Biology subjects

Borcherds, W. M.

Publications and source records attributed to Borcherds, W. M..

6 recordsLinked to original sources

bioRxiv2023

Sequence-encoded grammars determine material properties and physical aging of protein condensates

Biomolecular condensates are viscoelastic materials. Here, we report results from investigations into molecular-scale determinants of sequence-encoded and age-dependent viscoelasticity of condensates formed by prion-like low-complexity domains (PLCDs). The terminally viscous forms of PLCD condensates are Maxwell fluids. Measured viscoelastic moduli of these condensates are reproducible using a Rouse-Zimm model that accounts for the network-like organization engendered by reversible physical crosslinks among PLCDs in the dense phase. Measurements and computations show that the strengths of aromatic inter-sticker interactions determine the sequence-specific amplitudes of elastic and viscous moduli as well as the timescales over which elastic properties dominate. PLCD condensates also undergo physical aging on sequence-specific timescales. This is driven by mutations to spacer residues that weaken the metastability of terminally viscous phases. The aging of PLCD condensates is accompanied by disorder-to-order transitions, leading to the formation of non-fibrillar, beta-sheet-containing, semi-crystalline, terminally elastic, Kelvin-Voigt solids. Our results suggest that sequence grammars, which refer to the identities of stickers versus spacers in PLCDs, have evolved to afford control over the metastabilities of terminally viscous fluid phases of condensates. This selection can, in some cases, render barriers for conversion from metastable fluids to globally stable solids to be insurmountable on functionally relevant timescales.

biophysics↗

bioRxiv2023

Phase Separation in Mixtures of Prion-Like Low Complexity Domains is Driven by the Interplay of Homotypic and Heterotypic Interactions

Prion-like low-complexity domains (PLCDs) are involved in the formation and regulation of distinct biomolecular condensates that form via coupled associative and segregative phase transitions. We previously deciphered how evolutionarily conserved sequence features drive phase separation of PLCDs through homotypic interactions. However, condensates typically encompass a diverse mixture of proteins with PLCDs. Here, we combine simulations and experiments to study mixtures of PLCDs from two RNA binding proteins namely, hnRNPA1 and FUS. We find that 1:1 mixtures of the A1-LCD and FUS-LCD undergo phase separation more readily than either of the PLCDs on their own. The enhanced driving forces for phase separation of mixtures of A1-LCD and FUS-LCD arise partly from complementary electrostatic interactions between the two proteins. This complex coacervation-like mechanism adds to complementary interactions among aromatic residues. Further, tie line analysis shows that stoichiometric ratios of different components and their sequence-encoded interactions jointly contribute to the driving forces for condensate formation. These results highlight how expression levels might be tuned to regulate the driving forces for condensate formation in vivo. Simulations also show that the organization of PLCDs within condensates deviates from expectations based on random mixture models. Instead, spatial organization within condensates will reflect the relative strengths of homotypic versus heterotypic interactions. We also uncover rules for how interaction strengths and sequence lengths modulate conformational preferences of molecules at interfaces of condensates formed by mixtures of proteins. Overall, our findings emphasize the network-like organization of molecules within multicomponent condensates, and the distinctive, composition-specific conformational features of condensate interfaces. Significance StatementBiomolecular condensates are mixtures of different protein and nucleic acid molecules that organize biochemical reactions in cells. Much of what we know about how condensates form comes from studies of phase transitions of individual components of condensates. Here, we report results from studies of phase transitions of mixtures of archetypal protein domains that feature in distinct condensates. Our investigations, aided by a blend of computations and experiments, show that the phase transitions of mixtures are governed by a complex interplay of homotypic and heterotypic interactions. The results point to how expression levels of different protein components can be tuned in cells to modulate internal structures, compositions, and interfaces of condensates, thus affording distinct ways to control the functions of condensates.

biophysics↗

bioRxiv2022

Quantifying coexistence concentrations in multi-component phase-separating systems using analytical HPLC

