Biology subjects

Roden, C.

Publications and source records attributed to Roden, C..

6 recordsLinked to original sources

bioRxiv2024

Biomolecular condensates control and are defined by RNA-RNA interactions that arise in viral replication

Cells must limit RNA-RNA interactions to avoid irreversible RNA entanglement. Cells may prevent deleterious RNA-RNA interactions by genome organization to avoid complementarity however, RNA viruses generate long, perfectly complementary antisense RNA during replication. How do viral RNAs avoid irreversible entanglement? One possibility is RNA sequestration into biomolecular condensates. To test this, we reconstituted critical SARS-CoV-2 RNA-RNA interactions in Nucleocapsid condensates. We observed that RNAs with low propensity RNA-RNA interactions resulted in more round, liquid-like condensates while those with high sequence complementarity resulted in more heterogeneous networked morphology independent of RNA structure stability. Residue-resolution molecular simulations and direct sequencing-based detection of RNA-RNA interactions support that these properties arise from degree of trans RNA contacts. We propose that extensive RNA-RNA interactions in cell and viral replication are controlled via a combination of genome organization, timing, RNA sequence content, RNA production ratios, and emergent biomolecular condensate material properties. Graphical Abstract: SARS-CoV-2 replication cycle employs weak and strong RNA-RNA interactions O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=102 SRC="FIGDIR/small/630161v2_ufig1.gif" ALT="Figure 1000"> View larger version (32K): org.highwire.dtl.DTLVardef@1e75ad7org.highwire.dtl.DTLVardef@1fcda3aorg.highwire.dtl.DTLVardef@15b556eorg.highwire.dtl.DTLVardef@145b3b6_HPS_FORMAT_FIGEXP M_FIG C_FIG

biochemistry↗

bioRxiv2021

Double-stranded RNA drives SARS-CoV-2 nucleocapsid protein to undergo phase separation at specific temperatures

Betacoronavirus SARS-CoV-2 infections caused the global Covid-19 pandemic. The nucleocapsid protein (N-protein) is required for multiple steps in the betacoronavirus replication cycle. SARS-CoV-2-N-protein is known to undergo liquid-liquid phase separation (LLPS) with specific RNAs at particular temperatures to form condensates. We show that N-protein recognizes at least two separate and distinct RNA motifs, both of which require double-stranded RNA (dsRNA) for LLPS. These motifs are separately recognized by N-proteins two RNA binding domains (RBDs). Addition of dsRNA accelerates and modifies N-protein LLPS in vitro and in cells and controls the temperature condensates form. The abundance of dsRNA tunes N-protein-mediated translational repression and may confer a switch from translation to genome packaging. Thus, N-proteins two RBDs interact with separate dsRNA motifs, and these interactions impart distinct droplet properties that can support multiple viral functions. These experiments demonstrate a paradigm of how RNA structure can control the properties of biomolecular condensates.

molecular biology↗

bioRxiv2021

Role of spatial patterning of N-protein interactions in SARS-CoV-2 genome packaging

Viruses must efficiently and specifically package their genomes while excluding cellular nucleic acids and viral sub-genomic fragments. Some viruses use specific packaging signals, which are conserved sequence/structure motifs present only in the full-length genome. Recent work has shown that viral proteins important for packaging can undergo liquid-liquid phase separation (LLPS), where one or two viral nucleic acid binding proteins condense with the genome. The compositional simplicity of viral components lends itself well to theoretical modeling compared to more complex cellular organelles. Viral LLPS can be limited to one or two viral proteins and a single genome that is enriched in LLPS-promoting features. In our previous study, we observed that LLPS-promoting sequences of SARS-CoV-2 are located at the 5' and 3' ends of the genome, whereas the middle of the genome is predicted to consist mostly of solubilizing elements. Is this arrangement sufficient to drive single genome packaging, genome compaction, and genome cyclization? We addressed these questions using a coarse-grained polymer model, LASSI, to study the LLPS of nucleocapsid protein with RNA sequences that either promote LLPS or solubilization. With respect to genome cyclization, we find the most optimal arrangement restricts LLPS-promoting elements to the 5' and 3' ends of the genome, consistent with the native spatial patterning. Genome compaction is enhanced by clustered LLPS-promoting binding sites, while single genome packaging is most efficient when binding sites are distributed throughout the genome. These results suggest that many and variably positioned LLPS-promoting signals can support packaging in the absence of a singular packaging signal which argues against necessity of such a feature. We hypothesize that this model should be generalizable to multiple viruses as well as cellular organelles like paraspeckles, which enrich specific, long RNA sequences in a defined arrangement. Statement of significanceThe COVID-19 pandemic has motivated research of the basic mechanisms of coronavirus replication. A major challenge faced by viruses such as SARS-CoV-2 is the selective packaging of a large genome in a relatively small capsid while excluding host and sub-genomic nucleic acids. Genomic RNA of SARS-CoV-2 can condense with the Nucleocapsid (N-protein), a structural protein component critical for packaging of many viruses. Notably, certain regions of the genomic RNA drive condensation of N-protein while other regions solubilize it. Here, we explore how the spatial patterning of these opposing elements promotes single genome compaction, packaging, and cyclization. This model informs future in silico experiments addressing spatial patterning of genomic features that are experimentally intractable because of the length of the genome.

