Microbial metabolomics: past, present and future methodologies

Mechanisms and evolution of control logic in prokaryotic transcriptional regulation

A major part of organismal complexity and versatility of prokaryotes resides in their ability to fine-tune gene expression to adequately respond to internal and external stimuli. Evolution has been very innovative in creating intricate mechanisms by which different regulatory signals operate and interact at promoters to drive gene expression. The regulation of target gene expression by transcription factors (TFs) is governed by control logic brought about by the interaction of regulators with TF binding sites (TFBSs) in cis-regulatory regions. A factor that in large part determines the strength of the response of a target to a given TF is motif stringency, the extent to which the TFBS fits the optimal TFBS sequence for a given TF. Advances in high-throughput technologies and computational genomics allow reconstruction of transcriptional regulatory networks in silico. To optimize the prediction of transcriptional regulatory networks, i.e., to separate direct regulation from indirect regulation, a thorough understanding of the control logic underlying the regulation of gene expression is required. This review summarizes the state of the art of the elements that determine the functionality of TFBSs by focusing on the molecular biological mechanisms and evolutionary origins of cis-regulatory regions.

Towards the engineering of in vitro systems

Synthetic biology aims at rationally implementing biological systems from scratch. Given the complexity of living systems and our current lack of understanding of many aspects of living cells, this is a major undertaking. The design of in vitro systems can be considerably easier, because they can consist of fewer constituents, are quasi time invariant, their parameter space can be better accessed and they can be much more easily perturbed and then analysed chemically and mathematically. However, even for simplified in vitro systems, following a comprehensively rational design procedure is still difficult. When looking at a comparatively simple system, such as a medium-sized enzymatic reaction network as it is represented by glycolysis, major issues such as a lack of comprehensive enzyme kinetics and of suitable knowledge on crucial design parameters remain. Nevertheless, in vitro systems are very suitable to overcome these obstacles and therefore well placed to act as a stepping stone to engineering living systems.

Challenges in applying chemometrics to LC–MS-based global metabolite profile data

Metabolite profiling can provide insights into the metabolic status of complex living systems through the non-targeted analysis of metabolites in any biological sample. Metabolite profiling is complementary to genomics, transcriptomics and proteomics, and its applications span epidemiology, disease diagnosis, nutrition, pharmaceutical research, and toxicology. Metabolic phenotypes are a reflection of an organism’s environment, lifestyle, diet, gut microfloral composition and are also influenced by genetic factors, with important implications in genome-wide-association studies. Specialized analytical platforms, such as NMR spectroscopy and MS, are required to interrogate such metabolic complexity. The increased sophistication of such techniques has lead to a demand for improved data analysis approaches, including preprocessing and advanced chemometric techniques. This article discusses data generation, preprocessing, multivariate analysis and data interpretation for LC-MS-based metabolite profiling, focusing on challenges encountered and potential solutions.

Optimization of a GC-MS metabolic fingerprint method and its application in characterizing engineered bacterial metabolic shift

Metabolomics influences many aspects of life sciences including microbiology. Here, we describe the systematic optimization of metabolic quenching and a sample derivatization method for GC-MS metabolic fingerprint analysis. Methanol, ethanol, acetone, and acetonitrile were selected to evaluate their metabolic quenching ability, and acetonitrile was regarded as the most efficient agent. The optimized derivatization conditions were determined by full factorial design considering temperature, solvent, and time as parameters. The best conditions were attained with N,O-bis(trimethylsiyl) trifluoroacetamide as derivatization agent and pyridine as solvent at 75 degrees C for 45 min. Method validation ascertained the optimized method to be robust. The above method was applied to metabolomic analysis of six different strains and it is proved that the metabolic trait of an engineered strain can be easily deduced by clustering analysis of metabolic fingerprints.

