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Sequence-encoded and composition-dependent protein-RNA interactions control multiphasic condensate morphologies.

ABSTRACT: Multivalent protein-protein and protein-RNA interactions are the drivers of biological phase separation. Biomolecular condensates typically contain a dense network of multiple proteins and RNAs, and their competing molecular interactions play key roles in regulating the condensate composition and structure. Employing a ternary system comprising of a prion-like polypeptide (PLP), arginine-rich polypeptide (RRP), and RNA, we show that competition between the PLP and RNA for a single shared partner, the RRP, leads to RNA-induced demixing of PLP-RRP condensates into stable coexisting phases-homotypic PLP condensates and heterotypic RRP-RNA condensates. The morphology of these biphasic condensates (non-engulfing/ partial engulfing/ complete engulfing) is determined by the RNA-to-RRP stoichiometry and the hierarchy of intermolecular interactions, providing a glimpse of the broad range of multiphasic patterns that are accessible to these condensates. Our findings provide a minimal set of physical rules that govern the composition and spatial organization of multicomponent and multiphasic biomolecular condensates.

SUBMITTER: Kaur T

PROVIDER: S-EPMC7870978 | biostudies-literature | 2021 Feb

REPOSITORIES: biostudies-literature

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Sequence-encoded and composition-dependent protein-RNA interactions control multiphasic condensate morphologies.

Kaur Taranpreet T Raju Muralikrishna M Alshareedah Ibraheem I Davis Richoo B RB Potoyan Davit A DA Banerjee Priya R PR

Nature communications 20210208 1

Multivalent protein-protein and protein-RNA interactions are the drivers of biological phase separation. Biomolecular condensates typically contain a dense network of multiple proteins and RNAs, and their competing molecular interactions play key roles in regulating the condensate composition and structure. Employing a ternary system comprising of a prion-like polypeptide (PLP), arginine-rich polypeptide (RRP), and RNA, we show that competition between the PLP and RNA for a single shared partner ...[more]

PMID: 33558506

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Project description:BackgroundSequence determines the three-dimensional structure of RNAs, and thereby plays an important role in carrying out various biological functions. RNA duplexes containing Watson-Crick (WC) basepairs, interspersed with non-Watson-Crick basepairs, are the dominant structural unit and form the scaffold for the 3-dimensional structure of RNA. It is therefore crucial to understand the geometric variation in the dinucleotide steps that form the helices. We have carried out a detailed analysis of the dinucleotide steps formed by AU and GC Watson-Crick basepairs in RNA structures (both free and protein bound) and compared the results to that seen in DNA. Further, the effect of protein binding on these steps was examined by comparing steps in free RNA structures with protein bound RNA structures.ResultsCharacteristic sequence dependent geometries are observed for the RR, RY and YR type of dinucleotide steps in RNA. Their geometric parameters show correlated variations that are different from those observed in B-DNA helices. Subtle, but statistically significant differences are seen in roll, slide and average propeller-twist values, between the dinucleotide steps of free RNA and protein bound RNA structures. Many non-canonical cross-strand and intra-strand hydrogen bonds were identified that can stabilise the RNA dinucleotide steps, among which YR steps show presence of many new unreported interactions.ConclusionsOur work provides for the first time a detailed analysis of the conformational preferences exhibited by Watson-Crick basepair containing steps in RNA double helices. Overall, the WC dinucleotide steps show considerable conformational variability. Furthermore, we have identified hydrogen bond interactions in several of the dinucleotide steps that could play a role in determining the preferred geometry, in addition to the intra-basepair hydrogen bonds and stacking interactions. Protein binding affects the conformation of the steps that are in direct contact, as well as allosterically affect the steps that are not in direct physical contact.

Project description:BackgroundRNA-protein interactions (RPIs) play important roles in a wide variety of cellular processes, ranging from transcriptional and post-transcriptional regulation of gene expression to host defense against pathogens. High throughput experiments to identify RNA-protein interactions are beginning to provide valuable information about the complexity of RNA-protein interaction networks, but are expensive and time consuming. Hence, there is a need for reliable computational methods for predicting RNA-protein interactions.ResultsWe propose RPISeq, a family of classifiers for predicting RNA-protein interactions using only sequence information. Given the sequences of an RNA and a protein as input, RPIseq predicts whether or not the RNA-protein pair interact. The RNA sequence is encoded as a normalized vector of its ribonucleotide 4-mer composition, and the protein sequence is encoded as a normalized vector of its 3-mer composition, based on a 7-letter reduced alphabet representation. Two variants of RPISeq are presented: RPISeq-SVM, which uses a Support Vector Machine (SVM) classifier and RPISeq-RF, which uses a Random Forest classifier. On two non-redundant benchmark datasets extracted from the Protein-RNA Interface Database (PRIDB), RPISeq achieved an AUC (Area Under the Receiver Operating Characteristic (ROC) curve) of 0.96 and 0.92. On a third dataset containing only mRNA-protein interactions, the performance of RPISeq was competitive with that of a published method that requires information regarding many different features (e.g., mRNA half-life, GO annotations) of the putative RNA and protein partners. In addition, RPISeq classifiers trained using the PRIDB data correctly predicted the majority (57-99%) of non-coding RNA-protein interactions in NPInter-derived networks from E. coli, S. cerevisiae, D. melanogaster, M. musculus, and H. sapiens.ConclusionsOur experiments with RPISeq demonstrate that RNA-protein interactions can be reliably predicted using only sequence-derived information. RPISeq offers an inexpensive method for computational construction of RNA-protein interaction networks, and should provide useful insights into the function of non-coding RNAs. RPISeq is freely available as a web-based server at http://pridb.gdcb.iastate.edu/RPISeq/.

Dataset Information

Sequence-encoded and composition-dependent protein-RNA interactions control multiphasic condensate morphologies.

Publications

Sequence-encoded and composition-dependent protein-RNA interactions control multiphasic condensate morphologies.

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