 reduced the concentrations of most metabolites, as compared with anaerobic conditions. Transcription of most genes analyzed was reduced in 0%, 0.5% or 1.0% O2 relative to cells grown in 2.8% or 20.9% O2. Ethanol production was observed with 2.8% or less O2. After steady-state analysis in defined oxygen concentrations, the conditions were switched from aerobic to anaerobic. Metabolite and transcript levels were monitored for up to 96 h after the transition, and this showed that more than 30 h was required for the cells to fully adapt to anaerobiosis. Levels of metabolites of upper glycolysis and the TCA cycle increased following the transition to anaerobic conditions, whereas those of metabolites of lower glycolysis generally decreased. Gene regulation was more complex, with some genes showing transient upregulation or downregulation during the adaptation to anaerobic conditions.

Ammonium toxicity and potassium limitation in yeast

DNA microarray analysis of gene expression in steady-state chemostat cultures limited for potassium revealed a surprising connection between potassium and ammonium: potassium limits growth only when ammonium is the nitrogen source. Under potassium limitation, ammonium appears to be toxic for Saccharomyces cerevisiae. This ammonium toxicity, which appears to occur by leakage of ammonium through potassium channels, is recapitulated under high-potassium conditions by over-expression of ammonium transporters. Although ammonium toxicity is well established in metazoans, it has never been reported for yeast. To characterize the response to ammonium toxicity, we examined the filtrates of these cultures for compounds whose excretion might serve to detoxify the ammonium (such as urea in mammals). Using liquid chromatography-tandem mass spectrometry to assay for a wide array of metabolites, we detected excreted amino acids. The amounts of amino acids excreted increased in relation to the severity of growth impairment by ammonium, suggesting that amino acid excretion is used by yeast for ammonium detoxification.

Integrated sampling procedure for metabolome analysis

Metabolome analysis, the analysis of large sets of intracellular metabolites, has become an important systems analysis method in biotechnological and pharmaceutical research. In metabolic engineering, the integration of metabolome data with fluxome and proteome data into large-scale mathematical models promises to foster rational strategies for strain and cell line improvement. However, the development of reproducible sampling procedures for quantitative analysis of intracellular metabolite concentrations represents a major challenge, accomplishing (i) fast transfer of sample, (ii) efficient quenching of metabolism, (iii) quantitative metabolite extraction, and (iv) optimum sample conditioning for subsequent quantitative analysis. In addressing these requirements, we propose an integrated sampling procedure. Simultaneous quenching and quantitative extraction of intracellular metabolites were realized by short-time exposure of cells to temperatures < or =95 degrees C, where intracellular metabolites are released quantitatively. Based on these findings, we combined principles of heat transfer with knowledge on physiology, for example, turnover rates of energy metabolites, to develop an optimized sampling procedure based on a coiled single tube heat exchanger. As a result, this sampling procedure enables reliable and reproducible measurements through (i) the integration of three unit operations into a one unit operation, (ii) the avoidance of any alteration of the sample due to chemical reagents in quenching and extraction, and (iii) automation. A sampling frequency of 5 s(-)(1) and an overall individual sample processing time faster than 30 s allow observing responses of intracellular metabolite concentrations to extracellular stimuli on a subsecond time scale. Recovery and reliability of the unit operations were analyzed. Impact of sample conditioning on subsequent IC-MS analysis of metabolites was examined as well. The integrated sampling procedure was validated through consistent results from steady-state metabolite analysis of Escherichia coli cultivated in a chemostat at D = 0.1 h(-)(1).

Comparison of sampling techniques for parallel analysis of transcript and metabolite levels inSaccharomyces cerevisiae

Mathematical modelling of cellular processes is crucial for the understanding of the cell or organism as a whole. Genome-wide observations, at the levels of the transcriptome, proteome and metabolome, provide a high coverage of the molecular constituents of the system in study. Time-course experiments are important for gaining insight into a system's dynamics and are needed for mathematical modelling. In time-course experiments it is crucial to use efficient and fast sampling techniques. We evaluated several techniques to sample and process yeast cultures for parallel analysis of the transcriptome and metabolome. The evaluation was made by measuring the quality of the RNA obtained with UV-spectroscopy, capillary electrophoresis and microarray hybridization. The protocol developed involves rapid collection by spraying the sample into -40 degrees C tricine-buffered methanol (as previously described for yeast metabolome analysis), followed by the separation of cells from the culture medium in low-temperature rapid centrifugation. Removal of the residual methanol is carried out by freeze-drying the pellet at -35 degrees C. RNA and metabolites can then be extracted from the same freeze-dried sample obtained with this procedure.

