In-depth profiling of lysine-producing Corynebacterium glutamicum by combined analysis of the transcriptome, metabolome, and fluxome

Gas Chromatography-Quadrupole Time-of-Flight Mass Spectrometry-Based Determination of Isotopologue and Tandem Mass Isotopomer Fractions of Primary Metabolites for (13)C-Metabolic Flux Analysis

For the first time an analytical work flow based on accurate mass gas chromatography-quadrupole time-of-flight mass spectrometry (GC-QTOFMS) with chemical ionization for analysis providing a comprehensive picture of (13)C distribution along the primary metabolism is elaborated. The method provides a powerful new toolbox for (13)C-based metabolic flux analysis, which is an emerging strategy in metabolic engineering. In this field, stable isotope tracer experiments based on, for example, (13)C are central for providing characteristic patterns of labeled metabolites, which in turn give insights into the regulation of metabolic pathway kinetics. The new method enables the analysis of isotopologue fractions of 42 free intracellular metabolites within biotechnological samples, while tandem mass isotopomer information is also accessible for a large number of analytes. Hence, the method outperforms previous approaches in terms of metabolite coverage, while also providing rich isotopomer information for a significant number of key metabolites. Moreover, the established work flow includes novel evaluation routines correcting for isotope interference of naturally distributed elements, which is crucial following derivatization of metabolites. Method validation in terms of trueness, precision, and limits of detection was performed, showing excellent analytical figures of merit with an overall maximum bias of 5.8%, very high precision for isotopologue and tandem mass isotopomer fractions representing >10% of total abundance, and absolute limits of detection in the femtomole range. The suitability of the developed method is demonstrated on a flux experiment of Pichia pastoris employing two different tracers, i.e., 1,6(13)C2-glucose and uniformly labeled (13)C-glucose.

Multi -omics and metabolic modelling pipelines: challenges and tools for systems microbiology

Integrated -omics approaches are quickly spreading across microbiology research labs, leading to (i) the possibility of detecting previously hidden features of microbial cells like multi-scale spatial organization and (ii) tracing molecular components across multiple cellular functional states. This promises to reduce the knowledge gap between genotype and phenotype and poses new challenges for computational microbiologists. We underline how the capability to unravel the complexity of microbial life will strongly depend on the integration of the huge and diverse amount of information that can be derived today from -omics experiments. In this work, we present opportunities and challenges of multi -omics data integration in current systems biology pipelines. We here discuss which layers of biological information are important for biotechnological and clinical purposes, with a special focus on bacterial metabolism and modelling procedures. A general review of the most recent computational tools for performing large-scale datasets integration is also presented, together with a possible framework to guide the design of systems biology experiments by microbiologists.

Promiscuous activity of (S,S)-butanediol dehydrogenase is responsible for glycerol production from 1,3-dihydroxyacetone in Corynebacterium glutamicum under oxygen-deprived conditions

Corynebacterium glutamicum can consume glucose to excrete glycerol under oxygen deprivation. Although glycerol synthesis from 1,3-dihydroxyacetone (DHA) has been speculated, no direct evidence has yet been provided in C. glutamicum. Enzymatic and genetic investigations here indicate that the glycerol is largely produced from DHA and, unexpectedly, the reaction is catalyzed by (S,S)-butanediol dehydrogenase (ButA) that inherently catalyzes the interconversion between S-acetoin and (S,S)-2,3-butanediol. Consequently, the following pathway for glycerol biosynthesis in the bacterium emerges: dihydroxyacetone phosphate is dephosphorylated by HdpA to DHA, which is subsequently reduced to glycerol by ButA. This study emphasizes the importance of promiscuous activity of the enzyme in vivo.

Reliable Metabolic Flux Estimation in Escherichia coli Central Carbon Metabolism Using Intracellular Free Amino Acids

¹³C metabolic flux analysis (MFA) is a tool of metabolic engineering for investigation of in vivo flux distribution. A direct ¹³C enrichment analysis of intracellular free amino acids (FAAs) is expected to reduce time for labeling experiments of the MFA. Measurable FAAs should, however, vary among the MFA experiments since the pool sizes of intracellular free metabolites depend on cellular metabolic conditions. In this study, minimal ¹³C enrichment data of FAAs was investigated to perform the FAAs-based MFA. An examination of a continuous culture of Escherichia coli using ¹³C-labeled glucose showed that the time required to reach an isotopically steady state for FAAs is rather faster than that for conventional method using proteinogenic amino acids (PAAs). Considering 95% confidence intervals, it was found that the metabolic flux distribution estimated using FAAs has a similar reliability to that of the PAAs-based method. The comparative analysis identified glutamate, aspartate, alanine and phenylalanine as the common amino acids observed in E. coli under different culture conditions. The results of MFA also demonstrated that the ¹³C enrichment data of the four amino acids is required for a reliable analysis of the flux distribution.

