etiBsu1209: a comprehensive multiscale metabolic model for Bacillus subtilis
File(s)
Author(s)
Type
Journal Article
Abstract
Genome-scale metabolic models (GEMs) have been widely used to guide the computational design of microbial cell factories, and to date, seven GEMs have been reported for Bacillus subtilis, a model gram-positive microorganism widely used in bioproduction of functional nutraceuticals and food ingredients. However, none of them are widely used because they often lead to erroneous predictions due to their low predictive power and lack of information on regulatory mechanisms. In this work, we constructed a new version of GEM for B. subtilis (iBsu1209), which contains 1209 genes, 1595 metabolites, and 1948 reactions. We applied machine learning to fill gaps, which formed a relatively complete metabolic network able to predict with high accuracy (89.3%) the growth of 1209 mutants under 12 different culture conditions. In addition, we developed a visualization and code-free software, Model Tool, for multiconstraints model reconstruction and analysis. We used this software to construct etiBsu1209, a multiscale model that integrates enzymatic constraints, thermodynamic constraints, and transcriptional regulatory networks. Furthermore, we used etiBsu1209 to guide a metabolic engineering strategy (knocking out fabI and yfkN genes) for the overproduction of nutraceutical menaquinone-7, and the titer increased to 153.94 mg/L, 2.2-times that of the parental strain. To the best of our knowledge, etiBsu1209 is the first comprehensive multiscale model for B. subtilis and can serve as a solid basis for rational computational design of B. subtilis cell factories for bioproduction.
Date Issued
2023-06-01
Date Acceptance
2023-02-13
Citation
Biotechnology and Bioengineering, 2023, 120 (6), pp.1623-1639
ISSN
0006-3592
Publisher
Wiley
Start Page
1623
End Page
1639
Journal / Book Title
Biotechnology and Bioengineering
Volume
120
Issue
6
Copyright Statement
Copyright © 2023 Wiley Periodicals LLC. This is the peer reviewed version of the following article: Bi, X., Cheng, Y., Xu, X., Lv, X., Liu, Y., Li, J., Du, G., Chen, J., Ledesma-Amaro, R., & Liu, L. (2023). etiBsu1209: A comprehensive multiscale metabolic model for Bacillus subtilis. Biotechnology and Bioengineering, 120, 1623–1639. https://doi.org/10.1002/bit.28355, which has been published in final form at https://doi.org/10.1002/bit.28355. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions. This article may not be enhanced, enriched or otherwise transformed into a derivative work, without express permission from Wiley or by statutory rights under applicable legislation. Copyright notices must not be removed, obscured or modified. The article must be linked to Wiley’s version of record on Wiley Online Library and any embedding, framing or otherwise making available the article or pages thereof by third parties from platforms, services and websites other than Wiley Online Library must be prohibited.
Identifier
https://www.ncbi.nlm.nih.gov/pubmed/36788025
Subjects
Bacillus subtilis
Biotechnology & Applied Microbiology
comprehensive multiscale metabolic model
enzymatic constraints
GENOME
Life Sciences & Biomedicine
NETWORKS
RECONSTRUCTION
REFINEMENT
RIBOFLAVIN
Science & Technology
SEQUENCE
thermodynamics constraints
transcriptional regulatory network model
Publication Status
Published
Coverage Spatial
United States
Date Publish Online
2023-02-14