Predicting TCR and BCR specificity to microbiomes by massively mining RNA-seq samples

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T cells and B cells play important roles in our immune system by recognizing various antigens, including bacteria and viruses, through their diverse receptors T-cell receptors and B-cell receptors (TCRs and BCRs). The total set of TCRs and BCRs in a person is called immune repertoire, and analyzing immune repertoire can reveal valuable health information and guide treatment strategies. One of the key steps for understanding immune repertoire is to identify the binding target of each TCR and BCR. Researchers have developed experimental techniques to capture the receptors recognizing the input antigens. However, the profiled antigens on these platforms are very scarce, even when compared with the microbiome species with known genome sequences. Thanks to the development of sequencing technology, we can investigate the genomic or RNA information at bulk or single-cell level for a large number of samples. In a series of our previous works, we demonstrated the ability to extract micro biome information and immune repertoire information from sequencing data. With these methods, each sample can give a glimpse of the immune repertoire and microbiome interactions, suggesting that we may associate the TCRs and BCRs with their binding targets by inspecting sufficient samples. In order to efficiently process huge amounts of raw sequencing data sets, we will develop novel computational methods that can remarkably reduce the computational overhead. Additionally, we will extend these methods to work on a broader scope of sequencing platforms to incorporate more samples in this study. After obtaining the immune repertoire and microbiome data across the samples, we will curate the resources into a database and develop computational and statistical tools to annotate the user-input TCRs and BCRs with their microbiome binding targets.