Multi-scale data-driven engineering for biosynthetic titer improvement.
Journal
Current opinion in biotechnology
ISSN: 1879-0429
Titre abrégé: Curr Opin Biotechnol
Pays: England
ID NLM: 9100492
Informations de publication
Date de publication:
10 2020
10 2020
Historique:
received:
03
03
2020
revised:
18
03
2020
accepted:
17
04
2020
pubmed:
3
6
2020
medline:
2
3
2021
entrez:
3
6
2020
Statut:
ppublish
Résumé
Industrial biosynthesis is a very complex process which depends on a range of different factors, from intracellular genes and metabolites, to extracellular culturing conditions and bioreactor engineering. The identification of species that improve the titer of some reaction is akin to the task of finding a needle in a haystack. This review aims to summarize state-of-the-art biosynthesis titer improvement on different scales separately, particularly regarding the advancement of metabolic pathway rewiring and data-driven process optimization and control. By integrating multi-scale data and establishing a mathematical replica of a real biosynthesis, more refined quantitative insights can be gained for achieving a higher titer than ever.
Identifiants
pubmed: 32485576
pii: S0958-1669(20)30054-9
doi: 10.1016/j.copbio.2020.04.002
pii:
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Review
Langues
eng
Sous-ensembles de citation
IM
Pagination
205-212Informations de copyright
Copyright © 2020. Published by Elsevier Ltd.