Engineering thermotolerant microbial strains via TrRCC1 overexpression for efficient bioethanol production

Abstract

Efficient conversion of corn stover to bioethanol via simultaneous saccharification and fermentation (SSF) is a promising strategy for sustainable biofuel production. A major current barrier to this process is the limited thermotolerance of Saccharomyces cerevisiae, which hampers its performance under the high-temperature conditions required for efficient SSF. In this study, we identified TrRCC1, a gene from Trichoderma reesei, as a candidate for improving microbial stress resistance. Overexpression of TrRCC1 in both T. reesei Rut C30 and S. cerevisiae BY4741 significantly enhanced thermotolerance. In T. reesei Rut C30, TrRCC1 overexpression improved heat resistance and increased cellulase production by 2.5-fold compared to the wild-type strain. In S. cerevisiae BY4741, TrRCC1 overexpression resulted in enhanced thermotolerance and a 21.8 % increase in ethanol production during SSF of corn stover. The ethanol concentration achieved in the SSF process with TrRCC1-overexpressing S. cerevisiae was 44.1 g/L, which was a notable improvement over control strain production. These findings highlight the potential of TrRCC1 as a key gene for engineering microbial strains with improved stress resistance to enhance the efficiency of bioethanol production from lignocellulosic biomass.

Keywords

Trichodema reesei / RCC1 / Saccharomyces cerevisiae / Bioethanol / Temperature tolerance / Simultaneous saccharification and fermentation

Data Availability Statement

All data generated or analyzed during this study are included in this article.

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

CRediT Authorship Contribution Statement

Tingting Chen: Writing - original draft, Data curation. Xiao He: Formal analysis. Xinyan Zhang: Formal analysis. Tian Tian: Validation. Jian Cheng: Visualization. Tingting Long: Methodology. Yonghao Li: Writing - review & editing, Writing - original draft.

Acknowledgements

This work was supported by the National Natural Science Foundation of China (22378033), Natural Science Foundation Project of Chongqing, the Chongqing Science and Technology Commission (CN) (CSTB2022NSCQ-MSX0544), Science and Technology Research Program of Chongqing Municipal Education Commission (KJZD-M202401502 and KJQN202301546), and Postgraduate Research and Innovation Project of Chongqing University of Science and Technology (YKJCX2420531).

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