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Crohn's disease (CD) is a clinical subset of inflammatory bowel disease that is characterized by patchy transmural inflammation across the gastrointestinal tract. Although the exact etiology remains unknown, recent findings suggest that it is a complex multifactorial disease with contributions from the host genetics and environmental factors such as the microbiome. We have previously shown that the T cell repertoire of individuals with CD harbors a group of highly expanded T cells which hints toward an antigen-mediated pathology. We simultaneously profiled the αβ and γδ T cell repertoire in addition to the B cell repertoire of both the blood and the colonic mucosa of 27 treatment-naïve individuals with CD and 27 age-matched symptomatic controls. Regardless of disease status, we observed multiple physiological differences between the immune repertoire of blood and colonic mucosa. Additionally, by comparing the repertoire of individuals with CD relative to controls, we observed different alterations that were only detected in the blood or colonic mucosa. These include a depletion of mucosal-associated invariant T (MAIT) cells and an expansion of clonotypes in the blood repertoire of individuals with CD. Also, a significant depletion of multiple and clonotypes in the blood and gut IGH repertoire of individuals with CD. Our findings highlight the importance of studying the immune repertoire in a tissue-specific manner and the need to profile the T and B cell immune repertoire of gut tissues as not all disease-induced alterations will be detected in the blood.

In recent years, music therapy has gradually become an adjunct to conventional medicine and drug therapy. In this paper, genetic algorithms are used in conventional music therapy, and they are also used to optimize the combination of repertoire in music therapy. The repertoire mining model based on an improved genetic algorithm is constructed, and the optimized search is carried out with the genetic algorithm to mine the most effective therapeutic repertoire for patients. Based on the recommendation degree analysis, the personalized recommended repertoire is customized according to the specific conditions of patients. The therapeutic effect of this paper’s music therapy based on the optimization of repertoire by genetic algorithm is examined through comparative experiments from the changes in the therapeutic effects of the experimental and control groups before and after the experiments. Before the experiment, the experimental and control groups are not identical. After the experiment, the therapeutic effect of the experimental group was greatly improved, while the control group remained basically unchanged, the total score of the therapeutic effect of the two groups differed by 50.09 points, and showed significant differences in all dimensions of the therapeutic effect. The experimental group received an improvement of 4-8 points in each dimension of the treatment effect after the experiment, while the control group received an improvement of no more than 0.5 points. Both groups and inter- and intra-group differences were statistically significant.

It is increasingly clear that an extraordinarily diverse range of clinically important conditions—including infections, vaccinations, autoimmune diseases, transplants, transfusion reactions, aging, and cancers—leave telltale signatures in the millions of V(D)J-rearranged antibody and T cell receptor [TR per the Human Genome Organization (HUGO) nomenclature but more commonly known as TCR] genes collectively expressed by a person’s B cells (antibodies) and T cells. We refer to these as the immunome . Because of its diversity and complexity, the immunome provides singular opportunities for advancing personalized medicine by serving as the substrate for a highly multiplexed, near-universal blood test. Here we discuss some of these opportunities, the current state of immunome-based diagnostics, and highlight some of the challenges involved. We conclude with a call to clinicians, researchers, and others to join efforts with the Adaptive Immune Receptor Repertoire Community (AIRR-C) to realize the diagnostic potential of the immunome.

[This corrects the article DOI: 10.3389/fimmu.2020.01587.].

The V(D)J recombination forms the immunoglobulin genes by joining the variable (V), diversity (D), and joining (J) germline genes. Since variations in germline genes have been linked to various diseases, personalized immunogenomics aims at finding alleles of germline genes across various patients. Although recent studies described algorithms for inference of V and J genes from immunosequencing data, they stopped short of solving a more difficult problem of reconstructing D genes that form the highly divergent CDR3 regions and provide the most important contribution to the antigen binding. We present the IgScout algorithm for D gene reconstruction and apply it to reveal new alleles of human D genes and previously unknown D genes in camel, an important model organism in immunology. We further analyze non-canonical V(DD)J recombination that results in unusually long CDR3s with tandem fused IGHD genes and thus expands the diversity of the antibody repertoires. We demonstrate that tandem CDR3s represent a consistent and functional feature of all analyzed immunosequencing datasets, reveal ultra-long CDR3s, and shed light on the mechanism responsible for their formation.

Background The T-cell receptor (TCR), located on the surface of T cells, is responsible for the recognition of the antigen-major histocompatibility complex, leading to the initiation of an inflammatory response. Analysing the TCR repertoire may help to gain a better understanding of the immune system features and of the aetiology and progression of diseases, in particular those with unknown antigenic triggers. The extreme diversity of the TCR repertoire represents a major analytical challenge; this has led to the development of specialized methods which aim to characterize the TCR repertoire in-depth. Currently, next generation sequencing based technologies are most widely employed for the high-throughput analysis of the immune cell repertoire. Results Here, we report on the latest methodological advancements in the field by describing and comparing the available tools; from the choice of the starting material and library preparation method, to the sequencing technologies and data analysis. Finally, we provide a practical example and our own experience by reporting some exemplary results from a small internal benchmark study, where current approaches from the literature and the market are employed and compared. Conclusions Several valid methods for clonotype identification and TCR repertoire analysis exist, however, a gold standard method for the field has not yet been identified. Depending on the purpose of the scientific study, some approaches may be more suitable than others. Finally, due to possible method specific biases, scientists must be careful when comparing results obtained using different methods.

High-throughput sequencing has the power to reveal the nature of adaptive immunity as represented by the full complexity of T-cell receptor (TCR) and antibody (IG) repertoires, but is at present severely compromised by the quantitative bias, bottlenecks, and accumulated errors that inevitably occur in the course of library preparation and sequencing. Here we report an optimized protocol for the unbiased preparation of TCR and IG cDNA libraries for high-throughput sequencing, starting from thousands or millions of live cells in an investigated sample. Critical points to control are revealed, along with tips that allow researchers to minimize quantitative bias, accumulated errors, and cross-sample contamination at each stage, and to enhance the subsequent bioinformatic analysis. The protocol is simple, reliable, and can be performed in 1-2 days.