Advances in genome-scale metabolic models of industrially important fungi

被引：9

作者：

Han, Yichao ^{[1
,2
]}

Rangel, Albert Tafur ^{[3
,4
]}

Pomraning, Kyle R. ^{[1
,2
]}

Kerkhoven, Eduard J. ^{[3
,4
,5
]}

Kim, Joonhoon ^{[1
,2
,6
]}

机构：

[1] Pacific Northwest Natl Lab, Energy & Environm Directorate, Richland, WA 99352 USA

[2] Agile BioFoundry, Emeryville, CA 94608 USA

[3] Chalmers Univ Technol, Dept Comp Sci, SE-41296 Gothenburg, Sweden

[4] Tech Univ Denmark, Novo Nordisk Fdn Ctr Biosustainabil, DK-2800 Lyngby, Denmark

[5] Chalmers Univ Technol, SciLifeLab, SE-41296 Gothenburg, Sweden

[6] Joint BioEnergy Inst, Dept Energy, Emeryville, CA 94608 USA

来源：

CURRENT OPINION IN BIOTECHNOLOGY | 2023年 / 84卷

关键词：

RESOURCE;

D O I：

10.1016/j.copbio.2023.103005

中图分类号：

Q5 [生物化学];

学科分类号：

071010 ; 081704 ;

摘要：

Many fungal species have been used industrially for production of biofuels and bioproducts. Developing strains with better performance in biomanufacturing contexts requires a systematic understanding of cellular metabolism. Genome-scale metabolic models (GEMs) offer a comprehensive view of interconnected pathways and a mathematical framework for downstream analysis. Recently, GEMs have been developed or updated for several industrially important fungi. Some of them incorporate enzyme constraints, enabling improved predictions of cell states and proteome allocation. Here, we provide an overview of these newly developed GEMs and computational methods that facilitate construction of enzyme-constrained GEMs and utilize flux predictions from GEMs. Furthermore, we highlight the pivotal roles of these GEMs in iterative design-build-test-learn cycles, ultimately advancing the field of fungal biomanufacturing.

引用

页数：9

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