biophysics↗

bioRxiv2020

Post-transcriptional Regulation is the Major Driver of microRNA Expression Variation

MicroRNA (miRNA) expression patterns are highly variable across human tissues and across cancer specimens. The intuitive assumption is that transcription is the main contributor to mature miRNA expression patterns, with post-transcriptional processes further modifying miRNA expression levels. Here we report the surprising model that, on the global level, post-transcriptional regulation dominates over transcriptional regulation in determining mature miRNA expression patterns in both normal tissues and cancer. Taking advantage of large genomic datasets in which the expression of both mature miRNAs and their host genes have been quantified, we establish and validate transcriptional and post-transcriptional metrics, with miRNA host gene expression estimating transcriptional regulation and mature miRNA to host gene ratio estimating post-transcriptional regulation. On average, the post-transcriptional metric contributes 2.8-fold more than the transcriptional metric to the variance of mature miRNA expression. The variation of the balance between the two mature miRNAs (5p and 3p miRNAs) produced from the same precursor hairpin is a non-negligible contributor to miRNA expression, explaining [~]27% of the variance of miRNAs post-transcriptional metric. Data of normal tissues yield similar results as cancer specimens. Additionally, the post-transcriptional metric is superior to the transcriptional metric in classifying cancer types. We further demonstrate that the post-transcriptional metric separates miRNAs into distinct groups, suggesting that there are groups of miRNAs that are co-regulated on the post-transcriptional level. Our data support a model in which the post-transcriptional regulation is the major driver of miRNA expression variation, and paves a way toward better mechanistic understanding of post-transcriptional regulation of mature miRNA expression.

bioinformatics↗

bioRxiv2019

Regulation of FXR1 by alternative splicing is required for muscle development and controls liquid-like condensates in muscle cells

Fragile-X mental retardation autosomal homolog-1 (FXR1) is a muscle-enriched RNA-binding protein. FXR1 depletion is perinatally lethal in mice, Xenopus, and zebrafish; however, the mechanisms driving these phenotypes remain unclear. The FXR1 gene undergoes alternative splicing, producing multiple protein isoforms and mis-splicing has been implicated in disease. Furthermore, mutations that cause frameshifts in muscle-specific isoforms result in congenital multi-minicore myopathy. We observed that FXR1 alternative splicing is pronounced in the serine and arginine-rich intrinsically-disordered domain; these domains are known to promote biomolecular condensation. Here, we show that tissue-specific splicing of fxr1 is required for Xenopus development and alters the disordered domain of FXR1. FXR1 isoforms vary in the formation of RNA-dependent biomolecular condensates in cells and in vitro. This work shows that regulation of tissue-specific splicing can influence FXR1 condensates in muscle development and how mis-splicing promotes disease.\n\nHIGHLIGHTSO_LIThe muscle-specific exon 15 impacts FXR1 functions\nC_LIO_LIAlternative splicing of FXR1 is tissue- and developmental stage specific\nC_LIO_LIFXR1 forms RNA-dependent condensates\nC_LIO_LISplicing regulation changes FXR1 condensate properties\nC_LI

cell biology↗

bioRxiv2018

Single-cell microRNA/mRNA co-sequencing reveals non-genetic heterogeneity and novel regulatory mechanisms

Co-measurement of multiple omic profiles from the same single cells opens up the opportunity to decode molecular regulation that underlie intercellular heterogeneity in development and disease. Here, we present co-sequencing of microRNAs and mRNAs in the same single cells using a half-cell genomics approach. This method demonstrates good robustness (~95% success rate) and reproducibility (R2=0.93 for both miRNAs and mRNAs), and yields paired half-cell miRNA and mRNA profiles that could be independently validated. Linking the level of miRNAs to the expression of predicted target mRNAs across 19 single cells that are phenotypically identical, we observe that the predicted targets are significantly anti-correlated with the variation of abundantly expressed miRNAs, suggesting that miRNA expression variability alone may lead to non-genetic cell-to-cell heterogeneity. Genome-scale analysis of paired miRNA-mRNA co-profiles further allows us to derive and validate new regulatory relationships of cellular pathways controlling miRNA expression and variability.

systems biology↗