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Active matter

Why do moving protein filaments switch from swirls to aligned order?

Dunajova Z, Mateu BP, Radler P, et al. · Nature physics · 2023

Open access · cc by · source: Europe PMC

As treadmilling FtsZ filaments get more crowded they straighten out, so their collective pattern changes from rotating chiral rings to a nematic, liquid-crystal-like order, and a flexible-filament model reproduces this.

Study at a glance

Design
Computational / modelling — In vitro reconstituted FtsZ filaments on supported lipid bilayers imaged by TIRF, STED and high-speed AFM, compared quantitatively with coarse-grained simulations of self-propelled semiflexible chiral filaments.
N
No single sample size; experiments span a range of FtsZ concentrations and simulations span density, flexibility and attraction; the defect count comes from four HS-AFM measurements.
Population
Membrane-bound treadmilling FtsZ filaments (wild type and the L169R mutant) and simulated active filaments
Outcome
Large-scale pattern (disordered, chiral rings, nematic), filament curvature, ring probability and lifetime, topological defect density

Structured fields used in claim comparison tables when every cited study has a complete layer.

Key findings

At low density single filaments moved on curved paths about 1.16 µm across, at intermediate density they formed chiral rotating rings lasting about 5-6 minutes, and at high density the rings disappeared. Simulations matched these two transitions only for moderately flexible filaments (flexure number about 40), not very rigid or very floppy ones. High-speed AFM confirmed that filaments straighten as density rises (curvature fell twofold) and showed half-integer nematic defects; the stiffer mutant formed no rings or directional flows.

Methodology

The authors attached FtsZ, a bacterial filament-forming protein that moves by treadmilling, to a lipid membrane and raised its concentration from about 0.6 to 5.0 µM while filming the patterns with fluorescence microscopy and high-speed atomic force microscopy. They built a simulation of self-propelled, naturally curved, semiflexible filaments and varied density, stiffness and attraction to find which settings matched the experiments. They then tested a prediction with a mutant (L169R) whose filaments were expected to be straighter and stiffer.

Limitations

The model is deliberately minimal and ignores details such as finite filament lifetimes or stress-dependent growth, so agreement does not prove it is the only mechanism. Filament curvature could not be measured directly with fluorescence microscopy, and the defect density comes from only four AFM measurements. Results are from a flat reconstituted membrane, so links to the Z-ring inside dividing bacteria remain suggestive rather than tested.

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.

  • SupportsActive matterconcept

    How bendy active filaments are decides which collective phase appears.

    Treadmilling FtsZ filaments on lipid membranes changed with density from curved single paths to chiral rotating rings and then to a ring-free dense state, and simulations of self-propelled chiral filaments reproduced both transitions only for moderately flexible filaments; a stiffer mutant formed no rings.

    Evidence for the claim as stated.

  • ChallengesActive matterconcept

    The robot-swarm study used an equilibrium lattice model to predict aggregation, but its measured perimeter scaling (0.66) exceeded the predicted 0.5, which the authors partly attribute to the robots' irreversible, non-equilibrium motion; the Janus and FtsZ studies instead build explicitly non-equilibrium models from the start.

    Same question, contrary or null result.

Open questions

Tensions this paper is part of

From concept pages' “where studies disagree.” Disagreement means the same question; scope means different assays, populations, or outcomes.

Related papers in this topic

Same topic cluster — not a recommendation engine.