The metabolomics of carotenoids in engineered cell factory

Carotenoids such as beta-carotene, lycopene, and antheraxanthin have plenty of scientific and commercial value. The comprehensive investigation of carotenoids drives people to improve and develop all kinds of analytical techniques to approach or even achieve "versatile" analysis. The metabolic engineering efforts in plants and algae have progressed rapidly, aiming to enable the use of plants and algae as "cell factories" for producing specific or novel carotenoids, such as beta-carotene (provitamin A) in Gold rice, while the emerging technologies of metabolomics support it by providing comprehensive analysis of carotenoids biochemical characterizations. This review describes metabolomics as a high-throughput platform to study carotenoids, including the engineering methods in the plants or algae, the bioinformatics for metabolomics, and the metabolomics of carotenoids in engineered cell factory. Modern systems biology tools, together with the development of genomics and metabolomics databases, will dramatically facilitate the advancement of our knowledge in gene-to-metabolite networks in plants. Metabolomics accompanying genomics, transcriptomics, and proteomics as well as bioinformatics facilitate metabolic engineering efforts towards designing superior biocatalysts in cell factories. Ongoing advances in biological techniques coupled with crucial metabolic networks will further promote plants and algae as attractive platforms for the production of numerous high-value compounds such as carotenoids.

Challenges and developments in tandem mass spectrometry based clinical metabolomics

'Clinical metabolomics' aims at evaluating and predicting health and disease risk in an individual by investigating metabolic signatures in body fluids or tissues, which are influenced by genetics, epigenetics, environmental exposures, diet, and behaviour. Powerful analytical techniques like liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) offers a rapid, effective and economical way to analyze metabolic alterations of pre-defined target metabolites in biological samples. Novel hyphenated technical approaches like the combination of tandem mass spectrometry combined with linear ion trap (QTrap mass spectrometry) combines both identification and quantification of known and unknown metabolic targets. We describe new concepts and developments of mass spectrometry based multi-target metabolome profiling in the field of clinical diagnostics and research. Particularly, the experiences from newborn screening provided important insights about the diagnostic potential of metabolite profiling arrays and directs to the clinical aim of predictive, preventive and personalized medicine by metabolomics.

Beyond clinical phenotype: the biologic integratome

Current classification of medical diagnosis derives from observational correlation between clinical syndromes and pathologic analysis. Limited understanding of the molecular determinants of diseases encountered in the critically ill remains a major obstacle to the rationale selection of therapeutic targets. Indeed, many human diseases reflect a disorder in physiologic processes that are known to involve the interaction of many complex control loops and to respond to a variety of pharmacologic agents and environmental factors. The advent of whole-genome sequencing and other high-throughput technologies have changed biomedical research into a data-rich discipline. "Omics" data sets that describe virtually all biomolecules in the cell are now publicly available. One of the challenges faced by investigators now lies in the interpretation of vast amounts of biological data sets to derive fundamental and applied biological information about whole systems. As mechanistic understanding of disease requires more than an agglomeration of information on the expression and activities of disease-associated molecules, network analysis has been applied to biological problems. Network analysis of the biological integratome promises to identify factors that influence disease phenotype, providing unique insight into disease mechanism. Network analysis also provides a mechanistic basis for defining phenotypic differences through consideration of unique genetic and environmental factors that govern intermediate phenotypes contributing to disease expression. Lastly, network analysis offers a unique method for identifying therapeutic targets that can alter disease expression.

Transcriptomic and metabolomic profiling of Zymomonas mobilis during aerobic and anaerobic fermentations

BACKGROUND

Zymomonas mobilis ZM4 (ZM4) produces near theoretical yields of ethanol with high specific productivity and recombinant strains are able to ferment both C-5 and C-6 sugars. Z. mobilis performs best under anaerobic conditions, but is an aerotolerant organism. However, the genetic and physiological basis of ZM4's response to various stresses is understood poorly.

