IU Indianapolis ScholarWorks :: Browsing by Subject "RNA-binding proteins"

Browsing by Subject "RNA-binding proteins"

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Accurate in silico predictions of modified RNA interactions to a prototypical RNA-binding protein with λ-dynamics
(bioRxiv, 2024-12-11) Angelo, Murphy; Bhargava, Yash; Kierzek, Elzbieta; Kierzek, Ryszard; Hayes, Ryan L.; Zhang, Wen; Vilseck, Jonah Z.; Aoki, Scott Takeo; Biochemistry and Molecular Biology, School of Medicine
RNA-binding proteins shape biology through their widespread functions in RNA biochemistry. Their function requires the recognition of specific RNA motifs for targeted binding. These RNA binding elements can be composed of both unmodified and chemically modified RNAs, of which over 170 chemical modifications have been identified in biology. Unmodified RNA sequence preferences for RNA-binding proteins have been widely studied, with numerous methods available to identify their preferred sequence motifs. However, only a few techniques can detect preferred RNA modifications, and no current method can comprehensively screen the vast array of hundreds of natural RNA modifications. Prior work demonstrated that λ-dynamics is an accurate in silico method to predict RNA base binding preferences of an RNA-binding antibody. This work extends that effort by using λ-dynamics to predict unmodified and modified RNA binding preferences of human Pumilio, a prototypical RNA binding protein. A library of RNA modifications was screened at eight nucleotide positions along the RNA to identify modifications predicted to affect Pumilio binding. Computed binding affinities were compared with experimental data to reveal high predictive accuracy. In silico force field accuracies were also evaluated between CHARMM and Amber RNA force fields to determine the best parameter set to use in binding calculations. This work demonstrates that λ-dynamics can predict RNA interactions to a bona fide RNA-binding protein without the requirements of chemical reagents or new methods to experimentally test binding at the bench. Advancing in silico methods like λ-dynamics will unlock new frontiers in understanding how RNA modifications shape RNA biochemistry.
Comparative Analysis of Alternative Splicing Profiles in Th Cell Subsets Reveals Extensive Cell Type–Specific Effects Modulated by a Network of Transcription Factors and RNA-Binding Proteins
(American Association of Immunologists, 2021-09-28) Mir, Quoseena; Lakshmipati, Deepak K.; Ulrich, Benjamin J.; Kaplan, Mark H.; Janga, Sarath Chandra; Biomedical Engineering and Informatics, Luddy School of Informatics, Computing, and Engineering
Alternative splicing (AS) plays an important role in the development of many cell types; however, its contribution to Th subsets has been clearly defined. In this study, we compare mice naive CD4+ Th cells with Th1, Th2, Th17, and T regulatory cells and observed that the majority of AS events were retained intron, followed by skipped-exon events, with at least 1200 genes across cell types affected by AS events. A significant fraction of the AS events, especially retained intron events from the 72-h time point, were no longer observed 2 wk postdifferentiation, suggesting a role for AS in early activation and differentiation via preferential expression of specific isoforms required during T cell activation, but not for differentiation or effector function. Examining the protein consequence of the exon-skipping events revealed an abundance of structural proteins encoding for intrinsically unstructured peptide regions, followed by transmembrane helices, β strands, and polypeptide turn motifs. Analyses of expression profiles of RNA-binding proteins (RBPs) and their cognate binding sites flanking the discovered AS events revealed an enrichment for specific RBP recognition sites in each of the Th subsets. Integration with publicly available chromatin immunoprecipitation sequencing datasets for transcription factors support a model wherein lineage-determining transcription factors impact the RBP profile within the differentiating cells, and this differential expression contributes to AS of the transcriptome via a cascade of cell type-specific posttranscriptional rewiring events.
