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Biology subjects

Donepudi, G.

Publications and source records attributed to Donepudi, G..

2 recordsLinked to original sources

A Multispecies, Modality-Agnostic Scalable In Vivo Mosaic Screening Platform for Therapeutic Target Discovery

Validating therapeutic targets for complex diseases requires investigating gene functions within native tissue architectures rather than reductionist in vitro models. Here we present a modality-agnostic AAV-based in vivo high-throughput screening platform capable of delivering knockouts, gain-of-function, and synthetic miRNA knockdowns directly to cells within the diseased environment. This system scales to hundreds of perturbations and is adaptable to diverse species and organ systems. To translate high-dimensional screen data into therapeutic assessment, we established a curated analysis framework that scores single-cell transcriptomes against human disease-specific molecular signatures. This method enables quantitative ranking of targets across distinct biological domains ranging from structural fibrosis to inflammatory signaling, to narrow in on the therapeutic potential of each intervention. We applied this strategy to screen loss- and gain-of-function libraries in a murine pulmonary fibrosis model and within the spontaneously osteoarthritic joints of aged horses, identifying metabolic, antifibrotic, and immunomodulatory targets. Importantly, our analysis framework successfully predicted functional outcomes in orthogonal human ex vivo tissue models, including soluble collagen reduction in lung slices and glycosaminoglycan restoration in cartilage, thus establishing a powerful paradigm for prioritizing therapeutic targets by uniting human disease signatures with highly multiplexed in vivo functional genomics.

systems biology↗

Data driven refinement of gene expression signatures for enrichment analysis

Gene set enrichment methods measure biological process or pathway activation in gene expression data by testing coordinate up- or down-regulation of pathway members in a ranked list of genes. These methods rely on curated, annotated gene sets whose members coordinate expression is an indicator of a process or state. We therefore developed the Molecular Signatures Database (MSigDB), a collection of expertly annotated gene sets. While using, enhancing, and expanding MSigDB, we have observed that some gene sets can lack coordinate expression, especially those derived from canonical pathways. To address this challenge, we developed gene set refinement (GSR), a data-driven approach leveraging large-scale multi-omics compendia to extract context-specific sets, deconvolve heterogeneity, and reveal multiple downstream signaling. We applied this method to address cancer biology questions, and demonstrated successful, targeted refinement of existing MSigDB gene sets.

bioinformatics↗