Barcoding intracellular reverse transcription enables high-throughput phenotype-coupled T cell receptor analyses

Assays linking cellular phenotypes with T cell or B cell antigen receptor sequences are crucial for characterizing adaptive immune responses. Existing methodologies are limited by low sample throughput and high cost. Here, we present INtraCEllular Reverse Transcription with Sorting and sequencing (INCERTS), an approach that combines molecular indexing of receptor repertoires within intact cells and fluorescence-activated cell sorting (FACS). We demonstrate that INCERTS enables efficient processing of millions of cells from pooled human peripheral blood mononuclear cell (PBMC) samples while retaining robust association between T cell receptor (TCR) sequences and cellular phenotypes. We used INCERTS to discover antigen-specific TCRs from patients with cancer immunized with a novel mutant KRAS peptide vaccine. After ex vivo stimulation, 28 uniquely barcoded samples were pooled prior to FACS into peptide-reactive and non-reactive CD4+ and CD8+ populations. Combining complementary patient-matched single-cell RNA sequencing (scRNA-seq) data enabled retrieval of full-length, paired TCR alpha and beta chain sequences for future validation of therapeutic utility.

Inspecting the interaction between human immunodeficiency virus and the immune system through genetic turnover

Chronic infections of the human immunodeficiency virus (HIV) create a very complex coevolutionary process, where the virus tries to escape the continuously adapting host immune system. Quantitative details of this process are largely unknown and could help in disease treatment and vaccine development. Here we study a longitudinal dataset of ten HIV-infected people, where both the B-cell receptors and the virus are deeply sequenced. We focus on simple measures of turnover, which quantify how much the composition of the viral strains and the immune repertoire change between time points. At the single-patient level, the viral-host turnover rates do not show any statistically significant correlation, however, they correlate if one increases the amount of statistics by aggregating the information across patients. We identify an anti-correlation: large changes in the viral pool composition come with small changes in the B-cell receptor repertoire. This result seems to contradict the naïve expectation that when the virus mutates quickly, the immune repertoire needs to change to keep up. However, a simple model of antagonistically evolving populations can explain this signal. If it is sampled at intervals comparable with the sweep time, one population has had time to sweep while the second cannot start a counter-sweep, leading to the observed anti-correlation. This article is part of the theme issue 'Interdisciplinary approaches to predicting evolutionary biology'.

Measures of epitope binding degeneracy from T cell receptor repertoires

Adaptive immunity is driven by specific binding of hypervariable receptors to diverse molecular targets. The sequence diversity of receptors and targets are both individually known but because multiple receptors can recognize the same target, a measure of the effective "functional" diversity of the human immune system has remained elusive. Here, we show that sequence near-coincidences within T cell receptors that bind specific epitopes provide a new window into this problem and allow the quantification of how binding probability covaries with sequence. We find that near-coincidence statistics within epitope-specific repertoires imply a measure of binding degeneracy to amino acid changes in receptor sequence that is consistent across disparate experiments. Paired data on both chains of the heterodimeric receptor are particularly revealing since simultaneous near-coincidences are rare and we show how they can be exploited to estimate the number of epitope responses that created the memory compartment. In addition, we find that paired-chain coincidences are strongly suppressed across donors with different human leukocyte antigens, evidence for a central role of antigen-driven selection in making paired chain receptors public. These results demonstrate the power of coincidence analysis to reveal the sequence determinants of epitope binding in receptor repertoires.

Single-cell immunoprofiling after immunotherapy for allergic rhinitis reveals functional suppression of pathogenic Th2 cells and clonal conversion

BACKGROUND

Allergic rhinitis is a growing problem worldwide. Currently, the only treatment that can modify the disease is antigen-specific immunotherapy; however, its mechanism(s) of action is not fully understood.

OBJECTIVE

To comprehensively investigate the role and changes of antigen-specific T cells before and after sublingual immunotherapy (SLIT) for Japanese cedar pollinosis (JCP).

METHODS

We cultured PBMCs obtained both before and at 1 year after initiating SLIT and used a combination of single-cell RNA sequence and repertoire sequencing. To investigate biomarkers, we used PBMCs from patients participating a phase II/III trial of SLIT tablets for JCP and PBMCs from good and poor responders in outpatients.

