RNAPhaSep: a resource of RNAs undergoing phase separation

Bioinformatic approaches of liquid-liquid phase separation in human disease

ABSTRACT

Biomolecular aggregation within cellular environments via liquid-liquid phase separation (LLPS) spontaneously forms droplet-like structures, which play pivotal roles in diverse biological processes. These structures are closely associated with a range of diseases, including neurodegenerative disorders, cancer and infectious diseases, highlighting the significance of understanding LLPS mechanisms for elucidating disease pathogenesis, and exploring potential therapeutic interventions. In this review, we delineate recent advancements in LLPS research, emphasizing its pathological relevance, therapeutic considerations, and the pivotal role of bioinformatic tools and databases in facilitating LLPS investigations. Additionally, we undertook a comprehensive analysis of bioinformatic resources dedicated to LLPS research in order to elucidate their functionality and applicability. By providing comprehensive insights into current LLPS-related bioinformatics resources, this review highlights its implications for human health and disease.

Predicting condensate formation of protein and RNA under various environmental conditions

BACKGROUND

Liquid-liquid phase separation (LLPS) by biomolecules plays a central role in various biological phenomena and has garnered significant attention. The behavior of LLPS is strongly influenced by the characteristics of RNAs and environmental factors such as pH and temperature, as well as the properties of proteins. Recently, several databases recording LLPS-related biomolecules have been established, and prediction models of LLPS-related phenomena have been explored using these databases. However, a prediction model that concurrently considers proteins, RNAs, and experimental conditions has not been developed due to the limited information available from individual experiments in public databases.

RESULTS

To address this challenge, we have constructed a new dataset, RNAPSEC, which serves each experiment as a data point. This dataset was accomplished by manually collecting data from public literature. Utilizing RNAPSEC, we developed two prediction models that consider a protein, RNA, and experimental conditions. The first model can predict the LLPS behavior of a protein and RNA under given experimental conditions. The second model can predict the required conditions for a given protein and RNA to undergo LLPS.

CONCLUSIONS

RNAPSEC and these prediction models are expected to accelerate our understanding of the roles of proteins, RNAs, and environmental factors in LLPS.

Liquid-liquid phase separation-related lncRNA prognostic signature and ZNF32-AS2 as a novel biomarker in hepatocellular carcinoma

BACKGROUND

Liquid-liquid phase separation (LLPS) enhances oncogenic signaling pathways and advances cancer progression, and has been proposed as a promising cancer biomarker and intervention target. Nevertheless, doubts remain about the prognostic importance of LLPS-related long non-coding RNAs (lncRNAs) in hepatocellular carcinoma (HCC).

METHODS

An LLPS-related lncRNA prognostic signature was generated by drivers and regulators of LLPS, and was validated in external datasets. The underlying genetic changes and functional enrichment of the signature were assessed. The drug sensitivity and response to immunotherapy were predicted in patients categorized as high-risk and low-risk. Clinical samples, phase separation agonist, and dispersant were used to identify lncRNAs with the most significant expression change. Cancer cells with ZNF32-AS2 expression regulation were subjected to colony formation assay, scratch test assay, migration and invasion assay, sorafenib resistance assay, and xenograft tumor model.

RESULTS

The signature of LLPS-related hub lncRNAs identified through Weighted Gene Co-Expression Network Analysis showed outstanding performance in training and external validation cohorts consistently, and the molecular characteristics varied between different risk groups. Potential drugs for high-risk individuals were identified, and low-risk individuals demonstrated a more favorable reaction to immunotherapy. ZNF32-AS2 showed the most significant expression change in phase separation agonist and dispersant treatment. ZNF32-AS2 promoted the proliferation, mobility, and sorafenib resistance of liver cancer cells.

CONCLUSIONS

The LLPS-related lncRNA signature may help assess prognosis and predict treatment efficacy in clinical settings. LLPS-related ZNF32-AS2 promoted the proliferation, mobility, and sorafenib resistance of liver cancer cells, and may be a novel potential biomarker in hepatocellular carcinoma.