RESULTS

In this study, transcriptomic and metabolomic profiles for ZM4 aerobic and anaerobic fermentations were elucidated by microarray analysis and by high-performance liquid chromatography (HPLC), gas chromatography (GC) and gas chromatography-mass spectrometry (GC-MS) analyses. In the absence of oxygen, ZM4 consumed glucose more rapidly, had a higher growth rate, and ethanol was the major end-product. Greater amounts of other end-products such as acetate, lactate, and acetoin were detected under aerobic conditions and at 26 h there was only 1.7% of the amount of ethanol present aerobically as there was anaerobically. In the early exponential growth phase, significant differences in gene expression were not observed between aerobic and anaerobic conditions via microarray analysis. HPLC and GC analyses revealed minor differences in extracellular metabolite profiles at the corresponding early exponential phase time point. Differences in extracellular metabolite profiles between conditions became greater as the fermentations progressed. GC-MS analysis of stationary phase intracellular metabolites indicated that ZM4 contained lower levels of amino acids such as alanine, valine and lysine, and other metabolites like lactate, ribitol, and 4-hydroxybutanoate under anaerobic conditions relative to aerobic conditions. Stationary phase microarray analysis revealed that 166 genes were significantly differentially expressed by more than two-fold. Transcripts for Entner-Doudoroff (ED) pathway genes (glk, zwf, pgl, pgk, and eno) and gene pdc, encoding a key enzyme leading to ethanol production, were at least 30-fold more abundant under anaerobic conditions in the stationary phase based on quantitative-PCR results. We also identified differentially expressed ZM4 genes predicted by The Institute for Genomic Research (TIGR) that were not predicted in the primary annotation.

CONCLUSION

High oxygen concentrations present during Z. mobilis fermentations negatively influence fermentation performance. The maximum specific growth rates were not dramatically different between aerobic and anaerobic conditions, yet oxygen did affect the physiology of the cells leading to the buildup of metabolic byproducts that ultimately led to greater differences in transcriptomic profiles in stationary phase.

Development and application of a differential method for reliable metabolome analysis in Escherichia coli

Quantitative metabolomics of microbial cultures requires well-designed sampling and quenching procedures. We successfully developed and applied a differential method to obtain a reliable set of metabolome data for Escherichia coli K12 MG1655 grown in steady-state, aerobic, glucose-limited chemostat cultures. From a rigorous analysis of the commonly applied quenching procedure based on cold aqueous methanol, it was concluded that it was not applicable because of release of a major part of the metabolites from the cells. No positive effect of buffering or increasing the ionic strength of the quenching solution was observed. Application of a differential method in principle requires metabolite measurements in total broth and filtrate for each measurement. Different methods for sampling of culture filtrate were examined, and it was found that direct filtration without cooling of the sample was the most appropriate. Analysis of culture filtrates revealed that most of the central metabolites and amino acids were present in significant amounts outside the cells. Because the turnover time of the pools of extracellular metabolites is much larger than that of the intracellular pools, the differential method should also be applicable to short-term pulse response experiments without requiring measurement of metabolites in the supernatant during the dynamic period.

Comparative metabolomic analysis of Sinorhizobium sp. C4 during the degradation of phenanthrene

Comparative metabolic responses of Sinorhizobium sp. C4 were investigated. Comprehensive metabolites profiles, including polar metabolites, fatty acids, and polyhydroxyalkanoates were evaluated through untargeted metabolome analyses. Intracellular metabolomes during the degradation of phenanthrene were compared with those from natural carbon sources. Principal component analysis showed a clear separation of metabolomes of phenanthrene degradation from other carbon sources. Shift to more hydrophobic fatty acid was observed from the analysis of fatty acid methyl ester. Polyhydroxyalkanoate from strain C4 was composed mainly with 3-hydroxybutyric acid and small amount of 3-hydroxypentanoic acid, while the monomeric composition was independent on carbon sources. However, the amount of polyhydroxyalkanoates during degradation of phenanthrene was 50–210% less than those from other carbon sources. Among 207 gas chromatography–mass spectrometry peaks from the polar metabolite fraction, 60% of the peaks were identified and compared. Several intermediates in tricarboxylic acid cycles and glycolysis were increased during phenanthrene degradation. Accumulation of trehalose was also evident in the phenanthrene-treated bacterium. Some amino acid, including branched amino acids, glycine, homoserine, and valine, were also increased, while more than 70% of identified metabolites were decreased during the phenanthrene metabolism. Accumulation of sulfur amino acids and nicotinic acid suggested the possible oxidative stress conditions during phenanthrene metabolism.

