Human SARS-CoV-2 challenge uncovers local and systemic response dynamics.

The COVID-19 pandemic is an ongoing global health threat, yet our understanding of the dynamics of early cellular responses to this disease remains limited1. Here in our SARS-CoV-2 human challenge study, we used single-cell multi-omics profiling of nasopharyngeal swabs and blood to temporally resolve abortive, transient and sustained infections in seronegative individuals challenged with pre-Alpha SARS-CoV-2. Our analyses revealed rapid changes in cell-type proportions and dozens of highly dynamic cellular response states in epithelial and immune cells associated with specific time points and infection status. We observed that the interferon response in blood preceded the nasopharyngeal response. Moreover, nasopharyngeal immune infiltration occurred early in samples from individuals with only transient infection and later in samples from individuals with sustained infection. High expression of HLA-DQA2 before inoculation was associated with preventing sustained infection. Ciliated cells showed multiple immune responses and were most permissive for viral replication, whereas nasopharyngeal T cells and macrophages were infected non-productively. We resolved 54 T cell states, including acutely activated T cells that clonally expanded while carrying convergent SARS-CoV-2 motifs. Our new computational pipeline Cell2TCR identifies activated antigen-responding T cells based on a gene expression signature and clusters these into clonotype groups and motifs. Overall, our detailed time series data can serve as a Rosetta stone for epithelial and immune cell responses and reveals early dynamic responses associated with protection against infection.

Neoantigen-directed immune escape in lung cancer evolution.

The interplay between an evolving cancer and a dynamic immune microenvironment remains unclear. Here we analyse 258 regions from 88 early-stage, untreated non-small-cell lung cancers using RNA sequencing and histopathology-assessed tumour-infiltrating lymphocyte estimates. Immune infiltration varied both between and within tumours, with different mechanisms of neoantigen presentation dysfunction enriched in distinct immune microenvironments. Sparsely infiltrated tumours exhibited a waning of neoantigen editing during tumour evolution, indicative of historical immune editing, or copy-number loss of previously clonal neoantigens. Immune-infiltrated tumour regions exhibited ongoing immunoediting, with either loss of heterozygosity in human leukocyte antigens or depletion of expressed neoantigens. We identified promoter hypermethylation of genes that contain neoantigenic mutations as an epigenetic mechanism of immunoediting. Our results suggest that the immune microenvironment exerts a strong selection pressure in early-stage, untreated non-small-cell lung cancers that produces multiple routes to immune evasion, which are clinically relevant and forecast poor disease-free survival.

HLA-DR polymorphism in SARS-CoV-2 infection and susceptibility to symptomatic COVID-19.

SARS-CoV-2 infection results in different outcomes ranging from asymptomatic infection to mild or severe disease and death. Reasons for this diversity of outcome include differences in challenge dose, age, gender, comorbidity and host genomic variation. Human leukocyte antigen (HLA) polymorphisms may influence immune response and disease outcome. We investigated the association of HLAII alleles with case definition symptomatic COVID-19, virus-specific antibody and T-cell immunity. A total of 1364 UK healthcare workers (HCWs) were recruited during the first UK SARS-CoV-2 wave and analysed longitudinally, encompassing regular PCR screening for infection, symptom reporting, imputation of HLAII genotype and analysis for antibody and T-cell responses to nucleoprotein (N) and spike (S). Of 272 (20%) HCW who seroconverted, the presence of HLA-DRB1*13:02 was associated with a 6·7-fold increased risk of case definition symptomatic COVID-19. In terms of immune responsiveness, HLA-DRB1*15:02 was associated with lower nucleocapsid T-cell responses. There was no association between DRB1 alleles and anti-spike antibody titres after two COVID vaccine doses. However, HLA DRB1*15:01 was associated with increased spike T-cell responses following both first and second dose vaccination. Trial registration: NCT04318314 and ISRCTN15677965.

Decombinator V4: an improved AIRR compliant-software package for T-cell receptor sequence annotation?

