Autologous T-Cell-Free Antigen Presentation System Unveils hCMV-Specific NK Cell Response.

NK cells play a decisive role in controlling hCMV infection by combining innate and adaptive-like immune reactions. The hCMV-derived VMAPRTLFL (LFL) peptide is a potent activator of NKG2C+ NK cells. Proposed here is an autologous system of LFL stimulation without T lymphocytes and exogenous cytokines that allows us to evaluate NK-cell hCMV-specific responses in more native settings. In this model, we evaluated LFL-induced IFNγ production, focusing on signaling pathways and the degranulation and proliferation of NK cells orchestrated by microenvironment cytokine production and analyzed the transcriptome of expanded NK cells. NK cells of individuals having high anti-hCMV-IgG levels, in contrast to NK cells of hCMV-seronegative and low-positive donors, displayed increased IFNγ production and degranulation and activation levels and enhanced proliferation upon LFL stimulation. Cytokine profiles of these LFL-stimulated cultures demonstrated a proinflammatory shift. LFL-induced NK-cell IFNγ production was dependent on the PI3K and Ras/Raf/Mek signaling pathways, independently of cytokines. In hCMV-seropositive individuals, this model allowed obtaining NK-cell antigen-specific populations proliferating in response to LFL. The transcriptomic profile of these expanded NK cells showed increased adaptive gene expression and metabolic activation. The results complement the existing knowledge about hCMV-specific NK-cell response. This model may be further exploited for the identification and characterization of antigen-specific NK cells.

Convergence, plasticity, and tissue residence of regulatory T cell response via TCR repertoire prism.

Suppressive function of regulatory T cells (Treg) is dependent on signaling of their antigen receptors triggered by cognate self, dietary, or microbial peptides presented on MHC II. However, it remains largely unknown whether distinct or shared repertoires of Treg TCRs are mobilized in response to different challenges in the same tissue or the same challenge in different tissues. Here we use a fixed TCRß chain FoxP3-GFP mouse model to analyze conventional (eCD4) and regulatory (eTreg) effector TCRα repertoires in response to six distinct antigenic challenges to the lung and skin. This model shows highly 'digital' repertoire behavior with easy-to-track challenge-specific TCRα CDR3 clusters. For both eCD4 and eTreg subsets, we observe challenge-specific clonal expansions yielding homologous TCRα clusters within and across animals and exposure sites, which are also reflected in the draining lymph nodes but not systemically. Some CDR3 clusters are shared across cancer challenges, suggesting a response to common tumor-associated antigens. For most challenges, eCD4 and eTreg clonal response does not overlap. Such overlap is exclusively observed at the sites of certain tumor challenges, and not systematically, suggesting transient and local tumor-induced eCD4=>eTreg plasticity. This transition includes a dominant tumor-responding eCD4 CDR3 motif, as well as characteristic iNKT TCRα CDR3. In addition, we examine the homeostatic tissue residency of clonal eTreg populations by excluding the site of challenge from our analysis. We demonstrate that distinct CDR3 motifs are characteristic of eTreg cells residing in particular lymphatic tissues, regardless of the challenge. This observation reveals the tissue-resident, antigen-specific clonal Treg populations.

Structure-based prediction of T cell receptor recognition of unseen epitopes using TCRen.

T cell receptor (TCR) recognition of foreign peptides presented by major histocompatibility complex protein is a major event in triggering the adaptive immune response to pathogens or cancer. The prediction of TCR-peptide interactions has great importance for therapy of cancer as well as infectious and autoimmune diseases but remains a major challenge, particularly for novel (unseen) peptide epitopes. Here we present TCRen, a structure-based method for ranking candidate unseen epitopes for a given TCR. The first stage of the TCRen pipeline is modeling of the TCR-peptide-major histocompatibility complex structure. Then a TCR-peptide residue contact map is extracted from this structure and used to rank all candidate epitopes on the basis of an interaction score with the target TCR. Scoring is performed using an energy potential derived from the statistics of TCR-peptide contact preferences in existing crystal structures. We show that TCRen has high performance in discriminating cognate versus unrelated peptides and can facilitate the identification of cancer neoepitopes recognized by tumor-infiltrating lymphocytes.

Aberrant adaptive immune response underlies genetic susceptibility to tuberculosis.

Mycobacterium tuberculosis (Mtb) remains a major threat worldwide, although only a fraction of infected individuals develops tuberculosis (TB). TB susceptibility is shaped by multiple genetic factors, and we performed comparative immunological analysis of two mouse strains to uncover relevant mechanisms underlying susceptibility and resistance. C57BL/6 mice are relatively TB-resistant, whereas I/St mice are prone to develop severe TB, partly due to the MHC-II allelic variant that shapes suboptimal CD4+ T cell receptor repertoire. We investigated the repertoires of lung-infiltrating helper T cells and B cells at the progressed stage in both strains. We found that lung CD4+ T cell repertoires of infected C57BL/6 but not I/St mice contained convergent TCR clusters with functionally confirmed Mtb specificity. Transcriptomic analysis revealed a more prominent Th1 signature in C57BL/6, and expression of pro-inflammatory IL-16 in I/St lung-infiltrating helper T cells. The two strains also showed distinct Th2 signatures. Furthermore, the humoral response of I/St mice was delayed, less focused, and dominated by IgG/IgM isotypes, whereas C57BL/6 mice generated more Mtb antigen-focused IgA response. We conclude that the inability of I/St mice to produce a timely and efficient anti-Mtb adaptive immune responses arises from a suboptimal helper T cell landscape that also impacts the humoral response, leading to diffuse inflammation and severe disease.