scholarly journals High-Throughput Translational Profiling with riboPLATE-seq

2019 ◽  
Author(s):  
Jordan B. Metz ◽  
Nicholas J. Hornstein ◽  
Sohani Das Sharma ◽  
Jeremy Worley ◽  
Peter A. Sims
Keyword(s):  
Protein Synthesis ◽  
Protein Kinases ◽  
High Throughput ◽  
Binding Proteins ◽  
Rna Binding ◽  
Rna Binding Proteins ◽  
Library Preparation ◽  
Translational Machinery ◽  
Technological Limitations ◽  
Ribosome Association

ABSTRACTProtein synthesis is dysregulated in many diseases, but we lack a systems-level picture of how signaling molecules and RNA binding proteins interact with the translational machinery, largely due to technological limitations. Here we present riboPLATE-seq, a scalable method for generating paired libraries of ribosome-associated and total mRNA. As an extension of the PLATE-seq protocol, riboPLATE-seq utilizes barcoded primers for pooled library preparation, but additionally leverages rRNA immunoprecipitation on whole polysomes to measure ribosome association (RA). We demonstrate the performance of riboPLATE-seq and its utility in detecting translational alterations induced by inhibition of protein kinases.

scholarly journals Functional characterization of splicing regulatory elements

2021 ◽  
Author(s):  
Scott I Adamson ◽  
Lijun Zhan ◽  
Brenton R Graveley
Keyword(s):  
High Throughput ◽  
Binding Proteins ◽  
Rna Binding ◽  
Rna Binding Proteins ◽  
Functional Characterization ◽  
Regulatory Elements ◽  
Small Subset ◽  
General Sequence ◽  
Splicing Regulators ◽  
Splicing Regulatory Elements

Background: RNA binding protein-RNA interactions mediate a variety of processes including pre-mRNA splicing, translation, decay, polyadenylation and many others. Previous high-throughput studies have characterized general sequence features associated with increased and decreased splicing of certain exons, but these studies are limited by not knowing the mechanisms, and in particular, the mediating RNA binding proteins, underlying these associations. Results: Here we utilize ENCODE data from diverse data modalities to identify functional splicing regulatory elements and their associated RNA binding proteins. We identify features which make splicing events more sensitive to depletion of RNA binding proteins, as well as which RNA binding proteins act as splicing regulators sensitive to depletion. To analyze the sequence determinants underlying RBP-RNA interactions impacting splicing, we assay tens of thousands of sequence variants in a high-throughput splicing reporter called Vex-seq and confirm a small subset in their endogenous loci using CRISPR base editors. Finally, we leverage other large transcriptomic datasets to confirm the importance of RNA binding proteins which we designed experiments around and identify additional RBPs which may act as additional splicing regulators of the exons studied. Conclusions: This study identifies sequence and other features underlying splicing regulation mediated specific RNA binding proteins, as well as validates and identifies other potentially important regulators of splicing in other large transcriptomic datasets.

scholarly journals A Deep Boosting Based Approach for Capturing the Sequence Binding Preferences of RNA-Binding Proteins from High-Throughput CLIP-Seq Data

2016 ◽  
Author(s):  
Shuya Li ◽  
Fanghong Dong ◽  
Yuexin Wu ◽  
Sai Zhang ◽  
Chen Zhang ◽  
...  
Keyword(s):  
High Throughput ◽  
Large Scale ◽  
Binding Proteins ◽  
Rna Binding ◽  
Gene Expression Regulation ◽  
Rna Binding Proteins ◽  
False Negative ◽  
Functional Roles ◽  
Potential Applications ◽  
Validation Tests