RESULTS

Antigen-stimulated culturing after SLIT led to clonal expansion of Th2 and Treg cells, and most of these CD4⁺ T cells retained their CDR3 regions before and after treatment, indicating antigen-specific clonal responses and differentiation secondary to SLIT. However, SLIT reduced the number of clonal functional Th2 cells but increased the Trans-type Th2 cell population that expresses musculin (MSC), TGF-β, and IL-2. Trajectory analysis suggested that SLIT induced clonal differentiation of the Trans-type Th2 cells differentiated into Treg cells. Using real-time PCR, we found that the MSC levels increased in the active SLIT group and good responders after 1 year of treatment.

CONCLUSION

The combination of single-cell RNA sequencing and repertoire analysis helped reveal a part of the underlying mechanism-that SLIT promotes the expression of MSC on pathogenic Th2 cells and suppresses their function; MSC may be a potential biomarker of SLIT for allergic rhinitis.

Receptor editing constrains development of phosphatidyl choline-specific B cells in VH12-transgenic mice

B1 B cells reactive to phosphatidyl choline (PtC) exhibit restricted immunoglobulin heavy chain (HC) and light chain (LC) combinations, exemplified by V_H12/Vκ4/5H. Two checkpoints are thought to focus PtC⁺ B cell maturation in V_H12-transgenic mice (VH12 mice): V-J rearrangements encoding a "permissive" LC capable of V_H12 HC pairing are selected first, followed by positive selection based on PtC binding, often requiring LC receptor editing to salvage PtC^- B cells and acquire PtC reactivity. However, evidence obtained from breeding VH12 mice to editing-defective dnRAG1 mice and analyzing LC sequences from PtC⁺ and PtC^- B cell subsets instead suggests that receptor editing functions after initial positive selection to remove PtC⁺ B cells in VH12 mice. This offers a mechanism to constrain natural, polyreactive B cells to limit their frequency. Sequencing also reveals occasional in-frame hybrid LC genes, reminiscent of type 2 gene replacement, that, testing suggests, arise via a recombination-activating gene (RAG)-independent mechanism.

Clonal diversity of the B cell receptor repertoire in patients with coronary in-stent restenosis and type 2 diabetes

Type 2 diabetes mellitus (T2DM) is known as a risk factor for coronary in-stent restenosis (ISR) in patients with coronary artery disease (CAD). Evidence suggests that B cells play a functional role in the progression of atherosclerotic lesions. However, the B cell receptor (BCR) repertoire in patients with ISR remains unclear. This study aims to profile the BCR repertoire in patients with coronary ISR/T2DM. A total of 21 CAD patients with or without ISR/T2DM were enrolled. PBMCs were isolated and examined for BCR repertoire profiles using DNA-seq. Our results showed that the diversity of amino acid sequences in ISR DM patients was higher than that in ISR -DM patients. The frequencies of 21 V/J paired genes differed between ISR DM and -ISR DM patients, while frequencies of 5 V/J paired genes differed between ISR DM and ISR -DM. The -ISR -DM group presented the highest clonotype overlap rate, while ISR DM patients presented the lowest overlap rate. Our study presented the BCR repertoires in patients with ISR/T2DM. The data suggested different BCR signatures between patients with ISR and T2DM. Further analysis of BCR profiles would enhance understanding of ISR.

Early life imprints the hierarchy of T cell clone sizes

The adaptive immune system responds to pathogens by selecting clones of cells with specific receptors. While clonal selection in response to particular antigens has been studied in detail, it is unknown how a lifetime of exposures to many antigens collectively shape the immune repertoire. Here, using mathematical modeling and statistical analyses of T cell receptor sequencing data, we develop a quantitative theory of human T cell dynamics compatible with the statistical laws of repertoire organization. We find that clonal expansions during a perinatal time window leave a long-lasting imprint on the human T cell repertoire, which is only slowly reshaped by fluctuating clonal selection during adult life. Our work provides a mechanism for how early clonal dynamics imprint the hierarchy of T cell clone sizes with implications for pathogen defense and autoimmunity.

