Clonally Expanded Virus-Specific CD8 T Cells Acquire Diverse Transcriptional Phenotypes During Acute, Chronic, and Latent Infections

Distinct immune memory induced by SARS-CoV-2 in convalescent liver transplant recipients

The understanding of how the host immune response differs in T-cell phenotype and memory formation during SARS-CoV-2 infection in liver transplant recipients (LTRs) remains limited. LTRs who recovered from COVID-19 infection without prior vaccination represent a unique population for studying immune responses to SARS-CoV-2. Six LTRs with positive neutralizing antibodies (nAb+) and six LTRs with negative nAb (nAb-) were included at 6 months following COVID-19 infection. It was found that nAb+ LTRs had higher anti-RBD IgG titers and greater neutralizing percent inhibition compared to nAb- LTRs. Fifteen T-cell subsets were identified in COVID-19 convalescent LTRs, and it was shown that only terminal effector CD8+ - 3 decreased in the nAb+ group, while elevated IL-10 expression levels were found in the nAb- group. After stimulation with the SARS-CoV-2 XBB spike peptide pool in vitro, it was observed that the nAb+ group exhibited an increase in effector memory CD4+ cells with lower PD-1 expression, a reduction in effector memory CD4+ - 2 cells, and terminal effector CD8+ - 3 cells, while the nAb- group showed high expression of CTLA-4 and IL-10 in terminal effector CD8+ - 3 cells. Four SARS-CoV-2-specific T-cell subsets were identified, with high expression of TNF-α and IFN-γ in terminal effector CD8+ - 1 and terminal effector CD8+ - 2 cells in both groups. Perforin was mainly detected in terminal effector CD8+ - 2 cells in nAb+ LTRs. In addition to these proportional differences, stem cell memory CD4+ cells with higher IL-17A expression and stem cell memory CD8+ cells with higher CTLA-4 expression were also found in nAb- LTRs. These findings suggest that LTRs who developed nAb+ following SARS-CoV-2 infection exhibit stronger T-cell responses, with more robust immune activation and memory recall, compared to nAb- LTRs. This study underscores the importance of understanding T-cell responses during SARS-CoV-2 recovery for guiding vaccination strategies and managing immunity in LTRs.

Memory inflation: Beyond the acute phase of viral infection

Memory inflation is confirmed as the most commonly dysregulation of host immunity with antigen-independent manner in mammals after viral infection. By generating large numbers of effector/memory and terminal differentiated effector memory CD8+ T cells with diminished naïve subsets, memory inflation is believed to play critical roles in connecting the viral infection and the onset of multiple diseases. Here, we reviewed the current understanding of memory inflated CD8+ T cells in their distinct phenotypic features that different from exhausted subsets; the intrinsic and extrinsic roles in regulating the formation of memory inflation; and the key proteins in maintaining the expansion and proliferation of inflationary populations. More importantly, based on the evidences from both clinic and animal models, we summarized the potential mechanisms of memory inflation to trigger autoimmune neuropathies, such as Guillain-Barré syndrome and multiple sclerosis; the correlations of memory inflation between tumorigenesis and resistance of tumour immunotherapies; as well as the effects of memory inflation to facilitate vascular disease progression. To sum up, better understanding of memory inflation could provide us an opportunity to beyond the acute phase of viral infection, and shed a light on the long-term influences of CD8+ T cell heterogeneity in dampen host immune homeostasis.

Tissue determinants of the human T cell receptor repertoire

98% of T cells reside in tissues, yet nearly all human T cell analyses are performed from peripheral blood. We single-cell sequenced 5.7 million T cells from ten donors' autologous blood and tonsils and sought to answer key questions about T cell receptor biology previously unanswerable by smaller-scale experiments. We identified distinct clonal expansions and distributions in blood compared to tonsils, with surprisingly low (1-7%) clonal sharing. These few shared clones exhibited divergent phenotypes across bodily sites. Analysis of antigen-specific CD8 T cells revealed location as a main determinant of frequency, phenotype, and immunodominance. Finally, diversity estimates from the tissue recalibrates current repertoire diversity estimates, and we provide a refined estimate of whole-body repertoire. Given the tissue-restricted nature of T cell phenotypes, functions, differentiation, and clonality revealed by this dataset, we conclude that tissue analyses are crucial for accurate repertoire analysis and monitoring changes after perturbing therapies.