Customization of ¹³C-MFA strategy according to cell culture system

(13)C-MFA is far from being a simple assay for quantifying metabolic activity. It requires considerable up-front experimental planning and familiarity with the cell culture system in question, as well as optimized analytics and adequate computation frameworks. The success of a (13)C-MFA experiment is ultimately rated by the ability to accurately quantify the flux of one or more reactions of interest. In this chapter, we describe the different (13)C-MFA strategies that have been developed for the various fermentation or cell culture systems, as well as the limitations of the respective strategies. The strategies are affected by many factors and the (13)C-MFA modeling and experimental strategy must be tailored to conditions. The prevailing philosophy in the computation process is that any metabolic processes that produce significant systematic bias in the labeling pattern of the metabolites being measured must be described in the model. It is equally important to plan a labeling strategy by analytical screening or by heuristics.

Lysine overproducing Corynebacterium glutamicum is characterized by a robust linear combination of two optimal phenotypic states

A homoserine auxotroph strain of Corynebacterium glutamicum accumulates storage compound trehalose with lysine when limited by growth. Industrially lysine is produced from C. glutamicum through aspartate biosynthetic pathway, where enzymatic activity of aspartate kinase is allosterically controlled by the concerted feedback inhibition of threonine plus lysine. Ample threonine in the medium supports growth and inhibits lysine production (phenotype-I) and its complete absence leads to inhibition of growth in addition to accumulating lysine and trehalose (phenotype-II). In this work, we demonstrate that as threonine concentration becomes limiting, metabolic state of the cell shifts from maximizing growth (phenotype-I) to maximizing trehalose phenotype (phenotype-II) in a highly sensitive manner (with a Hill coefficient of 4). Trehalose formation was linked to lysine production through stoichiometry of the network. The study demonstrated that the net flux of the population was a linear combination of the two optimal phenotypic states, requiring only two experimental measurements to evaluate the flux distribution. The property of linear combination of two extreme phenotypes was robust for various medium conditions including varying batch time, initial glucose concentrations and medium osmolality.

Linking post-translational modifications and variation of phenotypic traits

Enzymes can be post-translationally modified, leading to isoforms with different properties. The phenotypic consequences of the quantitative variability of isoforms have never been studied. We used quantitative proteomics to dissect the relationships between the abundances of the enzymes and isoforms of alcoholic fermentation, metabolic traits, and growth-related traits in Saccharomyces cerevisiae. Although the enzymatic pool allocated to the fermentation proteome was constant over the culture media and the strains considered, there was variation in abundance of individual enzymes and sometimes much more of their isoforms, which suggests the existence of selective constraints on total protein abundance and trade-offs between isoforms. Variations in abundance of some isoforms were significantly associated to metabolic traits and growth-related traits. In particular, cell size and maximum population size were highly correlated to the degree of N-terminal acetylation of the alcohol dehydrogenase. The fermentation proteome was found to be shaped by human selection, through the differential targeting of a few isoforms for each food-processing origin of strains. These results highlight the importance of post-translational modifications in the diversity of metabolic and life-history traits.

Systematic applications of metabolomics in metabolic engineering

The goals of metabolic engineering are well-served by the biological information provided by metabolomics: information on how the cell is currently using its biochemical resources is perhaps one of the best ways to inform strategies to engineer a cell to produce a target compound. Using the analysis of extracellular or intracellular levels of the target compound (or a few closely related molecules) to drive metabolic engineering is quite common. However, there is surprisingly little systematic use of metabolomics datasets, which simultaneously measure hundreds of metabolites rather than just a few, for that same purpose. Here, we review the most common systematic approaches to integrating metabolite data with metabolic engineering, with emphasis on existing efforts to use whole-metabolome datasets. We then review some of the most common approaches for computational modeling of cell-wide metabolism, including constraint-based models, and discuss current computational approaches that explicitly use metabolomics data. We conclude with discussion of the broader potential of computational approaches that systematically use metabolomics data to drive metabolic engineering.

