Biology subjects

Gasior, K.

Publications and source records attributed to Gasior, K..

3 recordsLinked to original sources

bioRxiv2022

Bridging global actin network patterns to local molecular dynamics: a combined modeling and machine learning framework

Cells rely on their cytoskeleton for key processes including division and directed motility. Actin filaments are a primary constituent of the cytoskeleton. Although actin filaments can create a variety of network architectures linked to distinct cell functions, the microscale molecular interactions that give rise to these macroscale structures are not well understood. In this work, we investigate the microscale mechanisms that produce different branched actin network structures using an iterative classification approach. First, we employ a simple yet comprehensive agent-based model that produces synthetic actin networks with precise control over the microscale dynamics. Then we apply machine learning techniques to classify actin networks based on measurable network density and geometry, identifying key mechanistic processes that lead to particular branched actin network architectures. Extensive computational experiments reveal that the most accurate method uses a combination of supervised learning based on network density and unsupervised learning based on network symmetry. This framework can potentially serve as a powerful tool to discover the molecular interactions that produce the wide variety of actin network configurations associated with normal development as well as pathological conditions such as cancer.

biophysics↗

bioRxiv2020

TDP-43 and HSP70 phase separate into anisotropic, intranuclear liquid spherical annuli

The RNA binding protein TDP-43 naturally phase separates within cell nuclei and forms cytoplasmic aggregates in age-related neurodegenerative diseases. Here we show that acetylation-mediated inhibition of TDP-43 binding to RNA produces co-de-mixing of acetylated and unmodified TDP-43 into symmetrical, intranuclear spherical annuli whose shells and cores have liquid properties. Shells are anisotropic, like liquid crystals. Consistent with our modelling predictions that annulus formation is driven by components with strong self-interactions but weak interaction with TDP-43, the major components of annuli cores are identified to be HSP70 family proteins, whose chaperone activity is required to maintain liquidity of the core. Proteasome inhibition, mimicking reduction in proteasome activity during aging, induces TDP-43-containing annuli in neurons in rodents. Thus, we identify that TDP-43 phase separation is regulated by acetylation, proteolysis, and ATPase-dependent chaperone activity of HSP70. One Sentence SummaryAcetylation of TDP-43 drives its phase separation into spherical annuli that form a liquid-inside-a-liquid-inside-a-liquid.

cell biology↗

bioRxiv2020

Connecting actin polymer dynamics across multiple scales

Actin is an intracellular protein that constitutes a primary component of the cellular cytoskeleton and is accordingly crucial for various cell functions. Actin assembles into semi-flexible filaments that cross-link to form higher order structures within the cytoskeleton. In turn, the actin cytoskeketon regulates cell shape, and participates in cell migration and division. A variety of theoretical models have been proposed to investigate actin dynamics across distinct scales, from the stochastic nature of protein and molecular motor dynamics to the deterministic macroscopic behavior of the cytoskeleton. Yet, the relationship between molecular-level actin processes and cellular-level actin network behavior remains understudied, where prior models do not holistically bridge the two scales together. In this work, we focus on the dynamics of the formation of a branched actin structure as observed at the leading edge of motile eukaryotic cells. We construct a minimal agent-based model for the microscale branching actin dynamics, and a deterministic partial differential equation model for the macroscopic network growth and bulk diffusion. The microscale model is stochastic, as its dynamics are based on molecular level effects. The effective diffusion constant and reaction rates of the deterministic model are calculated from averaged simulations of the microscale model, using the mean displacement of the network front and characteristics of the actin network density. With this method, we design concrete metrics that connect phenomenological parameters in the reaction-diffusion system to the biochemical molecular rates typically measured experimentally. A parameter sensitivity analysis in the stochastic agent-based model shows that the effective diffusion and growth constants vary with branching parameters in a complementary way to ensure that the outward speed of the network remains fixed. These results suggest that perturbations to microscale rates can have significant consequences at the macroscopic level, and these should be taken into account when proposing continuum models of actin network dynamics.

biophysics↗