title: Evolution of response dynamics underlying bacterial chemotaxis.
abstract: BACKGROUND
  The ability to predict the function and structure of complex molecular mechanisms underlying cellular behaviour is one of the main aims of systems biology. To achieve it, we need to understand the evolutionary routes leading to a specific response dynamics that can underlie a given function and how biophysical and environmental factors affect which route is taken. Here, we apply such an evolutionary approach to the bacterial chemotaxis pathway, which is documented to display considerable complexity and diversity.
  
  
  RESULTS
  We construct evolutionarily accessible response dynamics starting from a linear response to absolute levels of attractant, to those observed in current-day Escherichia coli. We explicitly consider bacterial movement as a two-state process composed of non-instantaneous tumbling and swimming modes. We find that a linear response to attractant results in significant chemotaxis when sensitivity to attractant is low and when time spent tumbling is large. More importantly, such linear response is optimal in a regime where signalling has low sensitivity. As sensitivity increases, an adaptive response as seen in Escherichia coli becomes optimal and leads to 'perfect' chemotaxis with a low tumbling time. We find that as tumbling time decreases and sensitivity increases, there exist a parameter regime where the chemotaxis performance of the linear and adaptive responses overlap, suggesting that evolution of chemotaxis responses might provide an example for the principle of functional change in structural continuity.
  
  
  CONCLUSIONS
  Our findings explain several results from diverse bacteria and lead to testable predictions regarding chemotaxis responses evolved in bacteria living under different biophysical constraints and with specific motility machinery. Further, they shed light on the potential evolutionary paths for the evolution of complex behaviours from simpler ones in incremental fashion.
authors.affiliation: Systems Biology Program, College of Engineering, Computing, Mathematics and Physical Sciences, University of Exeter, Exeter, UK. O.S.Soyer@exeter.ac.uk
authors.forename: Orkun S
authors.initials: OS
authors.lastname: Soyer
authors.forename: Richard A
authors.initials: RA
authors.lastname: Goldstein
mesh_terms: D018407:Bacterial Physiological Phenomena; D005075:Biological Evolution; D002633:Chemotaxis / Q000502:physiology*; D003198:Computer Simulation; D004926:Escherichia coli; D008954:Models, Biological; D049490:Systems Biology / Q000379:methods*