SearcharxivSearch

arXiv subjects

Aishani Ghosal

Publications and source records attributed to Aishani Ghosal.

6 recordsLinked to original sources

Principles of Client Enrichment in Multicomponent Biomolecular Condensates

Biomolecular condensates are commonly organized by a small number of scaffold molecules that drive phase separation together with client molecules that do not condense on their own but become selectively recruited into the dense phase. A central open question is how client recruitment feeds back on scaffold interactions to determine condensate composition. Here we address this problem in a reconstituted focal adhesion system composed of focal adhesion kinase (FAK) and phosphorylated p130Cas (Cas) as scaffolds and the adaptor protein paxillin (PXN) as a client. We show that both FAK phosphorylation and PXN recruitment produce a common compositional response in which FAK becomes enriched while Cas is depleted within the condensate. To interpret these observations, we develop two complementary theoretical descriptions. First, within a two-component Flory-Huggins framework, we show that phosphorylation can be captured by either strengthening heterotypic FAK-Cas interactions or increasing the effective number of interaction-relevant segments on FAK, both of which bias partitioning toward FAK-rich condensates. Second, we introduce a minimal three-component Flory-Huggins theory without an explicit solvent and map it onto an effective two-component description, demonstrating that client recruitment renormalizes homotypic and heterotypic scaffold interactions. Analytical predictions for the location of the critical point are tested in reconstituted multicomponent systems through PXN addition, showing that client recruitment alone tunes proximity to criticality and reshapes condensate composition. Together, our results reveal distinct yet convergent physical routes by which post-translational modification and client recruitment control scaffold composition in multicomponent condensates.

q-bio.BM

Dissipation rates from experimental uncertainty

Active matter and driven systems exhibit statistical fluctuations in density and particle positions, providing an indirect indicator of dissipation across multiple length and time scales. Here, we quantitatively relate these measurable fluctuations to a thermodynamic speed limit that constrains the rates of heat and entropy production in nonequilibrium processes. By reparametrizing the speed limit, we show how to infer heat and entropy production rates from directly observable or controllable quantities. This approach can use available experimental data and avoid the need for analytically solvable microscopic models or full time-dependent probability distributions. The heat rate we predict agrees with experimental measurements for a Brownian particle and a microtubule active gel, which validates the approach and suggests potential for the design of experiments.

cond-mat.stat-mech

Utilizing time-series measurements for entropy production estimation in partially observed systems

Estimating the dissipation, or the entropy production rate (EPR), can provide insights into the underlying mechanisms of nonequilibrium driven processes. Experimentally, however, only partial information can be accessed, and the ability to estimate the EPR varies depending on the available data. Here, we test different degrees of observed information stemming from coarse-grained time-series trajectory data, and apply several EPR estimators. Given increasing amount of information, we show a hierarchy of lower bounds on the total EPR. Further, we present a novel approach for utilizing waiting times in hidden states to provide a tighter lower bound on the total EPR.

cond-mat.stat-mech

Universal bounds on entropy production inferred from observed statistics

Nonequilibrium processes break time-reversal symmetry and generate entropy. Living systems are driven out-of-equilibrium at the microscopic level of molecular motors that exploit chemical potential gradients to transduce free energy to mechanical work, while dissipating energy. The amount of energy dissipation, or the entropy production rate (EPR), sets thermodynamic constraints on cellular processes. Practically, calculating the total EPR in experimental systems is challenging due to the limited spatiotemporal resolution and the lack of complete information on every degree of freedom. Here, we propose a new inference approach for a tight lower bound on the total EPR given partial information, based on an optimization scheme that uses the observed transitions and waiting times statistics. We introduce hierarchical bounds relying on the first- and second-order transitions, and the moments of the observed waiting time distributions, and apply our approach to two generic systems of a hidden network and a molecular motor, with lumped states. Finally, we show that a lower bound on the total EPR can be obtained even when assuming a simpler network topology of the full system.

cond-mat.stat-mech

Model studies on motion of respiratory droplets driven through a face mask

Face masks are used to intercept respiratory droplets to prevent spreading of air-borne diseases. Designing face masks with better efficiency needs microscopic understanding on how respiratory droplets move through a mask. Here we study a simple model on the interception of droplets by a face mask. The mask is treated as a polymeric network in an asymmetric confinement, while the droplet is taken as a micrometer sized tracer colloidal particle, subject to driving force that mimics the breathing. We study numerically, using the Langevin dynamics, the tracer particle permeation through the polymeric network. We show that the permeation is an activated process following an Arrhenius dependence on temperature. The potential energy profile responsible for the activation process increases with tracer size, tracer bead interaction, network rigidity and decreases with the driving force and confinement length. A deeper energy barrier led to better efficiency to intercept the tracer particles of a given size in the presence of driving force at room temperature. Our studies may help to design mask with better efficiency.

cond-mat.soft

Inferring entropy production rate from partially observed Langevin dynamics under coarse-graining

This paper shows an estimation of a lower bound on the total entropy production rate(EPR) for a system following Langevin dynamics with a single observed variable coarse-grained into a few discrete states, by invoking the underlying broken time-reversal symmetry. We estimate the irreversibility in waiting time distributions of the partially observed system and find the effect of spatial resolution on the mean dwell-time asymmetry and the EPR.

cond-mat.stat-mech