RPS: a comprehensive database of RNAs involved in liquid-liquid 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.

Phase separation of RNF214 promotes the progression of hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is one of the most common malignant tumors, and the expression and function of an uncharacterized protein RNF214 in HCC are still unknown. Phase separation has recently been observed to participate in the progression of HCC. In this study, we investigated the expression, function, and phase separation of RNF214 in HCC. We found that RNF214 was highly expressed in HCC and associated with poor prognosis. RNF214 functioned as an oncogene to promote the proliferation, migration, and metastasis of HCC. Mechanically, RNF214 underwent phase separation, and the coiled-coil (CC) domain of RNF214 mediated its phase separation. Furthermore, the CC domain was necessary for the oncogenic function of RNF214 in HCC. Taken together, our data favored that phase separation of RNF214 promoted the progression of HCC. RNF214 may be a potential biomarker and therapeutic target for HCC.

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.

Gene expression networks regulated by human personality

Genome-wide association studies of human personality have been carried out, but transcription of the whole genome has not been studied in relation to personality in humans. We collected genome-wide expression profiles of adults to characterize the regulation of expression and function in genes related to human personality. We devised an innovative multi-omic approach to network analysis to identify the key control elements and interactions in multi-modular networks. We identified sets of transcribed genes that were co-expressed in specific brain regions with genes known to be associated with personality. Then we identified the minimum networks for the co-localized genes using bioinformatic resources. Subjects were 459 adults from the Young Finns Study who completed the Temperament and Character Inventory and provided peripheral blood for genomic and transcriptomic analysis. We identified an extrinsic network of 45 regulatory genes from seed genes in brain regions involved in self-regulation of emotional reactivity to extracellular stimuli (e.g., self-regulation of anxiety) and an intrinsic network of 43 regulatory genes from seed genes in brain regions involved in self-regulation of interpretations of meaning (e.g., production of concepts and language). We discovered that interactions between the two networks were coordinated by a control hub of 3 miRNAs and 3 protein-coding genes shared by both. Interactions of the control hub with proteins and ncRNAs identified more than 100 genes that overlap directly with known personality-related genes and more than another 4000 genes that interact indirectly. We conclude that the six-gene hub is the crux of an integrative network that orchestrates information-transfer throughout a multi-modular system of over 4000 genes enriched in liquid-liquid-phase-separation (LLPS)-related RNAs, diverse transcription factors, and hominid-specific miRNAs and lncRNAs. Gene expression networks associated with human personality regulate neuronal plasticity, epigenesis, and adaptive functioning by the interactions of salience and meaning in self-awareness.

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/.

RNA-dependent proteome solubility maintenance in Escherichia coli lysates analysed by quantitative mass spectrometry: Proteomic characterization in terms of isoelectric point, structural disorder, functional hub, and chaperone network

Protein aggregation, a consequence of misfolding and impaired proteostasis, can lead to cellular malfunctions such as various proteinopathies. The mechanisms protecting proteins from aggregation in complex cellular environments have long been investigated, often from a protein-centric viewpoint. However, our study provides insights into a crucial, yet overlooked actor: RNA. We found that depleting RNAs from Escherichia coli lysates induces global protein aggregation. Our quantitative mass spectrometry analysis identified over 900 statistically significant proteins from the Escherichia coli proteome whose solubility depends on RNAs. Proteome-wide characterization showed that the RNA dependency is particularly enriched among acidic proteins, intrinsically disordered proteins, and structural hub proteins. Moreover, we observed distinct differences in RNA-binding mode and Gene Ontology categories between RNA-dependent acidic and basic proteins. Notably, the solubility of key molecular chaperones [Trigger factor, DnaJ, and GroES] is largely dependent on RNAs, suggesting a yet-to-be-explored hierarchical relationship between RNA-based chaperone (termed as chaperna) and protein-based chaperones, both of which constitute the whole chaperone network. These findings provide new insights into the RNA-centric role in maintaining healthy proteome solubility in vivo, where proteins associate with a variety of RNAs, either stably or transiently.

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.

Comprehensive landscape of the miRNA-regulated prognostic marker LAYN with immune infiltration and stemness in pan-cancer

BACKGROUND

COVID-19 has created a significant risk to worldwide public health. According to recent research, C-type lectins may be SARS-CoV-2 receptors. Layilin (LAYN), a broadly expressed integral membrane hyaluronan receptor with a C-type lectin structural domain, is a gene related to cell senescence. There are a few studies on C-type lectins in pan-cancer, and no pan-cancer analysis has been conducted for LAYN.

METHODS

The genotype tissue expression (GTEx) portal and the cancer genome map (TCGA) database were used to collect samples from healthy and cancer patients. Bioinformatics methods are used to construct immune landscape, mutation landscape, and stemness landscape of LAYN. The single-cell sequencing data were used from the CancerSEA website to analyze the functions of LAYN. The prognosis potential of LAYN was discussed based on machine learning.

RESULTS

LAYN is differentially expressed among cancers. Survival analysis indicated that LAYN was related to a poor overall survival (OS) rate in cancers, like HNSC, MESO, and OV. Mutational landscapes of LAYN in SKCM and STAD were constructed. LAYN was negatively related to Tumor Mutation Burden (TMB) in THCA, PRAD, and UCEC, and with the Microsatellite Instability (MSI) in STAD, LUAD, and UCEC. The immune landscape in pan-cancer suggested that LAYN may be involved in tumor immune escape. LAYN plays a crucial role in the infiltration of immune cells in malignant tumors. LAYN participates in methylation modifications and affects tumor proliferation and metastasis by regulating stemness. Analysis of single-cell sequencing data suggests that LAYN may participate in several biological processes, like stemness, apoptosis, and DNA repair. LAYN transcript was predicted as a liquid-liquid phase separation (LLPS)-related RNA. The results of KIRC were verified in the GEO and ArrayExpress databases. Furthermore, prognostic models based on machine learning of LAYN-related genes were established. Hsa-miR-153-5p and hsa-miR-505-3p may be the upstream miRNAs of LAYN and have a high value for tumor prognosis.

CONCLUSION

This study elucidated the functional mechanisms of LAYN from a pan-cancer perspective and provided novel insights into cancer prognosis, metastasis, and immunotherapy. LAYN has the potential to become a new target of mRNA vaccines and molecular therapies in tumors.

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.

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.

Pseudogenes and Liquid Phase Separation in Epigenetic Expression

Pseudogenes have been considered as non-functional genes. However, peptides and long non-coding RNAs produced by pseudogenes are expressed in different tumors. Moreover, the dysregulation of pseudogenes is associated with cancer, and their expressions are higher in tumors compared to normal tissues. Recent studies show that pseudogenes can influence the liquid phase condensates formation. Liquid phase separation involves regulating different epigenetic stages, including transcription, chromatin organization, 3D DNA structure, splicing, and post-transcription modifications like m⁶A. Several membrane-less organelles, formed through the liquid phase separate, are also involved in the epigenetic regulation, and their defects are associated with cancer development. However, the association between pseudogenes and liquid phase separation remains unrevealed. The current study sought to investigate the relationship between pseudogenes and liquid phase separation in cancer development, as well as their therapeutic implications.

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/.