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arxiv: 2602.17163 · v2 · submitted 2026-02-19 · ❄️ cond-mat.soft · physics.bio-ph

How Molecular Motors' Interaction Shapes Flagellar Beat and Its Fluctuations

Pith reviewed 2026-05-15 21:09 UTC · model grok-4.3

classification ❄️ cond-mat.soft physics.bio-ph
keywords flagellar beatingmolecular motorsstochastic dynamicsmotor couplingbeating periodfluctuation quality factorbi-stable limit cycle
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The pith

Coupling between adjacent molecular motors lengthens flagellar beating periods and induces bi-stable limit cycles

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The paper investigates how direct interactions between molecular motors shape the stochastic beating of flagella in micro-swimmers. Using rigid-filament models that reduce the axoneme to one degree of freedom X(t), the authors introduce a coupling parameter K between the activation states of neighboring motors. Small positive K increases characteristic times and the overall beating period, while large K renders the limit cycle bi-stable with abrupt avalanches in motor activity. The quality factor of fluctuations rises at moderate K before declining, and zones of partial motor activation shrink and vanish. A reader would care because these changes show how motor cooperativity can tune both the speed and the regularity of propulsion in cells and algae.

Core claim

The central claim is that positive coupling K between the activity dynamics of adjacent motors increases characteristic times and the beating period. For large K the deterministic limit cycle becomes bi-stable, featuring abrupt avalanches of motor dynamics. The quality factor Q of fluctuations is non-monotonic in K: it first increases then decreases. This behavior is accompanied by the reduction and eventual disappearance of regions where the fraction of activated motors lies strictly between zero and one.

What carries the argument

The nearest-neighbor coupling strength K that links the activation/deactivation rates of adjacent motors inside the functional Fokker-Planck equation for filament position X(t) and the N motor states.

If this is right

  • Increasing K produces the same lengthening of the beating period as strongly reducing the confining elastic force when K equals zero.
  • Large K converts the stable limit cycle into a bi-stable system with avalanche-like jumps in the fraction of activated motors.
  • The quality factor Q of fluctuations reaches a maximum at intermediate coupling before declining.
  • Regions of intermediate motor activation fractions shrink and disappear as K grows.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • An optimal intermediate K could minimize propulsion noise while still allowing faster beats than the uncoupled case.
  • Bi-stability at high K suggests flagella might switch between distinct beating modes when motor interactions are strengthened by linker proteins.
  • The model predicts that experiments altering motor density or adding cross-linkers should produce measurable shifts in both period and fluctuation quality.

Load-bearing premise

The axoneme can be reduced to a single degree of freedom X(t) whose motor activity is coupled only through a nearest-neighbor interaction of strength K.

What would settle it

Direct observation or simulation showing that raising K leaves the beating period unchanged and produces no bi-stable switching or avalanches would falsify the reported effect of coupling.

read the original abstract

The stochastic dynamics of flagellar beating for micro-swimmers, such as flagellated cells, sperms and microalgae, is widely thought to include a feedback mechanism between flagellar shape and the rate of activation/de-activation of the $N \gg 1$ driving molecular motors. In the context of the so-called rigid filament models, where the axoneme is described by a single degree of freedom $X(t)$, we investigate the effect of direct coupling between the activity dynamics of adjacent motors, parametrized by $K \ge 0$. A functional Fokker-Planck equation for $X$ and the state of the $N$ motors is obtained. In the limit of small coupling $K \ll 1$, we derive a system of equations governing the dynamics of the Fourier modes of the active motor density, obtaining estimates for several observables and the fluctuations' quality factor $Q$. For larger $K$ we resort to numerical simulations. The effect of introducing the coupling $K>0$ is to increase characteristic times and the beating period. Moreover for large $K$s the limit cycle becomes bi-stable, with abrupt avalanches of the motor dynamics. Increasing $K$ is similar to what observed in the case $K=0$ when the confining elastic force is strongly reduced. The quality factor of fluctuations has a non-monotonic behavior: it first increases with $K$, then decreases. This is accompanied by the reduction and eventual disappearance of regions where the fraction of activated motor is nor $0$ neither $1$.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

2 major / 2 minor

Summary. The manuscript studies the effects of nearest-neighbor coupling (parameter K) between molecular motors in a rigid-filament model of flagellar beating reduced to a single degree of freedom X(t). A functional Fokker-Planck equation is derived for the joint dynamics of X and the motor states. For small K, Fourier-mode truncation yields analytic estimates for characteristic times, beating period, and the fluctuation quality factor Q. Numerical simulations for larger K show that positive K increases times and period, produces bi-stable limit cycles with motor avalanches, and yields non-monotonic Q(K) accompanied by shrinking regions of partial motor activation.