AbstractCharacterizing the binding behaviors of RNA-binding proteins (RBPs) is important for understanding their functional roles in gene expression regulation. However, current high-throughput experimental methods for identifying RBP targets, such as CLIP-seq and RNAcompete, usually suffer from the false positive and false negative issues. Here, we develop a deep boosting based machine learning approach, called DeBooster, to accurately model the binding sequence preferences and identify the corresponding binding targets of RBPs from CLIP-seq data. Comprehensive validation tests have shown that DeBooster can outperform other state-of-the-art approaches in predicting RBP targets and recover false negatives that are common in current CLIP-seq data. In addition, we have demonstrated several new potential applications of DeBooster in understanding the regulatory functions of RBPs, including the binding effects of the RNA helicase MOV10 on mRNA degradation, the influence of different binding behaviors of the ADAR proteins on RNA editing, as well as the antagonizing effect of RBP binding on miRNA repression. Moreover, DeBooster may provide an effective index to investigate the effect of pathogenic mutations in RBP binding sites, especially those related to splicing events. We expect that DeBooster will be widely applied to analyze large-scale CLIP-seq experimental data and can provide a practically useful tool for novel biological discoveries in understanding the regulatory mechanisms of RBPs.

scholarly journals High-throughput mutagenesis identifies mutations and RNA binding proteins controlling CD19 splicing and CART-19 therapy resistance

2021 ◽  
Author(s):  
Mariela Cortés-López ◽  
Laura Schulz ◽  
Mihaela Enculescu ◽  
Claudia Paret ◽  
Bea Spiekermann ◽  
...  
Keyword(s):  
High Throughput ◽  
Binding Proteins ◽  
Rna Binding ◽  
Rna Binding Proteins ◽  
Single Point ◽  
Point Mutations ◽  
Therapy Resistance ◽  
Regulatory Elements ◽  
Splice Isoforms ◽  
Exon 2

During CART-19 immunotherapy for B-cell acute lymphoblastic leukaemia (B-ALL), many patients relapse due to loss of the cognate CD19 epitope. Since epitope loss can be caused by aberrant CD19 exon 2 processing, we herein investigate the regulatory code that controls CD19 splicing. We combine high-throughput mutagenesis with mathematical modelling to quantitatively disentangle the effects of all mutations in the region comprising CD19 exons 1-3. Thereupon, we identify ~200 single point mutations that alter CD19 splicing and thus could predispose B-ALL patients to CART-19 resistance. Furthermore, we report almost 100 previously unknown splice isoforms that emerge from cryptic splice sites and likely encode non-functional CD19 proteins. We further identify cis-regulatory elements and trans-acting RNA-binding proteins that control CD19 splicing (e.g., PTBP1 and SF3B4) and validate that loss of these factors leads to enhanced CD19 mis-splicing. Our dataset represents a comprehensive resource for potential prognostic factors predicting success of CART-19 therapy.

Double-stranded RNA-binding Proteins and the Control of Protein Synthesis and Cell Growth

2001 ◽  
Vol 66 (0) ◽  
pp. 485-498 ◽  
Author(s):  
L.M. PARKER ◽  
I. FIERRO-MONTI ◽  
T.W. REICHMAN ◽  
S. GUNNERY ◽  
M.B. MATHEWS
Keyword(s):  
Protein Synthesis ◽  
Cell Growth ◽  
Binding Proteins ◽  
Rna Binding ◽  
Rna Binding Proteins ◽  
Double Stranded Rna

scholarly journals Transcriptome-wide high-throughput mapping of protein–RNA occupancy profiles using POP-seq

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Mansi Srivastava ◽  
Rajneesh Srivastava ◽  
Sarath Chandra Janga
Keyword(s):  
High Throughput ◽  
Binding Proteins ◽  
Rna Binding ◽  
Rna Binding Proteins ◽  
Interaction Network ◽  
K562 Cells ◽  
Genomic Variation ◽  
Interaction Sites ◽  
Protein Occupancy ◽  
Rna Interaction

