Two distinct mechanisms underlie dosage sensitivity in Pumilio1-associated diseases

SUMMARYThe RNA-binding protein (RBP) Pumilio1 (PUM1) is associated with two distinct diseases: a late-onset ataxia and a neurodevelopmental syndrome. The ataxia patients retain 75% of normal PUM1 levels, the syndromic patients ∼50%, but this seems inadequate to explain the difference in phenotypes. We hypothesized that mild disease results from dysregulation of PUM1 targets, whereas severe disease involves disruption of PUM1 complexes and deregulation of shared targets. We therefore developed a PUM1 interactome for the murine brain and found that PUM1 shares targets with several RBP interactors (PUM2, FMRP, AGO2, and RBFOX3). PUM1 haploinsufficiency destabilizes these RBPs to varying degrees by brain region and sex, and alters expression of their shared targets, but the milder disease-causing mutation affects only PUM1-specific targets. These data indicate that dosage-sensitive proteins can produce different phenotypes by different mechanisms, and that there may be more intimate cooperation among RBPs than expected.HIGHLIGHTS•RNA-binding proteins can cause disease via their targets or interactors•Interactions among RNA-binding proteins can differ by brain region and sex•A modest reduction in PUM1 levels affects PUM1-specific targets•Greater reductions in PUM1 levels disrupt interactors and shared targets

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Systematic discovery and functional interrogation of SARS-CoV-2 viral RNA-host protein interactions during infection

10.1101/2020.10.06.327445 ◽

2020 ◽

Cited By ~ 4

Author(s):

Ryan A. Flynn ◽

Julia A. Belk ◽

Yanyan Qi ◽

Yuki Yasumoto ◽

Cameron O. Schmitz ◽

...

Keyword(s):

Protein Interaction ◽

Protein Interactions ◽

Binding Proteins ◽

Rna Binding ◽

Rna Binding Proteins ◽

Viral Rna ◽

Host Protein ◽

List Type ◽

Genome Wide ◽

A Genome

AbstractSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the cause of a pandemic with growing global mortality. There is an urgent need to understand the molecular pathways required for host infection and anti-viral immunity. Using comprehensive identification of RNA-binding proteins by mass spectrometry (ChIRP-MS), we identified 309 host proteins that bind the SARS-CoV-2 RNA during active infection. Integration of this data with viral ChIRP-MS data from three other positive-sense RNA viruses defined pan-viral and SARS-CoV-2-specific host interactions. Functional interrogation of these factors with a genome-wide CRISPR screen revealed that the vast majority of viral RNA-binding proteins protect the host from virus-induced cell death, and we identified known and novel anti-viral proteins that regulate SARS-CoV-2 pathogenicity. Finally, our RNA-centric approach demonstrated a physical connection between SARS-CoV-2 RNA and host mitochondria, which we validated with functional and electron microscopy data, providing new insights into a more general virus-specific protein logic for mitochondrial interactions. Altogether, these data provide a comprehensive catalogue of SARS-CoV-2 RNA-host protein interactions, which may inform future studies to understand the mechanisms of viral pathogenesis, as well as nominate host pathways that could be targeted for therapeutic benefit.Highlights· ChIRP-MS of SARS-CoV-2 RNA identifies a comprehensive viral RNA-host protein interaction network during infection across two species· Comparison to RNA-protein interaction networks with Zika virus, dengue virus, and rhinovirus identify SARS-CoV-2-specific and pan-viral RNA protein complexes and highlights distinct intracellular trafficking pathways· Intersection of ChIRP-MS and genome-wide CRISPR screens identify novel SARS-CoV-2-binding proteins with pro- and anti-viral function· Viral RNA-RNA and RNA-protein interactions reveal specific SARS-CoV-2-mediated mitochondrial dysfunction during infection

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Egg activation triggers clearance of maternally deposited RNA binding proteins

10.1101/806968 ◽

2019 ◽

Author(s):

Michael Zavortink ◽

Lauren N. Rutt ◽

Svetlana Dzitoyeva ◽

Chloe Barrington ◽

Danielle Y. Bilodeau ◽

...

