Katharine Best

T-cell receptor repertoires share a restricted set of public and abundant CDR3 sequences that are associated with self-related immunity

The T-cell receptor (TCR) repertoire is formed by random recombinations of genomic precursor elements; the resulting combinatorial diversity renders unlikely extensive TCR sharing between individuals. Here, we studied CDR3β amino acid sequence sharing in a repertoire-wide manner, using high-throughput TCR-seq in 28 healthy mice. We uncovered hundreds of public sequences shared by most mice. Public CDR3 sequences, relative to private sequences, are two orders of magnitude more abundant on average, express restricted V/J segments, and feature high convergent nucleic acid recombination. Functionally, public sequences are enriched for MHC-diverse CDR3 sequences that were previously associated with autoimmune, allograft, and tumor-related reactions, but not with anti-pathogen-related reactions. Public CDR3 sequences are shared between mice of different MHC haplotypes, but are associated with different, MHC-dependent, V genes. Thus, despite their random generation process, TCR repertoires express a degree of uniformity in their post-genomic organization. These results, together with numerical simulations of TCR genomic rearrangements, suggest that biases and convergence in TCR recombination combine with ongoing selection to generate a restricted subset of self-associated, public CDR3 TCR sequences, and invite reexamination of the basic mechanisms of T-cell repertoire formation.

Tracking global changes induced in the CD4 T cell receptor repertoire by immunization with a complex antigen using short stretches of CDR3 protein sequence

Motivation: The clonal theory of adaptive immunity proposes that immunological responses are encoded by increases in the frequency of lymphocytes carrying antigen-specific receptors. In this study, we measure the frequency of different T-cell receptors (TcR) in CD4 + T cell populations of mice immunized with a complex antigen, killed Mycobacterium tuberculosis, using high throughput parallel sequencing of the TcRβ chain. Our initial hypothesis that immunization would induce repertoire convergence proved to be incorrect, and therefore an alternative approach was developed that allows accurate stratification of TcR repertoires and provides novel insights into the nature of CD4 + T-cell receptor recognition. Results: To track the changes induced by immunization within this heterogeneous repertoire, the sequence data were classified by counting the frequency of different clusters of short (3 or 4) continuous stretches of amino acids within the antigen binding complementarity determining region 3 (CDR3) repertoire of different mice. Both unsupervised (hierarchical clustering) and supervised (support vector machine) analyses of these different distributions of sequence clusters differentiated between immunized and unimmunized mice with 100% efficiency. The CD4 + TcR repertoires of mice 5 and 14 days postimmunization were clearly different from that of unimmunized mice but were not distinguishable from each other. However, the repertoires of mice 60 days postimmunization were distinct both from naive mice and the day 5/14 animals. Our results reinforce the remarkable diversity of the TcR repertoire, resulting in many diverse private TcRs contributing to the T-cell response even in genetically identical mice responding to the same antigen. However, specific motifs defined by short stretches of amino acids within the CDR3 region may determine TcR specificity and define a new approach to TcR sequence classification. Availability and implementation: The analysis was implemented in R and Python, and source code can be found in Supplementary Data. Contact: b.chain@ucl.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online.

Computational analysis of stochastic heterogeneity in PCR amplification efficiency revealed by single molecule barcoding

The polymerase chain reaction (PCR) is one of the most widely used techniques in molecular biology. In combination with High Throughput Sequencing (HTS), PCR is widely used to quantify transcript abundance for RNA-seq, and in the context of analysis of T and B cell receptor repertoires. In this study, we combine DNA barcoding with HTS to quantify PCR output from individual target molecules. We develop computational tools that simulate both the PCR branching process itself, and the subsequent subsampling which typically occurs during HTS sequencing. We explore the influence of different types of heterogeneity on sequencing output, and compare them to experimental results where the efficiency of amplification is measured by barcodes uniquely identifying each molecule of starting template. Our results demonstrate that the PCR process introduces substantial amplification heterogeneity, independent of primer sequence and bulk experimental conditions. This heterogeneity can be attributed both to inherited differences between different template DNA molecules, and the inherent stochasticity of the PCR process. The results demonstrate that PCR heterogeneity arises even when reaction and substrate conditions are kept as constant as possible, and therefore single molecule barcoding is essential in order to derive reproducible quantitative results from any protocol combining PCR with HTS.

Dynamic Perturbations of the T-Cell Receptor Repertoire in Chronic HIV Infection and following Antiretroviral Therapy.

HIV infection profoundly affects many parameters of the immune system and ultimately leads to AIDS, yet which factors are most important for determining resistance, pathology, and response to antiretroviral treatment – and how best to monitor them – remain unclear. We develop a quantitative high-throughput sequencing pipeline to characterize the TCR repertoires of HIV-infected individuals before and after antiretroviral therapy, working from small, unfractionated samples of peripheral blood. This reveals the TCR repertoires of HIV+ individuals to be highly perturbed, with considerably reduced diversity as a small proportion of sequences are highly overrepresented. HIV also causes specific qualitative changes to the repertoire including an altered distribution of V gene usage, depletion of public TCR sequences, and disruption of TCR networks. Short-term antiretroviral therapy has little impact on most of the global damage to repertoire structure, but is accompanied by rapid changes in the abundance of many individual TCR sequences, decreases in abundance of the most common sequences, and decreases in the majority of HIV-associated CDR3 sequences. Thus, high-throughput repertoire sequencing of small blood samples that are easy to take, store, and process can shed light on various aspects of the T-cell immune compartment and stands to offer insights into patient stratification and immune reconstitution.

