BACKGROUND

The modification of glucose import capacity is an engineering strategy that has been shown to improve the characteristics of Escherichia coli as a microbial factory. A reduction in glucose import capacity can have a positive effect on production strain performance, however, this is not always the case. In this study, E. coli W3110 and a group of four isogenic derivative strains, harboring single or multiple deletions of genes encoding phosphoenolpyruvate:sugar phosphotransferase system (PTS)-dependent transporters as well as non-PTS transporters were characterized by determining their transcriptomic response to reduced glucose import capacity.

RESULTS

These strains were grown in bioreactors with M9 mineral salts medium containing 20 g/L of glucose, where they displayed specific growth rates ranging from 0.67 to 0.27 h, and specific glucose consumption rates (qs) ranging from 1.78 to 0.37 g/g h. RNA-seq analysis revealed a transcriptional response consistent with carbon source limitation among all the mutant strains, involving functions related to transport and metabolism of alternate carbon sources and characterized by a decrease in genes encoding glycolytic enzymes and an increase in gluconeogenic functions. A total of 107 and 185 genes displayed positive and negative correlations with qs, respectively. Functions displaying positive correlation included energy generation, amino acid biosynthesis, and sugar import.

CONCLUSION

Changes in gene expression of E. coli strains with impaired glucose import capacity could be correlated with qs values and this allowed an inference of the physiological state of each mutant. In strains with lower qs values, a gene expression pattern is consistent with energy limitation and entry into the stationary phase. This physiological state could explain why these strains display a lower capacity to produce recombinant protein, even when they show very low rates of acetate production. The comparison of the transcriptomes of the engineered strains employed as microbial factories is an effective approach for identifying favorable phenotypes with the potential to improve the synthesis of biotechnological products.