Identification of a HAD superfamily phosphatase, HdpA, involved in 1,3-dihydroxyacetone production during sugar catabolism in Corynebacterium glutamicum

Corynebacterium glutamicum produces 1,3-dihydroxyacetone (DHA) as metabolite of sugar catabolism but the responsible enzyme is yet to be identified. Using a transposon mutant library, the gene hdpA (cgR_2128) was shown to encode a haloacid dehalogenase superfamily member that catalyzes dephosphorylation of dihydroxyacetone phosphate to produce DHA. Inactivation of hdpA led to a drastic decrease in DHA production from each of glucose, fructose, and sucrose, indicating that HdpA is the main enzyme responsible for DHA production from sugars in C. glutamicum. Confirmation of DHA production via dihydroxyacetone phosphatase finally confirms a long-speculated route through which bacteria produce DHA.

Increased lysine production by flux coupling of the tricarboxylic acid cycle and the lysine biosynthetic pathway--metabolic engineering of the availability of succinyl-CoA in Corynebacterium glutamicum

In this study, we demonstrate increased lysine production by flux coupling using the industrial work horse bacterium Corynebacterium glutamicum, which was mediated by the targeted interruption of the tricarboxylic acid (TCA) cycle at the level of succinyl-CoA synthetase. The succinylase branch of the lysine production pathway functions as the bridging reaction to convert succinyl-CoA to succinate in this aerobic bacterium. The mutant C. glutamicum ΔsucCD showed a 60% increase in the yield of lysine when compared to the advanced lysine producer which was used as parent strain. This mutant was highly vital and exhibited only a slightly reduced specific growth rate. Metabolic flux analysis with (13)C isotope studies confirmed that the increase in lysine production was mediated by pathway coupling. The novel strain exhibited an exceptional flux profile, which was closer to the optimum performance predicted by in silico pathway analysis than to the large set of lysine-producing strains analyzed thus far. Fluxomics and transcriptomics were applied as further targets for next-level strain engineering to identify the back-up mechanisms that were activated upon deletion of the enzyme in the mutant strain. It seemed likely that the cells partly recruited the glyoxylate shunt as a by-pass route. Additionally, the α-ketoglutarate decarboxylase pathway emerged as the potential compensation mechanism. This novel strategy appears equally promising for Escherichia coli, which is used in the industrial production of lysine, wherein this bacterium synthesizes lysine exclusively by succinyl-CoA activation of pathway intermediates. The channeling of a high flux pathway into a production pathway by pathway coupling is an interesting metabolic engineering strategy that can be explored to optimize bio-production in the future.

Quantification of proteome dynamics in Corynebacterium glutamicum by (15)N-labeling and selected reaction monitoring

Selected reaction monitoring allows quantitative measurements of proteins over several orders of magnitude in complex biological samples. Here we present a targeted approach for quantification of 19 enzymes from Corynebacterium glutamicum applying isotope dilution mass spectrometry coupled to high performance liquid chromatography (IDMS-LC-MS/MS). Investigations of protein dynamics upon growth on acetate and glucose as sole carbon source shows highly stable peptide amounts for enzymes of the central carbon metabolism during the transition phase and after substrate depletion. However significant adaptations of protein amounts are observed between both growth conditions well agreeing with known changes in metabolic fluxes. Time-resolved measurements of protein expression after metabolic switch from glycolytic to gluconeogenetic conditions reveal fast responses in protein synthesis rates for glyoxylate shunt enzymes.