Blood transcriptomic diagnosis of pulmonary and extrapulmonary tuberculosis

BACKGROUND. Novel rapid diagnostics for active tuberculosis (TB) are required to overcome the time delays and inadequate sensitivity of current microbiological tests that are critically dependent on sampling the site of disease. Multiparametric blood transcriptomic signatures of TB have been described as potential diagnostic tests. We sought to identify the best transcript candidates as host biomarkers for active TB, extend the evaluation of their specificity by comparison with other infectious diseases, and to test their performance in both pulmonary and extrapulmonary TB. METHODS. Support vector machine learning, combined with feature selection, was applied to new and previously published blood transcriptional profiles in order to identify the minimal TB‑specific transcriptional signature shared by multiple patient cohorts including pulmonary and extrapulmonary TB, and individuals with and without HIV-1 coinfection. RESULTS. We identified and validated elevated blood basic leucine zipper transcription factor 2 (BATF2) transcript levels as a single sensitive biomarker that discriminated active pulmonary and extrapulmonary TB from healthy individuals, with receiver operating characteristic (ROC) area under the curve (AUC) scores of 0.93 to 0.99 in multiple cohorts of HIV-1–negative individuals, and 0.85 in HIV-1–infected individuals. In addition, we identified and validated a potentially novel 4-gene signature comprising CD177, haptoglobin, immunoglobin J chain, and galectin 10 that discriminated active pulmonary and extrapulmonary TB from other febrile infections, giving ROC AUCs of 0.94 to 1. CONCLUSIONS. Elevated blood BATF2 transcript levels provide a sensitive biomarker that discriminates active TB from healthy individuals, and a potentially novel 4-gene transcriptional signature differentiates between active TB and other infectious diseases in individuals presenting with fever. FUNDING. MRC, Wellcome Trust, Rosetrees Trust, British Lung Foundation, NIHR.

Feature selection using a one dimensional naïve Bayes’ classifier increases the accuracy of support vector machine classification of CDR3 repertoires

Motivation: Somatic DNA recombination, the hallmark of vertebrate adaptive immunity, has the potential to generate a vast diversity of antigen receptor sequences. How this diversity captures antigen specificity remains incompletely understood. In this study we use high throughput sequencing to compare the global changes in T cell receptor &bgr; chain complementarity determining region 3 (CDR3&bgr;) sequences following immunization with ovalbumin administered with complete Freunds adjuvant (CFA) or CFA alone. Results: The CDR3&bgr; sequences were deconstructed into short stretches of overlapping contiguous amino acids. The motifs were ranked according to a one‐dimensional Bayesian classifier score comparing their frequency in the repertoires of the two immunization classes. The top ranking motifs were selected and used to create feature vectors which were used to train a support vector machine. The support vector machine achieved high classification scores in a leave‐one‐out validation test reaching >90% in some cases. Summary: The study describes a novel two‐stage classification strategy combining a one‐dimensional Bayesian classifier with a support vector machine. Using this approach we demonstrate that the frequency of a small number of linear motifs three amino acids in length can accurately identify a CD4 T cell response to ovalbumin against a background response to the complex mixture of antigens which characterize Complete Freunds Adjuvant. Availability and implementation: The sequence data is available at www.ncbi.nlm.nih.gov/sra/?term¼SRP075893. The Decombinator package is available at github.com/innate2adaptive/Decombinator. The R package e1071 is available at the CRAN repository https://cran.r‐project.org/web/packages/e1071/index.html. Contact: b.chain@ucl.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online.

Quantitative Characterization of the T Cell Receptor Repertoire of Naïve and Memory Subsets Using an Integrated Experimental and Computational Pipeline Which Is Robust, Economical, and Versatile

The T cell receptor (TCR) repertoire can provide a personalized biomarker for infectious and non-infectious diseases. We describe a protocol for amplifying, sequencing, and analyzing TCRs which is robust, sensitive, and versatile. The key experimental step is ligation of a single-stranded oligonucleotide to the 3′ end of the TCR cDNA. This allows amplification of all possible rearrangements using a single set of primers per locus. It also introduces a unique molecular identifier to label each starting cDNA molecule. This molecular identifier is used to correct for sequence errors and for effects of differential PCR amplification efficiency, thus producing more accurate measures of the true TCR frequency within the sample. This integrated experimental and computational pipeline is applied to the analysis of human memory and naive subpopulations, and results in consistent measures of diversity and inequality. After error correction, the distribution of TCR sequence abundance in all subpopulations followed a power law over a wide range of values. The power law exponent differed between naïve and memory populations, but was consistent between individuals. The integrated experimental and analysis pipeline we describe is appropriate to studies of T cell responses in a broad range of physiological and pathological contexts.