A biological treasure metagenome: pave a way for big science

The trend of recent researches, in which synthetic biology and white technology through system approaches based on "Omics technology" are recognized as the ground of biotechnology, indicates the coming of the 'metagenome era' that accesses the genomes of all microbes aiming at the understanding and industrial application of the whole microbial resources. The remarkable advance of technologies for digging out and analyzing metagenome is enabling not only practical applications of metagenome but also system approaches on a mixed-genome level based on accumulated information. In this situation, the present review is purposed to introduce the trends and methods of research on metagenome and to examine big science led by related resources in the future.

Affinity-capture tandem mass spectrometric characterization of polyprenyl-linked oligosaccharides: tool to study protein N-glycosylation pathways

N-glycosylation of proteins is recognized as one of the most common post-translational modifications. Until recently it was believed that N-glycosylation occurred exclusively in eukaryotes before the discovery of the general protein glycosylation pathway (Pgl) in Campylobacter jejuni. To date, most techniques to analyze lipid-linked oligosaccharides (LLOs) of these pathways involve the use of radiolabels and chromatographic separation. Technologies capable of characterizing eukaryotic and the newly described bacterial N-glycosylation systems from biologically relevant samples in a quick, accurate, and cost-effective manner are needed. In this paper a new glycomics strategy based on lectin-affinity capture was devised and validated on the C. jejuni N-glycan pathway and the engineered Escherichia coli strains expressing the functional C. jejuni pathway. The lipid-linked oligosaccharide intermediates of the Pgl pathway were then enriched using SBA-agarose affinity-capture and examined by capillary electrophoresis-mass spectrometry (CE-MS). We demonstrate that this method is capable of detecting low levels of LLOs, the sugars are indeed assembled on undecaprenylpyrophosphate, and structural information for expected and unexpected LLOs can be obtained without further sample manipulation. Furthermore, CE-MS analyses of C. jejuni and the E. coli "glyco-factories" showed striking differences in the assembly and control of N-glycan biosynthesis.

Analytical strategies for LC-MS-based targeted metabolomics

Recent advances in mass spectrometry are enabling improved analysis of endogenous metabolites. Here we discuss several issues relevant to developing liquid chromatography-electrospray ionization-mass spectrometry methods for targeted metabolomics (i.e., quantitative analysis of dozens to hundreds of specific metabolites). Sample preparation and liquid chromatography approaches are discussed, with an eye towards the challenge of dealing with a diversity of metabolite classes in parallel. Evidence is presented that heated electrospray ionization (ESI) generally gives improved signal compared to the more traditional unheated ESI. Applicability to targeted metabolomics of triple quadrupole mass spectrometry operating in multiple reaction monitoring (MRM) mode and high mass resolution full scan mass spectrometry (e.g., time-of-flight, Orbitrap) are described. We suggest that both are viable solutions, with MRM preferred when targeting a more limited number of analytes, and full scan preferred for its potential ability to bridge targeted and untargeted metabolomics.