Integrated proteomic and metabolomic analysis of an artificial microbial community for two-step production of vitamin C

An artificial microbial community consisted of Ketogulonicigenium vulgare and Bacillus megaterium has been used in industry to produce 2-keto-gulonic acid (2-KGA), the precursor of vitamin C. During the mix culture fermentation process, sporulation and cell lysis of B. megaterium can be observed. In order to investigate how these phenomena correlate with 2-KGA production, and to explore how two species interact with each other during the fermentation process, an integrated time-series proteomic and metabolomic analysis was applied to the system. The study quantitatively identified approximate 100 metabolites and 258 proteins. Principal Component Analysis of all the metabolites identified showed that glutamic acid, 5-oxo-proline, L-sorbose, 2-KGA, 2, 6-dipicolinic acid and tyrosine were potential biomarkers to distinguish the different time-series samples. Interestingly, most of these metabolites were closely correlated with the sporulation process of B. megaterium. Together with several sporulation-relevant proteins identified, the results pointed to the possibility that Bacillus sporulation process might be important part of the microbial interaction. After sporulation, cell lysis of B. megaterium was observed in the co-culture system. The proteomic results showed that proteins combating against intracellular reactive oxygen stress (ROS), and proteins involved in pentose phosphate pathway, L-sorbose pathway, tricarboxylic acid cycle and amino acids metabolism were up-regulated when the cell lysis of B. megaterium occurred. The cell lysis might supply purine substrates needed for K. vulgare growth. These discoveries showed B. megaterium provided key elements necessary for K. vulgare to grow better and produce more 2-KGA. The study represents the first attempt to decipher 2-KGA-producing microbial communities using quantitative systems biology analysis.

A systems biology approach uncovers cellular strategies used by Methylobacterium extorquens AM1 during the switch from multi- to single-carbon growth

Background

When organisms experience environmental change, how does their metabolic network reset and adapt to the new condition? Methylobacterium extorquens is a bacterium capable of growth on both multi- and single-carbon compounds. These different modes of growth utilize dramatically different central metabolic pathways with limited pathway overlap.

Methodology/Principal Findings

This study focused on the mechanisms of metabolic adaptation occurring during the transition from succinate growth (predicted to be energy-limited) to methanol growth (predicted to be reducing-power-limited), analyzing changes in carbon flux, gene expression, metabolites and enzymatic activities over time. Initially, cells experienced metabolic imbalance with excretion of metabolites, changes in nucleotide levels and cessation of cell growth. Though assimilatory pathways were induced rapidly, a transient block in carbon flow to biomass synthesis occurred, and enzymatic assays suggested methylene tetrahydrofolate dehydrogenase as one control point. This “downstream priming” mechanism ensures that significant carbon flux through these pathways does not occur until they are fully induced, precluding the buildup of toxic intermediates. Most metabolites that are required for growth on both carbon sources did not change significantly, even though transcripts and enzymatic activities required for their production changed radically, underscoring the concept of metabolic setpoints.

Conclusions/Significance

This multi-level approach has resulted in new insights into the metabolic strategies carried out to effect this shift between two dramatically different modes of growth and identified a number of potential flux control and regulatory check points as a further step toward understanding metabolic adaptation and the cellular strategies employed to maintain metabolic setpoints.

Metabolic response of Geobacter sulfurreducens towards electron donor/acceptor variation

Background

Geobacter sulfurreducens is capable of coupling the complete oxidation of organic compounds to iron reduction. The metabolic response of G. sulfurreducens towards variations in electron donors (acetate, hydrogen) and acceptors (Fe(III), fumarate) was investigated via ¹³C-based metabolic flux analysis. We examined the ¹³C-labeling patterns of proteinogenic amino acids obtained from G. sulfurreducens cultured with ¹³C-acetate.

Results

Using ¹³C-based metabolic flux analysis, we observed that donor and acceptor variations gave rise to differences in gluconeogenetic initiation, tricarboxylic acid cycle activity, and amino acid biosynthesis pathways. Culturing G. sulfurreducens cells with Fe(III) as the electron acceptor and acetate as the electron donor resulted in pyruvate as the primary carbon source for gluconeogenesis. When fumarate was provided as the electron acceptor and acetate as the electron donor, the flux analysis suggested that fumarate served as both an electron acceptor and, in conjunction with acetate, a carbon source. Growth on fumarate and acetate resulted in the initiation of gluconeogenesis by phosphoenolpyruvate carboxykinase and a slightly elevated flux through the oxidative tricarboxylic acid cycle as compared to growth with Fe(III) as the electron acceptor. In addition, the direction of net flux between acetyl-CoA and pyruvate was reversed during growth on fumarate relative to Fe(III), while growth in the presence of Fe(III) and acetate which provided hydrogen as an electron donor, resulted in decreased flux through the tricarboxylic acid cycle.