Liquid-liquid phase separation in Alzheimer's disease

The pathological aggregation and misfolding of tau and amyloid-β play a key role in Alzheimer's disease (AD). However, the underlying pathological mechanisms remain unclear. Emerging evidences indicate that liquid-liquid phase separation (LLPS) has great impacts on regulating human health and diseases, especially neurodegenerative diseases. A series of studies have revealed the significance of LLPS in AD. In this review, we summarize the latest progress of LLPS in AD, focusing on the impact of metal ions, small-molecule inhibitors, and proteinaceous partners on tau LLPS and aggregation, as well as toxic oligomerization, the role of LLPS on amyloid-β (Aβ) aggregation, and the cross-interactions between amyloidogenic proteins in AD. Eventually, the fundamental methods and techniques used in LLPS study are introduced. We expect to present readers a deeper understanding of the relationship between LLPS and AD.

EVLncRNAs 3.0: an updated comprehensive database for manually curated functional long non-coding RNAs validated by low-throughput experiments

Long noncoding RNAs (lncRNAs) have emerged as crucial regulators across diverse biological processes and diseases. While high-throughput sequencing has enabled lncRNA discovery, functional characterization remains limited. The EVLncRNAs database is the first and exclusive repository for all experimentally validated functional lncRNAs from various species. After previous releases in 2018 and 2021, this update marks a major expansion through exhaustive manual curation of nearly 25 000 publications from 15 May 2020, to 15 May 2023. It incorporates substantial growth across all categories: a 154% increase in functional lncRNAs, 160% in associated diseases, 186% in lncRNA-disease associations, 235% in interactions, 138% in structures, 234% in circular RNAs, 235% in resistant lncRNAs and 4724% in exosomal lncRNAs. More importantly, it incorporated additional information include functional classifications, detailed interaction pathways, homologous lncRNAs, lncRNA locations, COVID-19, phase-separation and organoid-related lncRNAs. The web interface was substantially improved for browsing, visualization, and searching. ChatGPT was tested for information extraction and functional overview with its limitation noted. EVLncRNAs 3.0 represents the most extensive curated resource of experimentally validated functional lncRNAs and will serve as an indispensable platform for unravelling emerging lncRNA functions. The updated database is freely available at https://www.sdklab-biophysics-dzu.net/EVLncRNAs3/.

MLOsMetaDB, a meta-database to centralize the information on liquid-liquid phase separation proteins and membraneless organelles

Over the past few years, there has been a focus on proteins that create separate liquid phases in the intracellular liquid environment, known as membraneless organelles (MLOs). These organelles allow for the spatiotemporal associations of macromolecules that dynamically exchange within the cellular milieu. They provide a form of compartmentalization crucial for organizing key functions in many cells. Metabolic processes and signaling pathways in both the cytoplasm and nucleus are among the functions performed by MLOs, which are facilitated by diverse combinations of proteins and nucleic acids. However, disruptions in these liquid-liquid phase separation processes (LLPS) may lead to several diseases, such as neurodegenerative disorders and cancer, among others. To foster the study of this process and MLO function, we present MLOsMetaDB (http://mlos.leloir.org.ar), a comprehensive resource of information on MLO- and LLPS-related proteins. Our database integrates and centralizes available information for every protein involved in MLOs, which is otherwise disseminated across a plethora of different databases. Our manuscript outlines the development and features of MLOsMetaDB, which provides an interactive and user-friendly environment with modern biological visualizations and easy and quick access to proteins based on LLPS role, MLO location, and organisms. In addition, it offers an advanced search for making complex queries to generate customized information. Furthermore, MLOsMetaDB provides evolutionary information by collecting the orthologs of every protein in the same database. Overall, MLOsMetaDB is a valuable resource as a starting point for researchers studying the many processes driven by LLPS proteins and membraneless organelles.

Phase separations in oncogenesis, tumor progressions and metastasis: a glance from hallmarks of cancer

Liquid-liquid phase separation (LLPS) is a novel principle for interpreting precise spatiotemporal coordination in living cells through biomolecular condensate (BMC) formation via dynamic aggregation. LLPS changes individual molecules into membrane-free, droplet-like BMCs with specific functions, which coordinate various cellular activities. The formation and regulation of LLPS are closely associated with oncogenesis, tumor progressions and metastasis, the specific roles and mechanisms of LLPS in tumors still need to be further investigated at present. In this review, we comprehensively summarize the conditions of LLPS and identify mechanisms involved in abnormal LLPS in cancer processes, including tumor growth, metastasis, and angiogenesis from the perspective of cancer hallmarks. We have also reviewed the clinical applications of LLPS in oncologic areas. This systematic summary of dysregulated LLPS from the different dimensions of cancer hallmarks will build a bridge for determining its specific functions to further guide basic research, finding strategies to intervene in LLPS, and developing relevant therapeutic approaches.