Individual-based modelling: an essential tool for microbiology

Micro-organisms play a central role in every ecosystem and in the global biomass cycle. They are strongly involved in many fields of human interest, from medicine to the food industry and waste control. Nevertheless, most micro-organisms remain almost unknown, and nearly 99% of them have not yet been successfully cultured in vitro. Therefore, new approaches and new tools must be developed in order to understand the collective behaviour of microbial communities in any natural or artificial setting. In particular, theoretical and practical methodologies to deal with such systems at a mesoscopic level of description (covering the range from 100 to 10(8) cells) are required. Individual-based modelling (IBM) has become a widely used tool for describing complex systems made up of autonomous entities, such as ecosystems and social networks. Individual-based models (IBMs) provide some advantages over the traditional whole-population models: (a) they are bottom-up approaches, so they describe the behaviour of a system as a whole by establishing procedural rules for the individuals and for their interactions, and thus allow more realistic assumptions for the model of the individuals than population models do; (b) they permit the introduction of randomness and individual variability, so they can reproduce the diversity found in real systems; and (c) they can account for individual adaptive behaviour to their environmental conditions, so the evolution of the whole system arises from the dynamics that govern individuals in their pursuit of optimal fitness. However, they also present some drawbacks: they lack the clarity of continuous models and may easily become rambling, which makes them difficult to analyse and communicate. All in all, IBMs supply a holistic description of microbial systems and their emerging properties. They are specifically appropriate to deal with microbial communities in non-steady states, and spatially explicit IBMs are particularly appropriate to study laboratory and natural microbiological systems with spatial heterogeneity. In this paper, we review IBM methodology applied to microbiology. We also present some results obtained from the application of Individual Discrete Simulations, an IBM of ours, to the study of bacterial communities, yeast cultures and Plasmodium falciparum-infected erythrocytes in vitro cultures of Plasmodium falciparum-infected erythrocytes.

Metabolic profiling of serum using Ultra Performance Liquid Chromatography and the LTQ-Orbitrap mass spectrometry system

Advances in analytical instrumentation can provide significant advantages to the volume and quality of biological knowledge acquired in metabolomic investigations. The interfacing of sub-2 microm liquid chromatography (UPLC ACQUITY) and LTQ-Orbitrap mass spectrometry systems provides many theoretical advantages. The applicability of the interfaced systems was investigated using a simple 11-component metabolite mix and a complex mammalian biofluid, serum. Metabolites were detected in the metabolite mix with signals that were linear with their concentration over 2.5-3.5 orders of magnitude, with correlation coefficients greater than 0.993 and limits of detection less than 1 micromol L(-1). Reproducibility of retention time (RSD<3%) and chromatographic peak area (RSD<15%) and a high mass accuracy (<2 ppm) were observed for 14 QC serum samples interdispersed with other serum samples, analysed over a period of 40 h. The evaluation of a single deconvolution software package (XCMS) was performed and showed that two parameters (snthresh and bw) provided significant changes to the number of peaks detected and the peak area reproducibility for the dataset used. The data were used to indicate possible biomarkers of pre-eclampsia and showed both the instruments and XCMS to be applicable to the reproducible and valid detection of disease biomarkers present in serum.

Comprehensive analysis of the metabolome of Pseudomonas putida S12 grown on different carbon sources

Metabolomics is an emerging, powerful, functional genomics technology that involves the comparative non-targeted analysis of the complete set of metabolites in an organism. We have set-up a robust quantitative metabolomics platform that allows the analysis of 'snapshot' metabolomes. In this study, we have applied this platform for the comprehensive analysis of the metabolite composition of Pseudomonas putida S12 grown on four different carbon sources, i.e. fructose, glucose, gluconate and succinate. This paper focuses on the microbial aspects of analyzing comprehensive metabolomes, and demonstrates that metabolomes can be analyzed reliably. The technical (i.e. sample work-up and analytical) reproducibility was on average 10%, while the biological reproducibility was approximately 40%. Moreover, the energy charge values of the microbial samples generated were determined, and indicated that no biotic or abiotic changes had occurred during sample work-up and analysis. In general, the metabolites present and their concentrations were very similar after growth on the different carbon sources. However, specific metabolites showed large differences in concentration, especially the intermediates involved in the degradation of the carbon sources studied. Principal component discriminant analysis was applied to identify metabolites that are specific for, i.e. not necessarily the metabolites that show those largest differences in concentration, cells grown on either of these four carbon sources. For selected enzymatic reactions, i.e. the glucose-6-phosphate isomerase, triosephosphate isomerase and phosphoglyceromutase reactions, the apparent equilibrium constants (K(app)) were calculated. In several instances a carbon source-dependent deviation between the apparent equilibrium constant (K(app)) and the thermodynamic equilibrium constant (K(eq)) was observed, hinting towards a potential point of metabolic regulation or towards bottlenecks in biosynthesis routes. For glucose-6-phosphate isomerase and phosphoglyceromutase, the K(app) was larger than K(eq), and the results suggested that the specific enzymatic activities of these two enzymes were too low to reach the thermodynamic equilibrium in growing cells. In contrast, with triosephosphate isomerase the K(app) was smaller than K(eq), and the results suggested that this enzyme is kinetically controlled.