MOTIVATION: Analysis of the T-cell receptor repertoire is rapidly entering the general toolbox used by researchers interested in cellular immunity. The annotation of T-cell receptors (TCRs) from raw sequence data poses specific challenges, which arise from the fact that TCRs are not germline encoded, and because of the stochastic nature of the generating process. RESULTS: In this study, we report the release of Decombinator V4, a tool for the accurate and fast annotation of large sets of TCR sequences. Decombinator was one of the early Python software packages released to analyse the rapidly increasing flow of T-cell receptor repertoire sequence data. The Decombinator package now provides Python 3 compatibility, incorporates improved sequencing error and PCR bias correction algorithms, and provides output which conforms to the international standards proposed by the Adaptive Immune Receptor Repertoire Community. AVAILABILITY AND IMPLEMENTATION: The entire Decombinator suite is freely available at: https://github.com/innate2adaptive/Decombinator. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

High-throughput sequencing of the T-cell receptor repertoire: pitfalls and opportunities.

T-cell specificity is determined by the T-cell receptor, a heterodimeric protein coded for by an extremely diverse set of genes produced by imprecise somatic gene recombination. Massively parallel high-throughput sequencing allows millions of different T-cell receptor genes to be characterized from a single sample of blood or tissue. However, the extraordinary heterogeneity of the immune repertoire poses significant challenges for subsequent analysis of the data. We outline the major steps in processing of repertoire data, considering low-level processing of raw sequence files and high-level algorithms, which seek to extract biological or pathological information. The latest generation of bioinformatics tools allows millions of DNA sequences to be accurately and rapidly assigned to their respective variable V and J gene segments, and to reconstruct an almost error-free representation of the non-templated additions and deletions that occur. High-level processing can measure the diversity of the repertoire in different samples, quantify V and J usage and identify private and public T-cell receptors. Finally, we discuss the major challenge of linking T-cell receptor sequence to function, and specifically to antigen recognition. Sophisticated machine learning algorithms are being developed that can combine the paradoxical degeneracy and cross-reactivity of individual T-cell receptors with the specificity of the overall T-cell immune response. Computational analysis will provide the key to unlock the potential of the T-cell receptor repertoire to give insight into the fundamental biology of the adaptive immune system and to provide powerful biomarkers of disease.

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 ß chain complementarity determining region 3 (CDR3ß) sequences following immunization with ovalbumin administered with complete Freund's adjuvant (CFA) or CFA alone. Results: The CDR3ß 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 Freund's Adjuvant. Availability and implementation: The sequence data is available at www.ncbi.nlm.nih.gov/sra/?term»SRP075893 . 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.

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 TcRß 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.

FUME-TCRseq Enables Sensitive and Accurate Sequencing of the T-cell Receptor from Limited Input of Degraded RNA.

Genomic analysis of the T-cell receptor (TCR) reveals the strength, breadth, and clonal dynamics of the adaptive immune response to pathogens or cancer. The diversity of the TCR repertoire, however, means that sequencing is technically challenging, particularly for samples with low-quality, degraded nucleic acids. Here, we developed and validated FUME-TCRseq, a robust and sensitive RNA-based TCR sequencing methodology that is suitable for formalin-fixed paraffin-embedded samples and low amounts of input material. FUME-TCRseq incorporates unique molecular identifiers into each molecule of cDNA, allowing correction for sequencing errors and PCR bias. Using RNA extracted from colorectal and head and neck cancers to benchmark the accuracy and sensitivity of FUME-TCRseq against existing methods demonstrated excellent concordance between the datasets. Furthermore, FUME-TCRseq detected more clonotypes than a commercial RNA-based alternative, with shorter library preparation time and significantly lower cost. The high sensitivity and the ability to sequence RNA of poor quality and limited amount enabled quantitative analysis of small numbers of cells from archival tissue sections, which is not possible with other methods. Spatially resolved FUME-TCRseq analysis of colorectal cancers using macrodissected archival samples revealed the shifting T-cell landscapes at the transition to an invasive phenotype and between tumor subclones containing distinct driver alterations. In summary, FUME-TCRseq represents an accurate, sensitive, and low-cost tool for the characterization of T-cell repertoires, particularly in samples with low-quality RNA that have not been accessible using existing methodology. SIGNIFICANCE: FUME-TCRseq is a TCR sequencing methodology that supports sensitive and spatially resolved detection of TCR clones in archival clinical specimens, which can facilitate longitudinal tracking of immune responses through disease course and treatment.

High affinity mAb infusion can enhance maximum affinity maturation during HIV Env immunization.

