Bacteria push the limits of chemotactic precision to navigate dynamic chemical gradients
Edited by Howard C. Berg, Harvard University, Cambridge, MA, and approved April 15, 2019 (received for review September 26, 2018)
Significance
The limited precision of sensory organs places fundamental constraints on organismal performance. An open question, however, is whether organisms are routinely pushed to these limits and how limits might influence interactions between populations of organisms and their environment. By combining a method to generate dynamic, replicable resource landscapes, high-speed tracking of freely moving bacteria, a mathematical theory, and agent-based simulations, we show that sensory noise ultimately limits when and where bacteria can detect and climb chemical gradients. Our results suggest that the typical chemical landscapes bacteria inhabit are dominated by noise that masks shallow gradients and that the spatiotemporal dynamics of bacterial aggregations can be predicted by mapping the region where gradient signal rises above noise.
Abstract
Ephemeral aggregations of bacteria are ubiquitous in the environment, where they serve as hotbeds of metabolic activity, nutrient cycling, and horizontal gene transfer. In many cases, these regions of high bacterial concentration are thought to form when motile cells use chemotaxis to navigate to chemical hotspots. However, what governs the dynamics of bacterial aggregations is unclear. Here, we use an experimental platform to create realistic submillimeter-scale nutrient pulses with controlled nutrient concentrations. By combining experiments, mathematical theory, and agent-based simulations, we show that individual Vibrio ordalii bacteria begin chemotaxis toward hotspots of dissolved organic matter (DOM) when the magnitude of the chemical gradient rises sufficiently far above the sensory noise that is generated by stochastic encounters with chemoattractant molecules. Each DOM hotspot is surrounded by a dynamic ring of chemotaxing cells, which congregate in regions of high DOM concentration before dispersing as DOM diffuses and gradients become too noisy for cells to respond to. We demonstrate that V. ordalii operates close to the theoretical limits on chemotactic precision. Numerical simulations of chemotactic bacteria, in which molecule counting noise is explicitly taken into account, point at a tradeoff between nutrient acquisition and the cost of chemotactic precision. More generally, our results illustrate how limits on sensory precision can be used to understand the location, spatial extent, and lifespan of bacterial behavioral responses in ecologically relevant environments.
Acknowledgments
We thank V. Sourjik, N. Wingreen, T. Emonet, F. Menolascina, K. Son, V. Fernandez, and J. Keegstra for useful discussions. This work was supported by an Australian Research Council Discovery Early Career Researcher Award DE180100911 (to D.R.B.); The University of Melbourne Computational Biology Research Initiative and high-performance computing system (D.R.B.); a Swiss National Science Foundation Early Mobility Postdoctoral Fellowship (F.C.); a James S. McDonnell Foundation Fellowship (A.M.H.); Army Research Office Grants W911NG-11-1-0385 and W911NF-14-1-0431 (to S.A.L.); Simons Foundation Grant 395890 (to S.A.L.); Gordon and Betty Moore Marine Microbial Initiative Investigator Award GBMF3783 (to R.S.); and Simons Foundation Grant 542395 (to R.S.) as part of the Principles of Microbial Ecosystems Collaborative (PriME).
Supporting Information
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Movie S1.
Numerical simulation of bacteria with the chemotactic precision factor Π = 1 (corresponding to trajectories in main text Fig. 4A).
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Movie S2.
Numerical simulation of bacteria with the chemotactic precision factor Π = 6.6 (corresponding to trajectories in main text Fig. 4B).
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Movie S3.
Numerical simulation of bacteria with the chemotactic precision factor Π = 100 (corresponding to trajectories in main text Fig. 4C).
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© 2019. Published under the PNAS license.
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Published online: May 16, 2019
Published in issue: May 28, 2019
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Acknowledgments
We thank V. Sourjik, N. Wingreen, T. Emonet, F. Menolascina, K. Son, V. Fernandez, and J. Keegstra for useful discussions. This work was supported by an Australian Research Council Discovery Early Career Researcher Award DE180100911 (to D.R.B.); The University of Melbourne Computational Biology Research Initiative and high-performance computing system (D.R.B.); a Swiss National Science Foundation Early Mobility Postdoctoral Fellowship (F.C.); a James S. McDonnell Foundation Fellowship (A.M.H.); Army Research Office Grants W911NG-11-1-0385 and W911NF-14-1-0431 (to S.A.L.); Simons Foundation Grant 395890 (to S.A.L.); Gordon and Betty Moore Marine Microbial Initiative Investigator Award GBMF3783 (to R.S.); and Simons Foundation Grant 542395 (to R.S.) as part of the Principles of Microbial Ecosystems Collaborative (PriME).
Notes
This article is a PNAS Direct Submission.
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The authors declare no conflict of interest.
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