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

Evolution of Virus-like Features and Intrinsically Disordered Regions in Retrotransposon-derived Mammalian Genes

Several mammalian genes have originated from the domestication of retrotransposons, selfish mobile elements related to retroviruses. Some of the proteins encoded by these genes have maintained virus-like features; including self-processing, capsid structure formation, and the generation of different isoforms through -1 programmed ribosomal frameshifting. Using quantitative approaches in molecular evolution and biophysical analyses, we studied 28 retrotransposon-derived genes, with a focus on the evolution of virus-like features. By analyzing the rate of synonymous substitutions, we show that the -1 programmed ribosomal frameshifting mechanism in three of these genes (PEG10, PNMA3, and PNMA5) is conserved across mammals and originates alternative proteins. These genes were targets of positive selection in primates, and one of the positively selected sites affects a B-cell epitope on the spike domain of the PNMA5 capsid, a finding reminiscent of observations in infectious viruses. More generally, we found that retrotransposon-derived proteins vary in their intrinsically disordered region content and this is directly associated with their evolutionary rates. Most positively selected sites in these proteins are located in intrinsically disordered regions and some of them impact protein posttranslational modifications, such as autocleavage and phosphorylation. Detailed analyses of the biophysical properties of intrinsically disordered regions showed that positive selection preferentially targeted regions with lower conformational entropy. Furthermore, positive selection introduces variation in binary sequence patterns across orthologues, as well as in chain compaction. Our results shed light on the evolutionary trajectories of a unique class of mammalian genes and suggest a novel approach to study how intrinsically disordered region biophysical characteristics are affected by evolution.

Bacterial chromatin proteins, transcription, and DNA topology: Inseparable partners in the control of gene expression

DNA in bacterial chromosomes is organized into higher-order structures by DNA-binding proteins called nucleoid-associated proteins (NAPs) or bacterial chromatin proteins (BCPs). BCPs often bind to or near DNA loci transcribed by RNA polymerase (RNAP) and can either increase or decrease gene expression. To understand the mechanisms by which BCPs alter transcription, one must consider both steric effects and the topological forces that arise when DNA deviates from its fully relaxed double-helical structure. Transcribing RNAP creates DNA negative (-) supercoils upstream and positive (+) supercoils downstream whenever RNAP and DNA are unable to rotate freely. This (-) and (+) supercoiling generates topological forces that resist forward translocation of DNA through RNAP unless the supercoiling is constrained by BCPs or relieved by topoisomerases. BCPs also may enhance topological stress and overall can either inhibit or aid transcription. Here, we review current understanding of how RNAP, BCPs, and DNA topology interplay to control gene expression.

Microglial-derived C1q integrates into neuronal ribonucleoprotein complexes and impacts protein homeostasis in the aging brain

Neuroimmune interactions mediate intercellular communication and underlie critical brain functions. Microglia, CNS-resident macrophages, modulate the brain through direct physical interactions and the secretion of molecules. One such secreted factor, the complement protein C1q, contributes to complement-mediated synapse elimination in both developmental and disease models, yet brain C1q protein levels increase significantly throughout aging. Here, we report that C1q interacts with neuronal ribonucleoprotein (RNP) complexes in an age-dependent manner. Purified C1q protein undergoes RNA-dependent liquid-liquid phase separation (LLPS) in vitro, and the interaction of C1q with neuronal RNP complexes in vivo is dependent on RNA and endocytosis. Mice lacking C1q have age-specific alterations in neuronal protein synthesis in vivo and impaired fear memory extinction. Together, our findings reveal a biophysical property of C1q that underlies RNA- and age-dependent neuronal interactions and demonstrate a role of C1q in critical intracellular neuronal processes.