Keyword(s):

Binding Proteins ◽

Rna Binding ◽

Rna Binding Proteins ◽

Ubiquitin Proteasome System ◽

Egg Activation ◽

List Type ◽

Maternal Genome ◽

Ubiquitin Conjugating Enzyme ◽

Ubiquitin Proteasome ◽

Conjugating Enzyme

SUMMARYThe maternal-to-zygotic transition (MZT) is a conserved step in animal development, where control is passed from the maternal genome to the zygotic one. Although the MZT is typically considered from its impact on the transcriptome, we previously found that three maternally deposited Drosophila RNA binding proteins (ME31B, Trailer Hitch [TRAL], and Cup) are also cleared during the MZT by unknown mechanisms. Here, we show that these proteins are degraded by the ubiquitin-proteasome system. Kondo, an E2 conjugating enzyme, and the E3 CTLH ligase are required for the destruction of ME31B, TRAL, and Cup. Importantly, despite occurring hours earlier, egg activation establishes the timer for clearance of these proteins by activating the Pan Gu kinase, which in turn stimulates translation of Kondo mRNA. In other words, egg activation triggers a series of regulatory events that culminate in the degradation of maternally deposited RNA binding proteins several hours later. Clearance of the maternal protein dowry thus appears to be a coordinated, but as-yet underappreciated, aspect of the MZT.HIGHLIGHTSDegradation of ME31B requires the PNG kinase, but not fertilizationThe ubiquitin-proteasome system degrades ME31B via CTLH E3 ligase and the UBC-E2H/Kondo ubiquitin-conjugating enzymeThe association of ME31B with the CTLH complex does not require PNG activityPNG kinase mediates the translational upregulation of Kondo at egg activation

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DeepCLIP: Predicting the effect of mutations on protein-RNA binding with Deep Learning

10.1101/757062 ◽

2019 ◽

Cited By ~ 1

Author(s):

Alexander Gulliver Bjørnholt Grønning ◽

Thomas Koed Doktor ◽

Simon Jonas Larsen ◽

Ulrika Simone Spangsberg Petersen ◽

Lise Lolle Holm ◽

...

Keyword(s):

Deep Learning ◽

Protein Binding ◽

Binding Sites ◽

Antisense Oligonucleotides ◽

Binding Proteins ◽

Rna Binding ◽

Rna Binding Proteins ◽

List Type ◽

Link Type ◽

Sequence Variations

ABSTRACTNucleotide variants can cause functional changes by altering protein-RNA binding in various ways that are not easy to predict. This can affect processes such as splicing, nuclear shuttling, and stability of the transcript. Therefore, correct modelling of protein-RNA binding is critical when predicting the effects of sequence variations. Many RNA-binding proteins recognize a diverse set of motifs and binding is typically also dependent on the genomic context, making this task particularly challenging. Here, we present DeepCLIP, the first method for context-aware modeling and predicting protein binding to nucleic acids using exclusively sequence data as input. We show that DeepCLIP outperforms existing methods for modelling RNA-protein binding. Importantly, we demonstrate that DeepCLIP is able to reliably predict the functional effects of contextually dependent nucleotide variants in independent wet lab experiments. Furthermore, we show how DeepCLIP binding profiles can be used in the design of therapeutically relevant antisense oligonucleotides, and to uncover possible position-dependent regulation in a tissue-specific manner. DeepCLIP can be freely used at http://deepclip.compbio.sdu.dk.HighlightsWe have designed DeepCLIP as a simple neural network that requires only CLIP binding sites as input. The architecture and parameter settings of DeepCLIP makes it an efficient classifier and robust to train, making high performing models easy to train and recreate.Using an extensive benchmark dataset, we demonstrate that DeepCLIP outperforms existing tools in classification. Furthermore, DeepCLIP provides direct information about the neural network’s decision process through visualization of binding motifs and a binding profile that directly indicates sequence elements contributing to the classification.To show that DeepCLIP models generalize to different datasets we have demonstrated that predictions correlate with in vivo and in vitro experiments using quantitative binding assays and minigenes.Identifying the binding sites for regulatory RNA-binding proteins is fundamental for efficient design of (therapeutic) antisense oligonucleotides. Employing a reported disease associated mutation, we demonstrate that DeepCLIP can be used for design of therapeutic antisense oligonucleotides that block regions important for binding of regulatory proteins and correct aberrant splicing.Using DeepCLIP binding profiles, we uncovered a possible position-dependent mechanism behind the reported tissue-specificity of a group of TDP-43 repressed pseudoexons.We have made DeepCLIP available as an online tool for training and application of proteinRNA binding deep learning models and prediction of the potential effects of clinically detected sequence variations (http://deepclip.compbio.sdu.dk/). We also provide DeepCLIP as a configurable stand-alone program (http://www.github.com/deepclip).

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