arXiv subjects

Shenshen Wang

Publications and source records attributed to Shenshen Wang.

At least 19 recordsLinked to original sources

arXiv2025

Mechanical activity enables patterning and discrimination at the immune synapse

Immune cells recognize and discriminate antigens through immunological synapses - dynamic intercellular junctions exhibiting highly organized receptor-ligand patterns. While much work has focused on molecular kinetics and passive mechanisms of pattern formation, the role of active mechanical control in patterning and discrimination remains underexplored. We develop a minimal continuum model coupling receptor binding kinetics, membrane deformation, and cytoskeletal forces, with elastohydrodynamic flow in the synaptic cleft. Numerical simulations and scaling analysis reveal that contractile cortical flows arrest coarsening and stabilize long-lived multifocal clusters, whereas active pulling accelerates cluster dissolution and elevates background receptor binding. Nonequilibrium mechanical forces enable adaptive control over the speed, sensitivity, and dynamic range of affinity discrimination in a pattern-dependent manner. Our results highlight how immune cells exploit cytoskeletal remodeling to robustly regulate antigen recognition through synaptic patterning.

q-bio.CB↗

arXiv2025

Adaptive mechanical proofreading toward faithful clonal selection

To ensure faithful information transmission, cells utilize nonequilibrium drives to reduce errors. Kinetic proofreading is a classic mechanism known to sharpen ligand discrimination by T lymphocytes. It remains an open question whether the adaptive immune system relies solely on kinetic proofreading to boost fidelity. Here, we suggest an alternative: an enhanced form of mechanical proofreading (MPR) in which adaptive force exertion via dynamic cell-cell contact allows faithful selection of high-affinity B lymphocytes. Using a minimal model validated with experiment, we show that adaptive MPR, characterized by mechanical feedback between force generation and contact formation, enables robust discrimination of receptor quality regardless of ligand quantity. Although MPR generically balances the tradeoffs between speed and fidelity, a negative scaling of contact duration with ligand abundance indicates the presence of feedback. Due to its ability to modulate interactions of distinct ligands that share load at membrane contacts, adaptive MPR can be harnessed to mitigate autoimmunity or enhance multivalent vaccines. Overall, this work suggests a generalization of the proofreading mechanism to encompass cellular designs that act across scales to enable competing functionalities.

physics.bio-ph↗

arXiv2024

Migration feedback induces emergent ecotypes and abrupt transitions in evolving populations

We explore the connection between migration patterns and emergent behaviors of evolving populations in spatially heterogeneous environments. Despite extensive studies in ecologically and medically important systems, a unifying framework that clarifies this connection and makes concrete predictions remains much needed. Using a simple evolutionary model on a network of interconnected habitats with distinct fitness landscapes, we demonstrate a fundamental connection between migration feedback, emergent ecotypes, and an unusual form of discontinuous critical transition. We show how migration feedback generates spatially non-local niches in which emergent ecotypes can specialize. Rugged fitness landscapes lead to a complex, yet understandable, phase diagram in which different ecotypes coexist under different migration patterns. The discontinuous transitions are distinct from the standard first-order phase transitions in statistical physics. They arise due to simultaneous transcritical bifurcations and exhibit a "fine structure" due to symmetry breaking between intra- and inter-ecotype interactions. We suggest feasible experiments to test our predictions.

q-bio.PE↗

arXiv2022

Multiple Phase Transitions Shape Biodiversity of a Migrating Population

In a wide variety of natural systems, closely-related microbial strains coexist stably, resulting in high levels of fine-scale biodiversity. However, the mechanisms that stabilize this coexistence are not fully understood. Spatial heterogeneity is one common stabilizing mechanism, but the rate at which organisms disperse throughout the heterogeneous environment may strongly impact the stabilizing effect that heterogeneity can provide. An intriguing example is the gut microbiome, where active mechanisms exist to control the movement of microbes and potentially maintain diversity. We investigate how biodiversity is affected by migration rate using a simple evolutionary model with heterogeneous selection pressure. We find that the biodiversity-migration rate relationship is shaped by multiple phase transitions, including a reentrant phase transition to coexistence. At each transition, an ecotype goes extinct and dynamics exhibit critical slowing down (CSD). CSD is encoded in the statistics of fluctuations due to demographic noise -- this may provide an experimental means for detecting and altering impending extinction.

