Metabolomic analysis of microorganisms

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Abstract

Molecular BioSystems Editorial Board members Hirotada Mori and Tadhg Begley introduce this theme issue on the field of metabolomic analysis in bacteria and its future direction.

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The investigation of cellular metabolic pathway networks is a remarkably varied field requiring a wide range of knowledge and theoretical and experimental tools taken from a diversity of scientific disciplines. This diversity, from basic to applied science, and involving interdisciplinary fields from mathematical modeling to experimental approaches, is well illustrated by the articles in this thematic issue of Molecular BioSystems, entitled “Metabolomic analysis of microorganisms”. The articles described here involve a systems approach to the study of metabolism in bacteria supported by comprehensive measurements made possible by the new technologies and theoretical and mathematical analyses which constitute the field now known as Systems Biology.

Systems Biology itself, however, is not a novel approach for understanding cellular systems. Over a couple of decades significant developments have been made. The difference between the past and present situation is the difference between the size of the target systems to be analyzed, based on comprehensive quantitative experimental data. The turning point has clearly been the “Genome Project” which has provided a fixed number of parts (i.e. the gene set) providing the cell system with biological and physiological information. Technological innovation during the 1990s for the Genome Project has been especially important for the dramatic expansion of Systems Biology. Comprehensive and quantitative measurements of transcription, translation, enzyme reactions and product amounts etc. in a cell were realized in practice. This remarkable progress has moved the Systems Biology field towards a more promising approach for understanding a cell system globally and quantitatively with the support of interdisciplinary research.

In this field, understanding and modeling metabolic networks is one of the most important targets, not only for engineering to produce valuable compounds, but also for a fundamental understanding of cellular physiology and for understanding molecular mechanisms of robustness, which are a very important cellular function.

In 2007, the comprehensive metabolomic analysis of E. coli, including fluxome, transcriptome and proteome analyses, was reported. They showed evidence of homeostasis in the level of metabolites using single gene deletion mutant strains.¹ What we learned from that paper was that the cell makes efforts to keep stable metabolite levels by changing transcription, translation and enzyme activity. In this thematic issue of Molecular BioSystems, we have made efforts to describe the present situation of metabolomic analysis and to consider its future direction.

Recently, it has been found that many major metabolic pathway genes are regulated by RpoS at the early stationary growing phase. It might be the case that the regulation of global dynamic changes in cellular metabolism is primarily controlled by transcription factors, especially by so-called global regulators, such as RpoS, CRP and SoxRS etc. In this context, Shimizu and Rahman at the Kyushu Institute of Technology have focused in this issue on the regulation of central metabolic pathway genes by the stress responsive sigma factor, RpoS. They describe the importance of RpoS regulation of TCA cycle genes for higher acetate consumption and biomass yield. They analyzed metabolism and the biomass yield of single gene deletion mutants regulated by RpoS. Those were tktB and talA genes of the non-oxidative pentose phosphate pathway and fumC and acnA genes of the TCA cycle. They measured comprehensively and quantitatively specific activities of central metabolic pathway enzymes and also some of the key metabolite concentrations. Based on their results, they concluded the importance of RpoS in relation to metabolism and biomass production.

Similarly, Hiroshi Shimizu and his colleagues at Osaka University have shown the importance of gene regulation in metabolic pathways. They analyzed the expression of genes involved in lysine biosynthesis in E. coli to obtain a quantitative understanding of the gene regulatory network. They used promoter fusions with GFP of genes associated with lysine biosynthesis and monitored time-dependent changes in gene expression in response to changes in lysine concentration. Based on the quantitative data from flow cytometry, they constructed dynamical and theoretical models of gene expression to estimate the parameters of gene regulation. The fitting parameters revealed the key step for gene regulation of the biosynthesis and enabled an elucidation of the gene expression dynamics in this biosynthetic pathway. Again, we realize the importance of gene regulation for metabolic activities.

Flux analysis is a very important method for understanding metabolic pathways. Metabolic flux analysis is an analytical technique that quantifies intracellular metabolic fluxes and analyzes functional aspects of their network in greater detail. This analysis is based on mass balances of cellular metabolites normally at a steady state of growth. Generally two methods have been used: stable isotope ¹³C-based flux analysis and constraint-based flux analysis. In this issue Sang Yup Lee and his colleagues have reviewed clearly the present flux analysis methods and have also described their limitations. Flux analysis is no exception to the dramatic changes occurring after the genome project during the 1990s and they have also illustrated the history of reconstruction of the genome-scale stoichiometric metabolic models. The latest achievement is that the comprehensive metabolic model of E. coli, composed of 2077 reactions and 1039 metabolites, has been established by Palsson and his colleagues at the University of California San Diego in 2007.² Finally, in their Highlight Lee and colleagues proposed three future directions from the limitations of simulating genome-scale stoichiometric models with constraint-based flux analysis: (i) integrating gene regulatory networks, (ii) development of methods to simulate the cell growth state other than exponential phase or chemostat culture, and (iii) new validation methods to monitor the accuracy of metabolic flux analysis.

