Dissecting Polyclonal Vaccine-Induced Humoral Immunity against HIV Using Systems Serology.

While antibody titers and neutralization are considered the gold standard for the selection of successful vaccines, these parameters are often inadequate predictors of protective immunity. As antibodies mediate an array of extra-neutralizing Fc functions, when neutralization fails to predict protection, investigating Fc-mediated activity may help identify immunological correlates and mechanism(s) of humoral protection. Here, we used an integrative approach termed Systems Serology to analyze relationships among humoral responses elicited in four HIV vaccine trials. Each vaccine regimen induced a unique humoral "Fc fingerprint." Moreover, analysis of case:control data from the first moderately protective HIV vaccine trial, RV144, pointed to mechanistic insights into immune complex composition that may underlie protective immunity to HIV. Thus, multi-dimensional relational comparisons of vaccine humoral fingerprints offer a unique approach for the evaluation and design of novel vaccines against pathogens for which correlates of protection remain elusive.

Evaluation of vaginal microbiome equilibrium states identifies microbial parameters linked to resilience after menses and antibiotic therapy.

The vaginal microbiome (VMB) is a complex microbial community that is closely tied to reproductive health. Optimal VMB communities have compositions that are commonly defined by the dominance of certain Lactobacillus spp. and can remain stable over time or transition to non-optimal states dominated by anaerobic bacteria and associated with bacterial vaginosis (BV). The ability to remain stable or undergo transitions suggests a system with either single (mono-stable) or multiple (multi-stable) equilibrium states, though factors that contribute to stability have been difficult to determine due to heterogeneity in microbial growth characteristics and inter-species interactions. Here, we use a computational model to determine whether differences in microbial growth and interaction parameters could alter equilibrium state accessibility and account for variability in community composition after menses and antibiotic therapies. Using a global uncertainty and sensitivity analysis that captures parameter sets sampled from a physiologically relevant range, model simulations predicted that 79.7% of microbial communities were mono-stable (gravitate to one composition type) and 20.3% were predicted to be multi-stable (can gravitate to more than one composition type, given external perturbations), which was not significantly different from observations in two clinical cohorts (HMP cohort, 75.2% and 24.8%; Gajer cohort, 78.1% and 21.9%, respectively). The model identified key microbial parameters that governed equilibrium state accessibility, such as the importance of non-optimal anaerobic bacteria interactions with Lactobacillus spp., which is largely understudied. Model predictions for composition changes after menses and antibiotics were not significantly different from those observed in clinical cohorts. Lastly, simulations were performed to illustrate how this quantitative framework can be used to gain insight into the development of new combinatorial therapies involving altered prebiotic and antibiotic dosing strategies. Altogether, dynamical models could guide development of more precise therapeutic strategies to manage BV.

Impact of vaginal microbiome communities on HIV antiretroviral-based pre-exposure prophylaxis (PrEP) drug metabolism.

Despite the efficacy of antiretroviral-based pre-exposure prophylactics (PrEP) in men who have sex with men, studies in women have produced widely varying outcomes. Recent evidence demonstrates that vaginal microbial communities are associated with increased HIV acquisition risk and may impact PrEP efficacy. Here, we investigate the mechanisms underlying how vaginal bacteria alter PrEP drug levels and impact HIV infection rates ex vivo. Using cervicovaginal lavages (CVLs) from women with or without bacterial vaginosis (BV), we identified microbial metabolism of PrEP drugs in BV samples through LC-MS/MS analysis of soluble drug levels and metabolite formation in dual T-cell cultures. CVL samples were assessed for microbiome analysis using sequencing of bacterial 16S rRNA genes. We also observed non-Lactobacillus bacteria that are associated with BV may potentially impact PrEP efficacy through increased HIV infection rates in co-cultures containing Lactobacillus or BV bacteria, PrEP drugs, CEM-GFP cells, and HIV-1LAI virus. Finally, we used these data to develop a novel predictive mathematical simulation modeling system to predict these drug interactions for future trials. These studies demonstrate how dysbiotic vaginal microbiota may impact PrEP drugs and provides evidence linking vaginal bacteria to PrEP efficacy in women.

