powerTCR: A model-based approach to comparative analysis of the clone size distribution of the T cell receptor repertoire

SURROGATE SELECTION OVERSAMPLES EXPANDED T CELL CLONOTYPES

Inference from immunological data on cells in the adaptive immune system may benefit from modeling specifications that describe variation in the sizes of various clonal sub-populations. We develop one such specification in order to quantify the effects of surrogate selection assays, which we confirm may lead to an enrichment for amplified, potentially disease-relevant T cell clones. Our specification couples within-clonotype birth-death processes with an exchangeable model across clonotypes. Beyond enrichment questions about the surrogate selection design, our framework enables a study of sampling properties of elementary sample diversity statistics; it also points to new statistics that may usefully measure the burden of somatic genomic alterations associated with clonal expansion. We examine statistical properties of immunological samples governed by the coupled model specification, and we illustrate calculations in surrogate selection studies of melanoma and in single-cell genomic studies of T cell repertoires.

Inferring the T cell repertoire dynamics of healthy individuals

The adaptive immune system is a diverse ecosystem that responds to pathogens by selecting cells with specific receptors. While clonal expansion in response to particular immune challenges has been extensively studied, we do not know the neutral dynamics that drive the immune system in the absence of strong stimuli. Here, we learn the parameters that underlie the clonal dynamics of the T cell repertoire in healthy individuals of different ages, by applying Bayesian inference to longitudinal immune repertoire sequencing (RepSeq) data. Quantifying the experimental noise accurately for a given RepSeq technique allows us to disentangle real changes in clonal frequencies from noise. We find that the data are consistent with clone sizes following a geometric Brownian motion and show that its predicted steady state is in quantitative agreement with the observed power-law behavior of the clone-size distribution. The inferred turnover time scale of the repertoire increases with patient age and depends on the clone size in some individuals.

Machine Learning Approaches to TCR Repertoire Analysis

Sparked by the development of genome sequencing technology, the quantity and quality of data handled in immunological research have been changing dramatically. Various data and database platforms are now driving the rapid progress of machine learning for immunological data analysis. Of various topics in immunology, T cell receptor repertoire analysis is one of the most important targets of machine learning for assessing the state and abnormalities of immune systems. In this paper, we review recent repertoire analysis methods based on machine learning and deep learning and discuss their prospects.

How Naive T-Cell Clone Counts Are Shaped By Heterogeneous Thymic Output and Homeostatic Proliferation

The specificity of T cells is that each T cell has only one T cell receptor (TCR). A T cell clone represents a collection of T cells with the same TCR sequence. Thus, the number of different T cell clones in an organism reflects the number of different T cell receptors (TCRs) that arise from recombination of the V(D)J gene segments during T cell development in the thymus. TCR diversity and more specifically, the clone abundance distribution, are important factors in immune functions. Specific recombination patterns occur more frequently than others while subsequent interactions between TCRs and self-antigens are known to trigger proliferation and sustain naive T cell survival. These processes are TCR-dependent, leading to clone-dependent thymic export and naive T cell proliferation rates. We describe the heterogeneous steady-state population of naive T cells (those that have not yet been antigenically triggered) by using a mean-field model of a regulated birth-death-immigration process. After accounting for random sampling, we investigate how TCR-dependent heterogeneities in immigration and proliferation rates affect the shape of clone abundance distributions (the number of different clones that are represented by a specific number of cells, or “clone counts”). By using reasonable physiological parameter values and fitting predicted clone counts to experimentally sampled clone abundances, we show that realistic levels of heterogeneity in immigration rates cause very little change to predicted clone-counts, but that modest heterogeneity in proliferation rates can generate the observed clone abundances. Our analysis provides constraints among physiological parameters that are necessary to yield predictions that qualitatively match the data. Assumptions of the model and potentially other important mechanistic factors are discussed.

