PLoS ONE (Jan 2015)

Investigation of Yersinia pestis Laboratory Adaptation through a Combined Genomics and Proteomics Approach.

  • Owen P Leiser,
  • Eric D Merkley,
  • Brian H Clowers,
  • Brooke L Deatherage Kaiser,
  • Andy Lin,
  • Janine R Hutchison,
  • Angela M Melville,
  • David M Wagner,
  • Paul S Keim,
  • Jeffrey T Foster,
  • Helen W Kreuzer

DOI
https://doi.org/10.1371/journal.pone.0142997
Journal volume & issue
Vol. 10, no. 11
p. e0142997

Abstract

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The bacterial pathogen Yersinia pestis, the cause of plague in humans and animals, normally has a sylvatic lifestyle, cycling between fleas and mammals. In contrast, laboratory-grown Y. pestis experiences a more constant environment and conditions that it would not normally encounter. The transition from the natural environment to the laboratory results in a vastly different set of selective pressures, and represents what could be considered domestication. Understanding the kinds of adaptations Y. pestis undergoes as it becomes domesticated will contribute to understanding the basic biology of this important pathogen. In this study, we performed a parallel serial passage experiment (PSPE) to explore the mechanisms by which Y. pestis adapts to laboratory conditions, hypothesizing that cells would undergo significant changes in virulence and nutrient acquisition systems. Two wild strains were serially passaged in 12 independent populations each for ~750 generations, after which each population was analyzed using whole-genome sequencing, LC-MS/MS proteomic analysis, and GC/MS metabolomics. We observed considerable parallel evolution in the endpoint populations, detecting multiple independent mutations in ail, pepA, and zwf, suggesting that specific selective pressures are shaping evolutionary responses. Complementary LC-MS/MS proteomic data provide physiological context to the observed mutations, and reveal regulatory changes not necessarily associated with specific mutations, including changes in amino acid metabolism and cell envelope biogenesis. Proteomic data support hypotheses generated by genomic data in addition to suggesting future mechanistic studies, indicating that future whole-genome sequencing studies be designed to leverage proteomics as a critical complement.