T Cell Repertoire Dynamics during Pregnancy in Multiple Sclerosis

Identifying T cell clones associated with human autoimmunity has remained challenging. Intriguingly, many autoimmune diseases, including multiple sclerosis (MS), show strongly diminished activity during pregnancy, providing a unique research paradigm to explore dynamics of immune repertoire changes during active and inactive disease. Here, we characterize immunomodulation at the single-clone level by sequencing the T cell repertoire in healthy women and female MS patients over the course of pregnancy. Clonality is significantly reduced from the first to third trimester in MS patients, indicating that the T cell repertoire becomes less dominated by expanded clones. However, only a few T cell clones are substantially modulated during pregnancy in each patient. Moreover, relapse-associated T cell clones identified in an individual patient contract during pregnancy and expand during a postpartum relapse. Our data provide evidence that profiling the T cell repertoire during pregnancy could serve as a tool to discover and track "private" T cell clones associated with disease activity in autoimmunity.

The naive T-cell receptor repertoire has an extremely broad distribution of clone sizes

The clone size distribution of the human naive T-cell receptor (TCR) repertoire is an important determinant of adaptive immunity. We estimated the abundance of TCR sequences in samples of naive T cells from blood using an accurate quantitative sequencing protocol. We observe most TCR sequences only once, consistent with the enormous diversity of the repertoire. However, a substantial number of sequences were observed multiple times. We detect abundant TCR sequences even after exclusion of methodological confounders such as sort contamination, and multiple mRNA sampling from the same cell. By combining experimental data with predictions from models we describe two mechanisms contributing to TCR sequence abundance. TCRα abundant sequences can be primarily attributed to many identical recombination events in different cells, while abundant TCRβ sequences are primarily derived from large clones, which make up a small percentage of the naive repertoire, and could be established early in the development of the T-cell repertoire.

Autoreactive IgG and IgA B Cells Evolve through Distinct Subclass Switch Pathways in the Autoimmune Disease Pemphigus Vulgaris

Lineage analysis of autoreactive B cells can reveal the origins of autoimmunity. In the autoimmune disease pemphigus vulgaris (PV), desmoglein 3 (DSG3) and DSG1 autoantibodies are predominantly of the IgG4 subclass and less frequently of IgG1 and IgA subclasses, prompting us to investigate whether anti-DSG IgG4 B cells share lineages with IgG1, IgA1, and IgA2. Combining subclass-specific B cell deep sequencing with high-throughput antibody screening, we identified 80 DSG-reactive lineages from 4 PV patients. Most anti-DSG IgG4 B cells lacked clonal relationships to other subclasses and preferentially targeted DSG adhesion domains, whereas anti-DSG IgA frequently evolved from or to other subclasses and recognized a broader range of epitopes. Our findings suggest that anti-DSG IgG4 B cells predominantly evolve independently or diverge early from other subclasses and that IgA is most often not the origin of IgG autoreactivity in PV. These data provide insight into how autoreactivity diversifies across B cell subclasses.

Ellebrecht et al. use next-generation sequencing to identify clonal relationships among antigen-specific B cells in the autoimmune disease pemphigus vulgaris. They find that autoreactive IgG4 B cells are largely clonally distinct from autoreactive IgG1 and IgA, thus elucidating the class-switch pathways that diversify and modify an autoimmune response in humans.

Single-Cell High-Throughput Technologies in Cerebrospinal Fluid Research and Diagnostics

High-throughput single-cell technologies have recently emerged as essential tools in biomedical research with great potential for clinical pathology when studying liquid and solid biopsies. We provide an update on current single-cell methods in cerebrospinal fluid research and diagnostics, focusing on high-throughput cell-type specific proteomic and genomic technologies. Proteomic methods comprising flow cytometry and mass cytometry as well as genomic approaches including immune cell repertoire and single-cell transcriptomic studies are critically reviewed and future directions discussed.

De novo Inference of Diversity Genes and Analysis of Non-canonical V(DD)J Recombination in Immunoglobulins

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 de novo 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 de novo 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.