Investigating the Interactions of the Cucumber Mosaic Virus 2b Protein with the Viral 1a Replicase Component and the Cellular RNA Silencing Factor Argonaute 1

The cucumber mosaic virus (CMV) 2b protein is a suppressor of plant defenses and a pathogenicity determinant. Amongst the 2b protein's host targets is the RNA silencing factor Argonaute 1 (AGO1), which it binds to and inhibits. In Arabidopsis thaliana, if 2b-induced inhibition of AGO1 is too efficient, it induces reinforcement of antiviral silencing by AGO2 and triggers increased resistance against aphids, CMV's insect vectors. These effects would be deleterious to CMV replication and transmission, respectively, but are moderated by the CMV 1a protein, which sequesters sufficient 2b protein molecules into P-bodies to prevent excessive inhibition of AGO1. Mutant 2b protein variants were generated, and red and green fluorescent protein fusions were used to investigate subcellular colocalization with AGO1 and the 1a protein. The effects of mutations on complex formation with the 1a protein and AGO1 were investigated using bimolecular fluorescence complementation and co-immunoprecipitation assays. Although we found that residues 56-60 influenced the 2b protein's interactions with the 1a protein and AGO1, it appears unlikely that any single residue or sequence domain is solely responsible. In silico predictions of intrinsic disorder within the 2b protein secondary structure were supported by circular dichroism (CD) but not by nuclear magnetic resonance (NMR) spectroscopy. Intrinsic disorder provides a plausible model to explain the 2b protein's ability to interact with AGO1, the 1a protein, and other factors. However, the reasons for the conflicting conclusions provided by CD and NMR must first be resolved.

Biophysical characterization of high-confidence, small human proteins

Significant efforts have been made to characterize the biophysical properties of proteins. Small proteins have received less attention because their annotation has historically been less reliable. However, recent improvements in sequencing, proteomics, and bioinformatics techniques have led to the high-confidence annotation of small open reading frames (smORFs) that encode for functional proteins, producing smORF-encoded proteins (SEPs). SEPs have been found to perform critical functions in several species, including humans. While significant efforts have been made to annotate SEPs, less attention has been given to the biophysical properties of these proteins. We characterized the distributions of predicted and curated biophysical properties, including sequence composition, structure, localization, function, and disease association of a conservative list of previously identified human SEPs. We found significant differences between SEPs and both larger proteins and control sets. Additionally, we provide an example of how our characterization of biophysical properties can contribute to distinguishing protein-coding smORFs from non-coding ones in otherwise ambiguous cases.

Protein structure-function continuum model: Emerging nexuses between specificity, evolution, and structure

The rationale for replacing the old binary of structure-function with the trinity of structure, disorder, and function has gained considerable ground in recent years. A continuum model based on the expanded form of the existing paradigm can now subsume importance of both conformational flexibility and intrinsic disorder in protein function. The disorder is actually critical for understanding the protein-protein interactions in many regulatory processes, formation of membrane-less organelles, and our revised notions of specificity as amply illustrated by moonlighting proteins. While its importance in formation of amyloids and function of prions is often discussed, the roles of intrinsic disorder in infectious diseases and protein function under extreme conditions are also becoming clear. This review is an attempt to discuss how our current understanding of protein function, specificity, and evolution fit better with the continuum model. This integration of structure and disorder under a single model may bring greater clarity in our continuing quest for understanding proteins and molecular mechanisms of their functionality.

Coiled-coil domains are sufficient to drive liquid-liquid phase separation in protein models

Liquid-liquid phase separation (LLPS) is thought to be a main driving force in the formation of membraneless organelles. Examples of such organelles include the centrosome, central spindle, and stress granules. Recently, it has been shown that coiled-coil (CC) proteins, such as the centrosomal proteins pericentrin, spd-5, and centrosomin, might be capable of LLPS. CC domains have physical features that could make them the drivers of LLPS, but it is unknown if they play a direct role in the process. We developed a coarse-grained simulation framework for investigating the LLPS propensity of CC proteins, in which interactions that support LLPS arise solely from CC domains. We show, using this framework, that the physical features of CC domains are sufficient to drive LLPS of proteins. The framework is specifically designed to investigate how the number of CC domains, as well as the multimerization state of CC domains, can affect LLPS. We show that small model proteins with as few as two CC domains can phase separate. Increasing the number of CC domains up to four per protein can somewhat increase LLPS propensity. We demonstrate that trimer-forming and tetramer-forming CC domains have a dramatically higher LLPS propensity than dimer-forming coils, which shows that multimerization state has a greater effect on LLPS than the number of CC domains per protein. These data support the hypothesis of CC domains as drivers of protein LLPS, and have implications in future studies to identify the LLPS-driving regions of centrosomal and central spindle proteins.

