Macromolecular phase separation is thought to be one of the processes that drives the formation of membraneless biomolecular condensates in cells. The dynamics of phase separation, especially at low endogenous concentrations found in cells, are thought to follow the tenets of classical nucleation theory describing a sharp transition between a dense phase and a dilute phase characterized by dispersed monomers. Here, we used in vitro biophysical studies to study subsaturated solutions of phase separating RNA binding proteins with intrinsically disordered prion like domains (PLDs) and RNA binding domains (RBDs). Surprisingly, we find that subsaturated solutions are characterized by heterogeneous distributions of clusters comprising tens to hundreds of molecules. These clusters also include low abundance mesoscale species that are several hundreds of nanometers in diameter. Our results show that cluster formation in subsaturated solutions and phase separation in supersaturated solutions are strongly coupled via sequence-encoded interactions. Interestingly, however, cluster formation and phase separation can be decoupled from one another using solutes that impact the solubilities of phase separating proteins. They can also be decoupled by specific types of mutations. Overall, our findings implicate the presence of distinct, sequence-specific energy scales that contribute to the overall phase behaviors of RNA binding proteins. We discuss our findings in the context of theories of associative polymers. Significance Statement Membraneless biomolecular condensates are molecular communities with distinct compositional preferences and functions. Considerable attention has focused on phase separation as the process that gives rise to condensates. Here, we show that subsaturated solutions of RNA binding proteins form heterogeneous distributions of clusters in subsaturated solutions. The formation of clusters in subsaturated solutions and condensates in supersaturated solution are coupled through sequence-specific interactions. Given the low endogenous concentrations of phase separating proteins, our findings suggest that clusters in subsaturated conditions might be of functional relevance in cells.

https://doi.org/10.1101/2022.02.03.478969

Phase-separating RNA-binding proteins form heterogeneous distributions of clusters in subsaturated solutions

Immune signalling pathways convert pathogenic stimuli into cytosolic events that lead to the resolution of infection. Upon ligand engagement, immune receptors together with their downstream adaptors and effectors undergo substantial conformational changes and spatial reorganization. During this process, nanometre-to-micrometre-sized signalling clusters have been commonly observed that are believed to be hotspots for signal transduction. Because of their large size and heterogeneous composition, it remains a challenge to fully understand the mechanisms by which these signalling clusters form and their functional consequences. Recently, phase separation has emerged as a new biophysical principle for organizing biomolecules into large clusters with fluidic properties. Although the field is still in its infancy, studies of phase separation in immunology are expected to provide new perspectives for understanding immune responses. Here, we present an up-to-date view of how liquid-liquid phase separation drives the formation of signalling condensates and regulates immune signalling pathways, including those downstream of T cell receptor, B cell receptor and the innate immune receptors cyclic GMP-AMP synthase (cGAS)-stimulator of interferon genes (STING) and retinoic acid-inducible gene I protein (RIG-I). We conclude with a summary of the current challenges the field is facing and outstanding questions for future studies.

Phase separation in immune signalling.

Abstract Biomolecular condensates form via coupled associative and segregative phase transitions of multivalent associative macromolecules. Phase separation coupled to percolation is one example of such transitions. Here, we characterize molecular and mesoscale structural descriptions of condensates formed by intrinsically disordered prion-like low complexity domains (PLCDs). These systems conform to sticker-and-spacers architectures. Stickers are cohesive motifs that drive associative interactions through reversible crosslinking and spacers affect the cooperativity of crosslinking and overall macromolecular solubility. Our computations reproduce experimentally measured sequence-specific phase behaviors of PLCDs. Within simulated condensates, networks of reversible inter-sticker crosslinks organize PLCDs into small-world topologies. The overall dimensions of PLCDs vary with spatial location, being most expanded at and preferring to be oriented perpendicular to the interface. Our results demonstrate that even simple condensates with one type of macromolecule feature inhomogeneous spatial organizations of molecules and interfacial features that likely prime them for biochemical activity. 

/pdf/condensates-formed-by-prion-like-low-complexity-domains-have-132dzvzy.pdf

Condensates formed by prion-like low-complexity domains have small-world network structures and interfaces defined by expanded conformations

http://www.cell.com/article/S1097276522006074/pdf

Sequence grammar underlying the unfolding and phase separation of globular proteins

Glycine-rich regions feature prominently in intrinsically disordered regions (IDRs) of proteins that drive phase separation and the regulated formation of membraneless biomolecular condensates. Interestingly, the Gly-rich IDRs seldom feature poly-Gly tracts. The protein fused in sarcoma (FUS) is an exception. This protein includes two 10-residue poly-Gly tracts within the prion-like domain (PLD) and at the interface between the PLD and the RNA binding domain. Poly-Gly tracts are known to be highly insoluble, being potent drivers of self-assembly into solid-like fibrils. Given that the internal concentrations of FUS and FUS-like molecules cross the high micromolar and even millimolar range within condensates, we reasoned that the intrinsic insolubility of poly-Gly tracts might be germane to emergent fluid-to-solid transitions within condensates. To assess this possibility, we characterized the concentration-dependent self-assembly for three non-overlapping 25-residue Gly-rich peptides derived from FUS. Two of the three peptides feature 10-residue poly-Gly tracts. These peptides form either long fibrils based on twisted ribbon-like structures or self-supporting gels based on physical cross-links of fibrils. Conversely, the peptide with similar Gly contents but lacking a poly-Gly tract does not form fibrils or gels. Instead, it remains soluble across a wide range of concentrations. Our findings highlight the ability of poly-Gly tracts within IDRs that drive phase separation to undergo self-assembly. We propose that these tracts are likely to contribute to nucleation of fibrillar solids within dense condensates formed by FUS.