Antigen-specific antibody infusion is known to enhance or suppress germinal center (GC) responses depending on the affinity of the infusion. We hypothesized that infusing monoclonal antibodies (mAbs) of escalating affinity during an immunization regimen may progressively escalate selection pressure on competing B cells, increasing their affinity. To test this, we immunized mice with HIV envelope gp120 and infused CD4 binding-site (CD4bs)-specific mAbs. While mAb infusion reduced somatic hypermutation (SHM) and affinity in most CD4bs-specific B cells, a sub-population was identified with greater SHM and affinity than control. High-throughput sequencing of plasma cells revealed that CD4bs-specific plasma cells possessed elevated SHM after mAb infusion, with phylogenetic tree topology that suggested more rapid differentiation. We therefore conclude, in accordance with other studies, that high-affinity mAb infusion primarily suppresses recruitment of most competing B cells but can increase and expedite affinity maturation of certain epitope-specific B cells.

Mucosal and systemic immune correlates of viral control after SARS-CoV-2 infection challenge in seronegative adults.

Human infection challenge permits in-depth, early, and pre-symptomatic characterization of the immune response, enabling the identification of factors that are important for viral clearance. Here, we performed intranasal inoculation of 34 young adult, seronegative volunteers with a pre-Alpha severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) strain. Of these participants, 18 (53%) became infected and showed an interferon-dominated mediator response with divergent kinetics between nasal and systemic sites. Peripheral CD4+ and CD8+ T cell activation and proliferation were early and robust but showed distinct kinetic and phenotypic profiles; antigen-specific T cells were largely CD38+Ki67+ and displayed central and effector memory phenotypes. Both mucosal and systemic antibodies became detectable around day 10, but nasal antibodies plateaued after day 14 while circulating antibodies continued to rise. Intensively granular measurements in nasal mucosa and blood allowed modeling of immune responses to primary SARS-CoV-2 infection that revealed CD8+ T cell responses and early mucosal IgA responses strongly associated with viral control, indicating that these mechanisms should be targeted for transmission-reducing intervention.

A cardinal role for cathepsin d in co-ordinating the host-mediated apoptosis of macrophages and killing of pneumococci.

The bactericidal function of macrophages against pneumococci is enhanced by their apoptotic demise, which is controlled by the anti-apoptotic protein Mcl-1. Here, we show that lysosomal membrane permeabilization (LMP) and cytosolic translocation of activated cathepsin D occur prior to activation of a mitochondrial pathway of macrophage apoptosis. Pharmacological inhibition or knockout of cathepsin D during pneumococcal infection blocked macrophage apoptosis. As a result of cathepsin D activation, Mcl-1 interacted with its ubiquitin ligase Mule and expression declined. Inhibition of cathepsin D had no effect on early bacterial killing but inhibited the late phase of apoptosis-associated killing of pneumococci in vitro. Mice bearing a cathepsin D(-/-) hematopoietic system demonstrated reduced macrophage apoptosis in vivo, with decreased clearance of pneumococci and enhanced recruitment of neutrophils to control pulmonary infection. These findings establish an unexpected role for a cathepsin D-mediated lysosomal pathway of apoptosis in pulmonary host defense and underscore the importance of apoptosis-associated microbial killing to macrophage function.

Proteomic evaluation and validation of cathepsin D regulated proteins in macrophages exposed to Streptococcus pneumoniae.

Macrophages are central effectors of innate immune responses to bacteria. We have investigated how activation of the abundant macrophage lysosomal protease, cathepsin D, regulates the macrophage proteome during killing of Streptococcus pneumoniae. Using the cathepsin D inhibitor pepstatin A, we demonstrate that cathepsin D differentially regulates multiple targets out of 679 proteins identified and quantified by eight-plex isobaric tag for relative and absolute quantitation. Our statistical analysis identified 18 differentially expressed proteins that passed all paired t-tests (α = 0.05). This dataset was enriched for proteins regulating the mitochondrial pathway of apoptosis or inhibiting competing death programs. Five proteins were selected for further analysis. Western blotting, followed by pharmacological inhibition or genetic manipulation of cathepsin D, verified cathepsin D-dependent regulation of these proteins, after exposure to S. pneumoniae. Superoxide dismutase-2 up-regulation was temporally related to increased reactive oxygen species generation. Gelsolin, a known regulator of mitochondrial outer membrane permeabilization, was down-regulated in association with cytochrome c release from mitochondria. Eukaryotic elongation factor (eEF2), a regulator of protein translation, was also down-regulated by cathepsin D. Using absence of the negative regulator of eEF2, eEF2 kinase, we confirm that eEF2 function is required to maintain expression of the anti-apoptotic protein Mcl-1, delaying macrophage apoptosis and confirm using a murine model that maintaining eEF2 function is associated with impaired macrophage apoptosis-associated killing of Streptococcus pneumoniae. These findings demonstrate that cathepsin D regulates multiple proteins controlling the mitochondrial pathway of macrophage apoptosis or competing death processes, facilitating intracellular bacterial killing.

