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连续适应性实验室进化增强了大肠杆菌的混合碳代谢能力。

Serial adaptive laboratory evolution enhances mixed carbon metabolic capacity of Escherichia coli.

机构信息

Department of Biological Sciences, Korea Advanced Institute of Science and Technology, Daejeon, 34141, Republic of Korea; KAIST Institute for the BioCentury, Korea Advanced Institute of Science and Technology, Daejeon, 34141, Republic of Korea.

Department of Bioengineering, University of California San Diego, La Jolla, CA, 92093, USA.

出版信息

Metab Eng. 2024 May;83:160-171. doi: 10.1016/j.ymben.2024.04.004. Epub 2024 Apr 16.

Abstract

Microbes have inherent capacities for utilizing various carbon sources, however they often exhibit sub-par fitness due to low metabolic efficiency. To test whether a bacterial strain can optimally utilize multiple carbon sources, Escherichia coli was serially evolved in L-lactate and glycerol. This yielded two end-point strains that evolved first in L-lactate then in glycerol, and vice versa. The end-point strains displayed a universal growth advantage on single and a mixture of adaptive carbon sources, enabled by a concerted action of carbon source-specialists and generalist mutants. The combination of just four variants of glpK, ppsA, ydcI, and rph-pyrE, accounted for more than 80% of end-point strain fitness. In addition, machine learning analysis revealed a coordinated activity of transcriptional regulators imparting condition-specific regulation of gene expression. The effectiveness of the serial adaptive laboratory evolution (ALE) scheme in bioproduction applications was assessed under single and mixed-carbon culture conditions, in which serial ALE strain exhibited superior productivity of acetoin compared to ancestral strains. Together, systems-level analysis elucidated the molecular basis of serial evolution, which hold potential utility in bioproduction applications.

摘要

微生物具有利用各种碳源的固有能力,但由于代谢效率低,它们的适应性通常较差。为了测试一个细菌菌株是否能够最佳地利用多种碳源,我们对大肠杆菌进行了 L-乳酸和甘油的连续进化。这产生了两种终点菌株,它们首先在 L-乳酸中进化,然后在甘油中进化,反之亦然。终点菌株在单一和混合适应性碳源上表现出普遍的生长优势,这得益于碳源专家和通才突变体的协同作用。仅仅 glpK、ppsA、ydcI 和 rph-pyrE 的四个变体的组合,就占了终点菌株适应性的 80%以上。此外,机器学习分析揭示了转录调节因子的协调活动,赋予了基因表达的条件特异性调节。在单一和混合碳培养条件下,评估了连续适应性实验室进化 (ALE) 方案在生物生产应用中的有效性,其中连续 ALE 菌株在乙酰丁酮的生产能力方面优于原始菌株。总的来说,系统水平的分析阐明了连续进化的分子基础,这在生物生产应用中具有潜在的用途。

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