Bacterial Motility Patterns Vary Smoothly with Spatial Confinement and Disorder

In unconfined environments, bacterial motility patterns directly reflect the internal states of the cell. Bacteria operating a run-and-tumble behavioral program swim forward when in a “run” state, and they are stalled in place when in a reorienting “tumble” state. However, in natural environments, motility dynamics are a convolution of bacterial behavior and physical constraints. Recent investigations showed that swimming through highly confined porous media exhibit extended periods of “trapping” punctuated by forward “hops,” suggesting a potential shift in motility strategy. We introduce a microfluidic device to systematically explore bacterial movement in a range of spatially structured environments, bridging the extremes of unconfined and highly confined conditions. We show that run-and-tumble and hop-and-trap are not distinct locomotive modes, but end points of a continuous spectrum of motility. We present the first unifying framework, “swim-and-stall”, to characterize this continuum of observed motility patterns. We demonstrate that a single control program underlies motility across all environments tested—that is, physical structure alone shapes changes in observed output. Our results establish a quantitative link between behavioral rules and environmental context, and show that can navigate dynamic, complex habitats without reprogramming their motility strategy. This robustness may explain the evolutionary persistence of run-and-tumble behavior in a diverse range of peritrichously flagellated bacteria and inform broader models of active transport in structured media.

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Publication Details

Journal
PRX Life
Published
2025-12-01
DOI
https://doi.org/10.1103/7hgr-pssv
Citations
1
Primary Topic
Micro and Nano Robotics
Type
article
Field-Weighted Citation Impact
1.26
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article

Bacterial Motility Patterns Vary Smoothly with Spatial Confinement and Disorder

Karl J. Friston
1 citations
PRX Life
Micro and Nano Robotics
1.26
article

Bacterial Motility Patterns Vary Smoothly with Spatial Confinement and Disorder

Karl J. Friston
article en
1 citations

Abstract

In unconfined environments, bacterial motility patterns directly reflect the internal states of the cell. Bacteria operating a run-and-tumble behavioral program swim forward when in a “run” state, and they are stalled in place when in a reorienting “tumble” state. However, in natural environments, motility dynamics are a convolution of bacterial behavior and physical constraints. Recent investigations showed that swimming through highly confined porous media exhibit extended periods of “trapping” punctuated by forward “hops,” suggesting a potential shift in motility strategy. We introduce a microfluidic device to systematically explore bacterial movement in a range of spatially structured environments, bridging the extremes of unconfined and highly confined conditions. We show that run-and-tumble and hop-and-trap are not distinct locomotive modes, but end points of a continuous spectrum of motility. We present the first unifying framework, “swim-and-stall”, to characterize this continuum of observed motility patterns. We demonstrate that a single control program underlies motility across all environments tested—that is, physical structure alone shapes changes in observed output. Our results establish a quantitative link between behavioral rules and environmental context, and show that can navigate dynamic, complex habitats without reprogramming their motility strategy. This robustness may explain the evolutionary persistence of run-and-tumble behavior in a diverse range of peritrichously flagellated bacteria and inform broader models of active transport in structured media.

PRX LifeVol. 4(1)
Georgia Institute of Technology (US), Princeton University (US), Cornell University (US), University of Chicago (US)
Openalex Percentile: Top 15%
Micro and Nano Robotics
1.26
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Bacterial Motility Patterns Vary Smoothly with Spatial Confinement and Disorder — Karl J. Friston · PRX Life (2025) | TGRS Research Map | TGRS