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Procedure for Adaptive Laboratory Evolution of Microorganisms Using a Chemostat
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Published on: September 20, 2016

Tracking recent adaptive evolution in microbial species using TimeZone.

Sujay Chattopadhyay1, Sandip Paul, Daniel E Dykhuizen

  • 1Department of Microbiology, University of Washington, Seattle, Washington, USA. sujayc@u.washington.edu

Nature Protocols
|March 9, 2013
PubMed
Summary
This summary is machine-generated.

This study introduces TimeZone, a software for detecting adaptive mutations in microbial pathogens to enhance infectious disease therapy. It identifies recent evolutionary changes missed by other tools, aiding virulence factor research.

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Last Updated: May 13, 2026

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06:03

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Published on: September 20, 2016

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08:03

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Published on: December 7, 2021

Area of Science:

  • Genomics
  • Microbial Evolution
  • Bioinformatics

Background:

  • Improving infectious disease therapy requires understanding microbial virulence.
  • Detecting genomic evolutionary changes that increase virulence is a major challenge.

Purpose of the Study:

  • Introduce TimeZone, a genome analysis software.
  • Detect footprints of positive selection for functionally adaptive point mutations.
  • Identify recent adaptive mutations overlooked by conventional tools.

Main Methods:

  • Analyze adaptive footprints in genes or genome sets using TimeZone.
  • Workflow includes orthologous gene set extraction, alignment, and phylogenetic analysis.
  • Identify genes under positive selection, considering recombination effects.

Main Results:

  • TimeZone predicts recent adaptive mutations.
  • The protocol is applicable to individual genes or multiple genomes.
  • Analysis of 14 Escherichia coli genomes completed in ~32 hours.

Conclusions:

  • TimeZone offers a novel approach to detect adaptive evolution in microbial pathogens.
  • The software aids in identifying virulence-associated genetic changes.
  • Facilitates improved therapeutic strategies against infectious diseases.