Evolutionary remodeling of global regulatory networks during long-term bacterial adaptation to human hosts
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Damkiær-2013-Evolutionary remodel.pdf
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Author(s)
Yang, Lei
Damkiaer, Soren
Molin, Soren
Jelsbak, Lars
Date Issued
April 2013
Journal
Proceedings of the National Academy of Sciences
Publisher
National Academy of Sciences (U.S.)
Citation
Damkiaer, S., L. Yang, S. Molin, and L. Jelsbak. “Evolutionary remodeling of global regulatory networks during long-term bacterial adaptation to human hosts.” Proceedings of the National Academy of Sciences 110, no. 19 (May 7, 2013): 7766-7771.
Version
Final published version
Abstract
The genetic basis of bacterial adaptation to a natural environment has been investigated in a highly successful Pseudomonas aeruginosa lineage (DK2) that evolved within the airways of patients with cystic fibrosis (CF) for more than 35 y. During evolution in the CF airways, the DK2 lineage underwent substantial phenotypic changes, which correlated with temporal fixation of specific mutations in the genes mucA (frame-shift), algT (substitution), rpoN (substitution), lasR (deletion), and rpoD (in-frame deletion), all encoding regulators of large gene networks. To clarify the consequences of these genetic changes, we moved the specific mutations, alone and in combination, to the genome of the reference strain PAO1. The phenotypes of the engineered PAO1 derivatives showed striking similarities with phenotypes observed among the DK2 isolates. The phenotypes observed in the DK2 isolates and PAO1 mutants were the results of individual, additive and epistatic effects of the regulatory mutations. The mutations fixed in the σ factor encoding genes algT, rpoN, and rpoD caused minor changes in σ factor activity, resulting in remodeling of the regulatory networks to facilitate generation of unexpected phenotypes. Our results suggest that adaptation to a highly selective environment, such as the CF airways, is a highly dynamic and complex process, which involves continuous optimization of existing regulatory networks to match the fluctuations in the environment.
MIT Department
Massachusetts Institute of Technology. Department of Biological Engineering
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DOI of Published Version
https://doi.org/10.1073/pnas.1221466110
