Intelligent host engineering for metabolic flux optimisation in biotechnology

Munro, Lachlan J and Kell, Douglas B ORCID: 0000-0001-5838-7963
(2021) Intelligent host engineering for metabolic flux optimisation in biotechnology. BIOCHEMICAL JOURNAL, 478 (20). pp. 3685-3721.

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Optimising the function of a protein of length N amino acids by directed evolution involves navigating a 'search space' of possible sequences of some 20N. Optimising the expression levels of P proteins that materially affect host performance, each of which might also take 20 (logarithmically spaced) values, implies a similar search space of 20P. In this combinatorial sense, then, the problems of directed protein evolution and of host engineering are broadly equivalent. In practice, however, they have different means for avoiding the inevitable difficulties of implementation. The spare capacity exhibited in metabolic networks implies that host engineering may admit substantial increases in flux to targets of interest. Thus, we rehearse the relevant issues for those wishing to understand and exploit those modern genome-wide host engineering tools and thinking that have been designed and developed to optimise fluxes towards desirable products in biotechnological processes, with a focus on microbial systems. The aim throughput is 'making such biology predictable'. Strategies have been aimed at both transcription and translation, especially for regulatory processes that can affect multiple targets. However, because there is a limit on how much protein a cell can produce, increasing kcat in selected targets may be a better strategy than increasing protein expression levels for optimal host engineering.

Item Type: Article
Uncontrolled Keywords: Bacterial Proteins, Fungal Proteins, Directed Molecular Evolution, Protein Engineering, Proteomics, Industrial Microbiology, Biotechnology, Protein Biosynthesis, Transcription, Genetic, Epistasis, Genetic, Genome, Bacterial, Genome, Fungal, Metabolic Networks and Pathways, Metabolomics, Genetic Association Studies, Metabolic Engineering
Divisions: Faculty of Health and Life Sciences
Faculty of Health and Life Sciences > Institute of Systems, Molecular and Integrative Biology
Depositing User: Symplectic Admin
Date Deposited: 17 Jan 2022 10:16
Last Modified: 18 Jan 2023 21:15
DOI: 10.1042/BCJ20210535
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