Muehlbauer, A. | bioRxiv Science

bioRxiv2026

Germline-encoded V(D)J gene usage does not impose strict constraints on the epitope-specificity of T cell receptors

The theoretical diversity of T cell receptors (TCRs), generated through V(D)J recombination, is enormous, yet the diversity of TCRs capable of recognizing the same epitope remains unknown. Defining this TCR solution space is essential for uncovering basic principles that govern TCR specificity. Using single-cell RNA and TCR sequencing, we generated ultra-deep (more than 4000 unique TCRs per epitope) epitope-specific TCR libraries derived from 560 immunized C57BL/6 mice, identifying over 27,000 unique epitope-reactive TCRs across three distinct CD8+ T cell epitopes presented by two major histocompatibility complex (MHC) class I alleles. Saturation analyses indicated that the solution space for all studied epitopes comprises many tens of thousands of unique TCRs. Despite highly skewed and peptide-dependent VJ-usage patterns, nearly the entire set of functional germline V/ and J/ segments was detected at least once within each epitope-specific repertoire. Therefore, diversity of epitope-specific TCRs is not limited by distinct germline combinations but rather can emerge from a near-to-complete combinatorial space of - and -chain, V and J segments paired with compatible CDR3 sequences.

immunology↗

bioRxiv2026

Metabolic modeling and functional genomics reveal taxa and host gene interactions in colorectal cancer

Colorectal cancer (CRC) is associated with changes in the microbial communities in the tumor microenvironment. Although metabolic reprogramming is an important feature of host cells in CRC, little is known about metabolic changes in the tumor-associated microbiota and how these microbial metabolic alterations can contribute to disease. Here, we investigated metabolic host-microbiome interactions in CRC using complementary computational and experimental approaches. Using patient-specific in silico metabolic models across three independent datasets, we discovered that Fusobacterium, a cancer-promoting taxon, consistently grows faster in tumor-associated versus normal tissue-associated microbiomes. This finding prompted us to investigate whether host metabolic changes drive these microbial growth advantages. By integrating our metabolic predictions with host transcriptomics data, we identified correlations between tumor gene expression and the growth of CRC-associated taxa (including Porphyromonadaceae, Blautia, and Streptococcus), as well as associations between host genes and microbial metabolism of dietary components (including choline, amino acids, and starch). To test whether these correlations reflect causal relationships, we simulated spent medium experiments in silico, demonstrating that Blautia preferentially grows on metabolites produced by tumor versus normal host cells. We further validated the direct impact of microbes on host metabolism using an in vitro system, where colon cancer cells exposed to human microbiomes showed gene expression changes in response to specific taxa including Bilophila, Anaerotruncus, and Escherichia. Together, these findings reveal a metabolic dialogue between host and microbiome in CRC, where tumor metabolic reprogramming creates a favorable environment for pathogenic microbes, which in turn may reinforce tumorigenic processes through metabolic crosstalk.

systems biology↗