Lung Microbiota Contribute to Pulmonary Inflammation and Disease Progression in Pulmonary Fibrosis.

Rationale: Idiopathic pulmonary fibrosis (IPF) causes considerable global morbidity and mortality, and its mechanisms of disease progression are poorly understood. Recent observational studies have reported associations between lung dysbiosis, mortality, and altered host defense gene expression, supporting a role for lung microbiota in IPF. However, the causal significance of altered lung microbiota in disease progression is undetermined. Objectives: To examine the effect of microbiota on local alveolar inflammation and disease progression using both animal models and human subjects with IPF. Methods: For human studies, we characterized lung microbiota in BAL fluid from 68 patients with IPF. For animal modeling, we used a murine model of pulmonary fibrosis in conventional and germ-free mice. Lung bacteria were characterized using 16S rRNA gene sequencing with novel techniques optimized for low-biomass sample load. Microbiota were correlated with alveolar inflammation, measures of pulmonary fibrosis, and disease progression. Measurements and Main Results: Disruption of the lung microbiome predicts disease progression, correlates with local host inflammation, and participates in disease progression. In patients with IPF, lung bacterial burden predicts fibrosis progression, and microbiota diversity and composition correlate with increased alveolar profibrotic cytokines. In murine models of fibrosis, lung dysbiosis precedes peak lung injury and is persistent. In germ-free animals, the absence of a microbiome protects against mortality. Conclusions: Our results demonstrate that lung microbiota contribute to the progression of IPF. We provide biological plausibility for the hypothesis that lung dysbiosis promotes alveolar inflammation and aberrant repair. Manipulation of lung microbiota may represent a novel target for the treatment of IPF.

Lung Dysbiosis, Inflammation, and Injury in Hematopoietic Cell Transplantation.

RATIONALE: Hematopoietic cell transplant (HCT) is a common treatment for hematological neoplasms and autoimmune disorders. Among HCT recipients, pulmonary complications are common, morbid, and/or lethal, and they have recently been associated with gut dysbiosis. The role of lung microbiota in post-HCT pulmonary complications is unknown. OBJECTIVES: To investigate the role of lung microbiota in post-HCT pulmonary complications using animal modeling and human BAL fluid. METHODS: For animal modeling, we used an established murine model of HCT with and without postengraftment herpes virus infection. For human studies, we characterized lung microbiota in BAL fluid from 43 HCT recipients. Lung bacteria were characterized using 16S ribosomal RNA gene sequencing and were compared with lung histology (murine) and with alveolar inflammation and pulmonary function testing (human). MEASUREMENTS AND MAIN RESULTS: Both HCT and viral infection independently altered the composition of murine lung microbiota, but they had no effect on lung microbial diversity. By contrast, combined HCT and viral infection profoundly altered lung microbiota, decreasing community diversity with an associated pneumonitis. Among human HCT recipients, increased relative abundance of the Proteobacteria phylum was associated with impaired pulmonary function, and lung microbiota were significantly associated with alveolar concentrations of inflammatory cytokines. CONCLUSIONS: In animal models and human subjects, lung dysbiosis is a prominent feature of HCT. Lung dysbiosis is correlated with histologic, immunologic, and physiologic features of post-HCT pulmonary complications. Our findings suggest the lung microbiome may be an unappreciated target for the prevention and treatment of post-HCT pulmonary complications.

Prospects from systems serology research.

Antibodies are highly functional glycoproteins capable of providing immune protection through multiple mechanisms, including direct pathogen neutralization and the engagement of their Fc portions with surrounding effector immune cells that induce anti-pathogenic responses. Small modifications to multiple antibody biophysical features induced by vaccines can significantly alter functional immune outcomes, though it is difficult to predict which combinations confer protective immunity. In order to give insight into the highly complex and dynamic processes that drive an effective humoral immune response, here we discuss recent applications of 'Systems Serology', a new approach that uses data-driven (also called 'machine learning') computational analysis and high-throughput experimental data to infer networks of important antibody features associated with protective humoral immunity and/or Fc functional activity. This approach offers the ability to understand humoral immunity beyond single correlates of protection, assessing the relative importance of multiple biophysical modifications to antibody features with multivariate computational approaches. Systems Serology has the exciting potential to help identify novel correlates of protection from infection and may generate a more comprehensive understanding of the mechanisms behind protection, including key relationships between specific Fc functions and antibody biophysical features (e.g. antigen recognition, isotype, subclass and/or glycosylation events). Reviewed here are some of the experimental and computational technologies available for Systems Serology research and evidence that the application has broad relevance to multiple different infectious diseases including viruses, bacteria, fungi and parasites.