q-bio.PE↗

arXiv2022

Effective Dynamics of Generative Adversarial Networks

Generative adversarial networks (GANs) are a class of machine-learning models that use adversarial training to generate new samples with the same (potentially very complex) statistics as the training samples. One major form of training failure, known as mode collapse, involves the generator failing to reproduce the full diversity of modes in the target probability distribution. Here, we present an effective model of GAN training, which captures the learning dynamics by replacing the generator neural network with a collection of particles in the output space; particles are coupled by a universal kernel valid for certain wide neural networks and high-dimensional inputs. The generality of our simplified model allows us to study the conditions under which mode collapse occurs. Indeed, experiments which vary the effective kernel of the generator reveal a mode collapse transition, the shape of which can be related to the type of discriminator through the frequency principle. Further, we find that gradient regularizers of intermediate strengths can optimally yield convergence through critical damping of the generator dynamics. Our effective GAN model thus provides an interpretable physical framework for understanding and improving adversarial training.

cond-mat.dis-nn↗

arXiv2022

Molecular tug of war reveals adaptive potential of an immune cell repertoire

The adaptive immune system constantly remodels its lymphocyte repertoire for better protection against future pathogens. Its ability to improve antigen recognition on the fly relies on somatic mutation and selective expansion of B lymphocytes expressing high-affinity antigen receptors. However, this Darwinian process inside an individual appears ineffective, hitting a modest ceiling of antigen-binding affinity. Experiment began to reveal that evolving B cells physically extract antigens from presenting cells and that the extraction level dictates clonal expansion; this challenges the prevailing assumption that the equilibrium constant of receptor-antigen binding determines selective advantage. We present a theoretical framework to explore whether, and how, such tug-of-war antigen extraction impacts the quality and diversity of an evolved B cell repertoire. We find that the apparent ineffectiveness of clonal selection can be a direct consequence of the non-equilibrium nature of antigen recognition. Our theory predicts that the physical strength of antigen tethering under tugging forces sets the affinity ceiling. Meanwhile, the model showed that, intriguingly, cells can use force variability to diversify binding phenotype without compromising fitness, thus remaining plastic under resource constraint. These results suggest that active probing of receptor quality via a molecular tug of war during antigen recognition limit the potency of response to the current antigen, but confer adaptive benefit for protection against future variants. Importantly, a saddle point in the fitness landscape of B cell phenotype evolution emerges from the tug-of-war setting, which rationalizes multiple key phenomenology and puts forward a role of active physical dynamics in immune adaptation.

physics.bio-ph↗

arXiv2022

Immune cells use active tugging forces to distinguish affinity and accelerate evolution

Cells are known to exert forces to sense their physical surroundings for guidance of motion and fate decisions. Here, we propose that cells might do mechanical work to drive their own evolution, taking inspiration from the adaptive immune system. Growing evidence indicates that immune B cells - capable of rapid Darwinian evolution - use cytoskeletal forces to actively extract antigen from other cells' surface. To elucidate the evolutionary significance of force usage, we develop a theory of tug-of-war antigen extraction that maps receptor binding characteristics to clonal reproductive fitness, revealing physical determinants of selection strength. This framework unifies mechanosensing and affinity-discrimination capabilities of evolving cells: pulling against stiff antigen tethers enhances discrimination stringency at the expense of absolute extraction. As a consequence, active force usage can accelerate adaptation but may also cause extinction of cell populations, resulting in an optimal range of pulling strength that matches molecular rupture forces observed in cells. Our work suggests that nonequilibrium, physical extraction of environmental signals can make biological systems more evolvable at a moderate energy cost.