Modulation of tissue resident memory T cells by glucocorticoids after acute cellular rejection in lung transplantation

Acute cellular rejection is common after lung transplantation and is associated with an increased risk of early chronic rejection. We present combined single-cell RNA and TCR sequencing on recipient-derived T cells obtained from the bronchoalveolar lavage of three lung transplant recipients with rejection and compare them with T cells obtained from the same patients after treatment of rejection with high-dose systemic glucocorticoids. At the time of rejection, we found an oligoclonal expansion of cytotoxic CD8+ T cells that all persisted as tissue resident memory T cells after successful treatment. Persisting CD8+ allograft-resident T cells have reduced gene expression for cytotoxic mediators after therapy with glucocorticoids but accumulate around airways. This clonal expansion is discordant with circulating T cell clonal expansion at the time of rejection, suggesting in situ expansion. We thus highlight the accumulation of cytotoxic, recipient-derived tissue resident memory T cells within the lung allograft that persist despite the administration of high-dose systemic glucocorticoids. The long-term clinical consequences of this persistence have yet to be characterized.

Immune signatures underlying post-acute COVID-19 lung sequelae

[Figure: see text].

T cell factor 1: A master regulator of the T cell response in disease

Recent advances have redefined a role for T cell factor 1 (TCF1) that goes beyond T cell development and T memory formation and encompasses new functions in the regulation of T cell biology. Here, we discuss the multifaceted and context-dependent role of TCF1 in peripheral T cells, particularly during disease-induced inflammatory states such as autoimmunity, cancer, and chronic infections. Understanding how TCF1 fine-tunes peripheral T cell biology holds the potential to tailor improved immune-targeted therapies.

Characteristics of T-cell receptor repertoire of stem cell-like memory CD4+ T cells

Stem cell-like memory T cells (Tscm) combine phenotypes of naïve and memory. However, it remains unclear how T cell receptor (TCR) characteristics contribute to heterogeneity in Tscm and other memory T cells. We compared the TCR-beta (TRB) repertoire characteristics of CD4+ Tscm with those of naïve and other CD4+ memory (Tm) in 16 human subjects. Compared with Tm, Tscm had an increased diversity across all stretches of TRB repertoire structure, a skewed gene usage, and a shorter length distribution of CDR3 region. These distinctions between Tscm and Tm were enlarged in top1000 abundant clonotypes. Furthermore, top1000 clonotypes in Tscm were more public than those in Tm and grouped in more clusters, implying more epitope types recognized by top1000 clonotypes in Tscm. Importantly, self-reactive clonotypes were public and enriched in Tscm rather than Tm, of type one diabetes patients. Therefore, this study highlights the unique features of Tscm different from those of other memory subsets and provides clues to understand the physiological and pathological functions of Tscm.

Recipient-specific T-cell repertoire reconstitution in the gut following murine hematopoietic cell transplant

Graft-versus-host disease (GVHD) is a complication of hematopoietic cell transplantation (HCT) caused by alloreactive T cells. Murine models of HCT are used to understand GVHD and T-cell reconstitution in GVHD target organs, most notably the gastrointestinal (GI) tract where the disease contributes most to patient mortality. T-cell receptor (TCR) repertoire sequencing was used to measure T-cell reconstitution from the same donor graft (C57BL/6 H-2b) in the GI tract of different recipients across a spectrum of matching, from syngeneic (C57BL/6), to minor histocompatibility (MHC) antigen mismatch BALB.B (H-2b), to major MHC mismatched B10.BR (H-2k) and BALB/c (H-2d). Although the donor T-cell pools had highly similar TCR, the TCR repertoire after HCT was very specific to recipients in each experiment independent of geography. A single invariant natural killer T clone was identifiable in every recipient group and was enriched in syngeneic recipients according to clonal count and confirmatory flow cytometry. Using a novel cluster analysis of the TCR repertoire, we could classify recipient groups based only on their CDR3 size distribution or TCR repertoire relatedness. Using a method for evaluating the contribution of common TCR motifs to relatedness, we found that reproducible sets of clones were associated with specific recipient groups within each experiment and that relatedness did not necessarily depend on the most common clones in allogeneic recipients. This finding suggests that TCR reconstitution is highly stochastic and likely does not depend on the evaluation of the most expanded TCR clones in any individual recipient but instead depends on a complex polyclonal architecture.