Proteomics: Clinical and research applications in respiratory diseases.

The proteome is the study of the protein content of a definable component of an organism in biology. However, the tissue-specific expression of proteins and the varied post-translational modifications, splice variants and protein-protein complexes that may form, make the study of protein a challenging yet vital tool in answering many of the unanswered questions in medicine and biology to date. Indeed, the spatial, temporal and functional composition of proteins in the human body has proven difficult to elucidate for many years. Given the effect of microRNA and epigenetic regulation on silencing and enhancing gene transcription, the study of protein arguably provides more accurate information on homeostasis and perturbation in health and disease. There have been significant advances in the field of proteomics in recent years, with new technologies and platforms available to the research community. In this review, we briefly discuss some of these new technologies and developments in the context of respiratory disease. We also discuss the types of data science approaches to analyses and interpretation of the large volumes of data generated in proteomic studies. We discuss the application of these technologies with regard to respiratory disease and highlight the potential for proteomics in generating major advances in the understanding of respiratory pathophysiology into the future.

Systems analysis of dynamic transcription factor activity identifies targets for treatment in Olaparib resistant cancer cells.

The development of resistance to targeted therapeutics is a challenging issue for the treatment of cancer. Cancers that have mutations in BRCA, a DNA repair protein, have been treated with poly(ADP-ribose) polymerase (PARP) inhibitors, which target a second DNA repair mechanism with the aim of inducing synthetic lethality. While these inhibitors have shown promise clinically, the development of resistance can limit their effectiveness as a therapy. This study investigated mechanisms of resistance in BRCA-mutated cancer cells (HCC1937) to Olaparib (AZD2281) using TRACER, a technique for measuring dynamics of transcription factor (TF) activity in living cells. TF activity was monitored in the parental HCC1937 cell line and two distinct resistant cell lines, one with restored wild-type BRCA1 and one with acquired resistance independent of BRCA1 for 48 h during treatment with Olaparib. Partial least squares discriminant analysis (PLSDA) was used to categorize the three cell types based on TF activity, and network analysis was used to investigate the mechanism of early response to Olaparib in the study cells. NOTCH signaling was identified as a common pathway linked to resistance in both Olaparib-resistant cell types. Western blotting confirmed upregulation of NOTCH protein, and sensitivity to Olaparib was restored through co-treatment with a gamma secretase inhibitor. The identification of NOTCH signaling as a common pathway contributing to PARP inhibitor resistance by TRACER indicates the efficacy of transcription factor dynamics in identifying targets for intervention in treatment-resistant cancer and provides a new method for determining effective strategies for directed chemotherapy. Biotechnol. Bioeng. 2017;114: 2085-2095. © 2017 Wiley Periodicals, Inc.

Molecular Signatures of Immune Activation and Epithelial Barrier Remodeling Are Enhanced during the Luteal Phase of the Menstrual Cycle: Implications for HIV Susceptibility.

