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Industrial strains have been traditionally improved by rational approaches and combinatorial methods involving mutagenesis and selection. Recently, other methods have emerged, such as the use of artificial transcription factors and engineering of the native ones. As methods for generating genetic diversity continue to proliferate, the need for quantifying phenotypic diversity and, hence, assessing the potential of various genetic libraries for strain improvement becomes more pronounced. Here, we present a metric based on the quantification of phenotypic diversity, using Lactobacillus plantarum as a model organism. We found that phenotypic diversity can be introduced by mutagenesis of the principal sigma factor, that this diversity can be modulated by tuning the sequence diversity, and that this method compares favorably with commonly used protocols for chemical mutagenesis. The results of the diversity metric here developed also correlated well with the probability of finding improved mutants in the different libraries, as determined by recursive screening under stress. In addition, we subjected our libraries to lactic and inorganic acids and found strains with improved growth in both conditions, with a concomitant increase in lactate productivity.

Assessing the potential of mutational strategies to elicit new phenotypes in industrial strains