q-bio.CB↗

arXiv2020

Aging-induced fragility of the immune system

The adaptive and innate branches of the vertebrate immune system work in close collaboration to protect organisms from harmful pathogens. As an organism ages its immune system undergoes immunosenescence, characterized by declined performance or malfunction in either immune branch, which can lead to disease and death. In this study we develop a mathematical framework of coupled innate and adaptive immune responses, namely the integrated immune branch (IIB) model. This model describes dynamics of immune components in both branches, uses a shape-space representation to encode pathogen-specific immune memory, and exhibits three steady states -- health, septic death, and chronic inflammation -- qualitatively similar to clinically-observed immune outcomes. In this model, the immune system (initialized in the health state) is subjected to a sequence of pathogen encounters, and we use the number of prior pathogen encounters as a proxy for the "age" of the immune system. We find that repeated pathogen encounters may trigger a fragility in which any encounter with a novel pathogen will cause the system to irreversibly switch from health to chronic inflammation. This transition is consistent with the onset of "inflammaging", a condition observed in aged individuals who experience chronic low-grade inflammation even in the absence of pathogens. The IIB model predicts that the onset of chronic inflammation strongly depends on the history of encountered pathogens; the timing of onset differs drastically when the same set of infections occurs in a different order. Lastly, the coupling between the innate and adaptive immune branches generates a trade-off between rapid pathogen clearance and a delayed onset of immunosenescence.

q-bio.TO↗

arXiv2019

Trait-space patterning and the role of feedback in antigen-immunity coevolution

Coevolutionary arms races form between interacting populations that constitute each other's environment and respond to mutual changes. This inherently far-from-equilibrium process finds striking manifestations in the adaptive immune system, where highly variable antigens and a finite repertoire of immune receptors coevolve on comparable timescales. This unique challenge to the immune system motivates general questions: How do ecological and evolutionary processes interplay to shape diversity? What determine the endurance and fate of coevolution? Here, we take the perspective of responsive environments and develop a phenotypic model of coevolution between receptors and antigens that both exhibit cross-reactivity (one-to-many responses). The theory predicts that the extent of asymmetry in cross-reactivity is a key determinant of repertoire composition: small asymmetry supports persistent large diversity, whereas strong asymmetry yields long-lived transients of quasispecies in both populations. The latter represents a new type of Turing mechanism. More surprisingly, patterning in the trait space feeds back on population dynamics: spatial resonance between the Turing modes breaks the dynamic balance, leading to antigen extinction or unrestrained growth. Model predictions can be tested via combined genomic and phenotypic measurements. Our work identifies cross-reactivity as an important regulator of diversity and coevolutionary outcome, and reveals the remarkable effect of ecological feedback in pattern-forming systems, which drives evolution toward non-steady states different than the Red Queen persistent cycles.

physics.bio-ph↗

arXiv2019

Tuning environmental timescales to evolve and maintain generalists

Natural environments can present diverse challenges, but some genotypes remain fit across many environments. Such `generalists' can be hard to evolve, out-competed by specialists fitter in any particular environment. Here, inspired by the search for broadly-neutralising antibodies during B-cell affinity maturation, we demonstrate that environmental changes on an intermediate timescale can reliably evolve generalists, even when faster or slower environmental changes are unable to do so. We find that changing environments on timescales comparable to evolutionary transients in a population enhances the rate of evolving generalists from specialists, without enhancing the reverse process. The yield of generalists is further increased in more complex dynamic environments, such as a `chirp' of increasing frequency. Our work offers design principles for how non-equilibrium fitness `seascapes' can dynamically funnel populations to genotypes unobtainable in static environments.

q-bio.PE↗

arXiv2019

Evolving generalists via dynamic sculpting of rugged landscapes

Evolving systems, be it an antibody repertoire in the face of mutating pathogens or a microbial population exposed to varied antibiotics, constantly search for adaptive solutions in time-varying fitness landscapes. Generalists correspond to genotypes that remain fit across diverse selective pressures; cross-reactive antibodies are much wanted but rare, while multi-drug resistant microbes are undesired yet prevalent. However, little is known about under what conditions such solutions with a high capacity to adapt would be efficiently discovered by evolution, as environmental changes alter the relative fitness and accessibility of neighboring genotypes. In addition, can epistasis --- the source of landscape ruggedness and path constraints --- play a different role, if the environments are correlated in time? We present a generative model to estimate the propensity of evolving generalists in rugged landscapes that are tunably related and cycling relatively slowly. We find that environment cycling can substantially facilitate the search for fit generalists by dynamically enlarging their effective basins of attraction. Importantly, these high performers are most likely to emerge at an intermediate level of both ruggedness and environmental relatedness, trading diversity for fitness and accessibility. Our work provides a conceptual framework to study evolution in correlated varying complex environments, and offers statistical understanding that suggests general strategies for speeding up the generation of broadly neutralizing antibodies or preventing microbes from evolving multi-drug resistance.