Over the last decade, evidence has accumulated to suggest that numerous instances of cellular compartmentalization can be explained by the phenomenon of phase separation. This is a process by which a macromolecular solution separates spontaneously into dense and dilute coexisting phases. Semi-quantitative, in vitro approaches for measuring phase boundaries have proven very useful in determining some key features of biomolecular condensates, but these methods often lack the precision necessary for generating quantitative models. Therefore, there is a clear need for techniques that allow quantitation of coexisting dilute and dense phase concentrations of phase-separating biomolecules, especially in systems with more than one type of macromolecule. Here we report the design and deployment of analytical High-Performance Liquid Chromatography (HPLC) for in vitro separation and quantification of distinct biomolecules that allows us to measure dilute and dense phase concentrations needed to reconstruct coexistence curves in multicomponent mixtures. This approach is label-free, detects lower amounts of material than is accessible with classic UV-spectrophotometers, is applicable to a broad range of macromolecules of interest, is a semi-high-throughput technique, and if needed, the macromolecules can be recovered for further use. The approach promises to provide quantitative insights into the balance of homotypic and heterotypic interactions in multicomponent phase-separating systems.

biophysics↗

bioRxiv2022

Condensates of disordered proteins have small-world network structures and interfaces defined by expanded conformations

The formation of membraneless biomolecular condensates is driven by macromolecules with sticker-and-spacer architectures that undergo phase separation coupled to percolation (PSCP). Driving forces for PSCP are governed by the interplay between reversible inter-sticker crosslinks and solvation preferences of spacers. Here, we introduce molecular and mesoscale descriptions of structures within, outside, and at the interfaces of condensates that are formed by prion-like low complexity domains (PLCDs), which are exemplars of intrinsically disordered, linear multivalent proteins. Our studies are based on simulations that accurately describe sequence-specific phase behaviors of PLCDs. We find that networks of reversible, intermolecular, inter-sticker crosslinks organize PLCDs into small-world topologies within condensates. These topologies result from distinct conformational preferences within dense, dilute, and interfacial regions. Specifically, the degree of conformational expansion varies non-monotonically, being most expanded at the interface and most compact in the dilute phase with molecules preferring to be oriented perpendicular to condensate interfaces. This contrasts with dense and dilute phases where molecules are randomly oriented relative to one another. Our results demonstrate that even simple condensates, with only one type of macromolecule, feature inhomogeneous spatial organizations of molecules and interfacial features that likely prime them for being locations of biochemical activity.

biophysics↗

bioRxiv2021

Conformational buffering underlies functional selection in intrinsically disordered protein regions

Many disordered proteins conserve essential functions in the face of extensive sequence variation. This makes it challenging to identify the forces responsible for functional selection. Viruses are robust model systems to investigate functional selection and they take advantage of protein disorder to acquire novel traits. Here, we combine structural and computational biophysics with evolutionary analysis to determine the molecular basis for functional selection in the intrinsically disordered adenovirus early gene 1A (E1A) protein. E1A competes with host factors to bind the retinoblastoma (Rb) protein, triggering early S-phase entry and disrupting normal cellular proliferation. We show that the ability to outcompete host factors depends on the picomolar binding affinity of E1A for Rb, which is driven by two binding motifs tethered by a hypervariable disordered linker. Binding affinity is determined by the spatial dimensions of the linker, which constrain the relative position of the two binding motifs. Despite substantial sequence variation across evolution, the linker dimensions are finely optimized through compensatory changes in amino acid sequence and sequence length, leading to conserved linker dimensions and maximal affinity. We refer to the mechanism that conserves spatial dimensions despite large-scale variations in sequence as conformational buffering. Conformational buffering explains how variable disordered proteins encode functions and could be a general mechanism for functional selection within disordered protein regions.

biophysics↗

bioRxiv2021

Deciphering how naturally occurring sequence features impact the phase behaviors of disordered prion-like domains

Phase separation of intrinsically disordered prion-like low-complexity domains (PLCDs) derived from RNA-binding proteins enable the formation of biomolecular condensates in cells. PLCDs have distinct amino acid compositions, and here we decipher the physicochemical impact of conserved compositional biases on the driving forces for phase separation. We find that tyrosine residues make for stronger drivers of phase separation than phenylalanine. Depending on their sequence contexts, arginine residues enhance or weaken phase separation, whereas lysine residues weaken cohesive interactions within PLCDs. Increased net charge per residue (NCPR) weakens the driving forces for phase separation of PLCDs and this effect can be modeled quantitatively. The effects of NCPR also weaken known correlations between the dimensions of single chains in dilute solution and the driving forces for phase separation. We build on experimental data to develop a coarse-grained model for accurate simulations of phase separation that yield novel insights regarding PLCD phase behavior.

biophysics↗