Biology subjects

Whitten, S. T.

Publications and source records attributed to Whitten, S. T..

7 recordsLinked to original sources

bioRxiv2026

A refined sticker-spacer grammar marks disordered regions with interpretable pathogenic missense variation

Intrinsically disordered regions (IDRs) of proteins show low sequence conservation, and sequence position alone is a weak predictor of disease risk. Phase-separating IDRs (PS-IDRs) are an exception, showing nearly three times higher pathogenic mutation rates than typical IDRs. Here we determine which sequences within that class show the greatest enrichment of pathogenic missense variants and what local features they share. Using pathogenic mutation rates as an independent biological readout, we isolated a core PS-IDR subclass that maximizes pathogenic enrichment. These sequences are defined less by bulk amino acid content than by a refined sticker-spacer grammar in which aromatic residues are embedded in short glycine-rich motifs, while homotypic charge tracts are avoided. Motifs such as YGG/YGGG, FGG/FGGG, and related patterns are elevated 7- to >200-fold relative to conventional IDRs. Comparison of pathogenic and benign substitutions then shows why genetic variation in IDRs has been confounding: the grammar itself is almost never mutated. Instead, the principal pathogenic targets are glycines directly flanked by non-glycine residues. These findings link a specific local sequence architecture to mutational vulnerability and provide a practical framework for interpreting variants in disordered proteins.

biophysics↗

bioRxiv2025

Missense mutations in intrinsically disordered protein regions link pathogenicity and phase separation

The impact of missense genetic variations on protein function is often enigmatic, especially for mutations that map to intrinsically disordered regions (IDRs). Given the functional importance of phase separation of IDRs, it has been proposed that mutations that modulate phase separation might preferentially lead to disease. To examine this idea, we used the robust predictability of phase-separating (PS) IDRs and annotation of disease-associated proteins and mutations to map the correlation between disease and phase separation. Consistent with previous work linking phase separation to cancer and autism spectrum disorder, we find a higher prevalence of predicted phase separation behavior in disease-associated proteins than typical for human proteins. We map the prevalence of phase separation across a wide range of diseases, finding that many, but not all, show an enrichment of phase separation in the proteins associated with them. Strikingly, the pathogenic mutation rate in predicted PS IDRs was elevated three-fold relative to IDRs not predicted to phase separate. Substitutions involving arginine and the aromatic types were among the most pathogenic for PS IDRs, while substitutions involving serine, threonine, and alanine the most benign. We applied these trends to mutations of uncertain clinical significance and predict that half found in PS IDRs are likely pathogenic. We find that phosphorylation sites were enriched in PS IDRs when compared to other protein regions, though mutations at such sites were mostly benign. Pathogenicity was highest for mutations in predicted PS IDRs when also found in a short linear motif, known mediators of protein-protein interactions.

biophysics↗

bioRxiv2024

Aggregation of an FG nucleoporin under crowded conditions

Macromolecular crowding can affect the aggregation behavior of intrinsically disordered proteins in unexpected ways. We studied the aggregation of a peptide derived from the disordered FG nucleoporins which line the nuclear pore complex. We measured its aggregation kinetics in the presence of both inert and non-specifically interacting crowding agents. Using fluorescence emission and NMR spectroscopy, we probed differences in the local chemical microenvironment of the peptides residues. Our results indicate differences in aggregation kinetics and residue microenvironment depending on the identity of the crowder, including differences between crowding with PEG and PVP, two polymers which are often used interchangeably as inert crowding agents.

biophysics↗

bioRxiv2023

ParSe 2.0: A web application that enables proteome-scale searches for sequences that drive protein-mediated phase separation

We have developed an algorithm, ParSe, that accurately identifies from the primary sequence those protein regions likely to exhibit physiological phase separation behavior. Originally, ParSe was designed to test the hypothesis that, for flexible proteins, phase separation potential is correlated to hydrodynamic size. While our results were consistent with that idea, we also found that many different descriptors could successfully differentiate between three classes of protein regions: folded, intrinsically disordered, and phase-separating intrinsically disordered. Consequently, numerous combinations of amino acid property scales can be used to make robust predictions of protein phase separation. Built from that finding, ParSe 2.0 uses an optimal set of property scales to predict domain-level organization and compute a sequence-based prediction of phase separation potential. The algorithm is fast enough to scan the whole of the human proteome in minutes on a single computer and is equally or more accurate than other published predictors in identifying proteins and regions within proteins that drive phase separation. Here, we describe a web application for ParSe 2.0 that may be accessed through a browser by visiting https://stevewhitten.github.io/Parse_v2_FASTA to quickly identify phase-separating proteins within large sequence sets, or by visiting https://stevewhitten.github.io/Parse_v2_web to evaluate individual protein sequences.