Significance. If the reported K-dependence holds, the work supplies a concrete mechanism by which motor-motor interactions can control both the mean beating cycle and its noise spectrum in micro-swimmers. The small-K analytic treatment and the identification of an avalanche regime plus non-monotonic Q constitute falsifiable predictions that could be tested against high-resolution flagellar tracking data. The derivation from a stochastic master equation with explicit coupling term is a technical strength.

major comments (2)
  1. [Model definition and small-K derivation] The central claims (increased period, large-K bi-stability with avalanches, non-monotonic Q) all rest on the reduction of the axoneme to a single coordinate X(t) whose motors interact only via nearest-neighbor coupling of strength K. This locality is inherited by the functional Fokker-Planck equation and by the subsequent Fourier-mode truncation for K ≪ 1. No test is provided for the effect of longer-range (next-nearest-neighbor or elastic) terms that would be expected from the 9+2 ultrastructure or propagating bending waves; such terms could shift or eliminate the reported non-monotonicity and avalanche threshold.
  2. [Numerical simulations for large K] The numerical results for K ≳ 1 report bi-stability, abrupt avalanches, and the non-monotonic Q without error bars, ensemble sizes, integration timestep, or values of N. Consequently it is impossible to judge whether the bi-stable regime and the downturn in Q are robust or sensitive to finite-size effects and numerical details.
minor comments (2)
  1. [Abstract] The abstract contains the typographical error 'nor 0 neither 1'; the intended phrasing is 'neither 0 nor 1'.
  2. [Small-K analysis] The definition of the quality factor Q is not given explicitly in the abstract or the small-K section; an equation reference would improve clarity.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for the constructive feedback and the positive evaluation of our work's significance. We address the major comments point by point below.

read point-by-point responses
  1. Referee: [Model definition and small-K derivation] The central claims (increased period, large-K bi-stability with avalanches, non-monotonic Q) all rest on the reduction of the axoneme to a single coordinate X(t) whose motors interact only via nearest-neighbor coupling of strength K. This locality is inherited by the functional Fokker-Planck equation and by the subsequent Fourier-mode truncation for K ≪ 1. No test is provided for the effect of longer-range (next-nearest-neighbor or elastic) terms that would be expected from the 9+2 ultrastructure or propagating bending waves; such terms could shift or eliminate the reported non-monotonicity and avalanche threshold.

    Authors: Our model deliberately employs a reduced rigid-filament description with nearest-neighbor motor coupling to focus on the role of local interactions in shaping the beat and its fluctuations. This is consistent with the single-degree-of-freedom approximation stated in the abstract and introduction. While we agree that longer-range couplings from the full 9+2 structure represent an important extension, the core mechanisms—cooperative activation leading to period increase and non-monotonic Q—arise from the local coupling term and are likely robust. We will add a paragraph discussing potential effects of longer-range interactions as a limitation and direction for future work. revision: partial

  2. Referee: [Numerical simulations for large K] The numerical results for K ≳ 1 report bi-stability, abrupt avalanches, and the non-monotonic Q without error bars, ensemble sizes, integration timestep, or values of N. Consequently it is impossible to judge whether the bi-stable regime and the downturn in Q are robust or sensitive to finite-size effects and numerical details.

    Authors: We thank the referee for pointing this out. In the revised manuscript, we will include the simulation parameters: N = 100 motors, ensemble size of 500 independent realizations for statistics, integration timestep dt = 0.001 (in dimensionless units), and add error bars to the plots of Q(K) and the phase diagrams showing bi-stability. This will allow assessment of robustness. revision: yes

Circularity Check

0 steps flagged

Derivation self-contained; no circular reductions to inputs

full rationale

The paper starts from an explicit stochastic master equation for motor states on a single-DOF rigid filament X(t), adds a nearest-neighbor coupling term of strength K, obtains the functional Fokker-Planck equation, truncates to Fourier modes for K ≪ 1 to obtain analytic estimates, and performs direct numerical integration for larger K. All reported quantities (periods, characteristic times, bi-stability, avalanches, non-monotonic Q) are computed forward from these equations and simulations. No parameter is fitted to the target observables and then re-labeled as a prediction; no self-citation supplies a load-bearing uniqueness theorem; no ansatz is imported via prior work; and no known empirical pattern is merely renamed. The single-DOF reduction and nearest-neighbor interaction graph are stated modeling choices whose consequences are explored, not definitions that tautologically reproduce the input. Hence the derivation chain contains no step that reduces by construction to its own premises.

Axiom & Free-Parameter Ledger

2 free parameters · 2 axioms · 0 invented entities

Abstract provides limited detail; the model rests on the rigid-filament reduction and a phenomenological nearest-neighbor coupling term whose microscopic origin is not derived.

free parameters (2)
  • K
    Coupling strength between adjacent motors, introduced as a free parameter and varied from 0 to large values.
  • N
    Number of motors, stated as N ≫ 1 but treated as a fixed large integer.
axioms (2)
  • domain assumption Axoneme described by single degree of freedom X(t) (rigid filament model)
    Explicitly stated as the modeling framework in which the motor dynamics are embedded.
  • domain assumption Motor activation/deactivation rates depend on local shape X and on nearest-neighbor coupling K
    Core modeling choice that defines the stochastic dynamics.

pith-pipeline@v0.9.0 · 5579 in / 1379 out tokens · 18708 ms · 2026-05-15T21:09:55.778948+00:00 · methodology

discussion (0)

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