Multispecific Antibody Development Platform Based on Human Heavy Chain Antibodies

Heavy chain-only antibodies (HCAbs) do not associate with light chains and their V_H regions are functional as single domains, forming the smallest active antibody fragment. These V_H regions are ideal building blocks for a variety of antibody-based biologics because they tolerate fusion to other molecules and may also be attached in series to construct multispecific antibodies without the need for protein engineering to ensure proper heavy and light chain pairing. Production of human HCAbs has been impeded by the fact that natural human V_H regions require light chain association and display poor biophysical characteristics when expressed in the absence of light chains. Here, we present an innovative platform for the rapid development of diverse sets of human HCAbs that have been selected in vivo. Our unique approach combines antibody repertoire analysis with immunization of transgenic rats, called UniRats, that produce chimeric HCAbs with fully human V_H domains in response to an antigen challenge. UniRats express HCAbs from large transgenic loci representing the entire productive human heavy chain V(D)J repertoire, mount robust immune responses to a wide array of antigens, exhibit diverse V gene usage and generate large panels of stable, high affinity, antigen-specific molecules.

Network Representation of T-Cell Repertoire- A Novel Tool to Analyze Immune Response to Cancer Formation

The T cell repertoire potentially presents complexity compatible, or greater than, that of the human brain. T cell based immune response is involved with practically every part of human physiology, and high-throughput biology needed to follow the T-cell repertoire has made great leaps with the advent of massive parallel sequencing [1]. Nevertheless, tools to handle and observe the dynamics of this complexity have only recently started to emerge [e.g., 2, 3, 4] in parallel with sequencing technologies. Here, we present a network-based view of the dynamics of the T cell repertoire, during the course of mammary tumors development in a mouse model. The transition from the T cell receptor as a feature, to network-based clustering, followed by network-based temporal analyses, provides novel insights to the workings of the system and provides novel tools to observe cancer progression via the perspective of the immune system. The crux of the approach here is at the network-motivated clustering. The purpose of the clustering step is not merely data reduction and exposing structures, but rather to detect hubs, or attractors, within the T cell receptor repertoire that might shed light on the behavior of the immune system as a dynamic network. The Clone-Attractor is in fact an extension of the clone concept, i.e., instead of looking at particular clones we observe the extended clonal network by assigning clusters to graph nodes and edges to adjacent clusters (editing distance metric). Viewing the system as dynamical brings to the fore the notion of an attractors landscape, hence the possibility to chart this space and map the sample state at a given time to a vector in this large space. Based on this representation we applied two different methods to demonstrate its effectiveness in identifying changes in the repertoire that correlate with changes in the phenotype: (1) network analysis of the TCR repertoire in which two measures were calculated and demonstrated the ability to differentiate control from transgenic samples, and, (2) machine learning classifier capable of both stratifying control and trangenic samples, as well as to stratify pre-cancer and cancer samples.

Epitope Specific Antibodies and T Cell Receptors in the Immune Epitope Database

The Immune Epitope Database (IEDB) is a free public resource which catalogs experiments characterizing immune epitopes. To accommodate data from next generation repertoire sequencing experiments, we recently updated how we capture and query epitope specific antibodies and T cell receptors. Specifically, we are now storing partial receptor sequences sufficient to determine CDRs and VDJ gene usage which are commonly identified by repertoire sequencing. For previously captured full length receptor sequencing data, we have calculated the corresponding CDR sequences and gene usage information using IMGT numbering and VDJ gene nomenclature format. To integrate information from receptors defined at different levels of resolution, we grouped receptors based on their host species, receptor type and CDR3 sequence. As of August 2018, we have cataloged sequence information for more than 22,510 receptors in 18,292 receptor groups, shown to bind to more than 2,241 distinct epitopes. These data are accessible as full exports and through a new dedicated query interface. The later combines the new ability to search by receptor characteristics with previously existing capability to search by epitope characteristics such as the infectious agent the epitope is derived from, or the kind of immune response involved in its recognition. We expect that this comprehensive capture of epitope specific immune receptor information will provide new insights into receptor-epitope interactions, and facilitate the development of novel tools that help in the analysis of receptor repertoire data.