AbstractInteraction between proteins and RNA is critical for post-transcriptional regulatory processes. Existing high throughput methods based on crosslinking of the protein–RNA complexes and poly-A pull down are reported to contribute to biases and are not readily amenable for identifying interaction sites on non poly-A RNAs. We present Protein Occupancy Profile-Sequencing (POP-seq), a phase separation based method in three versions, one of which does not require crosslinking, thus providing unbiased protein occupancy profiles on whole cell transcriptome without the requirement of poly-A pulldown. Our study demonstrates that ~ 68% of the total POP-seq peaks exhibited an overlap with publicly available protein–RNA interaction profiles of 97 RNA binding proteins (RBPs) in K562 cells. We show that POP-seq variants consistently capture protein–RNA interaction sites across a broad range of genes including on transcripts encoding for transcription factors (TFs), RNA-Binding Proteins (RBPs) and long non-coding RNAs (lncRNAs). POP-seq identified peaks exhibited a significant enrichment (p value < 2.2e−16) for GWAS SNPs, phenotypic, clinically relevant germline as well as somatic variants reported in cancer genomes, suggesting the prevalence of uncharacterized genomic variation in protein occupied sites on RNA. We demonstrate that the abundance of POP-seq peaks increases with an increase in expression of lncRNAs, suggesting that highly expressed lncRNA are likely to act as sponges for RBPs, contributing to the rewiring of protein–RNA interaction network in cancer cells. Overall, our data supports POP-seq as a robust and cost-effective method that could be applied to primary tissues for mapping global protein occupancies.

scholarly journals StoatyDive: Evaluation and classification of peak profiles for sequencing data

GigaScience ◽  
2021 ◽  
Vol 10 (6) ◽  
Author(s):  
Florian Heyl ◽  
Rolf Backofen
Keyword(s):  
Quality Control ◽  
High Throughput ◽  
Binding Sites ◽  
Binding Proteins ◽  
Rna Binding ◽  
Rna Binding Proteins ◽  
Typical Result ◽  
Sequence Motif ◽  
Peak Shape ◽  
Sequencing Data

Abstract Background The prediction of binding sites (peak-calling) is a common task in the data analysis of methods such as cross-linking immunoprecipitation in combination with high-throughput sequencing (CLIP-Seq). The predicted binding sites are often further analyzed to predict sequence motifs or structure patterns. When looking at a typical result of such high-throughput experiments, the obtained peak profiles differ largely on a genomic level. Thus, a tool is missing that evaluates and classifies the predicted peaks on the basis of their shapes. We hereby present StoatyDive, a tool that can be used to filter for specific peak profile shapes of sequencing data such as CLIP. Findings With StoatyDive we are able to classify peak profile shapes from CLIP-seq data of the histone stem-loop-binding protein (SLBP). We compare the results to existing tools and show that StoatyDive finds more distinct peak shape clusters for CLIP data. Furthermore, we present StoatyDive’s capabilities as a quality control tool and as a filter to pick different shapes based on biological or technical questions for other CLIP data from different RNA binding proteins with different biological functions and numbers of RNA recognition motifs. We finally show that proteins involved in splicing, such as RBM22 and U2AF1, have potentially sharper-shaped peaks than other RNA binding proteins. Conclusion StoatyDive finally fills the demand for a peak shape clustering tool for CLIP-Seq data that fine-tunes downstream analysis steps such as structure or sequence motif predictions and that acts as a quality control.

scholarly journals Quantitative Proteomics Links the LRRC59 Interactome to mRNA Translation on the ER Membrane

2020 ◽  
Vol 19 (11) ◽  
pp. 1826-1849
Author(s):  
Molly M. Hannigan ◽  
Alyson M. Hoffman ◽  
J. Will Thompson ◽  
Tianli Zheng ◽  
Christopher V. Nicchitta
Keyword(s):  
Protein Synthesis ◽  
Steady State ◽  
Membrane Protein ◽  
Binding Proteins ◽  
Rna Binding ◽  
Rna Binding Proteins ◽  
Mrna Translation ◽  
Integral Membrane Protein ◽  
Translation Factors ◽  
Er Membrane

