Dataset Information

Mapping the functional landscape of T cell receptor repertoires by single-T cell transcriptomics.

ABSTRACT: Many experimental and bioinformatics approaches have been developed to characterize the human T cell receptor (TCR) repertoire. However, the unknown functional relevance of TCR profiling hinders unbiased interpretation of the biology of T cells. To address this inadequacy, we developed tessa, a tool to integrate TCRs with gene expression of T cells to estimate the effect that TCRs confer on the phenotypes of T cells. Tessa leveraged techniques combining single-cell RNA-sequencing with TCR sequencing. We validated tessa and showed its superiority over existing approaches that investigate only the TCR sequences. With tessa, we demonstrated that TCR similarity constrains the phenotypes of T cells to be similar and dictates a gradient in antigen targeting efficiency of T cell clonotypes with convergent TCRs. We showed this constraint could predict a functional dichotomization of T cells postimmunotherapy treatment and is weakened in tumor contexts.

SUBMITTER: Zhang Z

PROVIDER: S-EPMC7799492 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature

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Mapping the functional landscape of T cell receptor repertoires by single-T cell transcriptomics.

Zhang Ze Z Xiong Danyi D Wang Xinlei X Liu Hongyu H Wang Tao T

Nature methods 20210106 1

Many experimental and bioinformatics approaches have been developed to characterize the human T cell receptor (TCR) repertoire. However, the unknown functional relevance of TCR profiling hinders unbiased interpretation of the biology of T cells. To address this inadequacy, we developed tessa, a tool to integrate TCRs with gene expression of T cells to estimate the effect that TCRs confer on the phenotypes of T cells. Tessa leveraged techniques combining single-cell RNA-sequencing with TCR sequen ...[more]

PMID: 33408405

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Project description:ObjectivesThe present study used single-cell RNA sequencing (scRNA-seq) to characterize the cellular composition of ovarian carcinosarcoma (OCS) and identify its molecular characteristics.MethodsscRNA-seq was performed in resected primary OCS for an in-depth analysis of tumor cells and the tumor microenvironment. Immunohistochemistry staining was used for validation. The scRNA-seq data of OCS were compared with those of high-grade serous ovarian carcinoma (HGSOC) tumors and other OCS tumors.ResultsBoth malignant epithelial and malignant mesenchymal cells were observed in the OCS patient of this study. We identified four epithelial cell subclusters with different biological roles. Among them, epithelial subcluster 4 presented high levels of breast cancer type 1 susceptibility protein homolog (BRCA1) and DNA topoisomerase 2-α (TOP2A) expression and was related to drug resistance and cell cycle. We analyzed the interaction between epithelial and mesenchymal cells and found that fibroblast growth factor (FGF) and pleiotrophin (PTN) signalings were the main pathways contributing to communication between these cells. Moreover, we compared the malignant epithelial and mesenchymal cells of this OCS tumor with our previous published HGSOC scRNA-seq data and OCS data. All the epithelial subclusters in the OCS tumor could be found in the HGSOC samples. Notably, the mesenchymal subcluster C14 exhibited specific expression patterns in the OCS tumor, characterized by elevated expression of cytochrome P450 family 24 subfamily A member 1 (CYP24A1), collagen type XXIII α1 chain (COL23A1), cholecystokinin (CCK), bone morphogenetic protein 7 (BMP7), PTN, Wnt inhibitory factor 1 (WIF1), and insulin-like growth factor 2 (IGF2). Moreover, this subcluster showed distinct characteristics when compared with both another previously published OCS tumor and normal ovarian tissue.ConclusionsThis study provides the single-cell transcriptomics signature of human OCS, which constitutes a new resource for elucidating OCS diversity.