Method for identification of condition-associated public antigen receptor sequences

Diverse repertoires of hypervariable immunoglobulin receptors (TCR and BCR) recognize antigens in the adaptive immune system. The development of immunoglobulin receptor repertoire sequencing methods makes it possible to perform repertoire-wide disease association studies of antigen receptor sequences. We developed a statistical framework for associating receptors to disease from only a small cohort of patients, with no need for a control cohort. Our method successfully identifies previously validated Cytomegalovirus and type one diabetes responsive TCRβ sequences .

T cell receptor sequencing of early-stage breast cancer tumors identifies altered clonal structure of the T cell repertoire

Tumor-infiltrating T cells play an important role in many cancers, and can improve prognosis and yield therapeutic targets. We characterized T cells infiltrating both breast cancer tumors and the surrounding normal breast tissue to identify T cells specific to each, as well as their abundance in peripheral blood. Using immune profiling of the T cell beta-chain repertoire in 16 patients with early-stage breast cancer, we show that the clonal structure of the tumor is significantly different from adjacent breast tissue, with the tumor containing ∼2.5-fold greater density of T cells and higher clonality compared with normal breast. The clonal structure of T cells in blood and normal breast is more similar than between blood and tumor, and could be used to distinguish tumor from normal breast tissue in 14 of 16 patients. Many T cell sequences overlap between tissue and blood from the same patient, including ∼50% of T cells between tumor and normal breast. Both tumor and normal breast contain high-abundance "enriched" sequences that are absent or of low abundance in the other tissue. Many of these T cells are either not detected or detected with very low frequency in the blood, suggesting the existence of separate compartments of T cells in both tumor and normal breast. Enriched T cell sequences are typically unique to each patient, but a subset is shared between many different patients. We show that many of these are commonly generated sequences, and thus unlikely to play an important role in the tumor microenvironment.

Computational Model Reveals Limited Correlation between Germinal Center B-Cell Subclone Abundancy and Affinity: Implications for Repertoire Sequencing

Immunoglobulin repertoire sequencing has successfully been applied to identify expanded antigen-activated B-cell clones that play a role in the pathogenesis of immune disorders. One challenge is the selection of the Ag-specific B cells from the measured repertoire for downstream analyses. A general feature of an immune response is the expansion of specific clones resulting in a set of subclones with common ancestry varying in abundance and in the number of acquired somatic mutations. The expanded subclones are expected to have BCR affinities for the Ag higher than the affinities of the naive B cells in the background population. For these reasons, several groups successfully proceeded or suggested selecting highly abundant subclones from the repertoire to obtain the Ag-specific B cells. Given the nature of affinity maturation one would expect that abundant subclones are of high affinity but since repertoire sequencing only provides information about abundancies, this can only be verified with additional experiments, which are very labor intensive. Moreover, this would also require knowledge of the Ag, which is often not available for clinical samples. Consequently, in general we do not know if the selected highly abundant subclone(s) are also the high(est) affinity subclones. Such knowledge would likely improve the selection of relevant subclones for further characterization and Ag screening. Therefore, to gain insight in the relation between subclone abundancy and affinity, we developed a computational model that simulates affinity maturation in a single GC while tracking individual subclones in terms of abundancy and affinity. We show that the model correctly captures the overall GC dynamics, and that the amount of expansion is qualitatively comparable to expansion observed from B cells isolated from human lymph nodes. Analysis of the fraction of high- and low-affinity subclones among the unexpanded and expanded subclones reveals a limited correlation between abundancy and affinity and shows that the low abundant subclones are of highest affinity. Thus, our model suggests that selecting highly abundant subclones from repertoire sequencing experiments would not always lead to the high(est) affinity B cells. Consequently, additional or alternative selection approaches need to be applied.