NMR-based metabolic profiling and metabonomic approaches to problems in molecular toxicology

We have reviewed the main contributions to the development of NMR-based metabonomic and metabolic profiling approaches for toxicological assessment, biomarker discovery, and studies on toxic mechanisms. The metabonomic approach, (defined as the quantitative measurement of the multiparametric metabolic response of living systems to pathophysiological stimuli or genetic modification) was originally developed to assist interpretation in NMR-based toxicological studies. However, in recent years there has been extensive fusion with metabolomic and other metabolic profiling approaches developed in plant biology, and there is much wider coverage of the biomedical and environmental fields. Specifically, metabonomics involves the use of spectroscopic techniques with statistical and mathematical tools to elucidate dominant patterns and trends directly correlated with time-related metabolic fluctuations within spectral data sets usually derived from biofluids or tissue samples. Temporal multivariate metabolic signatures can be used to discover biomarkers of toxic effect, as general toxicity screening aids, or to provide novel mechanistic information. This approach is complementary to proteomics and genomics and is applicable to a wide range of problems, including disease diagnosis, evaluation of xenobiotic toxicity, functional genomics, and nutritional studies. The use of biological fluids as a source of whole organism metabolic information enhances the use of this approach in minimally invasive longitudinal studies.

Microbial metabolomics: Toward a platform with full metabolome coverage

Achieving metabolome data with satisfactory coverage is a formidable challenge in metabolomics because metabolites are a chemically highly diverse group of compounds. Here we present a strategy for the development of an advanced analytical platform that allows the comprehensive analysis of microbial metabolomes. Our approach started with in silico metabolome information from three microorganisms-Escherichia coli, Bacillus subtilis, and Saccharomyces cerevisiae-and resulted in a list of 905 different metabolites. Subsequently, these metabolites were classified based on their physicochemical properties, followed by the development of complementary gas chromatography-mass spectrometry and liquid chromatography-mass spectrometry methods, each of which analyzes different metabolite classes. This metabolomics platform, consisting of six different analytical methods, was applied for the analysis of the metabolites for which commercial standards could be purchased (399 compounds). Of these 399 metabolites, 380 could be analyzed with the platform. To demonstrate the potential of this metabolomics platform, we report on its application to the analysis of the metabolome composition of mid-logarithmic E. coli cells grown on a mineral salts medium using glucose as the carbon source. Of the 431 peaks detected, 235 (=176 unique metabolites) could be identified. These include 61 metabolites that were not previously identified or annotated in existing E. coli databases.