Circulating clonally expanded T cells reflect functions of tumor-infiltrating T cells

Understanding the relationship between tumor and peripheral immune environments could allow longitudinal immune monitoring in cancer. Here, we examined whether T cells that share the same TCRαβ and are found in both tumor and blood can be interrogated to gain insight into the ongoing tumor T cell response. Paired transcriptome and TCRαβ repertoire of circulating and tumor-infiltrating T cells were analyzed at the single-cell level from matched tumor and blood from patients with metastatic melanoma. We found that in circulating T cells matching clonally expanded tumor-infiltrating T cells (circulating TILs), gene signatures of effector functions, but not terminal exhaustion, reflect those observed in the tumor. In contrast, features of exhaustion are displayed predominantly by tumor-exclusive T cells. Finally, genes associated with a high degree of blood-tumor TCR sharing were overexpressed in tumor tissue after immunotherapy. These data demonstrate that circulating TILs have unique transcriptional patterns that may have utility for the interrogation of T cell function in cancer immunotherapy.

Needle in a Haystack: The Naïve Repertoire as a Source of T Cell Receptors for Adoptive Therapy with Engineered T Cells

T cell engineering with antigen-specific T cell receptors (TCRs) has allowed the generation of increasingly specific, reliable, and versatile T cell products with near-physiological features. However, a broad applicability of TCR-based therapies in cancer is still limited by the restricted number of TCRs, often also of suboptimal potency, available for clinical use. In addition, targeting of tumor neoantigens with TCR-engineered T cell therapy moves the field towards a highly personalized treatment, as tumor neoantigens derive from somatic mutations and are extremely patient-specific. Therefore, relevant TCRs have to be de novo identified for each patient and within a narrow time window. The naïve repertoire of healthy donors would represent a reliable source due to its huge diverse TCR repertoire, which theoretically entails T cells for any antigen specificity, including tumor neoantigens. As a challenge, antigen-specific naïve T cells are of extremely low frequency and mostly of low functionality, making the identification of highly functional TCRs finding a "needle in a haystack." In this review, we present the technological advancements achieved in high-throughput mapping of patient-specific neoantigens and corresponding cognate TCRs and how these platforms can be used to interrogate the naïve repertoire for a fast and efficient identification of rare but therapeutically valuable TCRs for personalized adoptive T cell therapy.

T-cell repertoire analysis and metrics of diversity and clonality

The recent developments of high-throughput bulk and single-cell sequencing technologies accelerated the understanding of the complexity of immune repertoire dynamics combined to transcriptomics. Also, profiling of cellular repertoires in health or disease requires statistical metrics to capture clonal diversity characterized by clones frequency, repertoire richness and convergence. Here we present the common technologies of bulk and single-cell sequencing of T-cell receptors (TCRs), discuss current knowledge regarding computational tools clustering and predicting specificity of TCR repertoires based on shared structural motifs and review main indices for repertoire diversity and convergence analyses. These tools represent potential biomarkers to decipher the fitness of immune repertoires in diseased or treated patients but also the presages and promises of computational approaches to revolutionize personalized immunotherapy.

scRepertoire: An R-based toolkit for single-cell immune receptor analysis

Single-cell sequencing is an emerging technology in the field of immunology and oncology that allows researchers to couple RNA quantification and other modalities, like immune cell receptor profiling at the level of an individual cell. A number of workflows and software packages have been created to process and analyze single-cell transcriptomic data. These packages allow users to take the vast dimensionality of the data generated in single-cell-based experiments and distill the data into novel insights. Unlike the transcriptomic field, there is a lack of options for software that allow for single-cell immune receptor profiling. Enabling users to easily combine mRNA and immune profiling, scRepertoire was built to process data derived from 10x Genomics Chromium Immune Profiling for both T-cell receptor (TCR) and immunoglobulin (Ig) enrichment workflows and subsequently interacts with a number of popular R packages for single-cell expression, such as Seurat. The scRepertoire R package and processed data are open source and available on GitHub and provides in-depth tutorials on the capability of the package.