UNLABELLED: The variable infectivity and transmissibility of HIV/SHIV has been recently associated with the menstrual cycle, with particular susceptibility observed during the luteal phase in nonhuman primate models and ex vivo human explant cultures, but the mechanism is poorly understood. Here, we performed an unbiased, mass spectrometry-based proteomic analysis to better understand the mucosal immunological processes underpinning this observed susceptibility to HIV infection. Cervicovaginal lavage samples (n = 19) were collected, characterized as follicular or luteal phase using days since last menstrual period, and analyzed by tandem mass spectrometry. Biological insights from these data were gained using a spectrum of computational methods, including hierarchical clustering, pathway analysis, gene set enrichment analysis, and partial least-squares discriminant analysis with LASSO feature selection. Of the 384 proteins identified, 43 were differentially abundant between phases (P < 0.05, ≥2-fold change). Cell-cell adhesion proteins and antiproteases were reduced, and leukocyte recruitment (interleukin-8 pathway, P = 1.41E-5) and extravasation proteins (P = 5.62E-4) were elevated during the luteal phase. LASSO/PLSDA identified a minimal profile of 18 proteins that best distinguished the luteal phase. This profile included cytoskeletal elements and proteases known to be involved in cellular movement. Gene set enrichment analysis associated CD4(+) T cell and neutrophil gene set signatures with the luteal phase (P < 0.05). Taken together, our findings indicate a strong association between proteins involved in tissue remodeling and leukocyte infiltration with the luteal phase, which may represent potential hormone-associated mechanisms of increased susceptibility to HIV. IMPORTANCE: Recent studies have discovered an enhanced susceptibility to HIV infection during the progesterone-dominant luteal phase of the menstrual cycle. However, the mechanism responsible for this enhanced susceptibility has not yet been determined. Understanding the source of this vulnerability will be important for designing efficacious HIV prevention technologies for women. Furthermore, these findings may also be extrapolated to better understand the impact of exogenous hormone application, such as the use of hormonal contraceptives, on HIV acquisition risk. Hormonal contraceptives are the most widely used contraceptive method in sub-Saharan Africa, the most HIV-burdened area of the world. For this reason, research conducted to better understand how hormones impact host immunity and susceptibility factors important for HIV infection is a global health priority.

Inflammatory cytokine biomarkers to identify women with asymptomatic sexually transmitted infections and bacterial vaginosis who are at high risk of HIV infection.

BACKGROUND: Untreated sexually transmitted infections (STIs) and bacterial vaginosis (BV) cause genital inflammation and increase the risk of HIV infection. WHO-recommended syndromic STI and BV management is severely limited as many women with asymptomatic infections go untreated. The purpose of this cross-sectional study was to evaluate genital cytokine profiles as a biomarker of STIs and BV to identify women with asymptomatic, treatable infections. METHODS: Concentrations of 42 cytokines in cervicovaginal lavages from 227 HIV-uninfected women were measured using Luminex. All women were screened for BV by microscopy and STIs using molecular assays. Multivariate analyses were used to identify cytokine profiles associated with STIs/BV. RESULTS: A multivariate profile of seven cytokines (interleukin (IL)-1α, IL-1ß, tumour necrosis factor-ß, IL-4, fractalkine, macrophage-derived chemokine, and interferon-γ) most accurately predicted the presence of a treatable genital condition, with 77% classification accuracy and 75% cross-validation accuracy (sensitivity 72%; specificity 81%, positive predictive value (PPV) 86%, negative predictive value (NPV) 64%). Concomitant increased IL-1ß and decreased IP-10 concentrations predicted the presence of a treatable genital condition without a substantial reduction in predictive value (sensitivity 77%, specificity 72%, PPV 82% and NPV 65%), correctly classifying 75% of the women. This approach performed substantially better than clinical signs (sensitivity 19%, specificity 92%, PPV 79% and NPV 40%). CONCLUSIONS: Supplementing syndromic management with an assessment of IL-1ß and IP-10 as biomarkers of genital inflammation may improve STI/BV management for women, enabling more effective treatment of asymptomatic infections and potentially reducing their risk of HIV infection.

Genital inflammation and the risk of HIV acquisition in women.

