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The highly conserved and essential Plasmodium falciparum reticulocyte-binding protein homolog 5 (PfRH5) has emerged as the leading target for vaccines against the disease-causing blood stage of malaria. However, the features of the human vaccine-induced antibody response that confer highly potent inhibition of malaria parasite invasion into red blood cells are not well defined. Here, we characterize 236 human IgG monoclonal antibodies, derived from 15 donors, induced by the most advanced PfRH5 vaccine. We define the antigenic landscape of this molecule and establish that epitope specificity, antibody association rate, and intra-PfRH5 antibody interactions are key determinants of functional anti-parasitic potency. In addition, we identify a germline IgG gene combination that results in an exceptionally potent class of antibody and demonstrate its prophylactic potential to protect against P. falciparum parasite challenge in vivo. This comprehensive dataset provides a framework to guide rational design of next-generation vaccines and prophylactic antibodies to protect against blood-stage malaria.
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Mycobacterium tuberculosis (Mtb), the causative agent of tuberculosis (TB), remains a global health burden. While Mtb is primarily a respiratory pathogen, it can spread to other organs, including the brain and meninges, causing TB meningitis (TBM). However, little is known about the immunological mechanisms that leads to differential disease across organs. Attention has focused on differences in T cell responses in the control of Mtb in the lungs, but emerging data point to a role for antibodies, as both biomarkers of disease control and as antimicrobial molecules. Given an increasing appreciation for compartmentalized antibody responses across the blood brain barrier, here we characterized the antibody profiles across the blood and brain compartments during TBM, and determined whether Mtb-specific humoral immune responses differed between Mtb infection of the lung (pulmonary TB) and TBM. Using a high throughput systems serology approach, we deeply profiled the antibody responses against 10 different Mtb antigens, including lipoarabinomannan (LAM) and purified protein derivative (PPD), in HIV-negative adults with pulmonary TB (n=10) vs TBM (n=60). Antibody studies included analysis of immunoglobulin isotypes (IgG, IgM, IgA) and subclass levels (IgG1-4), the capacity of Mtb-specific antibodies to bind to Fc receptors or C1q, and to activate innate immune effectors functions (complement and NK cells activation, monocyte or neutrophil phagocytosis). Machine learning methods were applied to characterize serum and CSF responses in TBM, identify prognostic factors associated with disease severity, and define the key antibody features that distinguish TBM from pulmonary TB. In individuals with TBM, we identified CSF-specific antibody profiles that marked a unique and compartmentalized humoral response against Mtb, characterized by an enrichment of Mtb-specific antibodies able to robustly activate complement and drive phagocytosis by monocytes and neutrophils, all of which were associated with milder TBM severity at presentation. Moreover, individuals with TBM exhibited Mtb-specific antibodies in the serum with an increased capacity to activate phagocytosis by monocytes, compared to individuals with pulmonary TB, despite having lower IgG titers and Fcγ receptors (FcγR)-binding capacity. Collectively, these data point to functionally divergent humoral responses depending on the site of infection (i.e. lungs vs brain), and demonstrate a highly compartmentalized Mtb-specific antibody response within the CSF during TBM. Moreover, our results suggest that phagocytosis- and complement-mediating antibodies may promote attenuated neuropathology and milder TBM disease.
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Many diseases emerge from dysregulated cellular signaling, and drugs are often designed to target specific signaling proteins. Off-target effects are, however, common and may ultimately result in failed clinical trials. Here we develop a computer model of the cell's transcriptional response to drugs for improved understanding of their mechanisms of action. The model is based on ensembles of artificial neural networks and simultaneously infers drug-target interactions and their downstream effects on intracellular signaling. With this, it predicts transcription factors' activities, while recovering known drug-target interactions and inferring many new ones, which we validate with an independent dataset. As a case study, we analyze the effects of the drug Lestaurtinib on downstream signaling. Alongside its intended target, FLT3, the model predicts an inhibition of CDK2 that enhances the downregulation of the cell cycle-critical transcription factor FOXM1. Our approach can therefore enhance our understanding of drug signaling for therapeutic design.
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Lyme arthritis, caused by the spirochete Borrelia burgdorferi, is the most common feature of late disseminated Lyme disease in the United States. While most Lyme arthritis resolves with antibiotics, termed "antibiotic-responsive", some individuals develop progressive synovitis despite antibiotic therapy, called "antibiotic-refractory" Lyme arthritis (LA). The primary drivers behind antibiotic-refractory arthritis remain incompletely understood. We performed a matched, cross-compartmental comparison of antibody profiles from blood and joint fluid of individuals with antibiotic-responsive (n = 11) or antibiotic-refractory LA (n = 31). While serum antibody profiles poorly discriminated responsive from refractory patients, a discrete profile of B.burgdorferi-specific antibodies in joint fluid discriminated antibiotic-responsive from refractory LA. Cross-compartmental comparison of antibody glycosylation, IgA1, and antibody-dependent complement deposition (ADCD) revealed more poorly coordinated humoral responses and increased ADCD in refractory disease. These data reveal B.burgdorferi-specific serological markers that may support early stratification and clinical management, and point to antibody-dependent complement activation as a key mechanism underlying persistent disease.
