Biology subjects

Sosnick, T. R.

Publications and source records attributed to Sosnick, T. R..

7 recordsLinked to original sources

bioRxiv2026

Dynamic myosin 10 coupling to DCC and β1 integrin is mediated by intrinsically disordered regions during filopodial transport and patterning

Intrinsically disordered regions (IDRs) are key mediators of protein-protein interactions. IDRs are important components of Myosin 10 (Myo10) and cargo complexes that influence neuronal development and cell growth, yet how IDRs dictate Myo10s cargo affinity and selectivity is not fully understood. Here, we investigate how the actin motor protein Myo10 engages two distinct cargo receptors, DCC and {beta}1 integrin, in cellular protrusions known as filopodia. Using hydrogen-deuterium exchange mass spectrometry (HDX-MS), cross-linking mass spectrometry (XL-MS), live-cell imaging, and super-resolution microscopy, we show that Myo10 decodes IDR elements through two complementary mechanisms: disorder-to-order transitions and "fuzzy" binding. The cytoplasmic portion of DCC binds Myo10 via a weakly helical P3 motif that acts as a preformed recognition element, while additional disordered motifs contribute to affinity through dynamic, weak interactions. In contrast, the {beta}1 integrin tail interacts with Myo10 through short NPxY motifs that remain disordered. Both cargos engage a common Myo10 surface but also contact distinct sites. Super-resolution DNA-PAINT imaging reveals distinct patterning of cargo with Myo10 along and around filopodia. Concentration measurements show that DCC is primarily bound while {beta}1 integrin exhibits a broader range of occupancy along the filopodial shaft. Multiple additive weak contacts and a shared binding site implies that DCC can out-compete integrin for Myo10 binding, which causes redistribution of active {beta}1 integrin from the filopodial tip to the shaft. Our findings illustrate a tunable, multivalent binding strategy that allows Myo10 to selectively coordinate diverse signaling cargos, demonstrating how regulated disorder within IDRs is one mechanism underlying cargo binding and cellular signaling.

biophysics↗

bioRxiv2024

Transcriptome-wide mRNA condensation precedes stress granule formation and excludes stress-induced transcripts

Stress-induced mRNP condensation is conserved across eukaryotes, resulting in stress granule formation under intense stresses, yet the mRNA composition and function of these condensates remain unclear. Exposure of ribosome-free mRNA following stress is thought to cause condensation and stress granule formation through mRNA-sequence-dependent interactions, leading to disproportionate condensation of long mRNAs. Here we show that, in striking contrast, virtually all mRNAs condense in response to multiple stresses in budding yeast with minor length dependence and often without stress granule formation. New transcripts escape mRNP condensation, enabling their selective translation. Inhibiting translation initiation causes formation of mRNP condensates that are distinct from stress granules and P-bodies; these translation-initiation-inhibited condensates (TIICs) are omnipresent, even in unstressed cells. Stress-induced mRNAs are excluded from TIICs due to the timing of their expression, indicating determinants of escape that are independent of sequence. Together, our results reveal a previously undetected level of translation-linked molecular organization and stress-responsive regulation.

cell biology↗

bioRxiv2023

An adaptive biomolecular condensation response is conserved across environmentally divergent species

Cells must sense and respond to sudden maladaptive environmental changes--stresses--to survive and thrive. Across eukaryotes, stresses such as heat shock trigger conserved responses: growth arrest, a specific transcriptional response, and biomolecular condensation of protein and mRNA into structures known as stress granules under severe stress. The composition, formation mechanism, adaptive significance, and even evolutionary conservation of these condensed structures remain enigmatic. Here we provide an unprecedented view into stress-triggered condensation, its evolutionary conservation and tuning, and its integration into other well-studied aspects of the stress response. Using three morphologically near-identical budding yeast species adapted to different thermal environments and diverged by up to 100 million years, we show that proteome-scale biomolecular condensation is tuned to species-specific thermal niches, closely tracking corresponding growth and transcriptional responses. In each species, poly(A)-binding protein--a core marker of stress granules--condenses in isolation at species-specific temperatures, with conserved molecular features and conformational changes modulating condensation. From the ecological to the molecular scale, our results reveal previously unappreciated levels of evolutionary selection in the eukaryotic stress response, while establishing a rich, tractable system for further inquiry.