Conclusions

We gained detailed insight into the metabolism of G. sulfurreducens cells under various electron donor/acceptor conditions using ¹³C-based metabolic flux analysis. Our results can be used for the development of G. sulfurreducens as a chassis for a variety of applications including bioremediation and renewable biofuel production.

Size exclusion chromatography: an improved method to harvest Corynebacterium glutamicum cells for the analysis of cytosolic metabolites

The efficient separation of Corynebacterium glutamicum cells from culture medium by size exclusion chromatography (SEC) is presented. Residue analysis demonstrated that this method effectively depletes extracellular compounds. For evaluation, SEC was compared with the common methods cold methanol treatment, fast centrifugation and fast filtration. For this purpose, samples of C. glutamicum cells from fermenter cultures were harvested and subjected to a metabolome analysis. In particular, the wild type strain C. glutamicum ATCC13032 and the lysine production strain C. glutamicum DM1730 were grown in a minimal or in a complex medium. Comparison of metabolite pool sizes after harvesting C. glutamicum cells by the methods mentioned above by gas chromatography coupled to mass spectrometry (GC-MS) revealed that SEC is the most suitable method when intracellular metabolite pools are to be measured during growth in complex media or in the presence of significant amounts of secreted metabolites. In contrast to the other methods tested, the SEC method turned out to be fast and able to remove extracellular compounds almost completely.

Metabolic fluxes and beyond-systems biology understanding and engineering of microbial metabolism

The recent years have seen tremendous progress towards the understanding of microbial metabolism on a higher level of the entire functional system. Hereby, huge achievements including the sequencing of complete genomes and efficient post-genomic approaches provide the basis for a new, fascinating era of research-analysis of metabolic and regulatory properties on a global scale. Metabolic flux (fluxome) analysis displays the first systems oriented approach to unravel the physiology of microorganisms since it combines experimental data with metabolic network models and allows determining absolute fluxes through larger networks of central carbon metabolism. Hereby, fluxes are of central importance for systems level understanding because they fundamentally represent the cellular phenotype as integrated output of the cellular components, i.e. genes, transcripts, proteins, and metabolites. A currently emerging and promising area of research in systems biology and systems metabolic engineering is therefore the integration of fluxome data in multi-omics studies to unravel the multiple layers of control that superimpose the flux network and enable its optimal operation under different environmental conditions.

Prediction of metabolic fluxes by incorporating genomic context and flux-converging pattern analyses

Flux balance analysis (FBA) of a genome-scale metabolic model allows calculation of intracellular fluxes by optimizing an objective function, such as maximization of cell growth, under given constraints, and has found numerous applications in the field of systems biology and biotechnology. Due to the underdetermined nature of the system, however, it has limitations such as inaccurate prediction of fluxes and existence of multiple solutions for an optimal objective value. Here, we report a strategy for accurate prediction of metabolic fluxes by FBA combined with systematic and condition-independent constraints that restrict the achievable flux ranges of grouped reactions by genomic context and flux-converging pattern analyses. Analyses of three types of genomic contexts, conserved genomic neighborhood, gene fusion events, and co-occurrence of genes across multiple organisms, were performed to suggest a group of fluxes that are likely on or off simultaneously. The flux ranges of these grouped reactions were constrained by flux-converging pattern analysis. FBA of the Escherichia coli genome-scale metabolic model was carried out under several different genotypic (pykF, zwf, ppc, and sucA mutants) and environmental (altered carbon source) conditions by applying these constraints, which resulted in flux values that were in good agreement with the experimentally measured (13)C-based fluxes. Thus, this strategy will be useful for accurately predicting the intracellular fluxes of large metabolic networks when their experimental determination is difficult.

