Genome-scale modeling for Bacillus coagulans to understand the metabolic characteristics
Journal article, 2020

Lactic acid is widely used in many industries, especially in the production of poly-lactic acid. Bacillus coagulans is a promising lactic acid producer in industrial fermentation due to its thermophilic property. In this study, we developed the first genome-scale metabolic model (GEM) of B. coagulans iBag597, together with an enzyme-constrained model ec-iBag597. We measured strain-specific biomass composition and integrated the data into a biomass equation. Then, we validated iBag597 against experimental data generated in this study, including amino acid requirements and carbon source utilization, showing that simulations were generally consistent with the experimental results. Subsequently, we carried out chemostats to investigate the effects of specific growth rate and culture pH on metabolism of B. coagulans. Meanwhile, we used iBag597 to estimate the intracellular metabolic fluxes for those conditions. The results showed that B. coagulans was capable of generating ATP via multiple pathways, and switched among them in response to various conditions. With ec-iBag597, we estimated the protein cost and protein efficiency for each ATP-producing pathway to investigate the switches. Our models pave the way for systems biology of B. coagulans, and our findings suggest that maintaining a proper growth rate and selecting an optimal pH are beneficial for lactate fermentation.

Bacillus coagulans

lactic acid fermentation

metabolic switch

constraint-based model

chemostat

Author

Yu Chen

Chalmers, Biology and Biological Engineering, Systems and Synthetic Biology

East China University of Science and Technology

Yan Sun

East China University of Science and Technology

Zhihao Liu

East China University of Science and Technology

Fengqing Dong

East China University of Science and Technology

Yuanyuan Li

East China University of Science and Technology

Yonghong Wang

East China University of Science and Technology

Biotechnology and Bioengineering

0006-3592 (ISSN) 1097-0290 (eISSN)

Vol. 117 11 3545-3558

Subject Categories

Chemical Process Engineering

Bioinformatics (Computational Biology)

Bioinformatics and Systems Biology

DOI

10.1002/bit.27488

PubMed

32648961

More information

Latest update

11/5/2020