Project description:Abstract Motivation Single-cell sequencing now enables the recovery of full-length immune receptor repertoires [B cell receptor (BCR) and T cell receptor (TCR) repertoires], in addition to gene expression information. The feature-rich datasets produced from such experiments require extensive and diverse computational analyses, each of which can significantly influence the downstream immunological interpretations, such as clonal selection and expansion. Simulations produce validated standard datasets, where the underlying generative model can be precisely defined and furthermore perturbed to investigate specific questions of interest. Currently, there is no tool that can be used to simulate single-cell datasets incorporating immune receptor repertoires and gene expression. Results We developed Echidna, an R package that simulates immune receptors and transcriptomes at single-cell resolution with user-tunable parameters controlling a wide range of features such as clonal expansion, germline gene usage, somatic hypermutation, transcriptional phenotypes and spatial location. Echidna can additionally simulate time-resolved B cell evolution, producing mutational networks with complex selection histories incorporating class-switching and B cell subtype information. We demonstrated the benchmarking potential of Echidna by simulating clonal lineages and comparing the known simulated networks with those inferred from only the BCR sequences as input. Finally, we simulated immune repertoire information onto existing spatial transcriptomic experiments, thereby generating novel datasets that could be used to develop and integrate methods to profile clonal selection in a spatially resolved manner. Together, Echidna provides a framework that can incorporate experimental data to simulate single-cell immune repertoires to aid software development and bioinformatic benchmarking of clonotyping, phylogenetics, transcriptomics and machine learning strategies. Availability and implementation The R package and code used in this manuscript can be found at github.com/alexyermanos/echidna and also in the R package Platypus (Yermanos et al., 2021). Installation instructions and the vignette for Echidna is described in the Platypus Computational Ecosystem (https://alexyermanos.github.io/Platypus/index.html). Publicly available data and corresponding sample accession numbers can be found in Supplementary Tables S2 and S3. Supplementary information Supplementary data are available at Bioinformatics Advances online.

Project description:BackgroundMyasthenia gravis (MG) is the most prevalent autoimmune disorder affecting the neuromuscular junction. A rapid deterioration in respiratory muscle can lead to a myasthenic crisis (MC), which represents a life-threatening condition with high mortality in MG. Multiple CD4+ T subsets and hypercytokinemia have been identified in the peripheral pro-inflammatory milieu during the crisis. However, the pathogenesis is complicated due to the many types of cells involved, leaving the underlying mechanism largely unexplored.MethodsWe conducted single-cell transcriptomic and immune repertoire sequencing on 33,577 peripheral blood mononuclear cells (PBMCs) from two acetylcholine receptor antibody-positive (AChR +) MG patients during MC and again three months post-MC. We followed the Scanpy workflow for quality control, dimension reduction, and clustering of the single-cell data. Subsequently, we annotated high-resolution cell types utilizing transfer-learning models derived from publicly available single-cell immune datasets. RNA velocity calculations from unspliced and spliced mRNAs were applied to infer cellular state progression. We analyzed cell communication and MG-relevant cytokines and chemokines to identify potential inflammation initiators.ResultsWe identified a unique subset of monocytes, termed monocytes 3 (FCGR3B+ monocytes), which exhibited significant differential expression of pro-inflammatory signaling pathways during and after the crisis. In line with the activated innate immune state indicated by MC, a high neutrophil-lymphocyte ratio (NLR) was confirmed in an additional 22 AChR + MC patients in subsequent hemogram analysis and was associated with MG-relevant clinical scores. Furthermore, oligoclonal expansions were identified in age-associated B cells exhibiting high autoimmune activity, and in CD4+ and CD8+ T cells demonstrating persistent T exhaustion.ConclusionsIn summary, our integrated analysis of single-cell transcriptomics and TCR/BCR sequencing has underscored the role of innate immune activation which is associated with hypercytokinemia in MC. The identification of a specific monocyte cluster that dominates the peripheral immune profile may provide some hints into the etiology and pathology of MC. However, future functional studies are required to explore causality.

Dataset Information

Mapping the functional landscape of T cell receptor repertoires by single-T cell transcriptomics.

Publications

Mapping the functional landscape of T cell receptor repertoires by single-T cell transcriptomics.

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