T Cell Receptor Repertoire Analysis Reveals Signatures of T Cell Responses to Human Mycobacterium tuberculosis

Single-cell sequencing: Current applications in various tuberculosis specimen types

Tuberculosis (TB) is a chronic disease caused by Mycobacterium tuberculosis (M.tb) and responsible for millions of deaths worldwide each year. It has a complex pathogenesis that primarily affects the lungs but can also impact systemic organs. In recent years, single-cell sequencing technology has been utilized to characterize the composition and proportion of immune cell subpopulations associated with the pathogenesis of TB disease since it has a high resolution that surpasses conventional techniques. This paper reviews the current use of single-cell sequencing technologies in TB research and their application in analysing specimens from various sources of TB, primarily peripheral blood and lung specimens. The focus is on how these technologies can reveal dynamic changes in immune cell subpopulations, genes and proteins during disease progression after M.tb infection. Based on the current findings, single-cell sequencing has significant potential clinical value in the field of TB research. Next, we will focus on the real-world applications of the potential targets identified through single-cell sequencing for diagnostics, therapeutics and the development of effective vaccines.

Immunoglobulin and T cell receptor repertoire changes induced by a prototype vaccine against Chagas disease in naïve rhesus macaques

BACKGROUND

A vaccine against Trypanosoma cruzi, the agent of Chagas disease, would be an excellent additional tool for disease control. A recombinant vaccine based on Tc24 and TSA1 parasite antigens was found to be safe and immunogenic in naïve macaques.

METHODS

We used RNA-sequencing and performed a transcriptomic analysis of PBMC responses to vaccination of naïve macaques after each vaccine dose, to shed light on the immunogenicity of this vaccine and guide the optimization of doses and formulation. We identified differentially expressed genes and pathways and characterized immunoglobulin and T cell receptor repertoires.

RESULTS

RNA-sequencing analysis indicated a clear transcriptomic response of PBMCs after three vaccine doses, with the up-regulation of several immune cell activation pathways and a broad non-polarized immune profile. Analysis of the IgG repertoire showed that it had a rapid turnover with novel IgGs produced following each vaccine dose, while the TCR repertoire presented several persisting clones that were expanded after each vaccine dose.

CONCLUSIONS

These data suggest that three vaccine doses may be needed for optimum immunogenicity and support the further evaluation of the protective efficacy of this vaccine.

Immunoglobin and T cell receptor repertoire changes induced by a prototype vaccine against Chagas disease in naïve rhesus macaques

A vaccine against Trypanosoma cruzi, the agent of Chagas disease, would be an excellent additional tool for disease control. A recombinant vaccine based on Tc24 and TSA1 parasite antigens was found to be safe and immunogenic in naïve macaques. Here we performed a transcriptomic analysis of PBMC responses to vaccination, to shed light on the immunogenicity of this vaccine and guide the optimization of doses and formulation. RNA-sequencing analysis indicated a clear transcriptomic response of PBMCs from macaques after three vaccine doses, with the up-regulation of several immune cell activation pathways and a broad non-polarized immune profile. Analysis of the IgG repertoire showed that it had a rapid turnover with novel IgGs produced following each vaccine dose, while the TCR repertoire presented several persisting clones that were expanded after each vaccine dose. These data suggest that three vaccine doses may be needed for optimum immunogenecity and support the further evaluation of the protective efficacy of this vaccine.

SIGANEO: Similarity network with GAN enhancement for immunogenic neoepitope prediction

Target selection of the personalized cancer neoantigen vaccine, which is highly dependent on computational prediction algorithms, is crucial for its clinical efficacy. Due to the limited number of experimentally validated immunogenic neoepitopes as well as the complexity of neoantigens in eliciting T cell response, the accuracy of neoepitope immunogenicity prediction methods requires persistent efforts for improvement. We present a deep learning framework for neoepitope immunogenicity prediction - SIGANEO by integrating GAN-like network with similarity network to address issues of missing values and limited data concerning neoantigen prediction. This framework exhibits superior performance over competing machine-learning-based neoantigen prediction algorithms over an independent test dataset from TESLA consortium. Particularly for the clinical setting of neoantigen vaccine where only the top 10 and 20 predictions are selected for vaccine production, SIGANEO achieves significantly better accuracy for predicting experimentally validated neoepitopes. Our work demonstrates that deep learning techniques can greatly boost the accuracy of target identification for cancer neoantigen vaccine.

Research progress of single-cell sequencing in tuberculosis

Tuberculosis is a major infectious disease caused by Mycobacterium tuberculosis infection. The pathogenesis and immune mechanism of tuberculosis are not clear, and it is urgent to find new drugs, diagnosis, and treatment targets. A useful tool in the quest to reveal the enigmas related to Mycobacterium tuberculosis infection and disease is the single-cell sequencing technique. By clarifying cell heterogeneity, identifying pathogenic cell groups, and finding key gene targets, the map at the single cell level enables people to better understand the cell diversity of complex organisms and the immune state of hosts during infection. Here, we briefly reviewed the development of single-cell sequencing, and emphasized the different applications and limitations of various technologies. Single-cell sequencing has been widely used in the study of the pathogenesis and immune response of tuberculosis. We review these works summarizing the most influential findings. Combined with the multi-molecular level and multi-dimensional analysis, we aim to deeply understand the blank and potential future development of the research on Mycobacterium tuberculosis infection using single-cell sequencing technology.