physics.bio-ph↗

arXiv2018

Active tuning of synaptic patterns enhances immune discrimination

Immune cells learn about their antigenic targets using tactile sense: during recognition, a highly organized yet dynamic motif, named immunological synapse, forms between immune cells and antigen-presenting cells (APCs). Via synapses, immune cells selectively extract recognized antigen from APCs by applying mechanical pulling forces generated by the contractile cytoskeleton. Curiously, depending on its stage of development, a B lymphocyte exhibits distinct synaptic patterns and uses force at different strength and timing, which appear to strongly impact its capacity of distinguishing antigen affinities. However, the mechanism by which molecular binding affinity translates into the amount of antigen acquisition remains an unsolved puzzle. We use a statistical-mechanical model to study how the experimentally observed synaptic architectures can originate from normal cytoskeletal forces coupled to lateral organization of mobile receptors, and show how this active regulation scheme, collective in nature, may provide a robust grading scheme that allows efficient and broad affinity discrimination essential for proper immune function.

physics.bio-ph↗

arXiv2014

Active patterning and asymmetric transport in a model actomyosin network

Cytoskeletal networks, which are essentially motor-filament assemblies, play a major role in many developmental processes involving structural remodeling and shape changes. These are achieved by nonequilibrium self-organization processes that generate functional patterns and drive intracellular transport. We construct a minimal physical model that incorporates the coupling between nonlinear elastic responses of individual filaments and force-dependent motor action. By performing stochastic simulations we show that the interplay of motor processes, described as driving anti-correlated motion of the network vertices, and the network connectivity, which determines the percolation character of the structure, can indeed capture the dynamical and structural cooperativity which gives rise to diverse patterns observed experimentally. The buckling instability of individual filaments is found to play a key role in localizing collapse events due to local force imbalance. Motor-driven buckling-induced node aggregation provides a dynamic mechanism that stabilizes the two dimensional patterns below the apparent static percolation limit. Coordinated motor action is also shown to suppress random thermal noise on large time scales, the two dimensional configuration that the system starts with thus remaining planar during the structural development. By carrying out similar simulations on a three dimensional anchored network, we find that the myosin-driven isotropic contraction of a well-connected actin network, when combined with mechanical anchoring that confers directionality to the collective motion, may represent a novel mechanism of intracellular transport, as revealed by chromosome translocation in the starfish oocyte.

cond-mat.soft↗

arXiv2014

Entanglement tongue and quantum synchronization of disordered oscillators

We study the synchronization of dissipatively-coupled van der Pol oscillators in the quantum limit, when each oscillator is near its quantum ground state. Two quantum oscillators with different frequencies exhibit an entanglement tongue, which is the quantum analogue of an Arnold tongue. It means that the oscillators are entangled in steady state when the coupling strength is greater than a critical value, and the critical coupling increases with detuning. An ensemble of many oscillators with random frequencies still exhibits a synchronization phase transition in the quantum limit, and we analytically calculate how the critical coupling depends on the frequency disorder. Our results can be experimentally observed with trapped ions or neutral atoms.

quant-ph↗

arXiv2012

Microscopic theory of the glassy dynamics of passive and active network materials

