Abstract
Microbial transformation is a favored approach for environmental remediation. However, the effectiveness of microbial remediation has been limited by the lack of chassis cells with satisfactory contaminant degradation performance. Pseudomonas putida B6-2, with a wide substrate spectrum and high solvent tolerance, is a chassis strain with great potential for application in environmental remediation. Here, guided by bioinformatic analyses and genome-scale metabolic model (GEM) predictions, we successfully optimized P. putida B6-2 by rationally reducing its nonessential genetic components and generating a more robust genome-streamlined strain, P. putida BGR4. Several improvements were observed compared with the original P. putida B6-2 strain, including a 1.4 × 105-fold increase in electroporation efficiency, an 8.3-fold increase in conjugation efficiency, improved glycerol utilization capability, and increased phenol utilization after heterologous expression of the phenol monooxygenase encoded by dmpKLMNOP. Additionally, P. putida BGR4 exhibited enhanced tolerance to several stressors, including starvation, oxidative stress, and DNA damage. Transcriptomic analysis revealed that genome streamlining led to the upregulation of genes involved in the "carbon metabolism" and "tricarboxylic acid cycle" pathways in P. putida BGR4, which likely contributed to the superior phenotype of P. putida BGR4 in terms of carbon source utilization and contaminant degradation capabilities. Furthermore, the absence of four prophages was identified as a potential cause of the enhanced stress resistance observed in P. putida BGR4. Overall, we developed a combined genome-streamlining strategy involving bioinformatic analyses and GEM predictions and generated a more robust chassis strain, P. putida BGR4, which expands the repertoire of chassis cells for environmental remediation.IMPORTANCEDespite the development of many chassis cells, there is still a lack of robust chassis cells with satisfactory contaminant degradation performance. Targeted genome streamlining is an effective way to provide powerful chassis cells. However, genome streamlining does not always lead to the improved phenotypes of genome-streamlined chassis cells. In this research, a novel procedure that combined bioinformatic analyses and GEM predictions was proposed to guide genome streamlining and predict the effects of genome streamlining. This genome streamlining procedure was successfully applied to Pseudomonas putida B6-2, which was a chassis cell with great potential for application in environmental remediation and resulted in the generation of a more robust chassis cell, P. putida BGR4, thereby providing a superior chassis cell for efficient and sustainable environmental remediation and a valuable framework for guiding the genome streamlining of strains for other applications.