Biology subjects

Vaz, B.

Publications and source records attributed to Vaz, B..

7 recordsLinked to original sources

bioRxiv2025

Sequence based prediction of cell type specific microRNA binding and mRNA degradation for therapeutic discovery

MicroRNAs and RNA binding proteins are crucial elements of post-transcriptional gene regulation, which governs the fate of mRNA molecules in the cell. However, the landscape of these regulatory interactions, particularly across different mammalian cell types, remains underexplored. We describe REPRESS, a deep learning model that predicts cell-type-specific microRNA binding and mRNA degradation directly from RNA sequence. REPRESS was trained on AGO2-CLIP, miR-eCLIP and Degradome-Seq data profiling millions of microRNA binding and mRNA degradation sites across multiple cell types in human and mouse. It reveals biology that other state-of-the-art methods did not, such as identifying repressive non-canonical miRNA target sites and decoding the regulatory effects of sequence context and miRNA binding site multiplicity. REPRESS outperforms other advanced methods and neural architectures on a comprehensive suite of seven orthogonal tasks, including identifying genetic variants that affect microRNA binding, predicting out-of-distribution data from massively parallel reporter assays, and predicting canonical and non-canonical miRNA mediated repression. To demonstrate the general utility of REPRESS, we show that it provides insights into novel biology and the design of RNA therapeutics. Code is available at : https://github.com/deepgenomics/repress

genomics↗

bioRxiv2024

Synthesis and pharmacological characterization of UVI3502, a novel cannabinoid receptor 1 (CB1) antagonist/inverse agonist

The endocannabinoid (eCB) system regulates several brain functions and is implicated in neurological disorders. The pharmacological blockade of cannabinoid receptors has a therapeutic potential for various cognitive deficits, but also produces severe psychiatric side effects. Hence, new cannabinoid compounds that potentiate therapeutic effects, while minimizing toxicity, are required. In this study, we synthesized and characterized a novel antagonist/inverse agonist of CB1 receptors. UVI3502 showed affinity for two [3H]CP55,940 binding sites (IC50Hi 0.47 {+/-} 1.94 nM and IC50Lo 1470 {+/-} 1.80 nM). Subsequent binding assays performed in CB1 and CB2 overexpressing membranes determined that the low affinity binding site corresponded to CB1, but the high-affinity binding site of UVI3502 did not correspond to CB2 and the possibility of it corresponding to GPR55 was analyzed. The affinity of UVI3502 for CB1 receptors was further confirmed with neuroanatomical specificity by autoradiography in key brain areas, in which functional [35S]GTP{gamma}S assays demonstrated that UVI3502 behaved as an antagonist/inverse agonist of CB1 receptors, blocking the stimulation evoked by potent cannabinoid receptor agonist CP55,940 and decreasing basal [35S]GTP{gamma}S binding. The in silico characterization of the binding to CB1 receptor through molecular docking and molecular dynamics suggests that this activity is explained by the planar and rigid structure of UVI3502, which is optimal for interactions with the inactive state of the receptor. These results indicate that UVI3502 is a novel antagonist/inverse agonist of CB1 receptors, making it a compelling candidate for pharmacologically blocking cannabinoid receptors in the central nervous system. Significance StatementUVI3502 is a novel antagonist/inverse agonist of CB1 receptors, with almost no affinity for CB2 receptors and an additional high-affinity binding site for a third, cannabinoid-like receptor, potentially GPR55. In relevant brain areas for learning and memory processes with a high expression of CB1, UVI3502 blocks the stimulation evoked by the cannabinoid receptor agonist CP55,940, rendering it as an interesting compound for the pharmacological blockade of cannabinoid receptors in the central nervous system.

pharmacology and toxicology↗

bioRxiv2023

An RNA foundation model enables discovery of disease mechanisms and candidate therapeutics

Accurately modeling and predicting RNA biology has been a long-standing challenge, bearing significant clinical ramifications for variant interpretation and the formulation of tailored therapeutics. We describe a foundation model for RNA biology, "BigRNA", which was trained on thousands of genome-matched datasets to predict tissue-specific RNA expression, splicing, microRNA sites, and RNA binding protein specificity from DNA sequence. Unlike approaches that are restricted to missense variants, BigRNA can identify pathogenic non-coding variant effects across diverse mechanisms, including polyadenylation, exon skipping and intron retention. BigRNA accurately predicted the effects of steric blocking oligonucleotides (SBOs) on increasing the expression of 4 out of 4 genes, and on splicing for 18 out of 18 exons across 14 genes, including those involved in Wilson disease and spinal muscular atrophy. We anticipate that BigRNA and foundation models like it will have widespread applications in the field of personalized RNA therapeutics.