Hitting the mark: Localization of mRNA and biomolecular condensates in health and disease

Subcellular mRNA localization is critical to a multitude of biological processes such as development of cellular polarity, embryogenesis, tissue differentiation, protein complex formation, cell migration, and rapid responses to environmental stimuli and synaptic depolarization. Our understanding of the mechanisms of mRNA localization must now be revised to include formation and trafficking of biomolecular condensates, as several biomolecular condensates that transport and localize mRNA have recently been discovered. Disruptions in mRNA localization can have catastrophic effects on developmental processes and biomolecular condensate biology and have been shown to contribute to diverse diseases. A fundamental understanding of mRNA localization is essential to understanding how aberrations in this biology contribute the etiology of numerous cancers though support of cancer cell migration and biomolecular condensate dysregulation, as well as many neurodegenerative diseases, through misregulation of mRNA localization and biomolecular condensate biology. This article is categorized under: RNA Export and Localization > RNA Localization RNA in Disease and Development > RNA in Disease RNA in Disease and Development > RNA in Development.

N6-methyladenosine RNA methylation modulates liquid‒liquid phase separation in plants

Membraneless biomolecular condensates form distinct subcellular compartments that enable a cell to orchestrate numerous biochemical reactions in a spatiotemporal-specific and dynamic manner. Liquid‒liquid phase separation (LLPS) facilitates the formation of membraneless biomolecular condensates, which are crucial for many cellular processes in plants, including embryogenesis, the floral transition, photosynthesis, pathogen defense, and stress responses. The main component required for LLPS is a protein harboring key characteristic features, such as intrinsically disordered regions, low-complexity sequence domains, and prion-like domains. RNA is an additional component involved in LLPS. Increasing evidence indicates that modifications in proteins and RNAs play pivotal roles in LLPS. In particular, recent studies have indicated that N6-methyladenosine (m6A) modification of messenger RNA is crucial for LLPS in plants and animals. In this review, we provide an overview of recent developments in the role of mRNA methylation in LLPS in plant cells. Moreover, we highlight the major challenges in understanding the pivotal roles of RNA modifications and elucidating how m6A marks are interpreted by RNA-binding proteins crucial for LLPS.

Surfactants or scaffolds? RNAs of varying lengths control the thermodynamic stability of condensates differently

Biomolecular condensates, thought to form via liquid-liquid phase separation of intracellular mixtures, are multicomponent systems that can include diverse types of proteins and RNAs. RNA is a critical modulator of RNA-protein condensate stability, as it induces an RNA concentration-dependent reentrant phase transition-increasing stability at low RNA concentrations and decreasing it at high concentrations. Beyond concentration, RNAs inside condensates can be heterogeneous in length, sequence, and structure. Here, we use multiscale simulations to understand how different RNA parameters interact with one another to modulate the properties of RNA-protein condensates. To do so, we perform residue/nucleotide resolution coarse-grained molecular dynamics simulations of multicomponent RNA-protein condensates containing RNAs of different lengths and concentrations, and either FUS or PR25 proteins. Our simulations reveal that RNA length regulates the reentrant phase behavior of RNA-protein condensates: increasing RNA length sensitively rises the maximum value that the critical temperature of the mixture reaches, and the maximum concentration of RNA that the condensate can incorporate before beginning to become unstable. Strikingly, RNAs of different lengths are organized heterogeneously inside condensates, which allows them to enhance condensate stability via two distinct mechanisms: shorter RNA chains accumulate at the condensate's surface acting as natural biomolecular surfactants, while longer RNA chains concentrate inside the core to saturate their bonds and enhance the density of molecular connections in the condensate. Using a patchy particle model, we additionally demonstrate that the combined impact of RNA length and concentration on condensate properties is dictated by the valency, binding affinity, and polymer length of the various biomolecules involved. Our results postulate that diversity on RNA parameters within condensates allows RNAs to increase condensate stability by fulfilling two different criteria: maximizing enthalpic gain and minimizing interfacial free energy; hence, RNA diversity should be considered when assessing the impact of RNA on biomolecular condensates regulation.

