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Keshari, V.

Publications and source records attributed to Keshari, V..

2 recordsLinked to original sources

Target-agnostic discovery of Rett Syndrome therapeutics by coupling computational network analysis and CRISPR-enabled in vivo disease modeling

Many neurodevelopmental genetic disorders, such as Rett syndrome, are caused by a single gene mutation but trigger changes in expression and regulation of numerous other genes. This severely impair functions of multiple organs and organ systems beyond the central nervous system (CNS), adding to the challenge of developing broadly effective treatments based on a single drug target. This challenge is further complicated by the lack of sufficiently broad and biologically relevant drug screens, and the inherent complexity in identifying clinically relevant targets responsible for diverse phenotypes. Here, we combined human gene regulatory network-based computational drug prediction with in vivo screening in a population-level diversity, CRISPR-edited, Xenopus laevis tadpole model of Rett syndrome to carry out target-agnostic drug discovery, which rapidly led to the identification of the FDA-approved drug vorinostat as a potential repurposing candidate. Vorinostat broadly improved both CNS and non-CNS (e.g., gastrointestinal, respiratory, inflammatory) abnormalities in a pre-clinical mouse model of Rett syndrome. This is the first Rett syndrome treatment to demonstrate pre-clinical efficacy across multiple organ systems when dosed after the onset of symptoms, and network analysis revealed a putative therapeutic mechanism for its cross-organ normalizing effects based on its impact on acetylation metabolism and post-translational modifications of microtubules. Although traditionally considered an inhibitor of histone deacetylases (HDAC), vorinostat unexpectedly restored protein acetylation across both hypo- and hyperacetylated tissues, suggesting non-HDAC-mediated therapeutic mechanisms supported by proteomic analysis.

neuroscience↗

Enhancers of host immune tolerance to bacterial infection discovered using linked computational and experimental approaches

Current therapeutic strategies against bacterial infections focus on reduction of pathogen load through antibiotics; however, stimulation of host tolerance to infection might offer an alternative approach. Here we used computational transcriptomics and a Xenopus embryo infection model to rapidly discover infection response pathways, identify potential tolerance inducer drugs, and validate their ability to induce broad tolerance. Xenopus embryos exhibit natural tolerance to A. baumanii, K. pneumoniae, S. aureus, and S. pneumoniae bacteria, whereas A. hydrophila and P. aeruginosa produce infection that leads to death. Transcriptional profiling led to definition of a 20-gene signature that allows for discrimination between tolerant and susceptible states, as well as identification of active and passive tolerance responses based on the degree of engagement of gene transcription modulation. Upregulation of metal ion transport and hypoxia pathways reminiscent of responses observed in primate and mouse infection models were identified as tolerance mediators, and drug screening in the susceptible A. hydrophila infection model confirmed that a metal chelator (deferoxamine) and HIF-1 agonist (1,4-DPCA) increase embryo survival despite high pathogen load. These data demonstrate the value of combining the Xenopus embryo infection model with multi-omics analyses for mechanistic discovery and drug repurposing to induce host tolerance to bacterial infection.

immunology↗