cell biology↗

bioRxiv2022

LILAC: Enhanced actin imaging with an optogenetic Lifeact

We have designed an improved Lifeact variant that binds to actin under the control of light using the LOV2 protein. Light control enables one to subtract the pre-illumination signal of the unbound label, yielding an enhanced view of F-actin dynamics in cells. Furthermore, the tool eliminates actin network perturbations and cell sickness caused by Lifeact overexpression.

biophysics↗

bioRxiv2018

Aβ Fibrils Can Act as Aqueous Pores: a Molecular Dynamics Study

Aggregation of A{beta} peptides is important in the etiology of Alzheimers Disease (AD), an increasingly prevalent neurodegenerative disease. We ran multiple [~] 300 ns all-atom explicit solvent molecular dynamics (MD) simulations starting from three NMR-based structural models of A{beta}(1-40 residues) fibrils having 2-fold (pdb code 2LMN) or 3-fold rotational symmetry (2LMP, and 2M4J). The 2M4J structure is based on an AD brain-seeded fibril whereas 2LMP and 2LMN represent two all-synthetic fibrils. Fibrils are constructed to contain either 6 or an infinite number of layers made using periodic images. The 6 layer fibrils partially unravel over the simulation time, mainly at their ends, while infinitely long fibrils do not. Once formed, the D23-K28 salt bridges are very stable and form within and between chains. Fibrils tend to retain (2LMN and 2LMP) or develop (2M4J) a \"stagger\" or register shift of {beta}-strands along the fibril axis. The brain-seeded fibril rapidly develops gaps at the sides of the fibril, which allows bidirectional flow of water and ions from the bulk phase in and out the central longitudinal core of the fibril. Similar but less marked changes were also observed for the 2LMP fibrils. The residues defining the gaps largely coincide with those demonstrated to have relatively rapid Hydrogen-Deuterium exchange in solid state NMR studies. These observations suggest that A{beta}(1-40 residues) fibrils may act as aqueous pores that might disrupt water and ion fluxes if inserted into a cell membrane.

neuroscience↗

bioRxiv2018

Commonly-used FRET fluorophores promote collapse of an otherwise disordered protein.

The dimensions that unfolded proteins, including intrinsically disordered proteins (IDPs), adopt at low or no denaturant remains controversial. We recently developed an innovative analysis procedure for small-angle X-ray scattering (SAXS) profiles and found that even relatively hydrophobic IDPs remain nearly as expanded as the chemically denatured ensemble, rendering them significantly more expanded than generally inferred using fluorescence resonance energy transfer (FRET) measurements. We show here that fluorophores typical of those employed in FRET can contribute to this discrepancy. Specifically, we find that addition of Alexa488 to a normally expanded IDP causes contraction of its ensemble. In parallel, we also tested the recent suggestion that FRET and SAXS results can be reconciled if, in contrast to homopolymers, the radius of gyration (Rg) of an unfolded protein chain can vary independently from its end-to-end distance (Ree). To do so, we developed an analysis procedure that can accurately extract both Rg and Ree from SAXS profiles even if they are decoupled. Using this procedure, we find that Rg and Ree remain tightly coupled even for heteropolymeric IDPs. We thus conclude that, when combined with improved analysis procedures for both SAXS and FRET, fluorophore-driven interactions are sufficient to explain the preponderance of existing data regarding the nature of polypeptide chains unfolded in the absence of denaturant.

biophysics↗

bioRxiv2017

Trajectory-Based Parameterization of a Coarse-Grained Forcefield for High-Throughput Protein Simulation

The traditional trade-off in biomolecular simulation between accuracy and computational efficiency is predicated on the assumption that detailed forcefields are typically well-parameterized (i.e. obtaining a significant fraction of possible accuracy). We re-examine this trade-off in the more realistic regime in which parameterization is a greater source of bias than the level of detail in the forcefield. To address parameterization of coarse-grained forcefields, we use the contrastive divergence technique from machine learning to train directly from simulation trajectories on 450 proteins. In our scheme, the computational efficiency of the model enables high accuracy through precise tuning of the Boltzmann ensemble over a large collection of proteins. This method is applied to our recently developed Upside model [1], where the free energy for side chains are rapidly calculated at every time-step, allowing for a smooth energy landscape without steric rattling of the side chains. After our contrastive divergence training, the model is able to fold proteins up to approximately 100 residues de novo on a single core in CPU core-days. Additionally, the improved Upside model is a strong starting point both for investigation of folding dynamics and as an inexpensive Bayesian prior for protein physics that can be integrated with additional experimental or bioinformatic data.

biophysics↗