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.

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.

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.

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.

Large clones of pre-existing T cells drive early immunity against SARS-COV-2 and LCMV infection.

T cell responses precede antibody and may provide early control of infection. We analyzed the clonal basis of this rapid response following SARS-COV-2 infection. We applied T cell receptor (TCR) sequencing to define the trajectories of individual T cell clones immediately. In SARS-COV-2 PCR+ individuals, a wave of TCRs strongly but transiently expand, frequently peaking the same week as the first positive PCR test. These expanding TCR CDR3s were enriched for sequences functionally annotated as SARS-COV-2 specific. Epitopes recognized by the expanding TCRs were highly conserved between SARS-COV-2 strains but not with circulating human coronaviruses. Many expanding CDR3s were present at high frequency in pre-pandemic repertoires. Early response TCRs specific for lymphocytic choriomeningitis virus epitopes were also found at high frequency in the preinfection naive repertoire. High-frequency naive precursors may allow the T cell response to respond rapidly during the crucial early phases of acute viral infection.

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.

Evolutionary and immune microenvironment dynamics during neoadjuvant treatment of oesophagael adenocarcinoma.

Locally advanced oesophageal adenocarcinoma (EAC) remains difficult to treat because of common resistance to neoadjuvant therapy and high recurrence rates. The ecological and evolutionary dynamics responsible for treatment failure are incompletely understood. Here, we performed a comprehensive multi-omic analysis of samples collected from EAC patients in the MEMORI clinical trial, revealing major changes in gene expression profiles and immune microenvironment composition that did not appear to be driven by changes in clonal composition. Multi-region multi-timepoint whole exome (300x depth) and paired transcriptome sequencing was performed on 27 patients pre-, during and after neoadjuvant treatment. EAC showed major transcriptomic changes during treatment with upregulation of immune and stromal pathways and oncogenic pathways such as KRAS, Hedgehog and WNT. However, genetic data revealed that clonal sweeps were rare, suggesting that gene expression changes were not clonally driven. Additional longitudinal image mass cytometry was performed in a subset of 15 patients and T-cell receptor sequencing in 10 patients, revealing remodelling of the T-cell compartment during treatment and other shifts in microenvironment composition. The presence of immune escape mechanisms and a lack of clonal T-cell expansions were linked to poor clinical treatment response. This study identifies profound transcriptional changes during treatment with limited evidence that clonal replacement is the cause, suggesting phenotypic plasticity and immune dynamics as mechanisms for therapy resistance with pharmacological relevance.

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.

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.

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.

The Intra-Tumoral T Cell Receptor Repertoire: Steps Towards a Useful Clinical Biomarker.

Adaptive immunity recognizes and responds to tumors, although they are part of the immunological "self." T cells, both CD4+ and CD8+, play a key role in the process, and the specific set of receptors which recognize tumor antigens therefore has the potential to provide prognostic biomarkers for tracking tumor growth after cancer therapy, including immunotherapy. Most published data on the T cell repertoire continue to rely on commercial proprietary methods, which often do not allow access to the raw data, and are difficult to validate. We describe an open-source protocol for amplifying, sequencing, and analyzing T cell receptors which is economical, robust, sensitive, and versatile. The key experimental step is the ligation of a single-stranded oligonucleotide to the 3' end of the T cell receptor cDNA, which allows easy amplification of all possible rearrangements using only a single set of primers per locus, while simultaneously introducing a unique molecular identifier to label each starting cDNA molecule. After sequencing, this molecular identifier can be used to correct both sequence errors and the effects of differential PCR amplification efficiency, thus producing a more accurate measure of the true T cell receptor frequency within the sample. Samples are then tagged with unique pairs of indices, facilitating robotic scale-up and significantly reducing cross-sample contamination from index hopping. This method has been applied to the analysis of tumor-infiltrating lymphocytes and matched peripheral blood samples from patients with a variety of solid tumors.

A hierarchy of selection pressures determines the organization of the T cell receptor repertoire.

We systematically examine the receptor repertoire in T cell subsets in young, adult, and LCMV-infected mice. Somatic recombination generates diversity, resulting in the limited overlap between nucleotide sequences of different repertoires even within the same individual. However, statistical features of the repertoire, quantified by the V gene and CDR3 k-mer frequency distributions, are highly conserved. A hierarchy of immunological processes drives the evolution of this structure. Intra-thymic divergence of CD4+ and CD8+ lineages imposes subtle but dominant differences observed across repertoires of all subpopulations in both young and adult mice. Differentiation from naive through memory to effector phenotype imposes an additional gradient of repertoire diversification, which is further influenced by age in a complex and lineage-dependent manner. The distinct repertoire of CD4+ regulatory T cells is more similar to naive cells in young mice and to effectors in adults. Finally, we describe divergent (naive and memory) and convergent (CD8+ effector) evolution of the repertoire following acute infection with LCMV. This study presents a quantitative framework that captures the structure of the repertoire in terms of its fundamental statistical properties and describes how this structure evolves as individual T cells differentiate, migrate and mature in response to antigen exposure.

The importance of taking ART appropriately in children and adolescents with HIV-1 to reach the highest capacity of immune function later in life.