Dissecting the expression landscape of RNA-binding proteins in human cancers
(2014-01) Kechavarzi, Bobak; Janga, Sarath Chandra
Background RNA-binding proteins (RBPs) play important roles in cellular homeostasis by controlling gene expression at the post-transcriptional level. Results We explore the expression of more than 800 RBPs in sixteen healthy human tissues and their patterns of dysregulation in cancer genomes from The Cancer Genome Atlas project. We show that genes encoding RBPs are consistently and significantly highly expressed compared with other classes of genes, including those encoding regulatory components such as transcription factors, miRNAs and long non-coding RNAs. We also demonstrate that a set of RBPs, numbering approximately 30, are strongly upregulated (SUR) across at least two-thirds of the nine cancers profiled in this study. Analysis of the protein–protein interaction network properties for the SUR and non-SUR groups of RBPs suggests that path length distributions between SUR RBPs is significantly lower than those observed for non-SUR RBPs. We further find that the mean path lengths between SUR RBPs increases in proportion to their contribution to prognostic impact. We also note that RBPs exhibiting higher variability in the extent of dysregulation across breast cancer patients have a higher number of protein–protein interactions. We propose that fluctuating RBP levels might result in an increase in non-specific protein interactions, potentially leading to changes in the functional consequences of RBP binding. Finally, we show that the expression variation of a gene within a patient group is inversely correlated with prognostic impact. Conclusions Overall, our results provide a roadmap for understanding the impact of RBPs on cancer pathogenesis.
Long Non-Coding RNA Expression Levels Modulate Cell-Type-Specific Splicing Patterns by Altering Their Interaction Landscape with RNA-Binding Proteins
(MDPI, 2019-08-06) Porto, Felipe Wendt; Daulatabad, Swapna Vidhur; Janga, Sarath Chandra; BioHealth Informatics, School of Informatics and Computing
Recent developments in our understanding of the interactions between long non-coding RNAs (lncRNAs) and cellular components have improved treatment approaches for various human diseases including cancer, vascular diseases, and neurological diseases. Although investigation of specific lncRNAs revealed their role in the metabolism of cellular RNA, our understanding of their contribution to post-transcriptional regulation is relatively limited. In this study, we explore the role of lncRNAs in modulating alternative splicing and their impact on downstream protein-RNA interaction networks. Analysis of alternative splicing events across 39 lncRNA knockdown and wildtype RNA-sequencing datasets from three human cell lines-HeLa (cervical cancer), K562 (myeloid leukemia), and U87 (glioblastoma)-resulted in the high-confidence (false discovery rate (fdr) < 0.01) identification of 11,630 skipped exon events and 5895 retained intron events, implicating 759 genes to be impacted at the post-transcriptional level due to the loss of lncRNAs. We observed that a majority of the alternatively spliced genes in a lncRNA knockdown were specific to the cell type. In tandem, the functions annotated to the genes affected by alternative splicing across each lncRNA knockdown also displayed cell-type specificity. To understand the mechanism behind this cell-type-specific alternative splicing pattern, we analyzed RNA-binding protein (RBP)-RNA interaction profiles across the spliced regions in order to observe cell-type-specific alternative splice event RBP binding preference. Despite limited RBP binding data across cell lines, alternatively spliced events detected in lncRNA perturbation experiments were associated with RBPs binding in proximal intron-exon junctions in a cell-type-specific manner. The cellular functions affected by alternative splicing were also affected in a cell-type-specific manner. Based on the RBP binding profiles in HeLa and K562 cells, we hypothesize that several lncRNAs are likely to exhibit a sponge effect in disease contexts, resulting in the functional disruption of RBPs and their downstream functions. We propose that such lncRNA sponges can extensively rewire post-transcriptional gene regulatory networks by altering the protein-RNA interaction landscape in a cell-type-specific manner.