Mass spectrometry-based metabolomics

This review presents an overview of the dynamically developing field of mass spectrometry-based metabolomics. Metabolomics aims at the comprehensive and quantitative analysis of wide arrays of metabolites in biological samples. These numerous analytes have very diverse physico-chemical properties and occur at different abundance levels. Consequently, comprehensive metabolomics investigations are primarily a challenge for analytical chemistry and specifically mass spectrometry has vast potential as a tool for this type of investigation. Metabolomics require special approaches for sample preparation, separation, and mass spectrometric analysis. Current examples of those approaches are described in this review. It primarily focuses on metabolic fingerprinting, a technique that analyzes all detectable analytes in a given sample with subsequent classification of samples and identification of differentially expressed metabolites, which define the sample classes. To perform this complex task, data analysis tools, metabolite libraries, and databases are required. Therefore, recent advances in metabolomics bioinformatics are also discussed.

Elucidating the mode-of-action of compounds from metabolite profiling studies

Metabolite profiling has been carried out for decades and is as such not a new research area. However, the field has attracted increasing attention in the last couple of years, and the term metabolome is now often used to describe the complete pool of metabolites associated with an organism at any given time. Mass spectrometry (MS) and nuclear magnetic resonance (NMR) spectroscopy are the best candidates for comprehensive analysis of the metabolome and the application of these technologies is presented in this chapter. In this relation, the importance of efficient metabolite screening for discovery of novel drugs is discussed. Related to metabolite profiling, the principals underlying the application of labeled substrates to quantify in vivo metabolic fluxes are introduced, and the chapter is concluded by discussing the perspectives of metabolite measurements in systems biology.

Metabolomics of a superorganism

The human can be thought of as a human-microbe hybrid, and the health of this superorganism will be affected by intrinsic properties such as human genetics, diurnal cycles, and age and by extrinsic factors such as lifestyle choices (food and drink, drug intake) and the acquisition of a stable "healthy" gut microflora (the so-called microbiome). Alterations in this superorganism will be manifest in the metabolite complement within its serum and urine samples. The unraveling of this metabolic compartmentalization in this complex ecosystem will certainly be a challenge for systems biology and necessary for defining human health at the molecular level. Within the systems biology framework, functional analyses at the level of gene expression (transcriptomics), protein translation (proteomics), and, more recently, the metabolite network (metabolomics) have become increasingly popular. Metabolomics experiments aim to quantify all metabolites in a cellular system (cell or tissue) under defined states and at different time points so that the dynamics of any biotic, abiotic, or genetic perturbation can be accurately assessed. This article provides an overview of metabolomics and discusses how data are generated and analyzed within a systems biology framework. The role of metabolomics in nutrigenomics is also discussed, as are the concepts of the human being a superorganism and the complexities required to be overcome to understand human health and disease.

Standard reporting requirements for biological samples in metabolomics experiments: microbial and in vitro biology experiments

With the increasing use of metabolomics as a means to study a large number of different biological research questions, there is a need for a minimal set of reporting standards that allow the scientific community to evaluate, understand, repeat, compare and re-investigate metabolomics studies. Here we propose, a first draft of minimal requirements to effectively describe the biological context of metabolomics studies that involve microbial or in vitro biological subjects. This recommendation has been produced by the microbiology and in vitro biology working subgroup of the Metabolomics Standards Initiative in collaboration with the yeast systems biology network as part of a wider standardization initiative led by the Metabolomics Society. Microbial and in vitro biology metabolomics is defined by this sub-working group as studies with any cell or organism that require a defined external medium to facilitate growth and propagation. Both a minimal set and a best practice set of reporting standards for metabolomics experiments have been defined. The minimal set of reporting standards for microbial or in vitro biology metabolomics experiments includes those factors that are specific for metabolomics experiments and that critically determine the outcome of the experiments. The best practice set of reporting standards contains both the factors that are specific for metabolomics experiments and general aspects that critically determine the outcome of any microbial or in vitro biological experiment.