Cold glycerol–saline: The promising quenching solution for accurate intracellular metabolite analysis of microbial cells

Microbial metabolomics has been seriously limited by our inability to perform a reliable separation of intra- and extracellular metabolites with efficient quenching of cell metabolism. Microbial cells are sensitive to most (if not all) quenching agents developed to date, resulting in leakage of intracellular metabolites to the extracellular medium during quenching. Therefore, as yet we are unable to obtain an accurate concentration of intracellular metabolites from microbial cell cultures. However, knowledge of the in vivo concentrations of intermediary metabolites is of fundamental importance for the characterization of microbial metabolism so as to integrate meaningful metabolomics data with other levels of functional genomics analysis. In this article, we report a novel and robust quenching method for microbial cell cultures based on cold glycerol-saline solution as the quenching agent that prevents significant leakage of intracellular metabolites and, therefore, permits more accurate measurement of intracellular metabolite concentrations in microbial cells.

Recent advances in molecular techniques for the detection of phylogenetic markers and functional genes in microbial communities

The detection and analysis of nucleic acids extracted from microbial communities are the ultimate ways to determine the diversity and functional capability of microbial communities in the environments. However, it remains a challenge to use molecular techniques for unequivocal determination and quantification of microbial species composition and functional activities. Considerable efforts have been made to enhance the capability of molecular techniques. Here an update of the recent developments in molecular techniques for environmental microbiology is provided.

Comparison of quenching and extraction methodologies for metabolome analysis of Lactobacillus plantarum

Background

A reliable quenching and metabolite extraction method has been developed for Lactobacillus plantarum. The energy charge value was used as a critical indicator for fixation of metabolism.

Results

Four different aqueous quenching solutions, all containing 60% of methanol, were compared for their efficiency. Only the solutions containing either 70 mM HEPES or 0.85% (w/v) ammonium carbonate (pH 5.5) caused less than 10% cell leakage and the energy charge of the quenched cells was high, indicating rapid inactivation of the metabolism.

The efficiency of extraction of intracellular metabolites from cell cultures depends on the extraction methods, and is expected to vary between micro-organisms. For L. plantarum, we have compared five different extraction methodologies based on (i) cold methanol, (ii) perchloric acid, (iii) boiling ethanol, (iv) chloroform/methanol (1:1) and (v) chloroform/water (1:1). Quantification of representative intracellular metabolites showed that the best extraction efficiencies were achieved with cold methanol, boiling ethanol and perchloric acid.

Conclusion

The ammonium carbonate solution was selected as the most suitable quenching buffer for metabolomics studies in L. plantarum because (i) leakage is minimal, (ii) the energy charge indicates good fixation of metabolism, and (iii) all components are easily removed during freeze-drying. A modified procedure based on cold methanol extraction combined good extractability with mild extraction conditions and high enzymatic inactivation. These features make the combination of these quenching and extraction protocols very suitable for metabolomics studies with L. plantarum.

Shotgun metabolomics approach for the analysis of negatively charged water-soluble cellular metabolites from mouse heart tissue

A shotgun metabolomics approach using MALDI-TOF/TOF mass spectrometry was developed for the rapid analysis of negatively charged water-soluble cellular metabolites. Through the use of neutral organic solvents to inactivate endogenous enzyme activities (i.e., methanol/chloroform/H2O extraction), in conjunction with a matrix having minimal background noise (9-amnioacridine), a set of multiplexed conditions was developed that allowed identification of 285 peaks corresponding to negatively charged metabolites from mouse heart extracts. Identification of metabolite peaks was based on mass accuracy and was confirmed by tandem mass spectrometry for 90 of the identified metabolite peaks. Through multiplexing ionization conditions, new suites of metabolites could be ionized and "spectrometric isolation" of closely neighboring peaks for subsequent tandem mass spectrometric interrogation could be achieved. Moreover, assignments of ions from isomeric metabolites and quantitation of their relative abundance was achieved in many cases through tandem mass spectrometry by identification of diagnostic fragmentation ions (e.g., discrimination of ATP from dGTP). The high sensitivity of this approach facilitated the detection of extremely low abundance metabolites including important signaling metabolites such as IP3, cAMP, and cGMP. Collectively, these results identify a multiplexed MALDI-TOF/TOF MS approach for analysis of negatively charged metabolites in mammalian tissues.

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.