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Elfawy, H.

Publications and source records attributed to Elfawy, H..

2 recordsLinked to original sources

Transcriptomic signature of Human Cardiac Fibroblast in Hypertrophic Obstructive Cardiomyopathy

BackgroundHypertrophic Cardiomyopathy (HCM) is a cardiac disorder characterized by an increased interstitial fibrosis and Extracellular Matrix (ECM) remodeling. Cardiac fibroblasts (CFs) have a crucial role in ECM remodeling as well as influencing contractility. There is accumulating evidence that the phenotype of CFs is disease-specific. Here, we investigate the transcriptome signature of CFs in Hypertrophic obstructive Cardiomyopathy (HOCM) patients and its functional significance. MethodsPrimary CFs were isolated from myectomy specimens of 12 clinically phenotyped HOCM patients and 3 controls. RNA libraries were prepared from cell isolates for whole transcriptome sequencing. Differential expression analysis was conducted using the Tuxedo pipeline. Pathway and Gene Ontology (GO) enrichment were performed using Protein-protein interaction network analysis and functional clustering were performed using Cytoscape StringApp. Expression of candidate genes and proteins was validated using quantitative PCR, Immunocytochemistry, immunohistochemistry, cytokines/chemokines profiling and western blotting, in patient-derived CFs extracts, CFs-conditioned media, and myocardial tissue sections. ResultsWhole transcriptome analysis identified 265 significant differentially expressed genes (DEGs) in HOCM fibroblasts compared to controls. The most significant GO terms identified were associated with ECM organization and inflammatory response. The most significant GO terms identified were associated with ECM organization and inflammatory response, with circos plot analysis further highlighting pathway-specific gene overlap within inflammatory and structural signaling clusters. The DEGs encompassed gene families such as collagens, proteases, fibulins, inflammatory cytokines, integrins and signaling receptors and kinases. MYC was upregulated alongside chemokine ligands and receptors, highlighting a MYC-linked chemokine signaling axis within the inflammatory HOCM-CFs phenotype. The protein expression of selected extracellular Matrix organization and inflammatory response genes confirmed the transcriptome results. ConclusionTranscriptomic profiling of patient-derived HOCM-CFs identified genes and pathways associated with inflammatory signaling, ECM remodeling, and altered cell-cell/matrix communication. These findings show that advanced HOCM-CFs acquire an inflammatory-remodeling phenotype, with ECM genes other than collagens. Novelty and SignificanceO_ST_ABSWhat Is Known?C_ST_ABSO_LIHypertrophic cardiomyopathy is characterized by myocardial hypertrophy, interstitial fibrosis, extracellular matrix remodelling, and inflammatory signalling. C_LIO_LIMost human HCM transcriptomic studies have been performed using whole myocardial tissue, which limits resolution of fibroblast-specific disease programmes. C_LI What New Information Does This Article Contribute?O_LIPatient-derived cardiac fibroblasts from patients with advanced hypertrophic obstructive cardiomyopathy exhibit a distinct transcriptomic signature enriched for inflammatory signalling, extracellular matrix organization, chemokine activity, and altered cell-matrix communication. C_LIO_LIThe HOCM-CF signature is not characterized by uniform collagen gene induction, but by selective ECM remodelling involving fibulins, proteases, integrins, matricellular genes, and downregulation of selected collagen-associated matrix components. C_LIO_LIComparison with bulk myocardial RNA-sequencing and publicly available human cardiomyopathy data supports the biological relevance of the fibroblast-derived signature while highlighting the limited sensitivity of bulk tissue transcriptomics for resolving fibroblast-specific programmes. C_LI What Is the Significance?This study identifies a disease-associated inflammatory and ECM-remodelling state in patient-derived HOCM cardiac fibroblasts. The findings extend the role of cardiac fibroblasts in HOCM beyond classical collagen deposition and suggest that fibroblast-mediated matrix remodelling, cytokine/chemokine signalling, and altered cell-matrix communication may contribute to myocardial remodelling in advanced obstructive disease. These data support the value of fibroblast-focused profiling for uncovering disease-relevant mechanisms that may be masked in whole myocardial tissue analyses and provide candidate pathways for future mechanistic and therapeutic studies.

cell biology↗

Simultaneous single-cell CRISPR, RNA, and ATAC-seq enables multiomic CRISPR screens to identify gene regulatory relationships

The ability to identify gene functions and interactions in specific cellular contexts has been greatly enabled by functional genomics technologies. CRISPR-based genetic screens have proven invaluable in elucidating gene function in mammalian cells. Single-cell functional genomics methods, such as Perturb-seq and Spear-ATAC, have made it possible to achieve high-throughput mapping of the functional effects of gene perturbations by profiling transcriptomes and DNA accessibility, respectively. Combining single-cell chromatin accessibility and transcriptomic data via multiomic approaches has facilitated the discovery of novel cis and gene regulatory interactions. However, pseudobulk readouts from cell populations can often cloud the interpretation of results due to a heterogeneous response from cells receiving the same genetic perturbation, which could be mitigated by using transcriptional profiles of single cells to subset the ATAC-seq data. Existing methods to capture CRISPR guide RNAs to simultaneously assess the impact of genetic perturbations on RNA and ATAC profiles require either cloning of gRNA libraries in specialized vectors or implementing complex protocols with multiple rounds of barcoding. Here, we introduce CAT-ATAC, a technique that adds CRISPR gRNA capture to the existing 10X Genomics Multiome assay, generating paired transcriptome, chromatin accessibility and perturbation identity data from the same individual cells. We demonstrate up to 77% guide capture efficiency for both arrayed and pooled delivery of lentiviral gRNAs in induced pluripotent stem cells (iPSCs) and cancer cell lines. This capability allows us to construct gene regulatory networks (GRNs) in cells under drug and genetic perturbations. By applying CAT-ATAC, we were able to identify a GRN associated with dasatinib resistance, indirectly activated by the HIC2 gene. Using loss of function experiments, we further validated that the gene, ZFPM2, a component of the predicted GRN, also contributes to dasatinib resistance. CAT-ATAC can thus be used to generate high-content multidimensional genotype-phenotype maps to reveal novel gene and cellular interactions and functions.

genomics↗