Strategies to increase the robustness of microbial cell factories
Pei Xu, Nuo-Qiao Lin, Zhiqian Zhang, Jian-Zhong Liu
Abstract
Engineering microbial cell factories have achieved much progress in producing fuels, natural products and bulk chemicals. However, in industrial fermentation, microbial cells often face various predictable and stochastic disturbances resulting from intermediate metabolites or end product toxicity, metabolic burden and harsh environment. These perturbances can potentially decrease productivity and titer. Therefore, strain robustness is essential to ensure reliable and sustainable production efficiency. In this review, the current strategies to improve host robustness were summarized, including knowledge-based engineering approaches, such as transcription factors, membrane/transporters and stress proteins, and the traditional adaptive laboratory evolution based on natural selection. Computation-assisted (e.g. GEMs, deep learning and machine learning) design of robust industrial hosts was also introduced. Furthermore, the challenges and future perspectives on engineering microbial host robustness are proposed to promote the development of green, efficient and sustainable biomanufacturers.