The T cell receptor (TCR) initiates the elimination of pathogens and tumors by T cells. To avoid damage to the host, the receptor must be capable of discriminating between wild-type and mutated self and nonself peptide ligands presented by host cells. Exactly how the TCR does this is unknown. In resting T cells, the TCR is largely unphosphorylated due to the dominance of phosphatases over the kinases expressed at the cell surface. However, when agonist peptides are presented to the TCR by major histocompatibility complex proteins expressed by antigen-presenting cells (APCs), very fast receptor triggering, i.e., TCR phosphorylation, occurs. Recent work suggests that this depends on the local exclusion of the phosphatases from regions of contact of the T cells with the APCs. Here, we developed and tested a quantitative treatment of receptor triggering reliant only on TCR dwell time in phosphatase-depleted cell contacts constrained in area by cell topography. Using the model and experimentally derived parameters, we found that ligand discrimination likely depends crucially on individual contacts being ∼200 nm in radius, matching the dimensions of the surface protrusions used by T cells to interrogate their targets. The model not only correctly predicted the relative signaling potencies of known agonists and nonagonists but also achieved this in the absence of kinetic proofreading. Our work provides a simple, quantitative, and predictive molecular framework for understanding why TCR triggering is so selective and fast and reveals that, for some receptors, cell topography likely influences signaling outcomes.

The T-cell receptor (TCR) triggers the elimination of pathogens and tumors by T lymphocytes. In order for this to avoid damage to the host, the receptor has to discriminate between thousands of peptide ligands presented by each host cell. Exactly how the TCR does this is unknown. In resting T-cells, the TCR is largely unphosphorylated due to the dominance of phosphatases over kinases expressed at the cell surface. When agonist peptides are presented to the TCR by major histocompatibility complex (MHC) proteins expressed by antigen-presenting cells (APCs), very fast receptor triggering occurs, leading to TCR phosphorylation. Recent work suggests that this depends on the local exclusion of the phosphatases from regions of contact of the T cells with the APCs. Here, we develop and test a quantitative treatment of receptor triggering reliant only upon TCR dwell-time in phosphatase-depleted cell-cell contacts constrained in area by cell topography. Using the model and experimentally-derived parameters, we find that ligand discrimination is possible but that it depends crucially on individual contacts being 400 nm in diameter or smaller, i.e. the size generated by microvilli. The model not only correctly predicts the relative signaling potencies of known agonists and non-agonists, but achieves this in the absence of conventional, multi-step kinetic proof-reading. Our work provides a simple, quantitative and predictive molecular framework for understanding why TCR triggering is so selective and fast, and reveals that for some receptors, cell topography crucially influences signaling outcomes.Significance statementOne approach to testing biological theories is to determine if they are predictive. A simple, theoretical treatment of TCR triggering suggests that ligand discrimination by the receptor relies on just two physical principles: (1) the time TCRs spend in cell-cell contacts depleted of large tyrosine phosphatases; and (2) constraints on contact size imposed by T cells using finger-like protrusions to interrogate their targets. The theory not only allows agonistic and non-agonistic TCR ligands to be distinguished but predicts the relative signalling potencies of agonists with remarkable accuracy. This suggests that the theory captures the essential features of receptor triggering.

Edited by Norma AllewellProgrammed cell death-1 (PD-1) is an inhibitory receptor with an essential role in maintaining peripheral tolerance and is among the most promising immunotherapeutic targets for treating cancer, autoimmunity, and infectious diseases. A complete understanding of the consequences of PD-1 engagement by its ligands, PD-L1 and PD-L2, and of PD-L1 binding to B7-1 requires quantitative analysis of their interactions at the cell surface. We present here the first complete in situ kinetic analysis of the PD-1/PD-ligands/B7-1 system. Consistent with previous solution measurements, we observed higher in situ affinities for human (h) than murine (m) PD-1 interactions, stronger binding of hPD-1 to hPD-L2 than hPD-L1, and comparable binding of mPD-1 to both ligands. However, in contrast to the relatively weak solution affinities, the in situ affinities of PD-1 are as high as those of the T cell receptor for agonist pMHC and of LFA-1 (lymphocyte function-associated antigen 1) for ICAM-1 (intercellular adhesion molecule 1) but significantly lower than that of the B7-1/CTLA-4 interaction, suggesting a distinct basis for PD-1-versus CTLA-4-mediated inhibition. Notably, the in situ interactions of PD-1 are much stronger than that of B7-1 with PD-L1. Overall, the in situ affinity ranking greatly depends on the on-rate instead of the off-rate. In silico simulations predict that PD-1/PD-L1 interactions dominate at interfaces between activated T cells and mature dendritic cells and that these interactions will be highly sensitive to the dynamics of PD-L1 and PD-L2 expression. Our results provide a kinetic framework for better understanding inhibitory PD-1 activity in health and disease.PD-1 2 (CD279) is an immune checkpoint receptor expressed mainly on activated T cells and B cells. Its primary function is to maintain peripheral tolerance within the adaptive immune system. PD-1 deficiency results in spontaneous development of autoimmunity in mouse models (1, 2), and polymorphism of its gene PDCD1 in humans is associated with various autoimmune diseases including systemic lupus erythematosus, rheumatoid arthritis, type I diabetes, etc., among different populations (3). High surface expression of PD-1 has also been found to be a hallmark of T cell exhaustion, where antigen-specific CD8 ϩ T cells lose their ability to combat tumor cells or virus-infected cells (4, 5). Antibody blockade of the PD-1 pathway is able to restore the effector functions of exhausted CD8 ϩ T cells for tumor or viral clearance, and this approach is emerging as a promising immunotherapeutic strategy to treat a wide range of cancer and infectious diseases, e.g. nivolumab and pembrolizumab among others in the pipeline (3, 6). In addition, the more complex functions of PD-1 are evidenced by its important role in the generation and activity of induced regulatory T cells (7-9), its high expression on follicular helper CD4 ϩ T cells (10), the improved cognitive performance in an Alzheimer's mouse model with PD-1 blockade (11), and its expression ...