biophysics↗

bioRxiv2023

Convergent behavior of extended stalk regions from staphylococcal surface proteins with widely divergent sequence patterns

Staphylococcus epidermidis and S. aureus are highly problematic bacteria in hospital settings. This stems, at least in part, from strong abilities to form biofilms on abiotic or biotic surfaces. Biofilms are well-organized multicellular aggregates of bacteria, which, when formed on indwelling medical devices, lead to infections that are difficult to treat. Cell wall-anchored (CWA) proteins are known to be important players in biofilm formation and infection. Many of these proteins have putative stalk-like regions or regions of low complexity near the cell wall-anchoring motif. Recent work demonstrated the strong propensity of the stalk region of the S. epidermidis accumulation-associated protein (Aap) to remain highly extended under solution conditions that typically induce compaction or other significant conformational changes. This behavior is consistent with the expected function of a stalk-like region that is covalently attached to the cell wall peptidoglycan and projects the adhesive domains of Aap away from the cell surface. In this study, we evaluate whether the ability to resist compaction is a common theme among stalk regions from various staphylococcal CWA proteins. Circular dichroism spectroscopy was used to examine secondary structure changes as a function of temperature and cosolvents along with sedimentation velocity analytical ultracentrifugation and SAXS to characterize structural characteristics in solution. All stalk regions tested are intrinsically disordered, lacking secondary structure beyond random coil and polyproline type II helix, and they all sample highly extended conformations. Remarkably, the Ser-Asp dipeptide repeat region of SdrC exhibited nearly identical behavior in solution when compared to the Aap Pro/Gly-rich region, despite highly divergent sequence patterns, indicating conservation of function by various distinct staphylococcal CWA protein stalk regions.

biophysics↗

bioRxiv2022

Intrinsically disordered regions that drive phase separation form a robustly distinct protein class

Liquid-liquid phase separation (LLPS) of proteins is thought to be a primary driving force for the formation of membraneless organelles, which control a wide range of biological functions from stress response to ribosome biogenesis. LLPS of proteins in cells is primarily, though not exclusively, driven by intrinsically disordered (ID) domains. Accurate identification of ID regions (IDRs) that drive phase separation is important for testing the underlying mechanisms of phase separation, identifying biological processes that rely on phase separation, and designing sequences that modulate phase separation. To identify IDRs that drive phase separation, we first curated datasets of folded, ID, and phase-separating (PS) ID sequences. We then used these sequence sets to examine how broadly existing amino acids scales can be used to distinguish between the three classes of protein regions. We found that there are robust property differences between the classes and, consequently, that numerous combinations of amino acid property scales can be used to make robust predictions of LLPS. This result indicates that multiple, redundant mechanisms contribute to the formation of phase-separated droplets from IDRs. The top-performing scales were used to further optimize our previously developed predictor of PS IDRs, ParSe. We then modified ParSe to account for interactions between amino acids and obtained reasonable predictive power for mutations that have been designed to test the role of amino acid interactions in driving LLPS.

biophysics↗

bioRxiv2020

Beta Turn Propensity and Polymer Scaling Exponent Identify Intrinsically Disordered Proteins that Phase Separate

The complex cellular milieu can spontaneously de-mix in a process controlled in part by proteins that are intrinsically disordered (ID). A proteins propensity to de-mix is thought to be driven by the preference for protein-protein rather than protein-solvent interactions. The hydrodynamic size of monomeric proteins, as quantified by the polymer scaling exponent (v), is driven by a similar balance. We hypothesize that mean v, as predicted by the protein sequence, will be smaller for proteins with a strong propensity to de-mix. To test this hypothesis, we analyzed protein databases containing subsets that are either folded, disordered, or disordered and known to spontaneously phase separate. We find that the phase separating disordered proteins, on average, have lower calculated values of v compared to their non-phase separating counterparts. Moreover, these proteins have a higher sequence-predicted propensity for {beta}-turns. Using a simple, surface areabased model, we propose a physical mechanism for this difference: transient {beta}-turn structures reduce the desolvation penalty of forming a protein-rich phase and increase exposure of atoms involved in {pi}/sp2 electronic interactions. By this mechanism, {beta}-turns act as energetically favored nucleation points, which may explain the increased propensity for turns in ID regions (IDRs) that are utilized biologically for phase separation. Phase separating IDRs, non-phase separating IDRs, and folded regions could be distinguished by combining v and {beta}-turn propensity, and we propose a new algorithm, ParSe (partition sequence), for predicting phase separating protein regions. ParSe is able to accurately identify folded, disordered, and phase-separating protein regions from the primary sequence.

biophysics↗