Arabidopsis Transcription Regulatory Factor Domain/Domain Interaction Analysis Tool-Liquid/Liquid Phase Separation, Oligomerization, GO Analysis: A Toolkit for Interaction Data-Based Domain Analysis

Although a large number of databases are available for regulatory elements, a bottleneck has been created by the lack of bioinformatics tools to predict the interaction modes of regulatory elements. To reduce this gap, we developed the Arabidopsis Transcription Regulatory Factor Domain/Domain Interaction Analysis Tool-liquid/liquid phase separation (LLPS), oligomerization, GO analysis (ART FOUNDATION-LOG), a useful toolkit for protein-nucleic acid interaction (PNI) and protein-protein interaction (PPI) analysis based on domain-domain interactions (DDIs). LLPS, protein oligomerization, the structural properties of protein domains, and protein modifications are major components in the orchestration of the spatiotemporal dynamics of PPIs and PNIs. Our goal is to integrate PPI/PNI information into the development of a prediction model for identifying important genetic variants in peaches. Our program unified interdatabase relational keys based on protein domains to facilitate inference from the model species. A key advantage of this program lies in the integrated information of related features, such as protein oligomerization, LOG analysis, structural characterizations of domains (e.g., domain linkers, intrinsically disordered regions, DDIs, domain-motif (peptide) interactions, beta sheets, and transmembrane helices), and post-translational modification. We provided simple tests to demonstrate how to use this program, which can be applied to other eukaryotic organisms.

Sequence variations of phase-separating proteins and resources for studying biomolecular condensates

Phase separation (PS) is an important mechanism underlying the formation of biomolecular condensates. Physiological condensates are associated with numerous biological processes, such as transcription, immunity, signaling, and synaptic transmission. Changes in particular amino acids or segments can disturb the protein's phase behavior and interactions with other biomolecules in condensates. It is thus presumed that variations in the phase-separating-prone domains can significantly impact the properties and functions of condensates. The dysfunction of condensates contributes to a number of pathological processes. Pharmacological perturbation of these condensates is proposed as a promising way to restore physiological states. In this review, we characterize the variations observed in PS proteins that lead to aberrant biomolecular compartmentalization. We also showcase recent advancements in bioinformatics of membraneless organelles (MLOs), focusing on available databases useful for screening PS proteins and describing endogenous condensates, guiding researchers to seek the underlying pathogenic mechanisms of biomolecular condensates.

Protein-RNA interactions: from mass spectrometry to drug discovery

Proteins and RNAs are fundamental parts of biological systems, and their interactions affect many essential cellular processes. Therefore, it is crucial to understand at a molecular and at a systems level how proteins and RNAs form complexes and mutually affect their functions. In the present mini-review, we will first provide an overview of different mass spectrometry (MS)-based methods to study the RNA-binding proteome (RBPome), most of which are based on photochemical cross-linking. As we will show, some of these methods are also able to provide higher-resolution information about binding sites, which are important for the structural characterisation of protein-RNA interactions. In addition, classical structural biology techniques such as nuclear magnetic resonance (NMR) spectroscopy and biophysical methods such as electron paramagnetic resonance (EPR) spectroscopy and fluorescence-based methods contribute to a detailed understanding of the interactions between these two classes of biomolecules. We will discuss the relevance of such interactions in the context of the formation of membrane-less organelles (MLOs) by liquid-liquid phase separation (LLPS) processes and their emerging importance as targets for drug discovery.