Conformational ensembles of the human intrinsically disordered proteome

Intrinsically disordered proteins and regions (collectively, IDRs) are pervasive across proteomes in all kingdoms of life, help to shape biological functions and are involved in numerous diseases. IDRs populate a diverse set of transiently formed structures and defy conventional sequence-structure-function relationships1. Developments in protein science have made it possible to predict the three-dimensional structures of folded proteins at the proteome scale2. By contrast, there is a lack of knowledge about the conformational properties of IDRs, partly because the sequences of disordered proteins are poorly conserved and also because only a few of these proteins have been characterized experimentally. The inability to predict structural properties of IDRs across the proteome has limited our understanding of the functional roles of IDRs and how evolution shapes them. As a supplement to previous structural studies of individual IDRs3, we developed an efficient molecular model to generate conformational ensembles of IDRs and thereby to predict their conformational properties from sequences4,5. Here we use this model to simulate nearly all of the IDRs in the human proteome. Examining conformational ensembles of 28,058 IDRs, we show how chain compaction is correlated with cellular function and localization. We provide insights into how sequence features relate to chain compaction and, using a machine-learning model trained on our simulation data, show the conservation of conformational properties across orthologues. Our results recapitulate observations from previous studies of individual protein systems and exemplify how to link-at the proteome scale-conformational ensembles with cellular function and localization, amino acid sequence, evolutionary conservation and disease variants. Our freely available database of conformational properties will encourage further experimental investigation and enable the generation of hypotheses about the biological roles and evolution of IDRs.

EphA2 as a phase separation protein associated with ferroptosis and immune cell infiltration in colorectal cancer

Colorectal cancer is one of the most common malignant tumors in the digestive system, and its high incidence and metastasis rate make it a terrible killer that threatens human health. In-depth exploration of the targets affecting the progression of colorectal cancer cells and the development of specific targeted drugs for them are of great significance for the prognosis of colorectal cancer patients. Erythropoietin-producing hepatocellular A2 (EphA2) is a member of the Eph subfamily with tyrosine kinase activity, plays a key role in the regulation of signaling pathways related to the malignant phenotype of various tumor cells, but its specific regulatory mechanism in colorectal cancer needs to be further clarified. Here, we found that EphA2 was abnormally highly expressed in colorectal cancer and that patients with colorectal cancer with high EphA2 expression had a worse prognosis. We also found that EphA2 can form liquid-liquid phase separation condensates on cell membrane, which can be disrupted by ALW-II-41-27, an inhibitor of EphA2. In addition, we found that EphA2 expression in colorectal cancer was positively correlated with the expression of ferroptosis-related genes and the infiltration of multiple immune cells. These findings suggest that EphA2 is a novel membrane protein with phase separation ability and is associated with ferroptosis and immune cell infiltration, which further suggests that malignant progression of colorectal cancer may be inhibited by suppressing the phase separation ability of EphA2.

The variable domain from dynamin-related protein 1 promotes liquid-liquid phase separation that enhances its interaction with cardiolipin-containing membranes

Dynamins are an essential superfamily of mechanoenzymes that remodel membranes and often contain a "variable domain" important for regulation. For the mitochondrial fission dynamin, dynamin-related protein 1, a regulatory role for the variable domain (VD) is demonstrated by gain- and loss-of-function mutations, yet the basis for this is unclear. Here, the isolated VD is shown to be intrinsically disordered and undergo a cooperative transition in the stabilizing osmolyte trimethylamine N-oxide. However, the osmolyte-induced state is not folded and surprisingly appears as a condensed state. Other co-solutes including known molecular crowder Ficoll PM 70, also induce a condensed state. Fluorescence recovery after photobleaching experiments reveal this state to be liquid-like indicating the VD undergoes a liquid-liquid phase separation under crowding conditions. These crowding conditions also enhance binding to cardiolipin, a mitochondrial lipid, which appears to promote phase separation. Since dynamin-related protein 1 is found assembled into discrete punctate structures on the mitochondrial surface, the inference from the present work is that these structures might arise from a condensed state involving the VD that may enable rapid tuning of mechanoenzyme assembly necessary for fission.