BACKGROUND: Women in Africa, especially young women, have very high human immunodeficiency virus (HIV) incidence rates that cannot be fully explained by behavioral risks. We investigated whether genital inflammation influenced HIV acquisition in this group. METHODS: Twelve selected cytokines, including 9 inflammatory cytokines and chemokines (interleukin [IL]-1α, IL-1ß, IL-6, tumor necrosis factor-α, IL-8, interferon-γ inducible protein-10 [IP-10], monocyte chemoattractant protein-1, macrophage inflammatory protein [MIP]-1α, MIP-1ß), hematopoietic IL-7, and granulocyte macrophage colony-stimulating factor, and regulatory IL-10 were measured prior to HIV infection in cervicovaginal lavages from 58 HIV seroconverters and 58 matched uninfected controls and in plasma from a subset of 107 of these women from the Centre for the AIDS Programme of Research in South Africa 004 tenofovir gel trial. RESULTS: HIV seroconversion was associated with raised genital inflammatory cytokines (including chemokines MIP-1α, MIP-1ß, and IP-10). The risk of HIV acquisition was significantly higher in women with evidence of genital inflammation, defined by at least 5 of 9 inflammatory cytokines being raised (odds ratio, 3.2; 95% confidence interval, 1.3-7.9; P = .014). Genital cytokine concentrations were persistently raised (for about 1 year before infection), with no readily identifiable cause despite extensive investigation of several potential factors, including sexually transmitted infections and systemic cytokines. CONCLUSIONS: Elevated genital concentrations of HIV target cell-recruiting chemokines and a genital inflammatory profile contributes to the high risk of HIV acquisition in these African women.

Engineered Immunologic Niche Monitors Checkpoint Blockade Response and Probes Mechanisms of Resistance.

Antibodies to programmed cell death protein1 (anti-PD-1) have become a promising immunotherapy for triple negative breast cancer (TNBC), blocking PD-L1 signaling from pro-tumor cells through T cell PD-1 receptor binding. Nevertheless, only 10-20% of PD-L1+ metastatic TNBC patients who meet criteria benefit from ICB, and biomarkers to predict patient response have been elusive. We have previously developed an immunological niche, consisting of a microporous implant in the subcutaneous space, that supports tissue formation whose immune composition is consistent with that within vital organs. Herein, we investigated dynamic gene expression within this immunological niche to provide biomarkers of response to anti-PD-1. In a 4T1 model of metastatic TNBC, we observed sensitivity and resistance to anti-PD-1 based on primary tumor growth and survival. The niche was biopsied before, during, and after anti-PD-1 therapy, and analyzed for cell types and gene expression indicative of treatment refractivity. Myeloid cell-to-lymphocyte ratios were altered between ICB-sensitivity and resistance. Longitudinal analysis of gene expression implicated dynamic myeloid cell function that stratified sensitivity from resistance. A niche-derived gene signature predicted sensitivity or resistance prior to therapy. Analysis of the niche to monitor immunotherapy response presents a new opportunity to personalize care and investigate mechanisms underlying treatment resistance.

Dynamic and prognostic proteomic associations with FEV1 decline in chronic obstructive pulmonary disease.

Rationale: Identification and validation of circulating biomarkers for lung function decline in COPD remains an unmet need. Objective: Identify prognostic and dynamic plasma protein biomarkers of COPD progression. Methods: We measured plasma proteins using SomaScan from two COPD-enriched cohorts, the Subpopulations and Intermediate Outcomes Measures in COPD Study (SPIROMICS) and Genetic Epidemiology of COPD (COPDGene), and one population-based cohort, Multi-Ethnic Study of Atherosclerosis (MESA) Lung. Using SPIROMICS as a discovery cohort, linear mixed models identified baseline proteins that predicted future change in FEV1 (prognostic model) and proteins whose expression changed with change in lung function (dynamic model). Findings were replicated in COPDGene and MESA-Lung. Using the COPD-enriched cohorts, Gene Set Enrichment Analysis (GSEA) identified proteins shared between COPDGene and SPIROMICS. Metascape identified significant associated pathways. Measurements and Main Results: The prognostic model found 7 significant proteins in common (p < 0.05) among all 3 cohorts. After applying false discovery rate (adjusted p < 0.2), leptin remained significant in all three cohorts and growth hormone receptor remained significant in the two COPD cohorts. Elevated baseline levels of leptin and growth hormone receptor were associated with slower rate of decline in FEV1. Twelve proteins were nominally but not FDR significant in the dynamic model and all were distinct from the prognostic model. Metascape identified several immune related pathways unique to prognostic and dynamic proteins. Conclusion: We identified leptin as the most reproducible COPD progression biomarker. The difference between prognostic and dynamic proteins suggests disease activity signatures may be different from prognosis signatures.