bioinformatics↗

bioRxiv2020

Intercellular telomere transfer extends T cell lifespan

The common view is that T-lymphocytes activate telomerase, a DNA polymerase that extends telomeres at chromosome ends, to delay senescence. We show that independently of telomerase, T cells elongate telomeres by acquiring telomere vesicles from antigen-presenting cells (APCs). Upon contact with T cells, APCs degraded shelterin to donate telomeres, which were cleaved by TZAP, and then transferred in extracellular vesicles (EVs) at the immunological synapse. Telomere vesicles retained the Rad51 recombination factor that enabled them to fuse with T cell chromosomal ends causing an average lengthening of [~]3000 base pairs. Thus, we identify a previously unknown telomere transfer program that supports T cell lifespan.

immunology↗

bioRxiv2020

Transcriptome-Wide Off-Target Effects of Steric-Blocking Oligonucleotides

Steric-blocking oligonucleotides (SBOs) are short, single-stranded nucleic acids designed to modulate gene expression by binding to mRNA and blocking access from cellular machinery such as splicing factors. SBOs have the potential to bind to near-complementary sites in the transcriptome, causing off-target effects. In this study, we used RNA-seq to evaluate the off-target differential splicing events of 81 SBOs and differential expression events of 46 SBOs. Our results suggest that differential splicing events are predominantly hybridization-driven, while differential expression events are more common and driven by other mechanisms. We further evaluated the performance of in silico screens for off-target events, and found an edit distance cutoff of three to result in a sensitivity of 14% and false discovery rate of 99%. A machine learning model incorporating splicing predictions substantially improved the ability to prioritize low edit distance hits, increasing sensitivity from 4% to 26% at a fixed FDR. Despite these large improvements in performance, the approach does not detect the majority of events at a false discovery rate below 99%. Our results suggest that in silico methods are currently of limited use for predicting the off-target effects of SBOs.

molecular biology↗

bioRxiv2020

SPRTN protease and SUMOylation coordinate DNA-protein crosslink repair to prevent genome instability

DNA-protein crosslinks (DPCs) are a specific type of DNA lesions where proteins are covalently attached to DNA. Unrepaired DPCs lead to genomic instability, cancer, neurodegeneration and accelerated ageing. DPC proteolysis was recently discovered as a specialised pathway for DPC repair. The DNA-dependent SPRTN protease and 26S proteasome emerged as as two independent proteolytic systems for DPC repair. DPCs are also repaired by homologous recombination (HR), a canonical DNA repair pathway. While studying the role of ubiquitin and SUMO in DPC repair, we identified mutually exclusive signalling mechanisms associated with DPC repair pathway choice. DPC modification by SUMO-1 favours SPRTN proteolysis as the preferred pathway for DPC repair. DPC SUMOylation counteracts DPC ubiquitination, which promotes DNA breaks and the switch to HR. We propose that modification of DPCs by SUMO-1 promotes SPRTN proteolysis, which is essential for DPC removal to prevent DNA replication defects, chromosomal recombination and genomic instability.

cell biology↗

bioRxiv2018

SPRTN Protease and Checkpoint Kinase 1 Cross-Activation Loop Safeguards DNA Replication

The SPRTN metalloprotease is essential for DNA-protein crosslink (DPC) repair and DNA replication in vertebrate cells. Cells deficient in SPRTN protease activity exhibit severe DPC-induced replication stress and genome instability, manifesting as premature ageing and liver cancer in humans and mice. Strikingly, SPRTN-deficient cells also show a severe G2/M checkpoint defect and fail to activate a robust checkpoint kinase 1 (CHK1) signalling cascade normally triggered in response to replication stress. Here, we show that SPRTN activates the CHK1 signalling cascade during physiological (steady-state) DNA replication by proteolysis-dependent eviction of CHK1 from chromatin. The N-terminal CHK1 fragments cleaved by SPRTN protease still possess kinase activity and phosphorylate SPRTN. This CHK1-dependent phosphorylation stimulates SPRTN recruitment to chromatin to further promote CHK1 eviction from chromatin, DPC removal and unperturbed DNA replication. Our data suggest that a SPRTN-CHK1 cross-activation loop is essential for steady-state DNA replication and protection from DNA replication stress, a major source of genome instability in diseases that cause premature ageing and cancer. In addition, we disclose a mechanism of CHK1 activation during physiological DNA replication, when long stretches of single stranded (ss) DNA that are induced by genotoxic stress and activate canonical and robust CHK1 signalling are not present.

cell biology↗