Signatures of T cell immunity revealed using sequence similarity with TCRDivER algorithm.

Changes in the T cell receptor (TCR) repertoires have become important markers for monitoring disease or therapy progression. With the rise of immunotherapy usage in cancer, infectious and autoimmune disease, accurate assessment and comparison of the "state" of the TCR repertoire has become paramount. One important driver of change within the repertoire is T cell proliferation following immunisation. A way of monitoring this is by investigating large clones of individual T cells believed to bind epitopes connected to the disease. However, as a single target can be bound by many different TCRs, monitoring individual clones cannot fully account for T cell cross-reactivity. Moreover, T cells responding to the same target often exhibit higher sequence similarity, which highlights the importance of accounting for TCR similarity within the repertoire. This complexity of binding relationships between a TCR and its target convolutes comparison of immune responses between individuals or comparisons of TCR repertoires at different timepoints. Here we propose TCRDivER algorithm (T cell Receptor Diversity Estimates for Repertoires), a global method of T cell repertoire comparison using diversity profiles sensitive to both clone size and sequence similarity. This approach allowed for distinction between spleen TCR repertoires of immunised and non-immunised mice, showing the need for including both facets of repertoire changes simultaneously. The analysis revealed biologically interpretable relationships between sequence similarity and clonality. These aid in understanding differences and separation of repertoires stemming from different biological context. With the rise of availability of sequencing data we expect our tool to find broad usage in clinical and research applications.

Viral infection reveals hidden sharing of TCR CDR3 sequences between individuals.

The T cell receptor is generated by a process of random and imprecise somatic recombination. The number of possible T cell receptors which this process can produce is enormous, greatly exceeding the number of T cells in an individual. Thus, the likelihood of identical TCRs being observed in multiple individuals (public TCRs) might be expected to be very low. Nevertheless such public TCRs have often been reported. In this study we explore the extent of TCR publicity in the context of acute resolving Lymphocytic choriomeningitis virus (LCMV) infection in mice. We show that the repertoire of effector T cells following LCMV infection contains a population of highly shared TCR sequences. This subset of TCRs has a distribution of naive precursor frequencies, generation probabilities, and physico-chemical CDR3 properties which lie between those of classic public TCRs, which are observed in uninfected repertoires, and the dominant private TCR repertoire. We have named this set of sequences "hidden public" TCRs, since they are only revealed following infection. A similar repertoire of hidden public TCRs can be observed in humans after a first exposure to SARS-COV-2. The presence of hidden public TCRs which rapidly expand following viral infection may therefore be a general feature of adaptive immunity, identifying an additional level of inter-individual sharing in the TCR repertoire which may form an important component of the effector and memory response.

Quantifying changes in the T cell receptor repertoire during thymic development.

One of the feats of adaptive immunity is its ability to recognize foreign pathogens while sparing the self. During maturation in the thymus, T cells are selected through the binding properties of their antigen-specific T-cell receptor (TCR), through the elimination of both weakly (positive selection) and strongly (negative selection) self-reactive receptors. However, the impact of thymic selection on the TCR repertoire is poorly understood. Here, we use transgenic Nur77-mice expressing a T-cell activation reporter to study the repertoires of thymic T cells at various stages of their development, including cells that do not pass selection. We combine high-throughput repertoire sequencing with statistical inference techniques to characterize the selection of the TCR in these distinct subsets. We find small but significant differences in the TCR repertoire parameters between the maturation stages, which recapitulate known differentiation pathways leading to the CD4+ and CD8+ subtypes. These differences can be simulated by simple models of selection acting linearly on the sequence features. We find no evidence of specific sequences or sequence motifs or features that are suppressed by negative selection. These results favour a collective or statistical model for T-cell self non-self discrimination, where negative selection biases the repertoire away from self recognition, rather than ensuring lack of self-reactivity at the single-cell level.