MS0621, a novel small-molecule modulator of Ewing sarcoma chromatin accessibility, interacts with an RNA-associated macromolecular complex and influences RNA splicing
(Frontiers Media, 2023-01-30) Vital, Tamara; Wali, Aminah; Butler, Kyle V.; Xiong, Yan; Foster, Joseph P., II; Marcel, Shelsa S.; McFadden, Andrew W.; Nguyen, Valerie U.; Bailey, Benton M.; Lamb, Kelsey N.; James, Lindsey I.; Frye, Stephen V.; Mosely, Amber L.; Jin, Jian; Pattenden, Samantha G.; Davis, Ian J.; Biochemistry and Molecular Biology, School of Medicine
Ewing sarcoma is a cancer of children and young adults characterized by the critical translocation-associated fusion oncoprotein EWSR1::FLI1. EWSR1::FLI1 targets characteristic genetic loci where it mediates aberrant chromatin and the establishment of de novo enhancers. Ewing sarcoma thus provides a model to interrogate mechanisms underlying chromatin dysregulation in tumorigenesis. Previously, we developed a high-throughput chromatin-based screening platform based on the de novo enhancers and demonstrated its utility in identifying small molecules capable of altering chromatin accessibility. Here, we report the identification of MS0621, a molecule with previously uncharacterized mechanism of action, as a small molecule modulator of chromatin state at sites of aberrant chromatin accessibility at EWSR1::FLI1-bound loci. MS0621 suppresses cellular proliferation of Ewing sarcoma cell lines by cell cycle arrest. Proteomic studies demonstrate that MS0621 associates with EWSR1::FLI1, RNA binding and splicing proteins, as well as chromatin regulatory proteins. Surprisingly, interactions with chromatin and many RNA-binding proteins, including EWSR1::FLI1 and its known interactors, were RNA-independent. Our findings suggest that MS0621 affects EWSR1::FLI1-mediated chromatin activity by interacting with and altering the activity of RNA splicing machinery and chromatin modulating factors. Genetic modulation of these proteins similarly inhibits proliferation and alters chromatin in Ewing sarcoma cells. The use of an oncogene-associated chromatin signature as a target allows for a direct approach to screen for unrecognized modulators of epigenetic machinery and provides a framework for using chromatin-based assays for future therapeutic discovery efforts.
Predicting sequence and structural specificities of RNA binding regions recognized by splicing factor SRSF1
(Springer Nature, 2011) Wang, Xin; Juan, Liran; Lv, Junjie; Wang, Kejun; Sanford, Jeremy R.; Liu, Yunlong; Medical and Molecular Genetics, School of Medicine
Background: RNA-binding proteins (RBPs) play diverse roles in eukaryotic RNA processing. Despite their pervasive functions in coding and noncoding RNA biogenesis and regulation, elucidating the sequence specificities that define protein-RNA interactions remains a major challenge. Recently, CLIP-seq (Cross-linking immunoprecipitation followed by high-throughput sequencing) has been successfully implemented to study the transcriptome-wide binding patterns of SRSF1, PTBP1, NOVA and fox2 proteins. These studies either adopted traditional methods like Multiple EM for Motif Elicitation (MEME) to discover the sequence consensus of RBP's binding sites or used Z-score statistics to search for the overrepresented nucleotides of a certain size. We argue that most of these methods are not well-suited for RNA motif identification, as they are unable to incorporate the RNA structural context of protein-RNA interactions, which may affect to binding specificity. Here, we describe a novel model-based approach--RNAMotifModeler to identify the consensus of protein-RNA binding regions by integrating sequence features and RNA secondary structures. Results: As an example, we implemented RNAMotifModeler on SRSF1 (SF2/ASF) CLIP-seq data. The sequence-structural consensus we identified is a purine-rich octamer 'AGAAGAAG' in a highly single-stranded RNA context. The unpaired probabilities, the probabilities of not forming pairs, are significantly higher than negative controls and the flanking sequence surrounding the binding site, indicating that SRSF1 proteins tend to bind on single-stranded RNA. Further statistical evaluations revealed that the second and fifth bases of SRSF1octamer motif have much stronger sequence specificities, but weaker single-strandedness, while the third, fourth, sixth and seventh bases are far more likely to be single-stranded, but have more degenerate sequence specificities. Therefore, we hypothesize that nucleotide specificity and secondary structure play complementary roles during binding site recognition by SRSF1. Conclusion: In this study, we presented a computational model to predict the sequence consensus and optimal RNA secondary structure for protein-RNA binding regions. The successful implementation on SRSF1 CLIP-seq data demonstrates great potential to improve our understanding on the binding specificity of RNA binding proteins.
