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Systems biology as an integrated platform for bioinformatics, systems synthetic biology, and systems metabolic engineering.

ABSTRACT: Systems biology aims at achieving a system-level understanding of living organisms and applying this knowledge to various fields such as synthetic biology, metabolic engineering, and medicine. System-level understanding of living organisms can be derived from insight into: (i) system structure and the mechanism of biological networks such as gene regulation, protein interactions, signaling, and metabolic pathways; (ii) system dynamics of biological networks, which provides an understanding of stability, robustness, and transduction ability through system identification, and through system analysis methods; (iii) system control methods at different levels of biological networks, which provide an understanding of systematic mechanisms to robustly control system states, minimize malfunctions, and provide potential therapeutic targets in disease treatment; (iv) systematic design methods for the modification and construction of biological networks with desired behaviors, which provide system design principles and system simulations for synthetic biology designs and systems metabolic engineering. This review describes current developments in systems biology, systems synthetic biology, and systems metabolic engineering for engineering and biology researchers. We also discuss challenges and future prospects for systems biology and the concept of systems biology as an integrated platform for bioinformatics, systems synthetic biology, and systems metabolic engineering.

SUBMITTER: Chen BS

PROVIDER: S-EPMC3972654 | biostudies-literature | 2013 Oct

REPOSITORIES: biostudies-literature

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Systems biology as an integrated platform for bioinformatics, systems synthetic biology, and systems metabolic engineering.

Chen Bor-Sen BS Wu Chia-Chou CC

Cells 20131011 4

Systems biology aims at achieving a system-level understanding of living organisms and applying this knowledge to various fields such as synthetic biology, metabolic engineering, and medicine. System-level understanding of living organisms can be derived from insight into: (i) system structure and the mechanism of biological networks such as gene regulation, protein interactions, signaling, and metabolic pathways; (ii) system dynamics of biological networks, which provides an understanding of st ...[more]

PMID: 24709875

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Project description:Methanogenesis allows methanogenic archaea (methanogens) to generate cellular energy for their growth while producing methane. Hydrogenotrophic methanogens thrive on carbon dioxide and molecular hydrogen as sole carbon and energy sources. Thermophilic and hydrogenotrophic Methanothermobacter spp. have been recognized as robust biocatalysts for a circular carbon economy and are now applied in power-to-gas technology. Here, we generated the first manually curated genome-scale metabolic reconstruction for three Methanothermobacter spp.. We investigated differences in growth performance and gas consumption/production of three wild-type strains and one genetically engineered strain in two independent quadruplicate chemostat bioreactor experiments: 1) with molecular hydrogen and carbon dioxide; and 2) with sodium formate. In the first experiment, we found the highest methane production rate for Methanothermobacter thermautotrophicus ΔH, while Methanothermobacter marburgensis Marburg reached the highest biomass growth rate. We collected statistically reliable transcriptomics and proteomics data sets from these steady-state bioreactors, which we integrated within our genome-scale metabolic models. The implementation of an pan-model that contains combined reactions from all three microbes allowed us to perform an interspecies comparison of the complete omics data set. While the observed differences in the growth behavior cannot be fully explained, the comparison enabled us to identify crucial differences in growth-related pathways, such as formate anabolism. In the second experiment, we found stable growth with a M. thermautotrophicus ΔH plasmid-carrying strain on formate with similar performance parameters compared to wild-type Methanothermobacter thermautotrophicus Z-245. The results of the two studies demonstrate the advantages of an integrative approach using fermentation and omics data with genome-scale modeling for the investigation of lesser studied metabolisms, and the biotechnological potential of Methanothermobacter spp. as production platform hosts.

Dataset Information

Systems biology as an integrated platform for bioinformatics, systems synthetic biology, and systems metabolic engineering.

Publications

Systems biology as an integrated platform for bioinformatics, systems synthetic biology, and systems metabolic engineering.

Similar Datasets

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