Signatures of glassy dynamics have been identified experimentally for a rich variety of materials in which molecular networks provide rigidity. Here we present a theoretical framework to study the glassy behavior of both passive and active network materials. We construct a general microscopic network model that incorporates nonlinear elasticity of individual filaments and steric constraints due to crowding. Based on constructive analogies between structural glass forming liquids and random field Ising magnets implemented using a heterogeneous self-consistent phonon method, our scheme provides a microscopic approach to determine the mismatch surface tension and the configurational entropy, which compete in determining the barrier for structural rearrangements within the random first order transition theory of escape from a local energy minimum. The influence of crosslinking on the fragility of inorganic network glass formers is recapitulated by the model. For active network materials, the mapping, which correlates the glassy characteristics to the network architecture and properties of nonequilibrium motor processes, is shown to capture several key experimental observations on the cytoskeleton of living cells: Highly connected tense networks behave as strong glass formers; intense motor action promotes reconfiguration. The fact that our model assuming a negative motor susceptibility predicts the latter suggests that on average the motorized processes in living cells do resist the imposed mechanical load. Our calculations also identify a spinodal point where simultaneously the mismatch penalty vanishes and the mechanical stability of amorphous packing disappears.

cond-mat.stat-mech↗

arXiv2012

Tensegrity and Motor-Driven Effective Interactions in a Model Cytoskeleton

Actomyosin networks are major structural components of the cell. They provide mechanical integrity and allow dynamic remodeling of eukaryotic cells, self-organizing into the diverse patterns essential for development. We provide a theoretical framework to investigate the intricate interplay between local force generation, network connectivity and collective action of molecular motors. This framework is capable of accommodating both regular and heterogeneous pattern formation, arrested coarsening and macroscopic contraction in a unified manner. We model the actomyosin system as a motorized cat's cradle consisting of a crosslinked network of nonlinear elastic filaments subjected to spatially anti-correlated motor kicks acting on motorized (fibril) crosslinks. The phase diagram suggests there can be arrested phase separation which provides a natural explanation for the aggregation and coalescence of actomyosin condensates. Simulation studies confirm the theoretical picture that a nonequilibrium many-body system driven by correlated motor kicks can behave as if it were at an effective equilibrium, but with modified interactions that account for the correlation of the motor driven motions of the actively bonded nodes. Regular aster patterns are observed both in Brownian dynamics simulations at effective equilibrium and in the complete stochastic simulations. The results show that large-scale contraction requires correlated kicking.

physics.bio-ph↗

arXiv2012

Active contractility in actomyosin networks

Contractile forces are essential for many developmental processes involving cell shape change and tissue deformation. Recent experiments on reconstituted actomyosin networks, the major component of the contractile machinery, have shown that active contractility occurs above a threshold motor concentration and within a window of crosslink concentration. We present a microscopic dynamic model that incorporates two essential aspects of actomyosin self-organization: the asymmetric load response of individual actin filaments and the correlated motor-driven events mimicking myosin-induced filament sliding. Using computer simulations we examine how the concentration and susceptibility of motors contribute to their collective behavior and interplay with the network connectivity to regulate macroscopic contractility. Our model is shown to capture the formation and dynamics of contractile structures and agree with the observed dependence of active contractility on microscopic parameters including the contractility onset. Cooperative action of load-resisting motors in a force-percolating structure integrates local contraction/buckling events into a global contractile state via an active coarsening process, in contrast to the flow transition driven by uncorrelated kicks of susceptible motors.

physics.bio-ph↗

arXiv2011

The Interplay of Nonlinearity and Architecture in Equilibrium Cytoskeletal Mechanics

The interplay between cytoskeletal architecture and the nonlinearity of the interactions due to bucklable filaments plays a key role in modulating the cell's mechanical stability and affecting its structural rearrangements. We study a model of cytoskeletal structure treating it as an amorphous network of hard centers rigidly cross-linked by nonlinear elastic strings, neglecting the effects of motorization. Using simulations along with a self-consistent phonon method, we show that this minimal model exhibits diverse thermodynamically stable mechanical phases that depend on excluded volume, crosslink concentration, filament length and stiffness. Within the framework set by the free energy functional formulation and making use of the random first order transition theory of structural glasses, we further estimate the characteristic densities for a kinetic glass transition to occur in this model system. Network connectivity strongly modulates the transition boundaries between various equilibrium phases, as well as the kinetic glass transition density.

cond-mat.stat-mech↗