Liquid-liquid phase separation of protein tau: An emerging process in Alzheimer's disease pathogenesis

Metabolic reactions within cells occur in various isolated compartments with or without borders, the latter being known as membrane-less organelles (MLOs). The MLOs show liquid-like properties and are formed by a process known as liquid-liquid phase separation (LLPS). MLOs contribute to different molecules interactions such as protein-protein, protein-RNA, and RNA-RNA driven by various factors, such as multivalency of intrinsic disorders. MLOs are involved in several cell signaling pathways such as transcription, immune response, and cellular organization. However, disruption of these processes has been found in different pathologies. Recently, it has been demonstrated that protein aggregates, a characteristic of some neurodegenerative diseases, undergo similar phase separation. Tau protein is known as a major neurofibrillary tangles component in Alzheimer's disease (AD). This protein can undergo phase separation to form a MLO known as tau droplet in vitro and in vivo, and this process can be facilitated by several factors, including crowding agents, RNA, and phosphorylation. Tau droplet has been shown to mature into insoluble aggregates suggesting that this process may precede and induce neurodegeneration in AD. Here we review major factors involved in liquid droplet formation within a cell. Additionally, we highlight recent findings concerning tau aggregation following phase separation in AD, along with the potential therapeutic strategies that could be explored in this process against the progression of this pathology.

Molecular Determinants for the Layering and Coarsening of Biological Condensates

Many membraneless organelles, or biological condensates, form through phase separation, and play key roles in signal sensing and transcriptional regulation. While the functional importance of these condensates has inspired many studies to characterize their stability and spatial organization, the underlying principles that dictate these emergent properties are still being uncovered. In this review, we examine recent work on biological condensates, especially multicomponent systems. We focus on connecting molecular factors such as binding energy, valency, and stoichiometry with the interfacial tension, explaining the nontrivial interior organization in many condensates. We further discuss mechanisms that arrest condensate coalescence by lowering the surface tension or introducing kinetic barriers to stabilize the multidroplet state.

RNADisease v4.0: an updated resource of RNA-associated diseases, providing RNA-disease analysis, enrichment and prediction

Numerous studies have shown that RNA plays an important role in the occurrence and development of diseases, and RNA-disease associations are not limited to noncoding RNAs in mammals but also exist for protein-coding RNAs. Furthermore, RNA-associated diseases are found across species including plants and nonmammals. To better analyze diseases at the RNA level and facilitate researchers in exploring the pathogenic mechanism of diseases, we decided to update and change MNDR v3.0 to RNADisease v4.0, a repository for RNA-disease association (http://www.rnadisease.org/ or http://www.rna-society.org/mndr/). Compared to the previous version, new features include: (i) expanded data sources and categories of species, RNA types, and diseases; (ii) the addition of a comprehensive analysis of RNAs from thousands of high-throughput sequencing data of cancer samples and normal samples; (iii) the addition of an RNA-disease enrichment tool and (iv) the addition of four RNA-disease prediction tools. In summary, RNADisease v4.0 provides a comprehensive and concise data resource of RNA-disease associations which contains a total of 3 428 058 RNA-disease entries covering 18 RNA types, 117 species and 4090 diseases to meet the needs of biological research and lay the foundation for future therapeutic applications of diseases.

The 2022 Nucleic Acids Research database issue and the online molecular biology database collection

The 2022 Nucleic Acids Research Database Issue contains 185 papers, including 87 papers reporting on new databases and 85 updates from resources previously published in the Issue. Thirteen additional manuscripts provide updates on databases most recently published elsewhere. Seven new databases focus specifically on COVID-19 and SARS-CoV-2, including SCoV2-MD, the first of the Issue's Breakthrough Articles. Major nucleic acid databases reporting updates include MODOMICS, JASPAR and miRTarBase. The AlphaFold Protein Structure Database, described in the second Breakthrough Article, is the stand-out in the protein section, where the Human Proteoform Atlas and GproteinDb are other notable new arrivals. Updates from DisProt, FuzDB and ELM comprehensively cover disordered proteins. Under the metabolism and signalling section Reactome, ConsensusPathDB, HMDB and CAZy are major returning resources. In microbial and viral genomes taxonomy and systematics are well covered by LPSN, TYGS and GTDB. Genomics resources include Ensembl, Ensembl Genomes and UCSC Genome Browser. Major returning pharmacology resource names include the IUPHAR/BPS guide and the Therapeutic Target Database. New plant databases include PlantGSAD for gene lists and qPTMplants for post-translational modifications. The entire Database Issue is freely available online on the Nucleic Acids Research website (https://academic.oup.com/nar). Our latest update to the NAR online Molecular Biology Database Collection brings the total number of entries to 1645. Following last year's major cleanup, we have updated 317 entries, listing 89 new resources and trimming 80 discontinued URLs. The current release is available at http://www.oxfordjournals.org/nar/database/c/.