Conservation of the metabolomic response to starvation across two divergent microbes

We followed 68 cellular metabolites after carbon or nitrogen starvation of Escherichia coli and Saccharomyces cerevisiae, using a filter-culture methodology that allows exponential growth, nondisruptive nutrient removal, and fast quenching of metabolism. Dynamic concentration changes were measured by liquid chromatography-tandem mass spectrometry and viewed in clustered heat-map format. The major metabolic responses anticipated from metabolite-specific experiments in the literature were observed as well as a number of novel responses. When the data were analyzed by singular value decomposition, two dominant characteristic vectors were found, one corresponding to a generic starvation response and another to a nutrient-specific starvation response that is similar in both organisms. Together these captured a remarkable 72% of the metabolite concentration changes in the full data set. The responses described by the generic starvation response vector (42%) included, for example, depletion of most biosynthetic intermediates. The nutrient-specific vector (30%) included key responses such as increased phosphoenolpyruvate signaling glucose deprivation and increased alpha-ketoglutarate signaling ammonia deprivation. Metabolic similarity across organisms extends from the covalent reaction network of metabolism to include many elements of metabolome response to nutrient deprivation as well.

Accelerated nuclei preparation and methods for analysis of histone modifications in yeast

The continuing identification of new histone post-translational modifications and ongoing discovery of their roles in nuclear processes has increased the demand for quick, efficient, and precise methods for their analysis. In the budding yeast Saccharomyces cerevisiae, a variety of methods exist for the characterization of histone modifications on a global scale. However, a wide gap in preparation time and histone purity exists between the most widely used extraction methods, which include a simple whole cell extraction (WCE) and an intensive histone extraction. In this work we evaluate various published WCE buffers for their relative effectiveness in the detection of histone modifications by Western blot analysis. We also present a precise, yet time-efficient method for the detection of subtle changes in histone modification levels. Lastly, we present a protocol for the rapid small-scale purification of nuclei that improves the performance of antibodies that do not work efficiently in WCE. These new methods are ideal for the analysis of histone modifications and could be applied to the analysis and improved detection of other nuclear proteins.

Microbial metabolomics: past, present and future methodologies

Microbial metabolomics has received much attention in recent years mainly because it supports and complements a wide range of microbial research areas from new drug discovery efforts to metabolic engineering. Broadly, the term metabolomics refers to the comprehensive (qualitative and quantitative) analysis of the complete set of all low molecular weight metabolites present in and around growing cells at a given time during their growth or production cycle. This review focuses on the past, current and future development of various experimental protocols in the rapid developing area of metabolomics in the ongoing quest to reliably quantify microbial metabolites formed under defined physiological conditions. These developments range from rapid sample collection, instant quenching of microbial metabolic activity, extraction of the relevant intracellular metabolites as well as quantification of these metabolites using enzyme based and or modern high tech hyphenated analytical protocols, mainly chromatographic techniques coupled to mass spectrometry (LC-MS(n), GC-MS(n), CE-MS(n)), where n indicates the number of tandem mass spectrometry, and nuclear magnetic resonance spectroscopy (NMR).

Metabolomics: current technologies and future trends

The ability to sequence whole genomes has taught us that our knowledge with respect to gene function is rather limited with typically 30-40% of open reading frames having no known function. Thus, within the life sciences there is a need for determination of the biological function of these so-called orphan genes, some of which may be molecular targets for therapeutic intervention. The search for specific mRNA, proteins, or metabolites that can serve as diagnostic markers has also increased, as has the fact that these biomarkers may be useful in following and predicting disease progression or response to therapy. Functional analyses have become increasingly popular. They include investigations at the level of gene expression (transcriptomics), protein translation (proteomics) and more recently the metabolite network (metabolomics). This article provides an overview of metabolomics and discusses its complementary role with transcriptomics and proteomics, and within system biology. It highlights how metabolome analyses are conducted and how the highly complex data that are generated are analysed. Non-invasive footprinting analysis is also discussed as this has many applications to in vitro cell systems. Finally, for studying biotic or abiotic stresses on animals, plants or microbes, we believe that metabolomics could very easily be applied to large populations, because this approach tends to be of higher throughput and generally lower cost than transcriptomics and proteomics, whilst also providing indications of which area of metabolism may be affected by external perturbation.