Protein synthesis on the endoplasmic reticulum (ER) requires the dynamic coordination of numerous cellular components. Together, resident ER membrane proteins, cytoplasmic translation factors, and both integral membrane and cytosolic RNA-binding proteins operate in concert with membrane-associated ribosomes to facilitate ER-localized translation. Little is known, however, regarding the spatial organization of ER-localized translation. This question is of growing significance as it is now known that ER-bound ribosomes contribute to secretory, integral membrane, and cytosolic protein synthesis alike. To explore this question, we utilized quantitative proximity proteomics to identify neighboring protein networks for the candidate ribosome interactors SEC61β (subunit of the protein translocase), RPN1 (oligosaccharyltransferase subunit), SEC62 (translocation integral membrane protein), and LRRC59 (ribosome binding integral membrane protein). Biotin labeling time course studies of the four BioID reporters revealed distinct labeling patterns that intensified but only modestly diversified as a function of labeling time, suggesting that the ER membrane is organized into discrete protein interaction domains. Whereas SEC61β and RPN1 reporters identified translocon-associated networks, SEC62 and LRRC59 reporters revealed divergent protein interactomes. Notably, the SEC62 interactome is enriched in redox-linked proteins and ER luminal chaperones, with the latter likely representing proximity to an ER luminal chaperone reflux pathway. In contrast, the LRRC59 interactome is highly enriched in SRP pathway components, translation factors, and ER-localized RNA-binding proteins, uncovering a functional link between LRRC59 and mRNA translation regulation. Importantly, analysis of the LRRC59 interactome by native immunoprecipitation identified similar protein and functional enrichments. Moreover, [35S]-methionine incorporation assays revealed that siRNA silencing of LRRC59 expression reduced steady state translation levels on the ER by ca. 50%, and also impacted steady state translation levels in the cytosol compartment. Collectively, these data reveal a functional domain organization for the ER and identify a key role for LRRC59 in the organization and regulation of local translation.

scholarly journals FLASH: ultra-fast protocol to identify RNA–protein interactions in cells

2019 ◽  
Vol 48 (3) ◽  
pp. e15-e15 ◽  
Author(s):  
Ibrahim Avsar Ilik ◽  
Tugce Aktas ◽  
Daniel Maticzka ◽  
Rolf Backofen ◽  
Asifa Akhtar
Keyword(s):  
High Throughput ◽  
Protein Interactions ◽  
Binding Sites ◽  
Binding Proteins ◽  
High Throughput Sequencing ◽  
Rna Binding ◽  
Rna Binding Proteins ◽  
Affinity Purification ◽  
Sequencing Library

Abstract Determination of the in vivo binding sites of RNA-binding proteins (RBPs) is paramount to understanding their function and how they affect different aspects of gene regulation. With hundreds of RNA-binding proteins identified in human cells, a flexible, high-resolution, high-throughput, highly multiplexible and radioactivity-free method to determine their binding sites has not been described to date. Here we report FLASH (Fast Ligation of RNA after some sort of Affinity Purification for High-throughput Sequencing), which uses a special adapter design and an optimized protocol to determine protein–RNA interactions in living cells. The entire FLASH protocol, starting from cells on plates to a sequencing library, takes 1.5 days. We demonstrate the flexibility, speed and versatility of FLASH by using it to determine RNA targets of both tagged and endogenously expressed proteins under diverse conditions in vivo.

scholarly journals Post-transcriptional control of gene expression following stress: the role of RNA-binding proteins

2017 ◽  
Vol 45 (4) ◽  
pp. 1007-1014 ◽  
Author(s):  
Robert Harvey ◽  
Veronica Dezi ◽  
Mariavittoria Pizzinga ◽  
Anne E. Willis
Keyword(s):  
Protein Synthesis ◽  
Mammalian Cells ◽  
Cellular Response ◽  
Transcriptional Control ◽  
Binding Proteins ◽  
Rna Binding ◽  
Rna Binding Proteins ◽  
Major Influence ◽  
Functional Protein ◽  
Control Of Gene Expression

The ability of mammalian cells to modulate global protein synthesis in response to cellular stress is essential for cell survival. While control of protein synthesis is mediated by the regulation of eukaryotic initiation and elongation factors, RNA-binding proteins (RBPs) provide a crucial additional layer to post-transcriptional regulation. RBPs bind specific RNA through conserved RNA-binding domains and ensure that the information contained within the genome and transcribed in the form of RNA is exported to the cytoplasm, chemically modified, and translated prior to folding into a functional protein. Thus, this group of proteins, through mediating translational reprogramming, spatial reorganisation, and chemical modification of RNA molecules, have a major influence on the robust cellular response to external stress and toxic injury.

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