Design of the SPIROMICS Study of Early COPD Progression: SOURCE Study.

Background: The biological mechanisms leading some tobacco-exposed individuals to develop early-stage chronic obstructive pulmonary disease (COPD) are poorly understood. This knowledge gap hampers development of disease-modifying agents for this prevalent condition. Objectives: Accordingly, with National Heart, Lung and Blood Institute support, we initiated the SubPopulations and InteRmediate Outcome Measures In COPD Study (SPIROMICS) Study of Early COPD Progression (SOURCE), a multicenter observational cohort study of younger individuals with a history of cigarette smoking and thus at-risk for, or with, early-stage COPD. Our overall objectives are to identify those who will develop COPD earlier in life, characterize them thoroughly, and by contrasting them to those not developing COPD, define mechanisms of disease progression. Methods/Discussion: SOURCE utilizes the established SPIROMICS clinical network. Its goal is to enroll n=649 participants, ages 30-55 years, all races/ethnicities, with ≥10 pack-years cigarette smoking, in either Global initiative for chronic Obstructive Lung Disease (GOLD) groups 0-2 or with preserved ratio-impaired spirometry; and an additional n=40 never-smoker controls. Participants undergo baseline and 3-year follow-up visits, each including high-resolution computed tomography, respiratory oscillometry and spirometry (pre- and postbronchodilator administration), exhaled breath condensate (baseline only), and extensive biospecimen collection, including sputum induction. Symptoms, interim health care utilization, and exacerbations are captured every 6 months via follow-up phone calls. An embedded bronchoscopy substudy involving n=100 participants (including all never-smokers) will allow collection of lower airway samples for genetic, epigenetic, genomic, immunological, microbiome, mucin analyses, and basal cell culture. Conclusion: SOURCE should provide novel insights into the natural history of lung disease in younger individuals with a smoking history, and its biological basis.

New perspectives into the vaginal microbiome with systems biology.

The vaginal microbiome (VMB) is critical to female reproductive health; however, the mechanisms associated with optimal and non-optimal states remain poorly understood due to the complex community structure and dynamic nature. Quantitative systems biology techniques applied to the VMB have improved understanding of community composition and function using primarily statistical methods. In contrast, fewer mechanistic models that use a priori knowledge of VMB features to develop predictive models have been implemented despite their use for microbiomes at other sites, including the gastrointestinal tract. Here, we explore systems biology approaches that have been applied in the VMB, highlighting successful techniques and discussing new directions that hold promise for improving understanding of health and disease.

Polyfunctional antibodies: a path towards precision vaccines for vulnerable populations.

Vaccine efficacy determined within the controlled environment of a clinical trial is usually substantially greater than real-world vaccine effectiveness. Typically, this results from reduced protection of immunologically vulnerable populations, such as children, elderly individuals and people with chronic comorbidities. Consequently, these high-risk groups are frequently recommended tailored immunisation schedules to boost responses. In addition, diverse groups of healthy adults may also be variably protected by the same vaccine regimen. Current population-based vaccination strategies that consider basic clinical parameters offer a glimpse into what may be achievable if more nuanced aspects of the immune response are considered in vaccine design. To date, vaccine development has been largely empirical. However, next-generation approaches require more rational strategies. We foresee a generation of precision vaccines that consider the mechanistic basis of vaccine response variations associated with both immunogenetic and baseline health differences. Recent efforts have highlighted the importance of balanced and diverse extra-neutralising antibody functions for vaccine-induced protection. However, in immunologically vulnerable populations, significant modulation of polyfunctional antibody responses that mediate both neutralisation and effector functions has been observed. Here, we review the current understanding of key genetic and inflammatory modulators of antibody polyfunctionality that affect vaccination outcomes and consider how this knowledge may be harnessed to tailor vaccine design for improved public health.

A blood and bronchoalveolar lavage protein signature of rapid FEV1 decline in smoking-associated COPD.