Glycine-Rich Peptides from FUS Have an Intrinsic Ability to Self-Assemble into Fibers and Networked Fibrils

Uncovering non-random binary patterns within sequences of intrinsically disordered proteins

Mechanistic Inferences From Analysis of Measurements of Protein Phase Transitions in Live Cells.

The combination of phase separation and disorder-to-order transitions can give rise to ordered, semi-crystalline fibrillar assemblies that underlie prion phenomena namely, the non-Mendelian transfer of information across cells. Recently, a method known as Distributed Amphifluoric Foerster Resonance Energy Transfer (DAmFRET) was developed to study the convolution of phase separation and disorder-to-order transitions in live cells. In this assay, a protein of interest is expressed to a broad range of concentrations and the acquisition of local density and order, measured by changes in FRET, is used to map phase transitions for different proteins. The high-throughput nature of this assay affords the promise of uncovering sequence-to-phase behavior relationships in live cells. Here, we report the development of a supervised method to obtain automated and accurate classifications of phase transitions quantified using the DAmFRET assay. Systems that we classify as undergoing two-state discontinuous transitions are consistent with prion-like behaviors, although the converse is not always true. We uncover well-established and surprising new sequence features that contribute to two-state phase behavior of prion-like domains. Additionally, our method enables quantitative, comparative assessments of sequence-specific driving forces for phase transitions in live cells. Finally, we demonstrate that a modest augmentation of DAmFRET measurements, specifically time-dependent protein expression profiles, can allow one to apply classical nucleation theory to extract sequence-specific lower bounds on the probability of nucleating ordered assemblies. Taken together, our approaches lead to a useful analysis pipeline that enables the extraction of mechanistic inferences regarding phase transitions in live cells.

https://www.biorxiv.org/content/biorxiv/early/2020/11/05/2020.11.04.369017.full.pdf

Mechanistic inferences from analysis of measurements of protein phase transitions in live cells

Sequence-ensemble relationships of intrinsically disordered proteins (IDPs) are governed by binary patterns such as the linear clustering or mixing of specific residues or residue types with respect to one another. To enable the discovery of potentially important, shared patterns across sequence families, we describe a computational method referred to as NARDINI for Non-random Arrangement of Residues in Disordered Regions Inferred using Numerical Intermixing. This work was partially motivated by the observation that parameters that are currently in use for describing different binary patterns are not interoperable across IDPs of different amino acid compositions and lengths. In NARDINI, we generate an ensemble of scrambled sequences to set up a composition-specific null model for the patterning parameters of interest. We then compute a series of pattern-specific z-scores to quantify how each pattern deviates from a null model for the IDP of interest. The z-scores help in identifying putative non-random linear sequence patterns within an IDP. We demonstrate the use of NARDINI derived z-scores by identifying sequence patterns in three well-studied IDP systems. We also demonstrate how NARDINI can be deployed to study archetypal IDPs across homologs and orthologs. Overall, NARDINI is likely to aid in designing novel IDPs with a view toward engineering new sequence-function relationships or uncovering cryptic ones. We further propose that the z-scores introduced here are likely to be useful for theoretical and computational descriptions of sequence-ensemble relationships across IDPs of different compositions and lengths.

https://www.biorxiv.org/content/biorxiv/early/2021/10/24/2021.08.19.456831.full.pdf

Intrinsically disordered proteins / regions (IDPs / IDRs) pose unique challenges for deriving sequence-function relationships from multiple sequence alignments. These challenges arise from variations in sequence lengths, similarities, and identities across orthologs. Recent computational efforts have demonstrated the utility of comparing large numbers of distinct sequence features as a strategy to identify conserved sequence-function relationships in IDPs / IDRs. Inspired by these efforts, and by biophysical studies that have established the importance of binary patterning features in IDPs / IDRs, we present here a computational method, NARDINI (Non-random Arrangement of Residues in Disordered Regions Inferred using Numerical Intermixing), to uncover truly non-random binary patterns within disordered proteins / regions. Binary patterns refer to the linear clustering or dispersion of specific residues or residue types with respect to all other residues or specific types of residues. Our approach does not use, nor does it require sequence alignments. Instead for each IDR, we generate an ensemble of scrambled sequences and use this to set up expectations from a composition-specific null model for the patterning parameters of interest. We annotate each IDR in terms of pattern-specific z-score matrices by computing how specific patterns deviate from the null model. The z-scores help in identifying the non-random linear sequence patterns within an IDR. We tested the accuracy of NARDINI derived z-scores by assessing the ability to identify sequence patterns that have been identified as determinants of sequence-function relationships in specific IDPs / IDRs.

https://biorxiv.org/content/10.1101/2021.08.19.456831v1.full.pdf

Jared M. Lalmansingh

Papers

Uncovering non-random binary patterns within sequences of intrinsically disordered proteins

Mechanistic Inferences From Analysis of Measurements of Protein Phase Transitions in Live Cells.

Mechanistic inferences from analysis of measurements of protein phase transitions in live cells

Uncovering non-random binary patterns within sequences of intrinsically disordered proteins

Uncovering non-random sequence patterns within intrinsically disordered proteins