Genome-scale modeling and simulation has been pointed out as one of the important directions in the systems approach. In this issue of Molecular BioSystems Dieter Oesterhelt and his colleagues report a similar trial to reconstruct genome-scale modeling of the extreme halophile Halobacterium salinarum, which consists of 557 metabolites, 600 reactions associated with 417 genes and 111 transport reactions with 73 genes mainly from the KEGG database. Using their model, they report here the computational analysis of the aerobic growth of this organism using dynamic simulations in media with 15 available carbon and energy sources. They mention the usefulness of this approach for interpretation and for making hypotheses for next step experiments and show some biologically interesting predictions for ribose and shikimate biosynthesis. The experiments to confirm their predictions are now underway and we look forward to seeing the evidence in the near future.

Tomoyoshi Soga and his colleagues were the group which developed an efficient method to identify and quantify metabolites in a cell in a high throughput manner by combination of capillary electrophoresis with mass spectrometry in 2003.³ In this issue of Molecular BioSystems, they analyze the alteration of metabolite concentration profiles after histidine starvation in E. coli. For this analysis, they improved the extraction method of metabolites from E. coli cells. They analyzed 375 charged, hydrophilic intermediates in primary metabolism and 198 of them were quantitatively measured. The response of the E. coli cell to histidine starvation has been described yet this method still remains to be improved for analyzing the oxidation of metabolite pools. As mentioned earlier, like most areas of science, major advances in understanding the metabolism in a cell have come through the invention and development of new technologies. In this context, the method applied in this analysis should rank among such developments.

Recent analytical techniques, especially developments in mass spectrometry and its applications, can also encompass the analyses of lipids. The comprehensive and systematic approaches to characterize lipid molecular species and their biological roles with respect to the regulation of gene expression involved in lipid metabolism and function, known as ‘lipidomics’, has now emerged. Lipids are a complex molecular class with enormous structural diversity, mainly originating from various combinations of fatty acid chain lengths and possible head groups, such as glycerol-phospholipids. Molecules in this family play important structural, energy storage and signaling roles in biological systems. In this issue of Molecular BioSystems Matej Orešič and his colleagues have presented the whole picture regarding the recent approach to lipidomics. They also mention consortia in Europe, US and Japan, which reflect the growing need for a detailed understanding of lipids.

Biofilm formation is a critical step for infections by pathogens and has been implicated in the barrier for resistance of microbes to antibiotics and immune responses. Therefore, the efficient detection and quantification of key components are required to assist the design of clinical infection responses. To identify and quantify these biofilm components, which are secreted outside of the cell, is another important metabolome target especially for environmental response and bacterial pathogenicity. Mark Howard and his colleagues describe here a new method using NMR and its application for the identification of carbohydrate polymer components in crude biofilm extracts from Staphylococcus epidermidis.

Finally, from the papers in this themed issue of Molecular BioSystems, we can learn much about the field of metabolome analysis and its future directions. The importance of gene regulation in metabolic pathways, the review of flux analysis, which is an important analytical method for metabolic pathways, dynamic changes in metabolite profiles, new techniques to identify extra cellular components and dynamic changes in gene regulation are well illustrated in this issue. The mechanism of the robustness of metabolic pathways has still to become clear. The bacterial cell generally accepts a single gene deletion mutation to the chromosome and this clearly shows that the cell has alternative or bypass pathways for the removed metabolic step. This may be a further mechanism of robustness in addition to the regulation of transcription, translation and enzyme activity. To clarify this problem is the same as to elucidate the genetic network in a cell. In the bacterial field, however, comprehensive and systematic approaches to this problem have just started and the results are expected in the future.

We hope this issue will give you an opportunity to view the field of metabolomic analysis in bacteria and its future direction.

Hirotada Mori

Molecular BioSystems Editorial Board

Tadhg Begley

Molecular BioSystems Editorial Board

References

1. Ishii et al., Science, 2007, 316(5824), 593–597.
2. Feist et al., Mol. Syst. Biol., 2007, 3, article number 121.
3. Soga et al., J. Proteome Res., 2003, 2(5), 488–494.

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