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

T细胞和B细胞通过识别各种抗原在我们的免疫系统中发挥重要作用，包括 细菌和病毒通过其不同的受体T细胞受体和B细胞受体(TCR和 BCR)。一个人的TCR和BCR的全部集合被称为免疫谱，并分析免疫 曲目可以揭示有价值的健康信息，并指导治疗策略。关键步骤之一是 了解免疫谱系是确定每个TCR和BCR的结合靶点。研究人员已经 开发了实验技术来捕获识别输入抗原的受体。然而， 即使与微生物组物种相比，这些平台上的型式抗原也非常稀少。 已知的基因组序列。多亏了测序技术的发展，我们可以调查 大量样本的整体或单细胞水平的基因组或RNA信息。在我们的一系列节目中 以前的工作，我们演示了提取微量的能力 来自测序数据的生物组信息和免疫谱系信息。使用这些方法，每种方法 样本可以提供免疫系统和微生物组相互作用的一瞥，这表明我们可能 通过检查足够的样品，将TCR和BCR与其结合靶标相关联。为了 高效地处理大量的原始测序数据集，我们将开发新的计算 方法可以显著减少计算开销。此外，我们还将延长这些 方法在更广泛的测序平台上工作，以便在本研究中纳入更多的样本。 在获得所有样本的免疫谱系和微生物组数据后，我们将策划 将资源存入数据库，并开发计算和统计工具，对用户输入的TCR进行注释 和BCR及其微生物组结合靶标。

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.