Determination of adenine and pyridine nucleotides in glucose-limited chemostat cultures of Penicillium simplicissimum by one-step ethanol extraction and ion-pairing liquid chromatography

Under specific conditions Penicillium simplicissimum excretes large amounts of organic acids, mainly citrate. As the energetic status of the hyphae might play a role in that respect, we developed a method for the determination of adenine (adenosine triphosphate, adenosine diphosphate, and adenosine monophosphate) and pyridine (nicotinamide adenine dinucleotide and reduced nicotinamide adenine dinucleotide (NADH)) nucleotides in hyphae of P. simplicissimum. An optimum separation of the five compounds in less than 15 min was possible on a C-8 column, utilizing 50 mM aqueous triethylamine-buffer (pH 6.5) and acetonitrile as mobile phase; detection was performed at 254 nm. With the exception of NADH, which could not be determined accurately due to stability problems, the method was sensitive (LOD < or = 0.7 ng on-column), repeatable (sigma(rel) < or = 4.4%), accurate (recovery rates between 97.9 and 104.9%), and precise (intraday variation < or = 9.4%, interday variation < or = 6.2 %). For an optimum extraction of the nucleotides the chemostat samples were directly placed into hot (90 degrees C) 50% ethanol, and shaken for 10 min, followed by evaporation of the solvent and a solid phase extraction cleanup of the redissolved aqueous samples. With this method the nucleotide concentrations in hyphae from a glucose-limited chemostat culture and the respective energy charge were determined. Additionally, the effect of the time lag between sampling and extraction and the effect of a glucose pulse on nucleotide concentrations were determined.

Identifying decomposition products in extracts of cellular metabolites

Most methods of analyzing intracellular metabolites require extraction of metabolites from the cells. A concern in these methods is underestimation of metabolite levels due to incomplete extraction. In comparing extraction methods, then, it would seem that the best method for extracting a particular metabolite is the one that gives the largest yield. In extracting Escherichia coli with different methanol:water mixtures, we observed that >or=50% water gave an increased yield of nucleosides and bases compared with <or=20% water, as determined by liquid chromatography-tandem mass spectrometry analysis of the resulting extracts. Spiking of the extracts with isotope-labeled nucleotides revealed, however, that the high yield of nucleosides and bases occurred due to decomposition of nucleotides in the water-rich condition, not due to good extraction. Spiking combined with isotope labeling provides a general approach to detecting decomposition products in extracts of cellular metabolites. For extraction of E. coli with methanol:water, cold temperature and a high methanol fraction minimize artifacts due to metabolite decomposition.

Separation and quantitation of water soluble cellular metabolites by hydrophilic interaction chromatography-tandem mass spectrometry

A key unmet need in metabolomics is the ability to efficiently quantify a large number of known cellular metabolites. Here we present a liquid chromatography (LC)-electrospray ionization tandem mass spectrometry (ESI-MS/MS) method for reliable measurement of 141 metabolites, including components of central carbon, amino acid, and nucleotide metabolism. The selected LC approach, hydrophilic interaction chromatography with an amino column, effectively separates highly water soluble metabolites that fail to retain using standard reversed-phase chromatography. MS/MS detection is achieved by scanning through numerous selected reaction monitoring events on a triple quadrupole instrument. When applied to extracts of Escherichia coli grown in [12C]- versus [13C]glucose, the method reveals appropriate 12C- and 13C-peaks for 79 different metabolites.

Metabonomics techniques and applications to pharmaceutical research & development

In this review, the background to the approach known as metabonomics is provided, giving a brief historical perspective and summarizing the analytical and statistical techniques used. Some of the major applications of metabonomics relevant to pharmaceutical Research & Development are then reviewed including the study of various influences on metabolism, such as diet, lifestyle, and other environmental factors. The applications of metabonomics in drug safety studies are explained with special reference to the aims and achievements of the Consortium for Metabonomic Toxicology. Next, the role that metabonomics might have in disease diagnosis and therapy monitoring is provided with some examples, and the concept of pharmacometabonomics as a way of predicting an individual's response to treatment is highlighted. Some discussion is given on the strengths and weaknesses, opportunities of, and threats to metabonomics.

Fungal metabolite analysis in genomics and phenomics

Metabolomics consists of strategies to quantitatively identify cellular metabolites and to understand how trafficking of these biochemical messengers through the metabolic network influences phenotype. The application of metabolomics to fungi has been strongly pursued because these organisms are widely used for the production of chemicals, are well known for their diverse metabolic landscape and serve as excellent eukaryotic model organisms for studying metabolism and systems biology. Within the context of fungal systems, recent progress has been made in the development of analytical tools and mathematical strategies used in metabolite analysis that have enhanced our ability to crack the code underpinning the cellular inventory, regulatory schemes and communication mechanisms that dictate cellular function. Metabolomics has played a key role in functional genomics and strain classification.