Altering the sigma D factor of RNA polymerase and thereby improving the robustness of microbial cell factories.

We propose a robustness optimization strategy that combined gene mining and global transcription regulation. As a proof of concept, the common industrial host Escherichia coli was engineered as an example, and the RNA polymerase (RNAP) sigma factor , which governs nearly up to one thousand genes related to growth and stress resistance (The tolerate: A database of transcriptome-level contributions to diverse Escherichia coli resistance and tolerance phenotypes), was selected as the target. The natural rpoD variants were collected from GenBank genomic dataset of E. coli strains living in different environments. Candidate variants were screened based on their potentials in eliciting resistance towards industrially-relevant stresses, including acid stress, osmotic stress, and organic solvent stress. The rpoD that enhanced cell growth were investigated regarding their interactions with the core RNAP and the promoter DNA, as well as their perturbations on the gene expression profile. Instructed by mutation sites occurred in the selected variants, the MG1655 rpoD was reconstructed to elicit superior strain performances. Finally, effects of the naturally-derived and the reconstructed rpoD on robust biosynthesis were evaluated using lycopene and L-alanine production strains. This strategy can be theoretically extended to other global regulatory genes that govern cell functions not limited to anti-stress, carbon metabolism and biosynthesis, which should facilitate the reconstruction of high-performance MCFs.