Recent studies have shown that Escherichia coli in highly confined porous media exhibit extended periods of 'trapping' punctuated by forward 'hops', a significant restructuring of the classical run-and-tumble model of motility. However, bacterial species must navigate a diverse range of complex habitats, such as biological tissues, soil, and sediments. These natural environments display varying levels of both (1) packing density (i.e., confinement) and (2) packing structure (i.e., disorder). Here, we introduce a microfluidic device that enables precise tuning of these environmental parameters, allowing for a more systematic exploration of bacterial motility bridging the extremes of unconfined and highly confined conditions. We observe that motility patterns characteristic of both hop-and-trap and run-and-tumble models coexist in nearly all environments tested, with ensemble dynamics transitioning between these behaviors as both confinement and disorder increase. We demonstrate that dynamics expected from the hop-and-trap model emerge naturally from a modified run-and-tumble model under specific environmental constraints. Our results suggest that bacterial motility patterns lie along a continuum, rather than being confined to a small set of discrete locomotive modes.
Bacterial motility, E. coli, complex environments, microbial active matter, microfluidics
Haibei Zhang*1, Miles T. Wetherington*2,3, Hungtang Ko4, Cody E. FitzGerald5, Edwin M. Munro6, Jasmine A. Nirody7
- Graduate Program in Biophysical Sciences, University of Chicago, 929 East 57th St, Chicago, IL 60637
- School of Physics, Georgia Institute of Technology, 837 State St NW, Atlanta, GA 30332
- School of Applied and Engineering Physics, Cornell University, Clark Hall, 271, 142 Sciences Dr, Ithaca, NY 14853
- Department of Mechanical and Aerospace Engineering, Princeton University, 41 Olden St, 401 Princeton, NJ 08544
- Department of Engineering Sciences and Applied Mathematics, Northwestern University, 404 2145 Sheridan Rd, Evanston, IL 60208
- Department of Molecular Genetics and Cell Biology, University of Chicago, 920 E. 58th St, Chicago, Il 60637
- Department of Organismal Biology and Anatomy, University of Chicago, 1027 E 57th St, 407 Chicago, IL 60637
*These authors contributed equally to this work.
H.Z. and J.A.N. acknowledge funding support by NSF-Simons National Institute for Theory and Mathematics in Biology, which is jointly supported by the U.S. National Science Foundation (Award 2235451) and the Simons Foundation (Award MP-TMPS-00005320). H.Z. is also grateful for her graduate program in Biophysical Sciences at the University of Chicago. M.T.W., H.K., C.E.F., and J.A.N. acknowledge support from The Santa Fe Institute and The James S. McDonnell Foundation Postdoctoral Fellowship Award in Complex Systems (M.T.W: https://doi.org/10.37717/2020-1543; H.K.: https://doi.org/10.37717/2021-3524; C.E.F.: https://doi.org/10.37717/2020-1591; J.A.N.: https://doi.org/10.37717/220020527). C.E.F. is supported by the NSF-Simons Center for Quantitative Biology at Northwestern University (NSF: 1764421 and Simons Foundation/SFARI 597491-RWC). J.A.N. and E.M.M. acknowledge support from the National Science Foundation through the Center for Living Systems (Grant No. 2317138). This work was performed in part at the Cornell NanoScale Facility, a member of the National Nanotechnology Coordinated Infrastructure (NNCI), which is supported by the National Science Foundation (Grant NNCI-2025233). We thank Tom Pennell for his guidance and advice throughout the fabrication process at the Cornell NanoScale Facility. We also thank Benjamin R. Epley, Erin Brandt, and Peter Yunker for their insights and many thoughtful discussions.
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