Klebsiella is a genus of Gram-negative bacteria known to be opportunistic pathogens that may cause a variety of infections in humans. Highly drug-resistant Klebsiella species, especially K. pneumoniae, have emerged rapidly and are becoming a major concern in clinical management. Although K. pneumoniae is considered the most important pathogen within the genus, the true clinical significance of the other species is likely underrecognized due to the inability of conventional microbiological methods to distinguish between the species leading to high rates of misidentification. Bacterial whole-genome sequencing (WGS) enables precise species identification and characterization that other technologies do not allow. Herein, we have characterized the diversity and traits of Klebsiella spp. in community-onset infections by WGS of clinical isolates (n = 105) collected during a prospective sepsis study in Sweden. The sequencing revealed that 32 of the 82 isolates (39.0%) initially identified as K. pneumoniae with routine microbiological methods based on cultures followed by matrix-assisted laser desorption-time of flight mass spectrometry (MALDI-TOF MS) had been misidentified. Of these, 23 were identified as Klebsiella variicola and nine as other members of the K. pneumoniae complex. Comparisons of the number of resistance genes showed that significantly fewer resistance genes were detected in Klebsiella oxytoca compared to K. pneumoniae and K. variicola (both values of p < 0.001). Moreover, a high proportion of the isolates within the K. pneumoniae complex were predicted to be genotypically multidrug-resistant (MDR; 79/84, 94.0%) in contrast to K. oxytoca (3/16, 18.8%) and Klebsiella michiganensis (0/4, 0.0%). All isolates predicted as genotypically MDR were found to harbor the combination of β-lactam, fosfomycin, and quinolone resistance markers. Multi-locus sequence typing (MLST) revealed a high diversity of sequence types among the Klebsiella spp. with ST14 (10.0%) and ST5429 (10.0%) as the most prevalent ones for K. pneumoniae, ST146 for K. variicola (12.0%), and ST176 for K. oxytoca (25.0%). In conclusion, the results from this study highlight the importance of using high-resolution genotypic methods for identification and characterization of clinical Klebsiella spp. isolates. Our findings indicate that infections caused by other members of the K. pneumoniae complex than K. pneumoniae are a more common clinical problem than previously described, mainly due to high rates of misidentifications.

B and T cells are integral parts of the immune system and are implicated in many diseases, e.g. autoimmunity. Towards understanding the biology of B and T cells and subsets thereof, their transcriptomes can be analyzed using single-cell RNA sequencing. In some studies, the V(D)J transcripts encoding the variable regions of the B- and T-cell antigen receptors have been removed before the analyses. However, a systematic analysis of the effects of including versus excluding these genes is currently lacking. We have investigated the effects of these transcripts on unsupervised clustering and down-stream analyses of single-cell RNA sequencing data from B and T cells. We found that exclusion of the B−/T-cell receptor genes prior to unsupervised clustering resulted in clusters that represented biologically meaningful subsets, such as subsets of memory B and memory T cells. Furthermore, pseudo-time and trajectory inference analyses of early B-lineage cells resulted in a developmental pathway from progenitor to immature B cells. In contrast, when the B−/T-cell receptor genes were not removed, with the PCs used for clustering consisting of up to 70% V-genes, this resulted in some clusters being defined exclusively by V-gene segments. These did not represent biologically meaningful subsets; for instance in the early B-lineage cells, these clusters contained cells representing all developmental stages. Thus, in studies of B and T cells, to derive biologically meaningful results, it is imperative to remove the gene sequences that encode B- and T-cell receptors.