Corynebacterium glutamicum exhibits a membrane-related response to a small ferrocene-conjugated antimicrobial peptide

Multiresistant bacteria are becoming more and more widespread. It is therefore necessary to have new compound groups in hand, such as small cationic peptides, to cope with these challenges. In this work, we present a comprehensive approach by monitoring protein expression profiles in a gram-positive bacterium (Corynebacterium glutamicum) to investigate the cellular response to such a compound, a ferrocene-conjugated arginine- and tryptophan-rich pentapeptide. To achieve this, a proteomic outline was performed where the compound-treated sample was compared with an untreated control. This study comprises more than 900 protein identifications, including numerous integral membrane proteins, and among these 185 differential expressions. Surprisingly, unregulated catalase and no elevated H(2)O(2) levels demonstrate that no oxidative stress occurs after treatment with the iron-containing compound as a consequence of the potential Fenton reaction. A sufficient iron supply is evidenced by the iron-containing protein aconitase and SufB (the latter belongs to an iron-sulfur cluster assembly system) and decreased levels of ATP-binding-cassette-type cobalamin/Fe(3+) siderophore transporters. The organometallic peptide antibiotic targets the cell membrane, which is evident by decreased levels of various integral membrane proteins, such as peptide permeases and transporters, and an altered lipid composition. Conversion to a more rigid cell membrane seems to be a relevant protective strategy of C. glutamicum against the ferrocene-conjugated antimicrobial peptide compound.

Genetic and functional analysis of the soluble oxaloacetate decarboxylase from Corynebacterium glutamicum

Soluble, divalent cation-dependent oxaloacetate decarboxylases (ODx) catalyze the irreversible decarboxylation of oxaloacetate to pyruvate and CO(2). Although these enzymes have been characterized in different microorganisms, the genes that encode them have not been identified, and their functions have been only poorly analyzed so far. In this study, we purified a soluble ODx from wild-type C. glutamicum about 65-fold and used matrix-assisted laser desorption ionization-time of flight (MALDI-TOF) analysis and peptide mass fingerprinting for identification of the corresponding odx gene. Inactivation and overexpression of odx led to an absence of ODx activity and to a 30-fold increase in ODx specific activity, respectively; these findings unequivocally confirmed that this gene encodes a soluble ODx. Transcriptional analysis of odx indicated that there is a leaderless transcript that is organized in an operon together with a putative S-adenosylmethionine-dependent methyltransferase gene. Biochemical analysis of ODx revealed that the molecular mass of the native enzyme is about 62 +/- 1 kDa and that the enzyme is composed of two approximately 29-kDa homodimeric subunits and has a K(m) for oxaloacetate of 1.4 mM and a V(max) of 201 micromol of oxaloacetate converted per min per mg of protein, resulting in a k(cat) of 104 s(-1). Introduction of plasmid-borne odx into a pyruvate kinase-deficient C. glutamicum strain restored growth of this mutant on acetate, indicating that a high level of ODx activity redirects the carbon flux from oxaloacetate to pyruvate in vivo. Consistently, overexpression of the odx gene in an L-lysine-producing strain of C. glutamicum led to accumulation of less L-lysine. However, inactivation of the odx gene did not improve L-lysine production under the conditions tested.

Integration of systems biology with bioprocess engineering: L: -threonine production by systems metabolic engineering of Escherichia coli

Random mutation and selection or targeted metabolic engineering without consideration of its impact on the entire metabolic and regulatory networks can unintentionally cause genetic alterations in the region, which is not directly related to the target metabolite. This is one of the reasons why strategies for developing industrial strains are now shifted towards targeted metabolic engineering based on systems biology, which is termed systems metabolic engineering. Using systems metabolic engineering strategies, all the metabolic engineering works are conducted in systems biology framework, whereby entire metabolic and regulatory networks are thoroughly considered in an integrated manner. The targets for purposeful engineering are selected after all possible effects on the entire metabolic and regulatory networks are thoroughly considered. Finally, the strain, which is capable of producing the target metabolite to a high level close to the theoretical maximum value, can be constructed. Here we review strategies and applications of systems biology successfully implemented on bioprocess engineering, with particular focus on developing L: -threonine production strains of Escherichia coli.

Analysis and engineering of metabolic pathway fluxes in Corynebacterium glutamicum

The Gram-positive soil bacterium Corynebacterium glutamicum was discovered as a natural overproducer of glutamate about 50 years ago. Linked to the steadily increasing economical importance of this microorganism for production of glutamate and other amino acids, the quest for efficient production strains has been an intense area of research during the past few decades. Efficient production strains were created by applying classical mutagenesis and selection and especially metabolic engineering strategies with the advent of recombinant DNA technology. Hereby experimental and computational approaches have provided fascinating insights into the metabolism of this microorganism and directed strain engineering. Today, C. glutamicum is applied to the industrial production of more than 2 million tons of amino acids per year. The huge achievements in recent years, including the sequencing of the complete genome and efficient post genomic approaches, now provide the basis for a new, fascinating era of research - analysis of metabolic and regulatory properties of C. glutamicum on a global scale towards novel and superior bioprocesses.

