Biology subjects

Rosenbluh, J.

Publications and source records attributed to Rosenbluh, J..

13 recordsLinked to original sources

bioRxiv2025

Structures of tRNA-bound CRISPR-Cas13 reveal universal HEPN RNase mechanisms

Ribonucleases (RNases) are ubiquitous drivers of RNA metabolism across life. Higher eukaryotes and prokaryotes nucleotide-binding (HEPN) domain-containing RNases form a nuclease superfamily whose mechanisms of substrate selection and catalysis remain poorly understood. Here, we report substrate preferences for diverse Cas13 HEPN RNases, revealing precise cleavage of tRNA anticodons and acceptor stems. Using cryo-EM, we present a series of activated Leptotrichia buccalis Cas13a (LbuCas13a) structures engaged with substrate tRNA. We show LbuCas13a captures tRNA through shape- and sequence-specific recognition, cleaving U-rich anticodons independently of tRNA modifications. Leveraging these insights, we reprogram Cas13 specificity and engineer variants with accelerated RNase activity. These findings establish the molecular basis for Cas13 tRNase activity and indicate that the HEPN RNase superfamily obeys universally conserved mechanisms of substrate recognition and catalysis.

biochemistry↗

bioRxiv2025

Single-Cell Pharmacogenomic Landscapes of Epigenetic Therapy in Gastric Cancer

Gene expression signatures ("molecular phenotypes") are extensively utilized in cancer research. To study how gastric cancer (GC) molecular phenotypes are shaped by cell-intrinsic genetic alterations interacting with cell-extrinsic therapeutic pressures, we performed direct capture Perturb-seq (dcPerturb-seq) to interrogate >200 GC-related genes across 4 distinct epigenetic drug classes in multiple gastric lines. We captured 17.7 million pharmocogenomic expression interactions in 625,866 cells representing baseline and post-therapeutic molecular phenotypes. This single-cell pharmacogenomic compendium confirmed previously known gene-driven molecular phenotypes, elucidated poorly characterized genes, and uncovered novel gene dosage-molecular phenotype relationships. Molecular phenotypes in post-therapeutic surviving cells revealed diverse gene perturbation-associated pathways causing convergent drug resistance (EMT plasticity, cell cycle alterations, metabolic reprogramming), highlighting combinatorial strategies for restoring sensitivity. Mapping of in vitro molecular phenotypes to primary human GCs imparted prognostic information and insights into spatial heterogeneity. Comparative analysis of gene perturbations across therapies and lines revealed both conserved and context-specific molecular alterations. Our results illustrate how Perturb-seq approaches can systematically map diverse cancer-associated molecular phenotypes across multiple gene/drug/cell line interactions, yielding translational insights.

cancer biology↗

bioRxiv2025

Generation of two Betacellulin CRISPR-Cas9 knockout hiPSC lines to study affected EGF system paradigm in Schizophrenia

Several members of the epidermal growth factor (EGF) family have been implicated in the biology of schizophrenia (Ketharanathan et al., 2024). The EGF-related ligand, Betacellulin (BTC), plays an important role in the proliferation and differentiation of neural stem cells and our group found markedly reduced BTC levels in patients with schizophrenia. Nevertheless, the interplay of affected BTC and its participation in neural specification and neurodevelopment remains elusive. We generated Knockout (KO) - BTC clones from an existing hiPSC line through CRISPR/Cas9-mediated modification. Furthermore, we validated BTC-KO through genotyping/sequencing, FACS and Western Blot. Finally, we demonstrated trilineage differentiation potential in vitro.

neuroscience↗

bioRxiv2024

Pooled genetic screens identify breast cancer risk genes involved in evasion from T cell-mediated killing

Genome-wide association studies have identified more than 220 loci associated with breast cancer susceptibility. A major challenge is now to identify the effector genes with plausible functions in the context of breast cancer risk. We have previously performed pooled CRISPR screens to identify target genes at risk loci that drive cancer hallmarks including proliferation or modulating DNA damage response. We now extend these screens to identify genes involved in response to cytotoxic T lymphocyte (CTL) killing. We performed knockout and inhibition screens to identify genes that affect the response of the MCF7 human breast cancer cell line to CTL killing in an in vitro co-culture system. We identified 33 candidate risk genes associated with resistance or sensitisation to T cell-mediated killing. Using single gene perturbation, we showed that deletion of candidate risk genes IRF1, ATF7IP, CCDC170 and CASP8 induced resistance, while ablation of CFLAR, CREBBP, and PRMT7 sensitized cells to CTL killing. We used reporter assays to show that the risk-associated alleles at rs736801 and rs3769821 reduced transactivation of the IRF1 and CASP8 promoters, respectively. We showed that pharmacological inhibition of PRMT7 rendered breast cells sensitive to CTL killing and PRMT7 levels were negatively correlated with CD8+ infiltration and patient survival in luminal A breast cancer patient cohorts. Our results demonstrate that phenotypic pooled CRISPR screens are a useful approach for high throughput functional follow-up of GWAS findings, identifying genes which alter immune responses to breast cancer which offer opportunities to enhance immunotherapy.

