A metabolic model of Lipomyces starkeyi for predicting lipogenesis potential from diverse low-cost substrates.

Flux balance analysis Lipomyces starkeyi Metabolic model Theoretical lipid yield Triacylglycerol

Journal

Biotechnology for biofuels
ISSN: 1754-6834
Titre abrégé: Biotechnol Biofuels
Pays: England
ID NLM: 101316935

Informations de publication

Date de publication:
01 Jul 2021
Historique:
received: 16 04 2021
accepted: 17 06 2021
entrez: 2 7 2021
pubmed: 3 7 2021
medline: 3 7 2021
Statut: epublish

Résumé

Lipomyces starkeyi has been widely regarded as a promising oleaginous yeast with broad industrial application prospects because of its wide substrate spectrum, good adaption to fermentation inhibitors, excellent fatty acid composition for high-quality biodiesel, and negligible lipid remobilization. However, the currently low experimental lipid yield of L. starkeyi prohibits its commercial success. Metabolic model is extremely valuable to comprehend the complex biochemical processes and provide great guidance for strain modification to facilitate the lipid biosynthesis. A small-scale metabolic model of L. starkeyi NRRL Y-11557 was constructed based on the genome annotation information. The theoretical lipid yields of glucose, cellobiose, xylose, glycerol, and acetic acid were calculated according to the flux balance analysis (FBA). The optimal flux distribution of the lipid synthesis showed that pentose phosphate pathway (PPP) independently met the necessity of NADPH for lipid synthesis, resulting in the relatively low lipid yields. Several targets (NADP-dependent oxidoreductases) beneficial for oleaginicity of L. starkeyi with significantly higher theoretical lipid yields were compared and elucidated. The combined utilization of acetic acid and other carbon sources and a hypothetical reverse β-oxidation (RBO) pathway showed outstanding potential for improving the theoretical lipid yield. The lipid biosynthesis potential of L. starkeyi can be significantly improved through appropriate modification of metabolic network, as well as combined utilization of carbon sources according to the metabolic model. The prediction and analysis provide valuable guidance to improve lipid production from various low-cost substrates.

Sections du résumé

BACKGROUND BACKGROUND
Lipomyces starkeyi has been widely regarded as a promising oleaginous yeast with broad industrial application prospects because of its wide substrate spectrum, good adaption to fermentation inhibitors, excellent fatty acid composition for high-quality biodiesel, and negligible lipid remobilization. However, the currently low experimental lipid yield of L. starkeyi prohibits its commercial success. Metabolic model is extremely valuable to comprehend the complex biochemical processes and provide great guidance for strain modification to facilitate the lipid biosynthesis.
RESULTS RESULTS
A small-scale metabolic model of L. starkeyi NRRL Y-11557 was constructed based on the genome annotation information. The theoretical lipid yields of glucose, cellobiose, xylose, glycerol, and acetic acid were calculated according to the flux balance analysis (FBA). The optimal flux distribution of the lipid synthesis showed that pentose phosphate pathway (PPP) independently met the necessity of NADPH for lipid synthesis, resulting in the relatively low lipid yields. Several targets (NADP-dependent oxidoreductases) beneficial for oleaginicity of L. starkeyi with significantly higher theoretical lipid yields were compared and elucidated. The combined utilization of acetic acid and other carbon sources and a hypothetical reverse β-oxidation (RBO) pathway showed outstanding potential for improving the theoretical lipid yield.
CONCLUSIONS CONCLUSIONS
The lipid biosynthesis potential of L. starkeyi can be significantly improved through appropriate modification of metabolic network, as well as combined utilization of carbon sources according to the metabolic model. The prediction and analysis provide valuable guidance to improve lipid production from various low-cost substrates.

Identifiants

pubmed: 34210354
doi: 10.1186/s13068-021-01997-9
pii: 10.1186/s13068-021-01997-9
pmc: PMC8247262
doi:

Types de publication

Journal Article

Langues

eng

Pagination

148

Subventions

Organisme : the National Natural Science Foundation of China
ID : 51608400
Organisme : the Fundamental Research Funds for the Central Public Welfare Research Institutes
ID : ZZ13-YQ-085-C1
Organisme : the Fund from Key Laboratory of Hubei Province for Coal Conversion and New Carbon Materials
ID : WKDM202108

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Auteurs

Wei Zhou (W)

School of Chemistry and Chemical Engineering, Wuhan University of Science and Technology, 947 Heping Road, Wuhan, 430081, People's Republic of China.

Yanan Wang (Y)

State Key Laboratory Breeding Base of Dao-Di Herbs, National Resource Center for Chinese Materia Medica, China Academy of Chinese Medical Sciences, Beijing, 100700, People's Republic of China.

Junlu Zhang (J)

School of Chemistry and Chemical Engineering, Wuhan University of Science and Technology, 947 Heping Road, Wuhan, 430081, People's Republic of China.

Man Zhao (M)

School of Chemistry and Chemical Engineering, Wuhan University of Science and Technology, 947 Heping Road, Wuhan, 430081, People's Republic of China.

Mou Tang (M)

School of Chemistry and Chemical Engineering, Wuhan University of Science and Technology, 947 Heping Road, Wuhan, 430081, People's Republic of China.

Wenting Zhou (W)

School of Chemistry and Chemical Engineering, Wuhan University of Science and Technology, 947 Heping Road, Wuhan, 430081, People's Republic of China. gxuztw1986@wust.edu.cn.
HuBei Province Key Laboratory of Coal Conversion and New Carbon Materials, Wuhan University of Science and Technology, Wuhan, 430081, People's Republic of China. gxuztw1986@wust.edu.cn.

Zhiwei Gong (Z)

School of Chemistry and Chemical Engineering, Wuhan University of Science and Technology, 947 Heping Road, Wuhan, 430081, People's Republic of China. gongzhiwei@wust.edu.cn.
HuBei Province Key Laboratory of Coal Conversion and New Carbon Materials, Wuhan University of Science and Technology, Wuhan, 430081, People's Republic of China. gongzhiwei@wust.edu.cn.

Classifications MeSH