Integrating multiple 'omics' analysis for microbial biology: application and methodologies

Recent advances in various 'omics' technologies enable quantitative monitoring of the abundance of various biological molecules in a high-throughput manner, and thus allow determination of their variation between different biological states on a genomic scale. Several popular 'omics' platforms that have been used in microbial systems biology include transcriptomics, which measures mRNA transcript levels; proteomics, which quantifies protein abundance; metabolomics, which determines abundance of small cellular metabolites; interactomics, which resolves the whole set of molecular interactions in cells; and fluxomics, which establishes dynamic changes of molecules within a cell over time. However, no single 'omics' analysis can fully unravel the complexities of fundamental microbial biology. Therefore, integration of multiple layers of information, the multi-'omics' approach, is required to acquire a precise picture of living micro-organisms. In spite of this being a challenging task, some attempts have been made recently to integrate heterogeneous 'omics' datasets in various microbial systems and the results have demonstrated that the multi-'omics' approach is a powerful tool for understanding the functional principles and dynamics of total cellular systems. This article reviews some basic concepts of various experimental 'omics' approaches, recent application of the integrated 'omics' for exploring metabolic and regulatory mechanisms in microbes, and advances in computational and statistical methodologies associated with integrated 'omics' analyses. Online databases and bioinformatic infrastructure available for integrated 'omics' analyses are also briefly discussed.

Production of aromatic compounds in bacteria

The aromatic class of chemicals includes a large number of industrially important products. In bacteria and plants, the shikimate pathway and related biosynthetic pathways are a source of aromatic compounds having commercial value. Bacterial strains for the production of aromatic compounds from simple carbon sources as raw material have been generated by applying metabolic engineering and random/combinatorial strategies that modify central metabolism, aromatic biosynthetic pathways, transport, and regulatory functions. These strategies are complemented with heterologous gene expression and protein engineering. Engineered Escherichia coli and Pseudomonas putida strains are enabling the development of sustainable processes for the manufacture of 2-phenylethanol, p-hydroxycinnamic acid, p-hydroxystyrene, p-hydroxybenzoate, anthranilate, and cyclohexadiene-transdiols, among other useful chemicals.

Metabolic engineering of the tricarboxylic acid cycle for improved lysine production by Corynebacterium glutamicum

In the present work, lysine production by Corynebacterium glutamicum was improved by metabolic engineering of the tricarboxylic acid (TCA) cycle. The 70% decreased activity of isocitrate dehydrogenase, achieved by start codon exchange, resulted in a >40% improved lysine production. By flux analysis, this could be correlated to a flux shift from the TCA cycle toward anaplerotic carboxylation.

Multifunctional and highly sensitive precolumn reagents for amino acids in liquid chromatography/tandem mass spectrometry

We have developed novel precolumn derivatization reagent, p-N,N,N-trimethylammonioanilyl N'-hydroxysuccinimidyl carbamate iodide (TAHS), for sensitive analyses of amino acids using high-performance liquid chromatography/electrospray ionization tandem mass spectrometry (LC/ESI-MS/MS). TAHS, an activated carbamate, was reacted briefly with the amino group to form a ureide bond under mild condition. The derivatives provided selective cleavage at the binding site between the reagent and the amino acid in the collision cell of the mass spectrometer and produced a characteristic fragment derived from the reagent moiety. Using the precursor ion scan mode of the tandem mass spectrometry, amino acids derivatized with the reagents were simultaneously measured on the chromatogram. Selective cleavage also enabled the straightforward isotope ratio analysis of amino acids by the selected reaction monitoring mode, which was applicable in (13)C metabolic flux analysis. TAHS, which contains a cationic quaternary amine, achieved subfemtomole to attomole levels of amino acids detection by measurement in the selected reaction monitoring mode. We also synthesized trideuteriummethyl-substituted TAHS, TAHS-d(3), and demonstrated that the combination of TAHS and TAHS-d(3) is useful in comparing amino acid concentrations between two different samples using a single LC/MS/MS measurement.

