...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Nature Communications >High-throughput laboratory evolution reveals evolutionary constraints in Escherichia coli
【24h】

High-throughput laboratory evolution reveals evolutionary constraints in Escherichia coli

机译：高吞吐量实验室演变在大肠杆菌中揭示了进化的限制

获取原文
   

获取外文期刊封面封底 >>

       
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Understanding the constraints that shape the evolution of antibiotic resistance is critical for predicting and controlling drug resistance. Despite its importance, however, a systematic investigation of evolutionary constraints is lacking. Here, we perform a high-throughput laboratory evolution of Escherichia coli under the addition of 95 antibacterial chemicals and quantified the transcriptome, resistance, and genomic profiles for the evolved strains. Utilizing machine learning techniques, we analyze the phenotype–genotype data and identified low dimensional phenotypic states among the evolved strains. Further analysis reveals the underlying biological processes responsible for these distinct states, leading to the identification of trade-off relationships associated with drug resistance. We also report a decelerated evolution of β-lactam resistance, a phenomenon experienced by certain strains under various stresses resulting in higher acquired resistance to β-lactams compared to strains directly selected by β-lactams. These findings bridge the genotypic, gene expression, and drug resistance gap, while contributing to a better understanding of evolutionary constraints for antibiotic resistance. Understanding evolutionary constraints in antibiotic resistance is crucial for prediction and control. Here, the authors use high-throughput laboratory evolution of Escherichia coli alongside machine learning to identify trade-off relationships associated with drug resistance.
机译：了解塑造抗生素抗性演化的约束对于预测和控制耐药性至关重要。然而，尽管重要的是，缺乏对进化约束的系统调查。在这里，我们在添加95种抗菌化学物质下进行大肠杆菌的高通量实验室演化，并定量转录组，抗性和基因组谱的进化菌株。利用机器学习技术，我们分析了表型基因型数据，并在演化菌株中鉴定了低尺寸表型状态。进一步的分析揭示了负责这些独特状态的潜在的生物过程，导致鉴定与耐药相关的权衡关系。我们还报告了β-内酰胺抗性的减速的演化，其各种应力下的某些菌株经历的现象，导致与β-内酰胺直接选定的菌株相比，导致β-内酰胺的耐受性更高的抗性。这些发现桥接基因型，基因表达和耐药性差距，同时有助于更好地理解抗生素抗性的进化约束。理解抗生素抗性的进化约束对于预测和控制至关重要。在这里，作者使用大肠杆菌的高通量实验室演变，并沿着机器学习识别与耐药相关的权衡关系。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号