Immune checkpoint modulating T cells and NK cells response to Mycobacterium tuberculosis infection

Many subversive mechanisms promote the occurrence and development of chronic infectious diseases and cancer, among which the down-regulated expression of immune-activating receptors and the enhanced expression of immune-inhibitory receptors accelerate the occurrence and progression of the disease. Recently, the use of immune checkpoint inhibitors has shown remarkable efficacy in the treatment of tumors in multiple organs. However, the expression of immune checkpoint molecules on natural killer (NK) cells by Mycobacterium tuberculosis (Mtb) infection and its impact on NK cell effector functions have been poorly studied. In this review, we focus on what is currently known about the expression of various immune checkpoints in NK cells following Mtb infection and how it alters NK cell-mediated host cytotoxicity and cytokine secretion. Unraveling the function of NK cells after the infection of host cells by Mtb is crucial for a comprehensive understanding of the innate immune mechanism of NK cells involved in tuberculosis and the evaluation of the efficacy of immunotherapies using immune checkpoint inhibitors to treat tuberculosis. In view of some similarities in the immune characteristics of T cells and NK cells, we reviewed the molecular mechanism of the interaction between T cells and Mtb, which can help us to further understand and explore the specific interaction mechanism between NK cells and Mtb.

Antigen-specificity measurements are the key to understanding T cell responses

Antigen-specific T cells play a central role in the adaptive immune response and come in a wide range of phenotypes. T cell receptors (TCRs) mediate the antigen-specificities found in T cells. Importantly, high-throughput TCR sequencing provides a fingerprint which allows tracking of specific T cells and their clonal expansion in response to particular antigens. As a result, many studies have leveraged TCR sequencing in an attempt to elucidate the role of antigen-specific T cells in various contexts. Here, we discuss the published approaches to studying antigen-specific T cells and their specific TCR repertoire. Further, we discuss how these methods have been applied to study the TCR repertoire in various diseases in order to characterize the antigen-specific T cells involved in the immune control of disease.

Single-cell profiling identifies T cell subsets associated with control of tuberculosis dissemination

To identify T cell subsets associated with control of tuberculosis, single-cell transcriptome and T cell receptor sequencing were performed on total T cells from patients with tuberculosis and healthy controls. Fourteen distinct subsets of T cells were identified by unbiased UMAP clustering. A GZMK-expressing CD8⁺ cytotoxic T cell cluster and a SOX4-expressing CD4⁺ central memory T cell cluster were depleted, while a MKI67-expressing proliferating CD3⁺ T cell cluster was expanded in patients with tuberculosis compared with healthy controls. The ratio of Granzyme K-expressing CD8⁺CD161^-Ki-67^- and CD8⁺Ki-67⁺ T cell subsets was significantly reduced and inversely correlated with the extent of TB lesions in patients with TB. In contrast, ratio of Granzyme B-expressing CD8⁺Ki-67⁺ and CD4⁺CD161⁺Ki-67^- T cells and Granzyme A-expressing CD4⁺CD161⁺Ki-67^- T cells were correlated with the extent of TB lesions. It is concluded that granzyme K-expressing CD8⁺ T cell subsets might contribute to protection against tuberculosis dissemination.

Research progress on application of single-cell TCR/BCR sequencing technology to the tumor immune microenvironment, autoimmune diseases, and infectious diseases

Single-cell omics is the profiling of individual cells through sequencing and other technologies including high-throughput analysis for single-cell resolution, cell classification, and identification as well as time series analyses. Unlike multicellular studies, single-cell omics overcomes the problem of cellular heterogeneity. It provides new methods and perspectives for in-depth analyses of the behavior and mechanism of individual cells in the cell population and their relationship with the body, and plays an important role in basic research and precision medicine. Single-cell sequencing technologies mainly include single-cell transcriptome sequencing, single-cell assay for transposase accessible chromatin with high-throughput sequencing, single-cell immune profiling (single-cell T-cell receptor [TCR]/B-cell receptor [BCR] sequencing), and single-cell transcriptomics. Single-cell TCR/BCR sequencing can be used to obtain a large amount of single-cell gene expression and immunomics data at one time, and combined with transcriptome sequencing and TCR/BCR diversity data, can resolve immune cell heterogeneity. This paper summarizes the progress in applying single-cell TCR/BCR sequencing technology to the tumor immune microenvironment, autoimmune diseases, infectious diseases, immunotherapy, and chronic inflammatory diseases, and discusses its shortcomings and prospects for future application.