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

机译:评估突变策略在工业菌株中引发新表型的潜力

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摘要

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 σ 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.
机译:传统上已经通过涉及诱变和选择的合理方法和组合方法改良了工业菌株。最近,出现了其他方法,例如使用人工转录因子和对天然转录因子进行改造。随着产生遗传多样性的方法继续激增,对表型多样性进行量化以及评估各种遗传文库用于菌株改良的潜力的需求变得更加明显。在这里,我们提出了一种基于表型多样性量化的指标,使用植物乳杆菌作为模型生物。我们发现表型多样性可以通过诱变主σ因子来引入,可以通过调整序列多样性来调节这种多样性,并且该方法与化学诱变的常用协议相比具有优势。此处开发的多样性度量的结果也与在不同文库中发现改良突变体的可能性密切相关,这是通过在压力下进行递归筛选确定的。此外,我们对文库进行了乳酸和无机酸处理,发现在两种条件下生长均得到改善的菌株,同时乳酸生产率也得到了提高。

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