From pseudo to real-time dynamics of T cell thymic differentiation.

Numerous methods have recently emerged for ordering single cells along developmental trajectories. However, accurate depiction of developmental dynamics can only be achieved after rescaling the trajectory according to the relative time spent at each developmental point. We formulate a model which estimates local cell densities and fluxes, and incorporates cell division and apoptosis rates, to infer the real-time dimension of the developmental trajectory. We validate the model using mathematical simulations and apply it to experimental high dimensional cytometry data obtained from the mouse thymus to construct the true time profile of the thymocyte developmental process. Our method can easily be implemented in any of the existing tools for trajectory inference.

Generation of a C57BL/6J mouse strain expressing the CD45.1 epitope to improve hematopoietic stem cell engraftment and adoptive cell transfer experiments.

Adoptive cell transfer between genetically identical hosts relies on the use of a congenic marker to distinguish the donor cells from the host cells. CD45, a glycoprotein expressed by all hematopoietic cells, is one of the main congenic markers used because its two isoforms, CD45.1 and CD45.2, can be discriminated by flow cytometry. As a consequence, C57BL/6J (B6; CD45.2) and B6.SJL-Ptprca Pepcb/BoyJ (B6.SJL; CD45.1) mice are widely used in adoptive cell transfer experiments, under the presumption that they differ only at the CD45 (Ptprc) locus. However, recent studies have identified genetic variations between these congenic strains and have notably highlighted a differential expression of cathepsin E (CTSE). The B6.SJL mouse presents a number of functional differences in hematopoietic stem cell engraftment potential and immune cell numbers compared with the B6 mouse. In this study, we showed that B6 and B6.SJL mice also differ in their CD8+ T cell compartment and CD8+ T cell responses to viral infection. We identified Ctse as the most differentially expressed gene between CD8+ T cells of B6 and B6.SJL and demonstrated that the differences reported between these two mouse strains are not due to CTSE. Finally, using CRISPR-Cas9 genome editing, we generated a CD45.1-expressing B6 mouse by inserting one nucleotide mutation (A904G) leading to an amino acid change (K302E) in the Ptprc gene of the B6 mouse. We showed that this new B6-Ptprcem(K302E)Jmar/J mouse resolves the experimental biases reported between the B6 and B6.SJL mouse lines and should thus represent the new gold standard for adoptive cell transfer experiments in B6.

T-cell receptor determinants of response to chemoradiation in locally-advanced HPV16-driven malignancies.

Background: The effect of chemoradiation on the anti-cancer immune response is being increasingly acknowledged; however, its clinical implications in treatment responses are yet to be fully understood. Human papillomavirus (HPV)-driven malignancies express viral oncogenic proteins which may serve as tumor-specific antigens and represent ideal candidates for monitoring the peripheral T-cell receptor (TCR) changes secondary to chemoradiotherapy (CRT). Methods: We performed intra-tumoral and pre- and post-treatment peripheral TCR sequencing in a cohort of patients with locally-advanced HPV16-positive cancers treated with CRT. An in silico computational pipeline was used to cluster TCR repertoire based on epitope-specificity and to predict affinity between these clusters and HPV16-derived epitopes. Results: Intra-tumoral repertoire diversity, intra-tumoral and post-treatment peripheral CDR3ß similarity clustering were predictive of response. In responders, CRT triggered an increase peripheral TCR clonality and clonal relatedness. Post-treatment expansion of baseline peripheral dominant TCRs was associated with response. Responders showed more baseline clustered structures of TCRs maintained post-treatment and displayed significantly more maintained clustered structures. When applying clustering by TCR-specificity methods, responders displayed a higher proportion of intra-tumoral TCRs predicted to recognise HPV16 peptides. Conclusions: Baseline TCR characteristics and changes in the peripheral T-cell clones triggered by CRT are associated with treatment outcome. Maintenance and boosting of pre-existing clonotypes are key elements of an effective anti-cancer immune response driven by CRT, supporting a paradigm in which the immune system plays a central role in the success of CRT in current standard-of-care protocols.