OpenFLUX: efficient modelling software for 13C-based metabolic flux analysis

Background

The quantitative analysis of metabolic fluxes, i.e., in vivo activities of intracellular enzymes and pathways, provides key information on biological systems in systems biology and metabolic engineering. It is based on a comprehensive approach combining (i) tracer cultivation on ¹³C substrates, (ii) ¹³C labelling analysis by mass spectrometry and (iii) mathematical modelling for experimental design, data processing, flux calculation and statistics. Whereas the cultivation and the analytical part is fairly advanced, a lack of appropriate modelling software solutions for all modelling aspects in flux studies is limiting the application of metabolic flux analysis.

Results

We have developed OpenFLUX as a user friendly, yet flexible software application for small and large scale ¹³C metabolic flux analysis. The application is based on the new Elementary Metabolite Unit (EMU) framework, significantly enhancing computation speed for flux calculation. From simple notation of metabolic reaction networks defined in a spreadsheet, the OpenFLUX parser automatically generates MATLAB-readable metabolite and isotopomer balances, thus strongly facilitating model creation. The model can be used to perform experimental design, parameter estimation and sensitivity analysis either using the built-in gradient-based search or Monte Carlo algorithms or in user-defined algorithms. Exemplified for a microbial flux study with 71 reactions, 8 free flux parameters and mass isotopomer distribution of 10 metabolites, OpenFLUX allowed to automatically compile the EMU-based model from an Excel file containing metabolic reactions and carbon transfer mechanisms, showing it's user-friendliness. It reliably reproduced the published data and optimum flux distributions for the network under study were found quickly (<20 sec).

Conclusion

We have developed a fast, accurate application to perform steady-state ¹³C metabolic flux analysis. OpenFLUX will strongly facilitate and enhance the design, calculation and interpretation of metabolic flux studies. By providing the software open source, we hope it will evolve with the rapidly growing field of fluxomics.

Advances in analysis of microbial metabolic fluxes via (13)C isotopic labeling

Metabolic flux analysis via (13)C labeling ((13)C MFA) quantitatively tracks metabolic pathway activity and determines overall enzymatic function in cells. Three core techniques are necessary for (13)C MFA: (1) a steady state cell culture in a defined medium with labeled-carbon substrates; (2) precise measurements of the labeling pattern of targeted metabolites; and (3) evaluation of the data sets obtained from mass spectrometry measurements with a computer model to calculate the metabolic fluxes. In this review, we summarize recent advances in the (13)C-flux analysis technologies, including mini-bioreactor usage for tracer experiments, isotopomer analysis of metabolites via high resolution mass spectrometry (such as GC-MS, LC-MS, or FT-ICR), high performance and large-scale isotopomer modeling programs for flux analysis, and the integration of fluxomics with other functional genomics studies. It will be shown that there is a significant value for (13)C-based metabolic flux analysis in many biological research fields.

Induction of cadBA in an Escherichia coli lysine auxotroph transformed with a cad-gfp transcriptional fusion

CadBA functions as a part of overall Escherichia coli response to low extracellular pH. A gfpmut3 structural gene transcriptionally fused to the cadBA promoter (Pcad) was used as a reporter to monitor changes in intracellular lysine as a potential factor influencing cadBA induction. Different patterns of cadBA induction were observed in two E. coli strains with different lysine biosynthetic capabilities. In E. coli ZK126 (pJBA25-Pcad), a lysine prototroph, maximum levels of induction were detected 3 h after the transfer of bacterial cells under inducing conditions (pH 5.8; 3.4 microM extracellular lysine). The induction subsequently decreased until hour 7 after which no further change in expression was observed. However, in the lysine depleted strain E. coli ATCC 23812 (pJBA25-Pcad) which is an auxotroph for lysine, no decrease in cadBA expression was observed over time under the same induction conditions. Although no time dependent statistical differences in intracellular lysine were observed, bacterial cells depleted for no longer than 4 h (1.38 +/- 0.25 micromol lysine/g cell dry weight) exhibited more rapid induction of cadBA (after 3 h) and a lower maximum level of induction compared to cells with relatively lower intracellular lysine (approximately 1.08 micromol/g cell dry weight). For the latter, the detectable level of induction was delayed for 1 h but the maximum level of induction response was higher.