A framework based on fundamental biochemical principles to engineer microbial community dynamics.

Autor: González-Cabaleiro R; James Watt School of Engineering, Infrastructure and Environment Research Division, University of Glasgow, Rankine Building, Glasgow, G12 8LT, UK. Electronic address: rebeca.gonzalez-cabaleiro@glasgow.ac.uk., Martinez-Rabert E; James Watt School of Engineering, Infrastructure and Environment Research Division, University of Glasgow, Rankine Building, Glasgow, G12 8LT, UK., Argiz L; CRETUS Institute, Department of Chemical Engineering, Universidade de Santiago de Compostela, 15782 Santiago de Compostela, Galicia, Spain., van Kessel MA; Radboud University, Department of Microbiology, Institute of Water and Wetland Research, Radboud University, Nijmegen, The Netherlands., Smith CJ; James Watt School of Engineering, Infrastructure and Environment Research Division, University of Glasgow, Rankine Building, Glasgow, G12 8LT, UK.
Jazyk: angličtina
Zdroj: Current opinion in biotechnology [Curr Opin Biotechnol] 2021 Feb; Vol. 67, pp. 111-118. Date of Electronic Publication: 2021 Feb 01.
DOI: 10.1016/j.copbio.2021.01.001
Abstrakt: Microbial communities are complex but there are basic principles we can apply to constrain the assumed stochasticity of their activity. By understanding the trade-offs behind the kinetic parameters that define microbial growth, we can explain how local interspecies dependencies arise and shape the emerging properties of a community. If we integrate these theoretical descriptions with experimental 'omics' data and bioenergetics analysis of specific environmental conditions, predictions on activity, assembly and spatial structure can be obtained reducing the a priori unpredictable complexity of microbial communities. This information can be used to define the appropriate selective pressures to engineer bioprocesses and propose new hypotheses which can drive experimental research to accelerate innovation in biotechnology.
(Copyright © 2021 Elsevier Ltd. All rights reserved.)
Databáze: MEDLINE
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