Rbm15-Mkl1 interacts with the Setd1b histone H3-Lys4 methyltransferase via a SPOC domain that is required for cytokine-independent proliferation
(Public Library of Science, 2012) Lee, Jeong-Heon; Skalnik, David G.; Pediatrics, School of Medicine
The Rbm15-Mkl1 fusion protein is associated with acute megakaryoblastic leukemia (AMKL), although little is known regarding the molecular mechanism(s) whereby this fusion protein contributes to leukemogenesis. Here, we show that both Rbm15 and the leukemogenic Rbm15-Mkl1 fusion protein interact with the Setd1b histone H3-Lys4 methyltransferase (also known as KMT2G). This interaction is direct and requires the Rbm15 SPOC domain and the Setd1b LSD motif. Over-expression of Rbm15-Mkl1 in the 6133 megakaryoblastic leukemia cell line, previously established by expression of the Rbm15-Mkl1 fusion protein in mice (Mercher et al., [2009] J. Clin. Invest. 119, 852-864), leads to decreased levels of endogenous Rbm15 and increased levels of endogenous Mkl1. These cells exhibit enhanced proliferation and cytokine-independent cell growth, which requires an intact Rbm15 SPOC domain that mediates interaction between the Rbm15-Mkl1 fusion protein and the Setd1b methyltransferase. These results reveal altered Setd1b complex function and consequent altered epigenetic regulation as a possible molecular mechanism that mediates the leukemogenic activity of the Rbm15-Mkl1 fusion protein in AMKL.
Seten: a tool for systematic identification and comparison of processes, phenotypes, and diseases associated with RNA-binding proteins from condition-specific CLIP-seq profiles
(Cold Spring Harbor Laboratory Press, 2017-06) Budak, Gungor; Srivastava, Rajneesh; Janga, Sarath Chandra; BioHealth Informatics, School of Informatics and Computing
RNA-binding proteins (RBPs) control the regulation of gene expression in eukaryotic genomes at post-transcriptional level by binding to their cognate RNAs. Although several variants of CLIP (crosslinking and immunoprecipitation) protocols are currently available to study the global protein-RNA interaction landscape at single-nucleotide resolution in a cell, currently there are very few tools that can facilitate understanding and dissecting the functional associations of RBPs from the resulting binding maps. Here, we present Seten, a web-based and command line tool, which can identify and compare processes, phenotypes, and diseases associated with RBPs from condition-specific CLIP-seq profiles. Seten uses BED files resulting from most peak calling algorithms, which include scores reflecting the extent of binding of an RBP on the target transcript, to provide both traditional functional enrichment as well as gene set enrichment results for a number of gene set collections including BioCarta, KEGG, Reactome, Gene Ontology (GO), Human Phenotype Ontology (HPO), and MalaCards Disease Ontology for several organisms including fruit fly, human, mouse, rat, worm, and yeast. It also provides an option to dynamically compare the associated gene sets across data sets as bubble charts, to facilitate comparative analysis. Benchmarking of Seten using eCLIP data for IGF2BP1, SRSF7, and PTBP1 against their corresponding CRISPR RNA-seq in K562 cells as well as randomized negative controls, demonstrated that its gene set enrichment method outperforms functional enrichment, with scores significantly contributing to the discovery of true annotations. Comparative performance analysis using these CRISPR control data sets revealed significantly higher precision and comparable recall to that observed using ChIP-Enrich. Seten's web interface currently provides precomputed results for about 200 CLIP-seq data sets and both command line as well as web interfaces can be used to analyze CLIP-seq data sets. We highlight several examples to show the utility of Seten for rapid profiling of various CLIP-seq data sets.

Browsing by Subject "RNA-binding proteins"

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