Biology subjects

Vaikunthan, M.

Publications and source records attributed to Vaikunthan, M..

3 recordsLinked to original sources

bioRxiv2026

A modular transcript enrichment strategy for scalable, atlas-aligned, and clonotype-resolved single-cell transcriptomics

Existing targeted approaches either rely on per-gene barcoded probes and transcript tiling, which limit scalability, or forgo reverse transcription, precluding capture of highly variable transcripts. Here, we present targeted reverse transcription-linker (TRTL), a modular method that can be integrated into existing single-cell transcriptomic workflows to enable targeted readout of user-defined transcript panels, with minimal changes in protocol when scaling from tens to thousands of genes. Because TRTL retains reverse transcription, it also enables the capture of variable transcripts, such as TCR and BCR sequences. Applying TRTL and combinatorial indexing RNA-seq to the mouse brain, we show that carefully designed panels support robust alignment to existing reference atlases, enabling accurate cell type annotation and detection of cellular populations at low sequencing depths. Lastly, we combine TRTL with nuclear hashing-based multiplexing for a targeted-sci-Plex protocol and further demonstrate that targeted-sci-Plex can resolve dynamic T-cell fate trajectories following diverse activating exposures while concurrently profiling T-cell clonotypes.

genomics↗

bioRxiv2026

Mapping kinase-dependent tumor immune adaptation with multiplexed single-cell CRISPR screens

Immune dysfunction in cancer is enacted by multiple programs, including tumor cell-intrinsic responses to distinct immune subpopulations. A subset of these immune evasion programs can be systematically recapitulated through direct tumor-immune interactions in vitro. Here, we present an integrated, high-throughput single-cell CRISPR screening framework focused on the protein kinome for mapping the tumor-intrinsic regulation of T cell-driven immune pressure in glioblastoma (GBM). We combine pooled CRISPR interference and activation (CRISPRi/a) with immune-matched NY-ESO-1 antigen-specific allogeneic GBM-T cell co-culture and massively multiplexed single-cell transcriptomics to systematically quantify how genetic perturbation reshapes baseline tumor state and adaptive responses across graded effector-to-target ratios. We further leverage deep generative models for analyzing pooled CRISPR screens to decipher the effects of genetic perturbations on the mechanisms of tumor resistance. This framework resolves distinct modules of immune evasion and survival, including the regulation of the antigen-presentation machinery, interferon/NF-{kappa}B signaling, oxidative stress resilience, and checkpoint/cytokine programs, while identifying perturbations that reroute the continuous tumor transcriptional trajectory induced by T cell engagement. A secondary chemical screen in patient-derived GBM cultures identified putative kinase targets of immune evasion phenotypes (e.g., EPHA2 and PDGFRA), whose inhibition leads to the blockade of evasive programs and enhances T cell-mediated GBM killing. Together, this workflow provides a scalable blueprint for comprehensive charting of the genetic control of tumor-immune interactions.

genomics↗

bioRxiv2024

A heterogenous pharmaco-transcriptomic landscape induced by targeting a single oncogenic kinase

Over-activation of the epidermal growth factor receptor (EGFR) is a hallmark of glioblastoma. However, EGFR-targeted therapies have led to minimal clinical response. While delivery of EGFR inhibitors (EGFRis) to the brain constitutes a major challenge, how additional drug-specific features alter efficacy remains poorly understood. We introduce SCHEMATIC, which integrates multiplex single-cell chemical transcriptomics with deep-generative classification to resolve chemotype-specific and shared programs and apply it to to define the molecular response of glioblastoma to EGFRis. We identify programs that differ by the chemical properties of EGFRis, including induction of adaptive transcription and modulation of immunogenic gene expression. We find that induction of an adaptive transcriptional program is associated with persistence of surviving cells after EGFR inhibition, and that concurrent EGFR/PI3K inhibition attenuates this program. We also find that pro-immunogenic expression changes associated with a subset of tyrphostin-family EGFR inhibitors are accompanied by enhanced antigen-specific cytotoxic T-cell killing in vitro. Our study provides a framework that considers each agents unique and often unknown poly-pharmacology to prioritize compounds pre-clinically that induce favorable molecular responses.

genomics↗