Accelerated progression of chronic obstructive pulmonary disease (COPD) is associated with increased risks of hospitalization and death. Prognostic insights into mechanisms and markers of progression could facilitate development of disease-modifying therapies. Although individual biomarkers exhibit some predictive value, performance is modest and their univariate nature limits network-level insights. To overcome these limitations and gain insights into early pathways associated with rapid progression, we measured 1305 peripheral blood and 48 bronchoalveolar lavage proteins in individuals with COPD [n = 45, mean initial forced expiratory volume in one second (FEV1) 75.6 ± 17.4% predicted]. We applied a data-driven analysis pipeline, which enabled identification of protein signatures that predicted individuals at-risk for accelerated lung function decline (FEV1 decline ≥ 70 mL/year) ~ 6 years later, with high accuracy. Progression signatures suggested that early dysregulation in elements of the complement cascade is associated with accelerated decline. Our results propose potential biomarkers and early aberrant signaling mechanisms driving rapid progression in COPD.

A Quantitative Approach to Unravel the Role of Host Genetics in IgG-FcγR Complex Formation After Vaccination.

Fc-mediated immune functions have been correlated with protection in the RV144 HIV vaccine trial and are important for immunity to a range of pathogens. IgG antibodies (Abs) that form complexes with Fc receptors (FcRs) on innate immune cells can activate Fc-mediated immune functions. Genetic variation in both IgGs and FcRs have the capacity to alter IgG-FcR complex formation via changes in binding affinity and concentration. A growing challenge lies in unraveling the importance of multiple variations, especially in the context of vaccine trials that are conducted in homogenous genetic populations. Here we use an ordinary differential equation model to quantitatively assess how IgG1 allotypes and FcγR polymorphisms influence IgG-FcγRIIIa complex formation in vaccine-relevant settings. Using data from the RV144 HIV vaccine trial, we map the landscape of IgG-FcγRIIIa complex formation predicted post-vaccination for three different IgG1 allotypes and two different FcγRIIIa polymorphisms. Overall, the model illustrates how specific vaccine interventions could be applied to maximize IgG-FcγRIIIa complex formation in different genetic backgrounds. Individuals with the G1m1,17 and G1m1,3 allotypes were predicted to be more responsive to vaccine adjuvant strategies that increase antibody FcγRIIIa affinity (e.g. glycosylation modifications), compared to the G1m-1,3 allotype which was predicted to be more responsive to vaccine boosting regimens that increase IgG1 antibody titers (concentration). Finally, simulations in mixed-allotype populations suggest that the benefit of boosting IgG1 concentration versus IgG1 affinity may be dependent upon the presence of the G1m-1,3 allotype. Overall this work provides a quantitative tool for rationally improving Fc-mediated functions after vaccination that may be important for assessing vaccine trial results in the context of under-represented genetic populations.

SARS-CoV-2 infection results in immune responses in the respiratory tract and peripheral blood that suggest mechanisms of disease severity.

Respiratory tract infection with SARS-CoV-2 results in varying immunopathology underlying COVID-19. We examine cellular, humoral and cytokine responses covering 382 immune components in longitudinal blood and respiratory samples from hospitalized COVID-19 patients. SARS-CoV-2-specific IgM, IgG, IgA are detected in respiratory tract and blood, however, receptor-binding domain (RBD)-specific IgM and IgG seroconversion is enhanced in respiratory specimens. SARS-CoV-2 neutralization activity in respiratory samples correlates with RBD-specific IgM and IgG levels. Cytokines/chemokines vary between respiratory samples and plasma, indicating that inflammation should be assessed in respiratory specimens to understand immunopathology. IFN-α2 and IL-12p70 in endotracheal aspirate and neutralization in sputum negatively correlate with duration of hospital stay. Diverse immune subsets are detected in respiratory samples, dominated by neutrophils. Importantly, dexamethasone treatment does not affect humoral responses in blood of COVID-19 patients. Our study unveils differential immune responses between respiratory samples and blood, and shows how drug therapy affects immune responses during COVID-19.