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Richard Swiderski

Publications and source records attributed to Richard Swiderski.

4 recordsLinked to original sources

Stochastic Yield Catastrophe in Delay-Facilitated Self-Assembly

Self-assembly of supramolecular structures in cells and synthetic applications often proceeds under unfavorable biochemical conditions and at low copy numbers of final target structures, ranging from tens of bacterial microcompartments to a single bacterial flagellum per cell. Spatial organization through coupled reaction compartments of different reactivity (delay-facilitated assembly) can recover high yield in such environments at the mean-field level, but its robustness to stochastic fluctuations at low target numbers is unclear. Using stochastic simulations of a minimal two-compartment model, we show that delay-facilitated assembly is susceptible to a stochastic yield catastrophe at low target numbers: even when each compartment in isolation allows for high-yield assembly, slow exchange between them induces a substantial drop in the final yield. We trace the mechanism to a specific assembly stage, where the random order of rate-limiting exchange events of subunits and partially completed structures determines the ratio of productive growth to excess nucleation. Restricting the exchange of larger structures -- either by suppressing it entirely or letting exchange rates decrease with size -- restores most of the yield without altering the mean-field behavior. The same phenomenology appears for two-dimensional hexagonal subunits and in a cytosol-membrane geometry, where diffusion-limited exchange naturally implements the required size dependence. Our results show that equal success of assembly strategies at high target numbers does not imply their equal success at low target numbers, and that competing slow events occurring in random order are a common signature of stochastic yield catastrophes.

physics.bio-ph

Delay-facilitated self-assembly in compartmentalized systems

Self-assembly processes in biological and synthetic biomolecular systems are often governed by the spatial separation of biochemical processes. While previous work has focused on optimizing self-assembly through fine-tuned reaction parameters or using phase-separated liquid compartments with fast particle exchange, the role of slow inter-compartmental exchange remains poorly understood. Here, we demonstrate that slow particle exchange between reaction domains can enhance self-assembly efficiency through a cooperative mechanism: delay-facilitated assembly. Using a minimal model of irreversible self-assembly in two compartments with distinct reaction and exchange dynamics, we identify scenarios that maximize yield and minimize assembly time, even under conditions where isolated compartments would fail to facilitate any self-assembly. The mechanism relies on a separation of timescales between intra-compartmental reactions and inter-compartmental exchange and is robust across a wide range of geometries, including spatially extended domains with diffusive transport. We demonstrate that this effect enables geometric control of self-assembly processes through compartment volumes and exchange rates, eliminating the need for fine-tuning local reaction rates. These results offer a conceptual framework for leveraging spatial separation in synthetic self-assembly design and suggest that biological systems may use slow particle exchange to improve assembly efficiency. A video summary of this paper can be found at https://doi.org/10.5446/72056

physics.bio-ph

The role of mobility in epidemics near criticality

The general epidemic process (GEP), also known as susceptible-infected-recovered model (SIR), describes how an epidemic spreads within a population of susceptible individuals who acquire permanent immunization upon recovery. This model exhibits a second-order absorbing state phase transition, commonly studied assuming immobile healthy individuals. We investigate the impact of mobility on disease spreading near the extinction threshold by introducing two generalizations of GEP, where the mobility of susceptible and recovered individuals is examined independently. In both cases, including mobility violates GEP's rapidity reversal symmetry and alters the number of absorbing states. The critical dynamics of the models are analyzed through a perturbative renormalization group approach and large-scale stochastic simulations using a Gillespie algorithm. The renormalization group analysis predicts both models to belong to the same novel universality class describing the critical dynamics of epidemic spreading when the infected individuals interact with a diffusive species and gain immunization upon recovery. At the associated renormalization group fixed point, the immobile species decouples from the dynamics of the infected species, dominated by the coupling with the diffusive species. Numerical simulations in two dimensions affirm our renormalization group results by identifying the same set of critical exponents for both models. Violation of the rapidity reversal symmetry is confirmed by breaking the associated hyperscaling relation. Our study underscores the significance of mobility in shaping population spreading dynamics near the extinction threshold.

cond-mat.stat-mech

Anomalous Collective Dynamics of Auto-Chemotactic Populations

While the role of local interactions in nonequilibrium phase transitions is well studied, a fundamental understanding of the effects of long-range interactions is lacking. We study the critical dynamics of reproducing agents subject to autochemotactic interactions and limited resources. A renormalization group analysis reveals distinct scaling regimes for fast (attractive or repulsive) interactions; for slow signal transduction, the dynamics is dominated by a diffusive fixed point. Furthermore, we present a correction to the Keller-Segel nonlinearity emerging close to the extinction threshold and a novel nonlinear mechanism that stabilizes the continuous transition against the emergence of a characteristic length scale due to a chemotactic collapse.

cond-mat.stat-mech