T-cell dysfunctions in myelodysplastic syndromes

ABSTRACT

Escape from immune surveillance is a hallmark of cancer. Immune deregulation caused by intrinsic and extrinsic cellular factors, such as altered T-cell functions, leads to immune exhaustion, loss of immune surveillance, and clonal proliferation of tumoral cells. The T-cell immune system contributes to the pathogenesis, maintenance, and progression of myelodysplastic syndrome (MDS). Here, we comprehensively reviewed our current biological knowledge of the T-cell compartment in MDS and recent advances in the development of immunotherapeutic strategies, such as immune checkpoint inhibitors and T-cell- and antibody-based adoptive therapies that hold promise to improve the outcome of patients with MDS.

ePlatypus: an ecosystem for computational analysis of immunogenomics data

MOTIVATION

The maturation of systems immunology methodologies requires novel and transparent computational frameworks capable of integrating diverse data modalities in a reproducible manner.

RESULTS

Here, we present the ePlatypus computational immunology ecosystem for immunogenomics data analysis, with a focus on adaptive immune repertoires and single-cell sequencing. ePlatypus is an open-source web-based platform and provides programming tutorials and an integrative database that helps elucidate signatures of B and T cell clonal selection. Furthermore, the ecosystem links novel and established bioinformatics pipelines relevant for single-cell immune repertoires and other aspects of computational immunology such as predicting ligand-receptor interactions, structural modeling, simulations, machine learning, graph theory, pseudotime, spatial transcriptomics, and phylogenetics. The ePlatypus ecosystem helps extract deeper insight in computational immunology and immunogenomics and promote open science.

AVAILABILITY AND IMPLEMENTATION

Platypus code used in this manuscript can be found at github.com/alexyermanos/Platypus.

Individual Epitope-Specific CD8+ T Cell Immune Responses Are Shaped Differently during Chronic Viral Infection

A hallmark in chronic viral infections are exhausted antigen-specific CD8⁺ T cell responses and the inability of the immune system to eliminate the virus. Currently, there is limited information on the variability of epitope-specific T cell exhaustion within one immune response and the relevance to the T cell receptor (TCR) repertoire. The aim of this study was a comprehensive analysis and comparison of three lymphocytic choriomeningitis virus (LCMV) epitope-specific CD8⁺ T cell responses (NP396, GP33 and NP205) in a chronic setting with immune intervention, e.g., immune checkpoint inhibitor (ICI) therapy, in regard to the TCR repertoire. These responses, though measured within the same mice, were individual and independent from each other. The massively exhausted NP396-specific CD8⁺ T cells revealed a significantly reduced TCR repertoire diversity, whereas less-exhausted GP33-specific CD8⁺ T cell responses were rather unaffected by chronicity in regard to their TCR repertoire diversity. NP205-specific CD8⁺ T cell responses showed a very special TCR repertoire with a prominent public motif of TCR clonotypes that was present in all NP205-specific responses, which separated this from NP396- and GP33-specific responses. Additionally, we showed that TCR repertoire shifts induced by ICI therapy are heterogeneous on the epitope level, by revealing profound effects in NP396-, less severe and opposed effects in NP205-, and minor effects in GP33-specific responses. Overall, our data revealed individual epitope-specific responses within one viral response that are differently affected by exhaustion and ICI therapy. These individual shapings of epitope-specific T cell responses and their TCR repertoires in an LCMV mouse model indicates important implications for focusing on epitope-specific responses in future evaluations for therapeutic approaches, e.g., for chronic hepatitis virus infections in humans.

Echidna: integrated simulations of single-cell immune receptor repertoires and transcriptomes

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.

Single-cell immune repertoire sequencing of B and T cells in murine models of infection and autoimmunity

Adaptive immune repertoires are composed by the ensemble of B and T-cell receptors within an individual, reflecting both past and current immune responses. Recent advances in single-cell sequencing enable recovery of the complete adaptive immune receptor sequences in addition to transcriptional information. Here, we recovered transcriptome and immune repertoire information for polyclonal T follicular helper cells following lymphocytic choriomeningitis virus (LCMV) infection, CD8+ T cells with binding specificity restricted to two distinct LCMV peptides, and B and T cells isolated from the nervous system in the context of experimental autoimmune encephalomyelitis. We could relate clonal expansion, germline gene usage, and clonal convergence to cell phenotypes spanning activation, memory, naive, antibody secretion, T-cell inflation, and regulation. Together, this dataset provides a resource for immunologists that can be integrated with future single-cell immune repertoire and transcriptome sequencing datasets.