实验室连续适应性进化提高了大肠杆菌的混合碳代谢能力

IF 6.8 1区 生物学 Q1 BIOTECHNOLOGY & APPLIED MICROBIOLOGY
Kangsan Kim , Donghui Choe , Minjeong Kang , Sang-Hyeok Cho , Suhyung Cho , Ki Jun Jeong , Bernhard Palsson , Byung-Kwan Cho
{"title":"实验室连续适应性进化提高了大肠杆菌的混合碳代谢能力","authors":"Kangsan Kim ,&nbsp;Donghui Choe ,&nbsp;Minjeong Kang ,&nbsp;Sang-Hyeok Cho ,&nbsp;Suhyung Cho ,&nbsp;Ki Jun Jeong ,&nbsp;Bernhard Palsson ,&nbsp;Byung-Kwan Cho","doi":"10.1016/j.ymben.2024.04.004","DOIUrl":null,"url":null,"abstract":"<div><p>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, <em>Escherichia coli</em> 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 <em>glpK</em>, <em>ppsA</em>, <em>ydcI</em>, and <em>rph-pyrE</em>, 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.</p></div>","PeriodicalId":18483,"journal":{"name":"Metabolic engineering","volume":null,"pages":null},"PeriodicalIF":6.8000,"publicationDate":"2024-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Serial adaptive laboratory evolution enhances mixed carbon metabolic capacity of Escherichia coli\",\"authors\":\"Kangsan Kim ,&nbsp;Donghui Choe ,&nbsp;Minjeong Kang ,&nbsp;Sang-Hyeok Cho ,&nbsp;Suhyung Cho ,&nbsp;Ki Jun Jeong ,&nbsp;Bernhard Palsson ,&nbsp;Byung-Kwan Cho\",\"doi\":\"10.1016/j.ymben.2024.04.004\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>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, <em>Escherichia coli</em> 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 <em>glpK</em>, <em>ppsA</em>, <em>ydcI</em>, and <em>rph-pyrE</em>, 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.</p></div>\",\"PeriodicalId\":18483,\"journal\":{\"name\":\"Metabolic engineering\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":6.8000,\"publicationDate\":\"2024-04-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Metabolic engineering\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1096717624000582\",\"RegionNum\":1,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"BIOTECHNOLOGY & APPLIED MICROBIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Metabolic engineering","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1096717624000582","RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BIOTECHNOLOGY & APPLIED MICROBIOLOGY","Score":null,"Total":0}
引用次数: 0

摘要

微生物具有利用各种碳源的固有能力,但由于新陈代谢效率较低,它们往往表现出较低的适应性。为了测试细菌菌株是否能最佳利用多种碳源,大肠杆菌在 L-乳酸盐和甘油中连续进化。这样就产生了两个终点菌株,它们先在 L-乳酸盐中进化,然后在甘油中进化,反之亦然。在碳源专家和普通突变体的协同作用下,终端菌株在单一碳源和混合适应性碳源上显示出普遍的生长优势。glpK、ppsA、ydcI和rph-pyrE这四种变体的组合占终点菌株适合度的80%以上。此外,机器学习分析还揭示了转录调控因子的协调活动,从而对基因表达进行了条件特异性调控。在单碳和混碳培养条件下,评估了系列适应性实验室进化(ALE)方案在生物生产应用中的有效性。系统层面的分析阐明了序列进化的分子基础,这在生物生产应用中具有潜在的实用性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Serial adaptive laboratory evolution enhances mixed carbon metabolic capacity of Escherichia coli

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.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Metabolic engineering
Metabolic engineering 工程技术-生物工程与应用微生物
CiteScore
15.60
自引率
6.00%
发文量
140
审稿时长
44 days
期刊介绍: Metabolic Engineering (MBE) is a journal that focuses on publishing original research papers on the directed modulation of metabolic pathways for metabolite overproduction or the enhancement of cellular properties. It welcomes papers that describe the engineering of native pathways and the synthesis of heterologous pathways to convert microorganisms into microbial cell factories. The journal covers experimental, computational, and modeling approaches for understanding metabolic pathways and manipulating them through genetic, media, or environmental means. Effective exploration of metabolic pathways necessitates the use of molecular biology and biochemistry methods, as well as engineering techniques for modeling and data analysis. MBE serves as a platform for interdisciplinary research in fields such as biochemistry, molecular biology, applied microbiology, cellular physiology, cellular nutrition in health and disease, and biochemical engineering. The journal publishes various types of papers, including original research papers and review papers. It is indexed and abstracted in databases such as Scopus, Embase, EMBiology, Current Contents - Life Sciences and Clinical Medicine, Science Citation Index, PubMed/Medline, CAS and Biotechnology Citation Index.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信