Metabolic modelling of mixed culture anaerobic microbial processes
Biochemical process modelling (BPM) is at the process level and driven by observations while cellular level modelling (CLM) is at the cellular level and is driven by knowledge about the genetics and microbial capability. [Display omitted] •Multispecies metabolic modelling is essential to analyse ana...
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Veröffentlicht in: | Current opinion in biotechnology 2019-06, Vol.57, p.137-144 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | Biochemical process modelling (BPM) is at the process level and driven by observations while cellular level modelling (CLM) is at the cellular level and is driven by knowledge about the genetics and microbial capability.
[Display omitted]
•Multispecies metabolic modelling is essential to analyse anaerobic ecosystems.•Models can be built top down (empirical) or bottom up (based on genome).•Substantial gap in concept and s between the two approaches.•Effective modelling requires principles from both fields.
Mixed culture anaerobic processes are important to environmental systems, including the global carbon cycle, and industrial and environmental biotechnology. Mixed culture metabolic modelling (MM) is an essential tool to analyse these systems. MM predicts microbial function based on knowledge or assumption of cellular metabolism. It may be developed based on observations at the process level – biochemical process modelling (BPM) or fundamental knowledge of the cell being modelled – cellular level modelling (CLM). There is a substantial gap between these two fields, with BPM not considering genetic constraints, particularly where this may be important to interspecies interactions (e.g. amino acid transfer), and CLM commonly not considering mass transfer principles, such as advection/diffusion/migration. No unified approach is useful for all applications, but there is an increasing need to consider genetic information and constraints in developing BPM, and translate BPM principles (including mass-transfer and inorganic chemistry) for application to CLM. |
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ISSN: | 0958-1669 1879-0429 |
DOI: | 10.1016/j.copbio.2019.03.014 |