Transcriptional Profiling of Endobronchial Ultrasound-Guided Lymph Node Samples Aids Diagnosis of Mediastinal Lymphadenopathy

Background Endobronchial ultrasound (EBUS)-guided biopsy is the mainstay for investigation of mediastinal lymphadenopathy for laboratory diagnosis of malignancy, sarcoidosis, or TB. However, improved methods for discriminating between TB and sarcoidosis and excluding malignancy are still needed. We sought to evaluate the role of genomewide transcriptional profiling to aid diagnostic processes in this setting. Methods Mediastinal lymph node samples from 88 individuals were obtained by EBUS-guided aspiration for investigation of mediastinal lymphadenopathy and subjected to transcriptional profiling in addition to conventional laboratory assessments. Computational strategies were used to evaluate the potential for using the transcriptome to distinguish between diagnostic categories. Results Molecular signatures associated with granulomas or neoplastic and metastatic processes were clearly discernible in granulomatous and malignant lymph node samples, respectively. Support vector machine (SVM) learning using differentially expressed genes showed excellent sensitivity and specificity profiles in receiver operating characteristic curve analysis with area under curve values > 0.9 for discriminating between granulomatous and nongranulomatous disease, TB and sarcoidosis, and between cancer and reactive lymphadenopathy. A two-step decision tree using SVM to distinguish granulomatous and nongranulomatous disease, then between TB and sarcoidosis in granulomatous cases, and between cancer and reactive lymphadenopathy in nongranulomatous cases, achieved > 90% specificity for each diagnosis and afforded greater sensitivity than existing tests to detect TB and cancer. In some diagnostically ambiguous cases, computational classification predicted granulomatous disease or cancer before pathologic abnormalities were evident. Conclusions Machine learning analysis of transcriptional profiling in mediastinal lymphadenopathy may significantly improve the clinical utility of EBUS-guided biopsies.

The T Cell Response to the Contact Sensitizer Paraphenylenediamine Is Characterized by a Polyclonal Diverse Repertoire of Antigen-Specific Receptors

Paraphenylenediamine (PPD) is a common component of hair dyes and black henna tattoos and can cause skin sensitization and allergic contact dermatitis (ACD). The cutaneous inflammatory reaction associated with ACD is driven by both CD4+ and CD8+ T cells. However, the characteristics of such responses with respect to clonal breadth and magnitude are poorly defined. In this study, we have characterized the in vitro recall response of peripheral blood T cells prepared from PPD-allergic individuals to a PPD–human serum albumin (HSA) conjugate (PPD–HSA). Quantitative high throughput sequencing was used to characterize the changes in the repertoire of T cell receptor (TCR) α and β genes after exposure to antigen in vitro. The PPD conjugate induced expansion of T cells carrying selected TCRs, with around 800 sequences (around 1%) being 8 or more times as abundant after culture than before. The expanded sequences showed strong skewing of V and J usage, consistent with an antigen-driven clonal expansion. The complementarity-determining region 3 sequences of the expanded TCRs could be grouped into several families of related amino acid sequence, but the overall diversity of the expanded sample was not much less than that of a random sample of the same size. The results suggest a model in which PPD–HSA conjugate stimulates a broad diversity of TCRs, with a wide range of stimulation strengths, which manifest as different degrees of in vitro expansion.

Immune Tolerance Maintained by Cooperative Interactions between T Cells and Antigen Presenting Cells Shapes a Diverse TCR Repertoire

The T cell population in an individual needs to avoid harmful activation by self peptides while maintaining the ability to respond to an unknown set of foreign peptides. This property is acquired by a combination of thymic and extra-thymic mechanisms. We extend current models for the development of self/non-self discrimination to consider the acquisition of self-tolerance as an emergent system level property of the overall T cell receptor repertoire. We propose that tolerance is established at the level of the antigen presenting cell/T cell cluster, which facilitates and integrates cooperative interactions between T cells of different specificities. The threshold for self-reactivity is therefore imposed at a population level, and not at the level of the individual T cell/antigen encounter. Mathematically, the model can be formulated as a linear programing optimization problem that can be implemented as a multiplicative update algorithm, which shows a rapid convergence to a stable state. The model constrains self-reactivity within a predefined threshold, but maintains repertoire diversity and cross reactivity which are key characteristics of human T cell immunity. We show further that the size of individual clones in the model repertoire becomes heterogeneous, and that new clones can establish themselves even when the repertoire has stabilized. Our study combines the salient features of the “danger” model of self/non-self discrimination with the concepts of quorum sensing, and extends repertoire generation models to encompass the establishment of tolerance. Furthermore, the dynamic and continuous repertoire reshaping, which underlies tolerance in this model, suggests opportunities for therapeutic intervention to achieve long-term tolerance following transplantation.