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Transcriptional Potential Determines the Adaptability of Escherichia coli Strains with Different Fitness Backgrounds

  • Kitae Kim
  • , Soon Kyeong Kwon
  • , Pil Kim
  • , Jihyun F. Kim
  • Yonsei University
  • Gyeongsang National University

Research output: Contribution to journal › Article › peer-review

3 Scopus citations

Abstract

Adaptation through the fitness landscape may be influenced by the gene pool or expression network. However, genetic factors that determine the contribution of beneficial mutations during adaptive evolution are poorly understood. In this study, we experimentally evolved wild-type Escherichia coli K-12 MG1655 and its isogenic derivative that has two additional replication origins and shows higher background fitness. During the short time of experimental evolution, the fitness gains of the two E. coli strains with different fitness backgrounds converged. Populational genome sequencing revealed various mutations with different allele frequencies in evolved populations. Several mutations occurred in genes affecting transcriptional regulation (e.g., RNA polymerase subunit, RNase, ppGpp synthetase, and transcription termination/antitermination factor genes). When we introduced mutations into the ancestral E. coli strains, beneficial effects tended to be lower in the ancestor with higher initial fitness. Replication rate analysis showed that the various replication indices do not correlate with the growth rate. Transcriptome profiling showed that gene expression and gene ontology are markedly enriched in populations with lower background fitness after experimental evolution. Further, the degree of transcriptional change was proportional to the fitness gain. Thus, the evolutionary trajectories of bacteria with different fitness backgrounds can be complex and counterintuitive. Notably, transcriptional change is a major contributor to adaptability.

Original languageEnglish
JournalMicrobiology spectrum
Volume10
Issue number6
DOIs
StatePublished - Nov 2022

Bibliographical note

Publisher Copyright:
Copyright © 2022 Kim et al.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • chromosomal landscape
  • evolutionary adaptability
  • origin of replication
  • systems biology
  • transcriptome optimization

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