Current antiretroviral therapy (ART) guidelines recommend treating all children with HIV-1 infection. This has changed from the broader use of ART to treat children to improve morbidity and minimise mortality. However, prior to current recommendations, not everyone with HIV-1 received timely treatment. What happens to the paediatric immune system when HIV-1 replication is not appropriately supressed remains unclear. 11 samples from adolescents with HIV-1 on ART and uninfected controls in the UK, aged 12-25 years, were examined; overall, adolescents with CD4+ counts > 500/µl and a viral load < 50 copies/ml were compared with adolescents with CD4+ counts < 500/µl and a viral load > 50 copies/ml at time of sampling. Measurements of thymic output were combined with high throughput next generation sequencing and bioinformatics to systematically organize CD4+ and CD8+ T cell receptor (TCR) repertoires. TCR repertoire diversity, clonal expansions, TCR sequence sharing, and formation of TCR clusters in HIV-1 infected adolescents with successful HIV-1 suppression were compared to adolescents with ineffective HIV-1 suppression. Thymic output and CD4+ T cell numbers were decreased in HIV-1 infected adolescents with poor HIV-1 suppression. A strong homeostatic TCR response, driven by the decreased CD4+ T cell compartment and reduced thymic output was observed in the virally uncontrolled HIV-1-infected adolescents. Formation of abundant robust TCR clusters and structurally related TCRs were found in the adolescents with effective HIV-1 suppression. Numerous CD4+ T cell numbers in the virally controlled adolescents emphasize the importance of high thymic output and formation of robust TCR clusters in the maintenance of HIV-1 suppression. While the profound capacity for immune recovery in children may allow better opportunity to deal with immunological stress, when ART is taken appropriately, this study demonstrates new insights into the unique paediatric immune system and the immunological changes when HIV-1 replication is ongoing.

Tracking down tumor-specific T cells.

Two papers published in this edition of Cancer Cell (Zheng et al., 2022 and Veatch et al., 2022) provide an elegant illustration of how single-cell sequencing can be used to define a molecular phenotype which identifies tumor-specific T cells.

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.

Plasticity of the Immune System in Children Following Treatment Interruption in HIV-1 Infection.

It is intriguing that, unlike adults with HIV-1, children with HIV-1 reach a greater CD4+ T cell recovery following planned treatment cessation. The reasons for the better outcomes in children remain unknown but may be related to increased thymic output and diversity of T cell receptor repertoires. HIV-1 infected children from the PENTA 11 trial tolerated planned treatment interruption without adverse long-term clinical, virological, or immunological consequences, once antiretroviral therapy was re-introduced. This contrasts to treatment interruption trials of HIV-1 infected adults, who had rapid changes in T cells and slow recovery when antiretroviral therapy was restarted. How children can develop such effective immune responses to planned treatment interruption may be critical for future studies. PENTA 11 was a randomized, phase II trial of planned treatment interruptions in HIV-1-infected children (ISRCTN 36694210). In this sub-study, eight patients in long-term follow-up were chosen with CD4+ count>500/ml, viral load <50c/ml at baseline: four patients on treatment interruption and four on continuous treatment. Together with measurements of thymic output, we used high-throughput next generation sequencing and bioinformatics to systematically organize memory CD8+ and naïve CD4+ T cell receptors according to diversity, clonal expansions, sequence sharing, antigen specificity, and T cell receptor similarities following treatment interruption compared to continuous treatment. We observed an increase in thymic output following treatment interruption compared to continuous treatment. This was accompanied by an increase in T cell receptor clonal expansions, increased T cell receptor sharing, and higher sequence similarities between patients, suggesting a more focused T cell receptor repertoire. The low numbers of patients included is a limitation and the data should be interpreted with caution. Nonetheless, the high levels of thymic output and the high diversity of the T cell receptor repertoire in children may be sufficient to reconstitute the T cell immune repertoire and reverse the impact of interruption of antiretroviral therapy. Importantly, the effective T cell receptor repertoires following treatment interruption may inform novel therapeutic strategies in children infected with HIV-1.

Predicting T Cell Receptor Antigen Specificity From Structural Features Derived From Homology Models of Receptor-Peptide-Major Histocompatibility Complexes.

The physical interaction between the T cell receptor (TCR) and its cognate antigen causes T cells to activate and participate in the immune response. Understanding this physical interaction is important in predicting TCR binding to a target epitope, as well as potential cross-reactivity. Here, we propose a way of collecting informative features of the binding interface from homology models of T cell receptor-peptide-major histocompatibility complex (TCR-pMHC) complexes. The information collected from these structures is sufficient to discriminate binding from non-binding TCR-pMHC pairs in multiple independent datasets. The classifier is limited by the number of crystal structures available for the homology modelling and by the size of the training set. However, the classifier shows comparable performance to sequence-based classifiers requiring much larger training sets.

Information-Driven Docking for TCR-pMHC Complex Prediction.

T cell receptor (TCR) recognition of peptides presented by major histocompatibility complex (MHC) molecules is a fundamental process in the adaptive immune system. An understanding of this recognition process at the molecular level is crucial for TCR based therapeutics and vaccine design. The broad nature of TCR diversity and cross-reactivity presents a challenge for traditional structural resolution. Computational modelling of TCR-pMHC complexes offers an efficient alternative. This study compares the ability of four general-purpose docking platforms (ClusPro, LightDock, ZDOCK and HADDOCK) to make use of varying levels of binding interface information for accurate TCR-pMHC modelling. Each platform was tested on an expanded benchmark set of 44 TCR-pMHC docking cases. In general, HADDOCK is shown to be the best performer. Docking strategy guidance is provided to obtain the best models for each platform for future research. The TCR-pMHC docking cases used in this study can be downloaded from https://github.com/innate2adaptive/ExpandedBenchmark.