Affiliations 

  • 1 School of Life Sciences, University of Nottingham, Nottingham, NG7 2RD, United Kingdom
  • 2 Institute of Biological Sciences, Faculty of Science, University of Malaya, 50603, Kuala Lumpur, Malaysia
  • 3 Department of Zoology, University of Oxford, South Parks Road, Oxford, OX1 3PS, United Kingdom
  • 4 Centre for Immunity, Infection and Evolution, Ashworth Laboratories, University of Edinburgh, King's Buildings, West Mains Road, Edinburgh, EH9 3JT, United Kingdom
  • 5 School of Life Sciences, University of Nottingham, Nottingham, NG7 2RD, United Kingdom. steve.diggle@nottingham.ac.uk
Evolution, 2015 Sep;69(9):2371-83.
PMID: 26282874 DOI: 10.1111/evo.12751

Abstract

Animals use signals to coordinate a wide range of behaviors, from feeding offspring to predator avoidance. This poses an evolutionary problem, because individuals could potentially signal dishonestly to coerce others into behaving in ways that benefit the signaler. Theory suggests that honest signaling is favored when individuals share a common interest and signals carry reliable information. Here, we exploit the opportunities offered by bacterial signaling to test these predictions with an experimental evolution approach. We show that: (1) reduced relatedness leads to the relative breakdown of signaling, (2) signaling breaks down by the invasion of mutants that show both reduced signaling and reduced response to signal, (3) the genetic route to signaling breakdown is variable, and (4) the addition of artificial signal, to interfere with signal information, also leads to reduced signaling. Our results provide clear support for signaling theory, but we did not find evidence for previously predicted coercion at intermediate relatedness, suggesting that mechanistic details can alter the qualitative nature of specific predictions. Furthermore, populations evolved under low relatedness caused less mortality to insect hosts, showing how signal evolution in bacterial pathogens can drive the evolution of virulence in the opposite direction to that often predicted by theory.

* Title and MeSH Headings from MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.