Streamlining Natural Products Biomanufacturing With Omics and Machine Learning Driven Microbial Engineering.
biomanufacturing
machine learning
microbial engineering
omics technology
synthetic biology
systems biology
Journal
Frontiers in bioengineering and biotechnology
ISSN: 2296-4185
Titre abrégé: Front Bioeng Biotechnol
Pays: Switzerland
ID NLM: 101632513
Informations de publication
Date de publication:
2020
2020
Historique:
received:
22
09
2020
accepted:
18
11
2020
entrez:
7
1
2021
pubmed:
8
1
2021
medline:
8
1
2021
Statut:
epublish
Résumé
Increasing demands for the supply of biopharmaceuticals have propelled the advancement of metabolic engineering and synthetic biology strategies for biomanufacturing of bioactive natural products. Using metabolically engineered microbes as the bioproduction hosts, a variety of natural products including terpenes, flavonoids, alkaloids, and cannabinoids have been synthesized through the construction and expression of known and newly found biosynthetic genes primarily from model and non-model plants. The employment of omics technology and machine learning (ML) platforms as high throughput analytical tools has been increasingly leveraged in promoting data-guided optimization of targeted biosynthetic pathways and enhancement of the microbial production capacity, thereby representing a critical debottlenecking approach in improving and streamlining natural products biomanufacturing. To this end, this mini review summarizes recent efforts that utilize omics platforms and ML tools in strain optimization and prototyping and discusses the beneficial uses of omics-enabled discovery of plant biosynthetic genes in the production of complex plant-based natural products by bioengineered microbes.
Identifiants
pubmed: 33409270
doi: 10.3389/fbioe.2020.608918
pmc: PMC7779585
doi:
Types de publication
Journal Article
Review
Langues
eng
Pagination
608918Informations de copyright
Copyright © 2020 Ramzi, Baharum, Bunawan and Scrutton.
Déclaration de conflit d'intérêts
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
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