Active matter
Why do swimming bacteria drift sideways in a flowing channel?
Open access · cc by · source: Europe PMC
The corkscrew shape of E. coli's flagella makes the bacteria drift across the flow at a speed that rises linearly with shear at first and then levels off well below their swimming speed.
Study at a glance
- Design
- Other — Microfluidic Poiseuille-flow experiments tracking fluorescent E. coli and passive tracers, compared with Brownian dynamics simulations and an analytical orientation model.
- N
- No single N; many bacterial tracks recorded at several flow rates and heights in one channel geometry, plus simulated ensembles (e.g. 1000 averaged trajectories for orientation maps).
- Population
- Wild-type run-and-tumble Escherichia coli (strain RP437) swimming in a PDMS microchannel
- Outcome
- Mean rheotactic (vorticity-direction) drift velocity and distributions of swimming velocity and orientation versus local shear rate
Structured fields used in claim comparison tables when every cited study has a complete layer.
Key findings
Bacteria drifted to one side in the lower half of the channel and the other side in the upper half, with drift growing with local shear rate and saturating at around half the free swimming speed. Plotting drift against local shear rate collapsed data from different heights and flow rates, and the simulations matched both the means and the full velocity and orientation distributions once the chiral strength was set to 0.06. A dimensionless chirality number (shear rate times chiral strength divided by effective rotational diffusion) collapsed simulations with different parameters at low shear, giving a drift length of about 0.75 μm per unit shear rate. The saturation arises because the sideways orientation is only a marginally stable fixed point, so bacteria circle around it instead of locking in.
Methodology
The authors pumped a dilute suspension of swimming E. coli through a microchannel 600 μm wide and 100 μm high and tracked thousands of bacteria and passive tracer beads at different heights and flow rates. They measured how fast the bacteria drifted perpendicular to the flow and how their swimming directions were distributed. They then built a model that adds a chirality-induced rotation to the classic Jeffery rotation of elongated bodies plus rotational noise and tumbling, simulated it, and analysed its fixed points.
Limitations
The chiral strength and aspect ratio were fitted to the same experimental data the model is compared against, so the agreement is partly by construction. Experiments only see 2D projections of 3D trajectories, and at the highest flow rates the camera could not resolve tracks, so the high-shear regime relies on simulations. Only one wild-type strain in one channel height was used, trajectories near the walls were excluded, and the scaling collapse for tumbling versus non-tumbling bacteria was not exact.
How this study connects
Role on claims
Each row is a claim on a concept or method page where this paper supports, challenges, or qualifies the statement. Roles are hand-checked — not a model guess.
Not yet placed on a claim. This paper has study layers, but no concept page yet cites it as support, challenge, or qualifier.
Related papers in this topic
Same topic cluster — not a recommendation engine.
- Can light alone drive and steer tiny swimming particles?
- Can simple buzzing robots be programmed to clump like a material?
- Can magnetic beads stack themselves upward against gravity?
- Why do swimming micro-disks clump into slow pairs?
- Can a particle-based fluid simulation capture active nematic turbulence?