BPS2026 – Uncovering biophysical characteristics of nonequilibrium steady state(s) of microtubule dynamics

How do cells divide, organize internally, and move? These fundamental processes rely on microtubules (MTs), energy-utilizing cytoskeletal polymers of protein tubulin, that harness the chemical energy of GTP hydrolysis to remain dynamic—an essential prerequisite for their diverse cellular roles. Dynamic instability (DI), the property of MTs to switch between growth and shortening phases stochastically, invalidates the notion of one “critical concentration” (CC) of classical equilibrium polymer theory, splitting it into at least two—CC elongation and CC net-assembly . When free tubulin concentration lies between these values, regular DI occurs at the filament-level, while at the system-level by continuous energy dissipation directs MT populations toward nonequilibrium steady states (NESS). This raises critical questions: How many NESSs can MT systems sustain? Can they be characterized quantitatively? What governs the polymer-system-level transient and steady-state dynamics? To address these, we developed a computational framework combining agent-based simulations with reduced-order models grounded in stochastic thermodynamics. We employed two Monte Carlo simulations with experimentally tuned user-defined inputs (tubulin concentration, cell volume, nucleation sites, and kinetic rates)—a mesoscopic model treating MTs as simplified linear polymers and a molecularly detailed model resolving individual subunits—allowing hours-long simulations that capture behaviors consistently across subunit, filament, and population scales. Remarkably, simulations reveal universalities—Monod-like saturation kinetics for ensemble dynamics and exponential saturation for GTP-cap dynamics. We uncover that dynamic MT populations progress through at least three distinct NESS: GTP-cap-steady-state, polymer-mass-steady-state, and polymer-length-distribution-steady-state. The affine-invariant behaviors of steady-state attributes such as polymer-mass, GTP-content across concentrations enables predictions of time-to-NESS and NESS-values as functions of tubulin concentrations. By mathematically profiling the NESS(s) we not only establish a multiscale predictive understanding of entropy-driven MT dynamics but also provide rules for experimental tuning of cytoskeletal behavior, engineering next-generation biopolymers, and fundamentally understanding nonequilibrium dynamics in biology.