Fluctuating fitness shapes the clone-size distribution of immune repertoires

The adaptive immune system relies on the diversity of receptors expressed on the surface of B- and T cells to protect the organism from a vast amount of pathogenic threats. The proliferation and degradation dynamics of different cell types (B cells, T cells, naive, memory) is governed by a variety of antigenic and environmental signals, yet the observed clone sizes follow a universal power-law distribution. Guided by this reproducibility we propose effective models of somatic evolution where cell fate depends on an effective fitness. This fitness is determined by growth factors acting either on clones of cells with the same receptor responding to specific antigens, or directly on single cells with no regard for clones. We identify fluctuations in the fitness acting specifically on clones as the essential ingredient leading to the observed distributions. Combining our models with experiments, we characterize the scale of fluctuations in antigenic environments and we provide tools to identify the relevant growth signals in different tissues and organisms. Our results generalize to any evolving population in a fluctuating environment.

Neutralizing antibodies against West Nile virus identified directly from human B cells by single-cell analysis and next generation sequencing

West Nile virus (WNV) infection is an emerging mosquito-borne disease that can lead to severe neurological illness and currently has no available treatment or vaccine. Using microengraving, an integrated single-cell analysis method, we analyzed a cohort of subjects infected with WNV - recently infected and post-convalescent subjects - and efficiently identified four novel WNV neutralizing antibodies. We also assessed the humoral response to WNV on a single-cell and repertoire level by integrating next generation sequencing (NGS) into our analysis. The results from single-cell analysis indicate persistence of WNV-specific memory B cells and antibody-secreting cells in post-convalescent subjects. These cells exhibited class-switched antibody isotypes. Furthermore, the results suggest that the antibody response itself does not predict the clinical severity of the disease (asymptomatic or symptomatic). Using the nucleotide coding sequences for WNV-specific antibodies derived from single cells, we revealed the ontogeny of expanded WNV-specific clones in the repertoires of recently infected subjects through NGS and bioinformatic analysis. This analysis also indicated that the humoral response to WNV did not depend on an anamnestic response, due to an unlikely previous exposure to the virus. The innovative and integrative approach presented here to analyze the evolution of neutralizing antibodies from natural infection on a single-cell and repertoire level can also be applied to vaccine studies, and could potentially aid the development of therapeutic antibodies and our basic understanding of other infectious diseases.

Diversity index of mucosal resident T lymphocyte repertoire predicts clinical prognosis in gastric cancer

A characteristic immunopathology of human cancers is the induction of tumor antigen-specific T lymphocyte responses within solid tumor tissues. Current strategies for immune monitoring focus on the quantification of the density and differentiation status of tumor-infiltrating T lymphocytes; however, properties of the TCR repertoire ‒ including antigen specificity, clonality, as well as its prognostic significance ‒ remain elusive. In this study, we enrolled 28 gastric cancer patients and collected tumor tissues, adjacent normal mucosal tissues, and peripheral blood samples to study the landscape and compartmentalization of these patients' TCR β repertoire by deep sequencing analyses. Our results illustrated antigen-driven expansion within the tumor compartment and the contracted size of shared clonotypes in mucosa and peripheral blood. Most importantly, the diversity of mucosal T lymphocytes could independently predict prognosis, which strongly underscores critical roles of resident mucosal T-cells in executing post-surgery immunosurveillance against tumor relapse.

Fast multiclonal clusterization of V(D)J recombinations from high-throughput sequencing

BACKGROUND

V(D)J recombinations in lymphocytes are essential for immunological diversity. They are also useful markers of pathologies. In leukemia, they are used to quantify the minimal residual disease during patient follow-up. However, the full breadth of lymphocyte diversity is not fully understood.

RESULTS

We propose new algorithms that process high-throughput sequencing (HTS) data to extract unnamed V(D)J junctions and gather them into clones for quantification. This analysis is based on a seed heuristic and is fast and scalable because in the first phase, no alignment is performed with germline database sequences. The algorithms were applied to TR γ HTS data from a patient with acute lymphoblastic leukemia, and also on data simulating hypermutations. Our methods identified the main clone, as well as additional clones that were not identified with standard protocols.

CONCLUSIONS

The proposed algorithms provide new insight into the analysis of high-throughput sequencing data for leukemia, and also to the quantitative assessment of any immunological profile. The methods described here are implemented in a C++ open-source program called Vidjil.