Post-acute sequelae of COVID-19 (PASC) represent an emerging global crisis. However, quantifiable risk-factors for PASC and their biological associations are poorly resolved. We executed a deep multi-omic, longitudinal investigation of 309 COVID-19 patients from initial diagnosis to convalescence (2-3 months later), integrated with clinical data, and patient-reported symptoms. We resolved four PASC-anticipating risk factors at the time of initial COVID-19 diagnosis: type 2 diabetes, SARS-CoV-2 RNAemia, Epstein-Barr virus viremia, and specific autoantibodies. In patients with gastrointestinal PASC, SARS-CoV-2-specific and CMV-specific CD8 + T cells exhibited unique dynamics during recovery from COVID-19. Analysis of symptom-associated immunological signatures revealed coordinated immunity polarization into four endotypes exhibiting divergent acute severity and PASC. We find that immunological associations between PASC factors diminish over time leading to distinct convalescent immune states. Detectability of most PASC factors at COVID-19 diagnosis emphasizes the importance of early disease measurements for understanding emergent chronic conditions and suggests PASC treatment strategies.

We present an integrated analysis of the clinical measurements, immune cells and plasma multi-omics of 139 COVID-19 patients representing all levels of disease severity, from serial blood draws collected during the first week of infection following diagnosis. We identify a major shift between mild and moderate disease, at which point elevated inflammatory signaling is accompanied by the loss of specific classes of metabolites and metabolic processes. Within this stressed plasma environment at moderate disease, multiple unusual immune cell phenotypes emerge and amplify with increasing disease severity. We condensed over 120,000 immune features into a single axis to capture how different immune cell classes coordinate in response to SARS-CoV-2. This immune-response axis independently aligns with the major plasma composition changes, with clinical metrics of blood clotting, and with the sharp transition between mild and moderate disease. This study suggests that moderate disease may provide the most effective setting for therapeutic intervention.

Summary In order to survey a universe of MHC-presented peptide antigens whose numbers greatly exceed the diversity of the T cell repertoire, T cell receptors (TCRs) are thought to be cross-reactive. However, the nature and extent of TCR cross-reactivity has not been conclusively measured experimentally. We developed a system to identify MHC-presented peptide ligands by combining TCR selection of highly diverse yeast-displayed peptide-MHC libraries with deep sequencing. While we identified hundreds of peptides reactive with each of five different mouse and human TCRs, the selected peptides possessed TCR recognition motifs that bore a close resemblance to their known antigens. This structural conservation of the TCR interaction surface allowed us to exploit deep sequencing information to computationally identify activating microbial and self-ligands for human autoimmune TCRs. The mechanistic basis of TCR cross-reactivity described here enables effective surveillance of diverse self and foreign antigens, but without necessitating degenerate recognition of non-homologous peptides.

TCR-signaling strength generally correlates with peptide-MHC binding affinity; however, exceptions exist. We find high-affinity, yet non-stimulatory, interactions occur with high frequency in the human T cell repertoire. Here, we studied human TCRs that are refractory to activation by pMHC ligands despite robust binding. Analysis of 3D affinity, 2D dwell time, and crystal structures of stimulatory versus non-stimulatory TCR-pMHC interactions failed to account for their different signaling outcomes. Using yeast pMHC display, we identified peptide agonists of a formerly non-responsive TCR. Single-molecule force measurements demonstrated the emergence of catch bonds in the activating TCR-pMHC interactions, correlating with exclusion of CD45 from the TCR-APC contact site. Molecular dynamics simulations of TCR-pMHC disengagement distinguished agonist from non-agonist ligands based on the acquisition of catch bonds within the TCR-pMHC interface. The isolation of catch bonds as a parameter mediating the coupling of TCR binding and signaling has important implications for TCR and antigen engineering for immunotherapy.

SUMMARY Interleukin-2 (IL-2) is a pleiotropic cytokine that regulates immune cell homeostasis, and has been used to treat a range of disorders such as cancer and autoimmune disease. IL-2 signals via interleukin-2 receptor-β (IL-2Rβ):IL-2Rγ heterodimers on cells expressing high (regulatory T cells, Treg) or low (effector cells) amounts of IL-2Rα (CD25). When complexed with IL-2, certain anti-cytokine antibodies preferentially stimulate expansion of Treg (JES6-1) or effector (S4B6) cells, offering a strategy for targeted disease therapy. We found that JES6-1 sterically blocked the IL-2:IL-2Rβ and IL-2:IL-2Rγ interactions, but also allosterically lowered the IL-2:IL-2Rα affinity through a ‘triggered exchange’ mechanism favoring IL-2Rαhi Treg cells, creating a positive feedback loop for IL-2Rαhi cell activation. Conversely, S4B6 sterically blocked the IL-2:IL-2Rα interaction, while also conformationally stabilizing the IL-2:IL-2Rβ interaction, thus stimulating all IL-2 responsive immune cells, particularly IL-2Rβhi effector cells. Our insights provide a molecular blueprint for engineering selectively potentiating therapeutic antibodies.