Inherently disordered regions of axonemal dynein assembly factors

The dynein-driven beating of cilia is required to move individual cells and to generate fluid flow across surfaces and within cavities. These motor enzymes are highly complex and can contain upwards of 20 different protein components with a total mass approaching 2 MDa. The dynein heavy chains are enormous proteins consisting of ~4500 residues and ribosomes take approximately 15 min to synthesize one. Studies in a broad array of organisms ranging from the green alga Chlamydomonas to humans has identified 19 cytosolic factors (DNAAFs) that are needed to specifically build axonemal dyneins; defects in many of these proteins lead to primary ciliary dyskinesia in mammals which can result in infertility, severe bronchial problems, and situs inversus. How all these factors cooperate in a spatially and temporally regulated manner to promote dynein assembly in cytoplasm remains very uncertain. These DNAAFs contain a variety of well-folded domains many of which provide protein interaction surfaces. However, many also exhibit large regions that are predicted to be inherently disordered. Here I discuss the nature of these unstructured segments, their predicted propensity for driving protein phase separation, and their potential for adopting more defined conformations during the dynein assembly process.

ParSe 2.0: A web tool to identify drivers of protein phase separation at the proteome level

We have developed an algorithm, ParSe, which 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.

Overview Update: Computational Prediction of Intrinsic Disorder in Proteins

There are over 100 computational predictors of intrinsic disorder. These methods predict amino acid-level propensities for disorder directly from protein sequences. The propensities can be used to annotate putative disordered residues and regions. This unit provides a practical and holistic introduction to the sequence-based intrinsic disorder prediction. We define intrinsic disorder, explain the format of computational prediction of disorder, and identify and describe several accurate predictors. We also introduce recently released databases of intrinsic disorder predictions and use an illustrative example to provide insights into how predictions should be interpreted and combined. Lastly, we summarize key experimental methods that can be used to validate computational predictions. © 2023 Wiley Periodicals LLC.

DEPICTER2: a comprehensive webserver for intrinsic disorder and disorder function prediction

Intrinsic disorder in proteins is relatively abundant in nature and essential for a broad spectrum of cellular functions. While disorder can be accurately predicted from protein sequences, as it was empirically demonstrated in recent community-organized assessments, it is rather challenging to collect and compile a comprehensive prediction that covers multiple disorder functions. To this end, we introduce the DEPICTER2 (DisorderEd PredictIon CenTER) webserver that offers convenient access to a curated collection of fast and accurate disorder and disorder function predictors. This server includes a state-of-the-art disorder predictor, flDPnn, and five modern methods that cover all currently predictable disorder functions: disordered linkers and protein, peptide, DNA, RNA and lipid binding. DEPICTER2 allows selection of any combination of the six methods, batch predictions of up to 25 proteins per request and provides interactive visualization of the resulting predictions. The webserver is freely available at http://biomine.cs.vcu.edu/servers/DEPICTER2/.

Biophysical and Integrative Characterization of Protein Intrinsic Disorder as a Prime Target for Drug Discovery

Protein intrinsic disorder is increasingly recognized for its biological and disease-driven functions. However, it represents significant challenges for biophysical studies due to its high conformational flexibility. In addressing these challenges, we highlight the complementary and distinct capabilities of a range of experimental and computational methods and further describe integrative strategies available for combining these techniques. Integrative biophysics methods provide valuable insights into the sequence–structure–function relationship of disordered proteins, setting the stage for protein intrinsic disorder to become a promising target for drug discovery. Finally, we briefly summarize recent advances in the development of new small molecule inhibitors targeting the disordered N-terminal domains of three vital transcription factors.