About this Research Topic
The emergence of certain tools in synthetic biology and knowledge in genomic sciences has opened opportunities for better understanding microbial metabolism and further designing chassis microbes to produce renewable fuels/chemicals. Yet realizing this potential is not straightforward, largely due to limited knowledge in the complexity of interacting metabolic networks, the underlying regulations and signaling, as well as pathway bottlenecks.
Fluxomics, especially isotope tracer directed metabolic flux analysis, could fill these knowledge gaps and provide a high-quality road map to design, modify, and optimize microbes for beneficial purposes. With a tight relevance to microbiology and metabolic engineering, fluxomics provides an integrated experimental/computational approach that is designed to systematically quantify the rates of biochemical reactions within a biological system. The fluxomics information mirrors the metabolic phenotype in a comprehensive and quantitative way.
The progress in technologies used for fluxomics has occurred at a very high rate during the last decade. In its earliest appearance, fluxomics emerged as a computational methodology based on Flux Balance Analysis (FBA), by which intracellular fluxes are estimated from stoichiometric reaction models with a handful of experimental inputs (e.g. extracellular consumption and secretion rates). It has developed to be more elaborate by employing isotope tracer experiments in which stable isotopes (e.g. 13C, 15N, 2H, etc.) are incorporated by cells and imprinted into downstream metabolites. Metabolic flux information within labeled metabolites can be quantitatively analyzed by means of Mass Spectrometry (MS) and/or Nuclear Magnetic Resonance (NMR) measurements. Nowadays, innovative methods and techniques have greatly expanded the range and quality of data that can be obtained by fluxomic approaches. For instance, fluxomics has evolved from the steady-state labeling strategy to dynamic flux analysis that is able to provide kinetic details and knowledge about interconversion of biomolecules. This progress provides metabolite labeling trajectories as a function of time and allows the acquisition of information on functional aspects and regulatory features.
Microorganisms represent as an ideal model system for fluxomic research and microbial fluxomics can address specific metabolic features of microbes like archaea, bacteria or fungi. In recent years, an advanced fluxomic approach has been used to investigate a few important metabolic processes in microbes. It has been applied to understand nitrogen metabolism in E. coli and photosynthetic microalgae, unveil the topological structure of the tricarboxylic acid cycle in cyanobacteria, and pinpoint the rate-limiting reactions in engineered isoprene biosynthetic pathway, etc. We anticipate even broader applications of fluxomic method in this field.
With this research topic our purpose is to congregate an issue related to recent advances on fluxomics and its latest applications in deciphering microbial metabolism: for example, experimental design, technical issues, data analysis for fluxomics, and new insights into metabolic pathways obtained from fluxomic approach. Research articles on the combination of fluxomic method and other -omics approaches to understand microbial physiology are very much encouraged. Abstracts for manuscripts describing original research, methods, opinions, reviews, and mini reviews are welcome.
Fluxomics, especially isotope tracer directed metabolic flux analysis, could fill these knowledge gaps and provide a high-quality road map to design, modify, and optimize microbes for beneficial purposes. With a tight relevance to microbiology and metabolic engineering, fluxomics provides an integrated experimental/computational approach that is designed to systematically quantify the rates of biochemical reactions within a biological system. The fluxomics information mirrors the metabolic phenotype in a comprehensive and quantitative way.
The progress in technologies used for fluxomics has occurred at a very high rate during the last decade. In its earliest appearance, fluxomics emerged as a computational methodology based on Flux Balance Analysis (FBA), by which intracellular fluxes are estimated from stoichiometric reaction models with a handful of experimental inputs (e.g. extracellular consumption and secretion rates). It has developed to be more elaborate by employing isotope tracer experiments in which stable isotopes (e.g. 13C, 15N, 2H, etc.) are incorporated by cells and imprinted into downstream metabolites. Metabolic flux information within labeled metabolites can be quantitatively analyzed by means of Mass Spectrometry (MS) and/or Nuclear Magnetic Resonance (NMR) measurements. Nowadays, innovative methods and techniques have greatly expanded the range and quality of data that can be obtained by fluxomic approaches. For instance, fluxomics has evolved from the steady-state labeling strategy to dynamic flux analysis that is able to provide kinetic details and knowledge about interconversion of biomolecules. This progress provides metabolite labeling trajectories as a function of time and allows the acquisition of information on functional aspects and regulatory features.
Microorganisms represent as an ideal model system for fluxomic research and microbial fluxomics can address specific metabolic features of microbes like archaea, bacteria or fungi. In recent years, an advanced fluxomic approach has been used to investigate a few important metabolic processes in microbes. It has been applied to understand nitrogen metabolism in E. coli and photosynthetic microalgae, unveil the topological structure of the tricarboxylic acid cycle in cyanobacteria, and pinpoint the rate-limiting reactions in engineered isoprene biosynthetic pathway, etc. We anticipate even broader applications of fluxomic method in this field.
With this research topic our purpose is to congregate an issue related to recent advances on fluxomics and its latest applications in deciphering microbial metabolism: for example, experimental design, technical issues, data analysis for fluxomics, and new insights into metabolic pathways obtained from fluxomic approach. Research articles on the combination of fluxomic method and other -omics approaches to understand microbial physiology are very much encouraged. Abstracts for manuscripts describing original research, methods, opinions, reviews, and mini reviews are welcome.
Keywords: Metabolic Flux Analysis, Stable Isotope Labelling, Metabolic Pathways, Mass Spectroscopy, Modelling
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