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Tracking recent adaptive evolution in microbial species using TimeZone

Nature Protocols volume 8, pages 652–665 (2013)Cite this article

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Abstract

An important goal of the analysis of sequenced genomes of microbial pathogens is to improve the therapy of infectious diseases. In this context, a major challenge is to detect genomic-level evolutionary changes that increase microbial virulence. TimeZone, a genome analysis software package, is designed to detect footprints of positive selection for functionally adaptive point mutations. The uniqueness of TimeZone lies in its ability to predict recent adaptive mutations that are overlooked by conventional microevolutionary tools. This protocol describes the use of TimeZone to analyze adaptive footprints in either individual genes or in sets of genomes. Three major workflows are described: (i) extraction of orthologous gene sets from multiple genomes; (ii) alignment and phylogenetic analysis of genes; and (iii) identification of candidate genes under positive selection for point mutations, taking into account the effect of recombination events. This software package can be downloaded free from http://sourceforge.net/projects/timezone1/. In the case, for example, of the analysis of 14 Escherichia coli genomes, the protocol described here can be completed in ∼32 h.

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Figure 1: Representation of 'source-sink' dynamics.
Figure 3: Example of a zonal phylogeny tree.
Figure 4: Protein phylogram reporting different types of convergent or hotspot mutations along the phylogeny branches.
Figure 2
Figure 5
Figure 6: Screenshots of TimeZone run commands.
Figure 7
Figure 8: Distribution of the nature of hotspot mutations in recombinant and nonrecombinant genes, as inferred from the analysis of sequencing data on 14 genomes of E. coli strains27, respectively.

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Acknowledgements

We gratefully acknowledge S. Moseley (University of Washington) for critical reading of the manuscript and helpful advice. This work was supported by US National Institutes of Health (NIH) grants R01 GM084318 and RC4 AI092828.

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Authors and Affiliations

  1. Department of Microbiology, University of Washington, Seattle

    Sujay Chattopadhyay, Sandip Paul & Evgeni V Sokurenko

  2. Washington, USA

    Sujay Chattopadhyay, Sandip Paul & Evgeni V Sokurenko

  3. Department of Ecology and Evolution, Stony Brook University, Stony Brook, New York, USA

    Daniel E Dykhuizen

Authors
  1. Sujay Chattopadhyay
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Contributions

S.C. designed the protocol, wrote scripts, performed analyses and wrote the manuscript. S.P. tested and developed the protocol, and performed analyses. D.E.D. revised the manuscript. E.V.S. conceived the protocol and wrote the manuscript.

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Correspondence to Sujay Chattopadhyay.

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The authors declare no competing financial interests.

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Chattopadhyay, S., Paul, S., Dykhuizen, D. et al. Tracking recent adaptive evolution in microbial species using TimeZone. Nat Protoc 8, 652–665 (2013). https://doi.org/10.1038/nprot.2013.031

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