Biology subjects

Vijaykumar, B.

Publications and source records attributed to Vijaykumar, B..

5 recordsLinked to original sources

bioRxiv2026

The αβTCR repertoire at scale in the immgenT dataset

The immense T cell receptor (TCR) repertoire is shaped by VDJ combinatorial diversity, imprecise rearrangements, and clonal selection. The immgenT Project generated scRNA and TCRseq to map paired {beta}TCR repertoires across 734 mouse samples from diverse tissues and challenge conditions. Compositional analysis uncovered some extreme junctional architectures. Beyond probabilistic V and J pairing, over-represented joins suggested non-randomness in fine joining, broadening the precedent of quasi-invariant iNKT and MAIT TCRs. We charted public clonotypes linked to self or environmental antigens in the main lineages. Tissue analyses revealed compartmentalized tissue-specific expansions. Unproductive and productive rearrangements of a V gene appeared to interfere specifically with each other, at chromatin or RNA levels. Unexpectedly, allelic exclusion at TCR{beta} proved less stringent than thought, and we identified rearrangements of TCR in immature pre-T stages. This organism-wide look into the TCR repertoire offers novel insights on the evolutionary and immunological pressures on TCR repertoire selection.

immunology↗

bioRxiv2025

REPTRA: Mapping Immune T Cell Receptor Activity from Full Sequences with a Debiased Contrastive Loss

Contrastive learning is amenable to representing the vast space of interaction between highly specific T cell receptors (TCRs) and the epitopes to which they bind, potentially enabling diverse applications in immune engineering. However, progress in mapping TCR-epitope recognition has been limited by skewed datasets and training approaches that may exacerbate biases and obfuscate model performance. Furthermore, most TCR-epitope models represent only one of three complementaritydetermining regions (CDRs) of the TCR, potentially limiting performance. Here, we present a CLIP-style contrastive-learning model for representation of epitopes and T cell receptor activity (REPTRA), incorporating full TCR sequences and trained using a debiased InfoNCE loss. We trained this model on a dataset with over fivefold more epitope diversity than previous reports, collected using the DECODE platform (Repertoire Immune Medicines). We demonstrate resulting improvements in model performance, and ablate the modified loss and TCR representation to demonstrate the contributions of this approach. Furthermore, we apply an interpretability analysis to the REPTRA attention-pooling projection heads to reveal that CDR1 and CDR2, in addition to CDR3, are important for learning TCR-epitope recognition. In doing so, we develop a performant model for contrastive mapping of T cell receptor activity.

immunology↗

bioRxiv2021

A virus-specific monocyte inflammatory phenotype is induced by SARS-CoV2 at the immune-epithelial interface

Infection by SARS-CoV2 provokes a potentially fatal pneumonia with multiorgan failure, and high systemic inflammation. To gain mechanistic insight and ferret out the root of this immune dysregulation, we modeled by in vitro co-culture the interactions between infected epithelial cells and immunocytes. A strong response was induced in monocytes and B cells, with a SARS-CoV2-specific inflammatory gene cluster distinct from that seen in influenza-A or Ebola virus-infected co-cultures, and which reproduced deviations reported in blood or lung myeloid cells from COVID-19 patients. A substantial fraction of the effect could be reproduced after individual transfection of several SARS-CoV2 proteins (Spike and some non-structural proteins), mediated by soluble factors, but not via transcriptional induction. This response was greatly muted in monocytes from healthy children, perhaps a clue to the age-dependency of COVID-19. These results suggest that the inflammatory malfunction in COVID-19 is rooted in the earliest perturbations that SARS-CoV2 induces in epithelia.

immunology↗

bioRxiv2021

Multicellular immune hubs and their organization in MMRd and MMRp colorectal cancer

Immune responses to cancer are highly variable, with mismatch repair-deficient (MMRd) tumors exhibiting more anti-tumor immunity than mismatch repair-proficient (MMRp) tumors. To understand the rules governing these varied responses, we transcriptionally profiled 371,223 cells from colorectal tumors and adjacent normal tissues of 28 MMRp and 34 MMRd patients. Analysis of 88 cell subsets and their 204 associated gene expression programs revealed extensive transcriptional and spatial remodeling across tumors. To discover hubs of interacting malignant and immune cells, we identified expression programs in different cell types that co-varied across patient tumors and used spatial profiling to localize coordinated programs. We discovered a myeloid cell-attracting hub at the tumor-luminal interface associated with tissue damage, and an MMRd-enriched immune hub within the tumor, with activated T cells together with malignant and myeloid cells expressing T-cell-attracting chemokines. By identifying interacting cellular programs, we thus reveal the logic underlying spatially organized immune-malignant cell networks.

cancer biology↗

bioRxiv2020

Profound Treg perturbations correlate with COVID-19 severity

The hallmark of severe COVID-19 disease has been an uncontrolled inflammatory response, resulting from poorly understood immunological dysfunction. We explored the hypothesis that perturbations in FoxP3+ T regulatory cells (Treg), key enforcers of immune homeostasis, contribute to COVID-19 pathology. Cytometric and transcriptomic profiling revealed a distinct Treg phenotype in severe COVID-19 patients, with an increase in both Treg proportions and intracellular levels of the lineage-defining transcription factor FoxP3, which correlated with poor outcomes. Accordingly, these Tregs over-expressed a range of suppressive effectors, but also pro-inflammatory molecules like IL32. Most strikingly, they acquired similarity to tumor-infiltrating Tregs, known to suppress local anti-tumor responses. These traits were most marked in acute patients with severe disease, but persisted somewhat in convalescent patients. These results suggest that Tregs may play nefarious roles in COVID-19, via suppressing anti-viral T cell responses during the severe phase of the disease, and/or via a direct pro-inflammatory role.

immunology↗