genetics↗

bioRxiv2024

A basic framework governing splice-site choice in eukaryotes

Changes in splicing are observed between cells, tissues, organs, individuals, and species. These changes can mediate phenotypic variation ranging from flowering time differences in plants to genetic diseases in humans. However, the genomic determinants of splicing variation are largely unknown. Here, we quantified the usage of individual splice-sites and uncover extensive variation between individuals (genotypes) in Arabidopsis, Drosophila and Humans. We used this robust quantitative measure as a phenotype and mapped variation in splice-site usage using Genome-Wide Association Studies (GWAS). By carrying out more than 130,000 GWAS with splice-site usage phenotypes, we reveal genetic variants associated with differential usage of specific splice-sites. Our analysis conclusively shows that most of the common, genetically controlled variation in splicing is cis and there are no major trans hotspots in any of the three analyzed species. High-resolution mapping allowed us to determine genome-wide patterns that govern splice-site choice. We reveal that the variability in the intronic hexamer sequence (GT[N]4 or [N]4AG) differentiates intrinsic splice-site strength and is among the primary determinants of splice-site choice. Experimental analysis validates the primary role for intronic hexamer sequences in conferring splice-site decisions. Transcriptome analyses in diverse species across the tree of life reveals that hexamer rankings explains splice-site choices from yeast to plants to humans, forming the basic framework of the splicing code in eukaryotes.

genetics↗

bioRxiv2024

SRP19 and the protein secretion machinery is a targetable vulnerability in cancers with APC loss

Adenomatous Polyposis Coli (APC) is a tumour suppressor that is frequently lost in colorectal and other cancers. A common mechanism for APC loss includes heterozygous APC deletion. Here, we show that SRP19, is located near APC and is often co-deleted in these tumours. Heterozygous APC/SRP19 loss leads to lower levels of SRP19 mRNA and protein. Consequently, cells with APC/SRP19 loss are vulnerable to partial suppression of SRP19. We show that SRP19 loss is a unique vulnerability since SRP19 is rate limiting for the formation of the Signal Recognition Particle (SRP), a complex that mediates translocation of proteins to the ER. Consistent with these observations, partial SRP19 knock-down or low dose Arsenic Trioxide treatment induces ER stress and inhibits proliferation in APC/SRP19 loss cancers. Our work identifies a new strategy to treat cancers with APC/SRP19 heterozygous deletions and provides a framework for identifying vulnerabilities associated with loss of a tumour suppressor.

cancer biology↗

bioRxiv2024

SAM-DNMT3A, a strategy for induction of genome-wide DNA methylation, identifies DNA methylation as a vulnerability in ER-positive breast cancers

DNA methylation is an epigenetic mark that plays a critical role in regulation of gene expression. DNA methylase (DNMT) inhibitors, inhibit global DNA methylation, and have been a key tool in studies of DNA methylation in healthy or disease conditions. A major bottleneck is the lack of tools to induce global DNA methylation. Here, we engineered a CRISPR based approach, that was initially designed, to enable site specific DNA methylation. Using the synergistic activation mediator (SAM) system, we unexpectedly found that regardless of the targeted sequence any sgRNA induced global genome-wide DNA methylation. We termed this new method SAM-DNMT3A and show that induction of global DNA methylation is a unique vulnerability in ER-positive breast cancer suggesting a therapeutic approach. Our findings highlight the need of caution when using CRISPR based approaches for inducing DNA methylation and demonstrate a new method for global induction of DNA methylation.

genetics↗

bioRxiv2023

CRISPR-Cas13d screens identify KILR a breast cancer risk-associated lncRNA that regulates DNA replication and repair.

Long noncoding RNAs (lncRNAs) have surpassed the number of protein-coding genes, yet the majority have no known function. We previously discovered >800 lncRNAs at regions identified by breast cancer genome-wide association studies (GWAS). Here, we performed a pooled CRISPR-Cas13d RNA knockdown screen to identify which of these lncRNAs altered cell proliferation. We found that KILR, a lncRNA that functions as a tumor suppressor, safeguards breast cells against uncontrolled proliferation. The half-life of KILR is significantly reduced by the risk haplotype, revealing an alternative mechanism by which variants alter cancer risk. We showed that KILR sequesters RPA1, a subunit of the RPA complex, required for DNA replication and repair. Reduced KILR expression promotes cell proliferation by increasing the available pool of RPA1 and the speed of DNA replication. Our findings confirm lncRNAs as mediators of breast cancer risk, emphasize the need to annotate noncoding transcripts in relevant cell types when investigating GWAS variants and provide a scalable platform for mapping phenotypes associated with lncRNAs.