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Chimeric antigen receptor therapies have demonstrated potent efficacy in treating B cell malignancies, but have yet to meaningfully translate to solid tumors. Here, we utilize our pooled screening platform, CARPOOL, to expedite the discovery of CARs with anti-tumor functions necessary for solid tumor efficacy. We performed selections in primary human T cells expressing a library of 1.3×10 6 3 rd generation CARs targeting IL13Rα2, a cancer testis antigen commonly expressed in glioblastoma. Selections were performed for cytotoxicity, proliferation, memory formation, and persistence upon repeated antigen challenge. Each enriched CAR robustly produced the phenotype for which it was selected, and one enriched CAR triggered potent cytotoxicity and long-term proliferation upon in vitro tumor rechallenge. It also showed significantly improved persistence and comparable antigen-specific tumor control in a microphysiological human in vitro model and a xenograft model of human glioblastoma. Taken together, this work demonstrates the utility of extending CARPOOL to diseases beyond hematological malignancies and represents the largest exploration of signaling combinations in human primary cells to date.
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The development of therapeutics and vaccines for human diseases requires a systematic understanding of human biology. Although animal and in vitro culture models can elucidate some disease mechanisms, they typically fail to adequately recapitulate human biology as evidenced by the predominant likelihood of clinical trial failure. To address this problem, we developed AutoTransOP, a neural network autoencoder framework, to map omics profiles from designated species or cellular contexts into a global latent space, from which germane information for different contexts can be identified without the typically imposed requirement of matched orthologues. This approach was found in general to perform at least as well as current alternative methods in identifying animal/culture-specific molecular features predictive of other contexts-most importantly without requiring homology matching. For an especially challenging test case, we successfully applied our framework to a set of inter-species vaccine serology studies, where 1-to-1 mapping between human and non-human primate features does not exist.
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Aprendizado Profundo , Animais , Redes Neurais de ComputaçãoRESUMO
Completion of a COVID-19 vaccination series during pregnancy effectively reduces COVID-19 hospitalization among infants less than 6 months of age. The dynamics of transplacental transfer of maternal vaccine-induced antibodies, and their persistence in infants at 2, 6, 9, and 12 months, have implications for new vaccine development and optimal timing of vaccine administration in pregnancy. We evaluated anti-COVID antibody IgG subclass, Fc-receptor binding profile, and activity against wild-type Spike and RBD plus five variants of concern (VOCs) in 153 serum samples from 100 infants. Maternal IgG1 and IgG3 responses persisted in 2- and 6-month infants to a greater extent than the other IgG subclasses, with high persistence of antibodies binding placental neonatal Fc-receptor and FcγR3A. Lowest persistence was observed against the Omicron RBD-specific region. Maternal vaccine timing, placental Fc-receptor binding capabilities, antibody subclass, fetal sex, and VOC all impact the persistence of antibodies in infants through 12 months of age.
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The anti-tumor function of engineered T cells expressing chimeric antigen receptors (CARs) is dependent on signals transduced through intracellular signaling domains (ICDs). Different ICDs are known to drive distinct phenotypes, but systematic investigations into how ICD architectures direct T cell function-particularly at the molecular level-are lacking. Here, we use single-cell sequencing to map diverse signaling inputs to transcriptional outputs, focusing on a defined library of clinically relevant ICD architectures. Informed by these observations, we functionally characterize transcriptionally distinct ICD variants across various contexts to build comprehensive maps from ICD composition to phenotypic output. We identify a unique tonic signaling signature associated with a subset of ICD architectures that drives durable in vivo persistence and efficacy in liquid, but not solid, tumors. Our findings work toward decoding CAR signaling design principles, with implications for the rational design of next-generation ICD architectures optimized for in vivo function.
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Although young children generally experience mild symptoms following infection with SARS-CoV-2, severe acute and long-term complications can occur. SARS-CoV-2 mRNA vaccines elicit robust immunoglobulin profiles in children ages 5 years and older, and in adults, corresponding with substantial protection against hospitalizations and severe disease. Whether similar immune responses and humoral protection can be observed in vaccinated infants and young children, who have a developing and vulnerable immune system, remains poorly understood. To study the impact of mRNA vaccination on the humoral immunity of infant, we use a system serology approach to comprehensively profile antibody responses in a cohort of children ages 6 months to 5 years who were vaccinated with the mRNA-1273 COVID-19 vaccine (25 µg). Responses are compared with vaccinated adults (100 µg), in addition to naturally infected toddlers and young children. Despite their lower vaccine dose, vaccinated toddlers elicit a functional antibody response as strong as adults, with higher antibody-dependent phagocytosis compared to adults, without report of side effects. Moreover, mRNA vaccination is associated with a higher IgG3-dependent humoral profile against SARS-CoV-2 compared to natural infection, supporting that mRNA vaccination is effective at eliciting a robust antibody response in toddlers and young children.