cancer biology↗

bioRxiv2023

Identification of resistance mechanisms to small-molecule inhibition of TEAD-regulated transcription

The Hippo tumour suppressor pathway controls transcription by regulating nuclear abundance of YAP and TAZ, which activate transcription with the TEAD1-TEAD4 DNA-binding proteins. Recently, several small-molecule inhibitors of YAP and TEADs have been reported, with some now entering clinical trials for different cancers. Here, we investigated the cellular response to TEAD palmitoylation inhibitors, using a combination of genomic and genetic strategies. Genome-wide CRISPR/Cas9 screens identified genes that modulate the cellular response to TEAD inhibition, including members of the Hippo, MAPK and JAK-STAT signaling pathways. By exploring gene expression programs of mutant cells, we found that MAPK pathway hyperactivation confers resistance to TEAD inhibition by reinstating expression of a subset of YAP/TEAD target genes. Consistent with this, combined inhibition of TEAD and the MAPK protein MEK, synergistically blocked proliferation of several mesothelioma and lung cancer cell lines and more potently reduced the growth of patient-derived lung cancers in vivo. Collectively, we reveal mechanisms by which cells can overcome small-molecule inhibition of TEADs and potential strategies to enhance the anti-tumor activity of emerging Hippo pathway targeted therapies.

cancer biology↗

bioRxiv2022

Systematic loss of function screens identify pathway specific functional circular RNAs

Circular RNAs (circRNAs) are covalently closed single stranded RNAs that are produced by RNA back-splicing. A small number of circRNAs have been implicated as functional, however, we still lack systematic understanding of cellular processes and signalling pathways that are regulated by circRNAs. A major gap in understanding circRNA function is the ability to define pathways that are regulated by circRNAs. Here, we generated a pooled shRNA library targeting the back-splice junction of 3,354 human circRNAs that are expressed at low to high levels in humans. We used this library for loss of function proliferation screens in a panel of 18 cancer cell lines from four tissue types that harbour mutations leading to constitutive activity of defined pathways. Using this dataset, we identify context specific and non-specific circRNAs. We validated these observations with a secondary screen and uncovered a role for circRERE, a cell essential circRNA that regulates ferroptosis. Furthermore, we characterised the functional roles of pathway-specific circRNA, circSMAD2, a novel regulator of the WNT pathway and circMTO1, a regulator of MAPK signalling in a PTEN dependent manner. Our work sheds light on molecular pathways regulated by circRNAs and provides a catalogue of circRNAs with a measurable function in human cells.

genetics↗

bioRxiv2021

CRISPR screens identify gene targets and drug repositioning opportunities at breast cancer risk loci

Genome-wide association studies (GWAS) have identified >200 loci associated with breast cancer (BC) risk. The majority of candidate causal variants (CCVs) are in non-coding regions and are likely to modulate cancer risk by regulating gene expression. We recently developed a scoring system, INQUISIT, to predict candidate risk genes at BC-risk loci. Here, we used pooled CRISPR activation and suppression screens to validate INQUISIT predictions, and to define the cancer phenotypes they mediate. We measured proliferation in 2D, 3D, and in immune-deficient mice, as well as the effect on the DNA damage response. We performed 60 CRISPR screens and identified 21 high-confidence INQUISIT predictions that mediate a cancer phenotype. We validated the direct regulation of a subset of genes by BC-risk variants using HiCHIP and CRISPRqtl. Furthermore, we show the utility of expression profiling for drug repurposing against these targets. We provide a platform for identifying gene targets of risk variants, and lay a blueprint of interventions for BC risk reduction and treatment.

cancer biology↗

bioRxiv2019

Chromatin interactome mapping at 139 independent breast cancer risk signals

Genome-wide association studies have identified 196 high confidence independent signals associated with breast cancer susceptibility. Variants within these signals frequently fall in distal regulatory DNA elements that control gene expression. We designed a Capture Hi-C array to enrich for chromatin interactions between the credible causal variants and target genes in six human mammary epithelial and breast cancer cell lines. We show that interacting regions are enriched for open chromatin, histone marks for active enhancers and transcription factors relevant to breast biology. We exploit this comprehensive resource to identify candidate target genes at 139 independent breast cancer risk signals, and explore the functional mechanism underlying altered risk at the 12q24 risk region. Our results demonstrate the power of combining genetics, computational genomics and molecular studies to rationalize the identification of key variants and candidate target genes at breast cancer GWAS signals.

molecular biology↗

bioRxiv2017

A unified web platform for network-based analyses of genomic data

Functional genomics networks are widely used to identify unexpected pathway relationships in large genomic datasets. However, it is challenging to quantitatively compare the signal-to-noise ratio of different networks, the biology they describe, and to identify the optimal network to interpret a particular genetic dataset. Via GeNets users can train a machine-learning model (Quack) to make such comparisons; and they can execute, store, and share analyses of genetic and RNA sequencing datasets.

genomics↗