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People with HIV (PWH) appear to be at higher risk for suboptimal pathogen responses and for worse COVID-19 outcomes, but the effects of host factors and COVID-19 on the humoral repertoire remain unclear. We assessed the antibody isotype/subclass and Fc-receptor binding Luminex arrays of non-SARS-CoV-2 and SARS-CoV-2 humoral responses among antiretroviral therapy-treated (ART-treated) PWH. Among the entire cohort, COVID-19 infection was associated with higher cytomegalovirus (CMV) responses (vs. the COVID- cohort ), potentially signifying increased susceptibility or a consequence of persistent inflammation. Among the COVID+ participants, (a) higher BMI was associated with a striking amplification of SARS-CoV-2 responses, suggesting exaggerated inflammatory responses, and (b) lower nadir CD4 was associated with higher SARS-CoV-2 IgM and FcγRIIB binding capacity, indicating poorly functioning extrafollicular and inhibitory responses. Among the COVID-19- participants, female sex, older age, and lower nadir CD4 were associated with unique repertoire shifts. In this first comprehensive assessment of the humoral repertoire in a global cohort of PWH, we identify distinct SARS-CoV-2-specific humoral immune profiles among PWH with obesity or lower nadir CD4+ T cell count, underlining plausible mechanisms associated with worse COVID-19-related outcomes in this setting. Host factors associated with the humoral repertoire in the COVID-19- cohort enhance our understanding of these important shifts among PWH.

Despite the robust immunogenicity of SARS-CoV-2 mRNA vaccines, emerging data have revealed enhanced neutralizing antibody and T cell cross-reactivity among individuals that previously experienced COVID-19, pointing to a hybrid immune advantage with infection-associated immune priming. Beyond neutralizing antibodies and T cell immunity, mounting data point to a potential role for additional antibody effector functions, including opsinophagocytic activity, in the resolution of symptomatic COVID-19. Whether hybrid immunity modifies the Fc-effector profile of the mRNA vaccine-induced immune response remains incompletely understood. Thus, here we profiled the SARS-CoV-2 specific humoral immune response in a group of individuals with and without prior COVID-19. As expected, hybrid Spike-specific antibody titers were enhanced following the primary dose of the mRNA vaccine but were similar to those achieved by naive vaccinees after the second mRNA vaccine dose. Conversely, Spike-specific vaccine-induced Fc-receptor binding antibody levels were higher after the primary immunization in individuals with prior COVID-19 and remained higher following the second dose compared to those in naive individuals, suggestive of a selective improvement in the quality, rather than the quantity, of the hybrid humoral immune response. Thus, while the magnitude of antibody titers alone may suggest that any two antigen exposures-either hybrid immunity or two doses of vaccine alone-represent a comparable prime/boost immunologic education, we find that hybrid immunity offers a qualitatively improved antibody response able to better leverage Fc-effector functions against conserved regions of the virus. IMPORTANCE Recent data indicates improved immunity to SARS-CoV-2 in individuals who experience a combination of two mRNA vaccine doses and infection, "hybrid immunity," compared to individuals who receive vaccination or experience infection alone. While previous infection accelerates the vaccine-induced immune response following the first dose of mRNA vaccination, subsequent doses demonstrate negligible increases in antibody titers or T cell immunity. Here, using systems serology, we observed a unique antibody profile induced by hybrid immunity, marked by the unique induction of robust Fc-recruiting antibodies directed at the conserved region of the viral Spike antigen, the S2-domain, induced at lower levels in individuals who only received mRNA vaccination. Thus, hybrid immunity clearly redirects vaccine-induced immunodominance, resulting in the induction of a robust functional humoral immune response to the most highly conserved region of the SARS-CoV-2 Spike antigen, which may be key to protection against existing and emerging variants of concern. Thus, next-generation vaccines able to mimic hybrid immunity and drive a balanced response to conserved regions of the Spike antigen may confer enhanced protection against disease.

BackgroundHuman immunodeficiency virus type 1 (HIV-1) sequence diversity and the presence of archived epitope muta-tions in antibody binding sites are a major obstacle for the clinical application of broadly neutralizing antibodies (bNAbs) against HIV-1. Specifically, it is unclear to what degree the viral reservoir is compartmentalized and if virus susceptibility to antibody neutralization differs across tissues.MethodsThe Last Gift cohort enrolled 7 people with HIV diagnosed with a terminal illness and collected antemortem blood and postmortem tissues across 33 anatomical compartments for near full-length env HIV genome sequencing. Using these data, we applied a Bayesian machine-learning model (Markov chain Monte Carlo-support vector machine) that uses HIV-1 envelope sequences and approximated glycan-occupancy information to quantitatively predict the half-maximal inhib-itory concentrations (IC50) of bNAbs, allowing us to map neutralization resistance pattern across tissue reservoirs.ResultsPredicted mean susceptibilities across tissues within participants were relatively homogenous, and the susceptibility pattern observed in blood often matched what was predicted for tissues. However, selected tissues, such as the brain, showed ev-idence of compartmentalized viral populations with distinct neutralization susceptibilities in some participants. Additionally, we found substantial heterogeneity in the range of neutralization susceptibilities across tissues within and between indi-viduals, and between bNAbs within individuals (standard deviation of log2(IC50) >3.4).ConclusionsBlood-based screening methods to determine viral susceptibility to bNAbs might underestimate the presence of resistant viral variants in tissues. The extent to which these resistant viruses are clinically relevant, that is, lead to bNAb therapeutic failure, needs to be further explored.

Preexisting cross-reactive antibodies have been implicated in both protection and pathogenesis during subsequent infections with different dengue virus (DENV) serotypes (DENV1-4). Nonetheless, humoral immune correlates and mechanisms of protection have remained elusive. Using a systems serology approach to evaluate humoral responses, we profiled plasma collected before inapparent or symptomatic secondary DENV3 infection from our pediatric cohort in Nicaragua. Children protected from symptomatic infections had more anti-envelope (E) and anti-nonstructural protein 1 (NS1) total immunoglobulin G (IgG), IgG4, and greater Fc effector functions than those with symptoms. Fc effector functions were also associated with protection from hemorrhagic manifestations in the pre-symptomatic group. Furthermore, in vitro virological assays using these plasma samples revealed that protection mediated by antibody-dependent complement deposition was associated with both lysis of virions and DENV-infected cells. These data suggest that E- and NS1-specific Fc functions may serve as correlates of protection, which can be potentially applied toward the design and evaluation of dengue vaccines.

While antiretroviral therapy (ART) has effectively revolutionized HIV care, the virus is never fully eliminated. Instead, immune dysfunction, driven by persistent non-specific immune activation, ensues and progressively leads to premature immunologic aging. Current biomarkers monitoring immunologic changes encompass generic inflammatory biomarkers, that may also change with other infections or disease states, precluding the antigen-specific monitoring of HIV-infection associated changes in disease. Given our growing appreciation of the significant changes in qualitative and quantitative properties of disease-specific antibodies in HIV infection, we used a systems approach to explore humoral profiles associated with HIV control. We found that HIV-specific antibody profiles diverge by spontaneous control of HIV, treatment status, viral load and reservoir size. Specifically, HIV-specific antibody profiles representative of changes in viral load were largely quantitative, reflected by differential HIV-specific antibody levels and Fc-receptor binding. Conversely, HIV-specific antibody features that tracked with reservoir size exhibited a combination of quantitative and qualitative changes marked by more distinct subclass selection profiles and unique HIV-specific Fc-glycans. Our analyses suggest that HIV-specific antibody Fc-profiles provide antigen-specific resolution on both cell free and cell-associated viral loads, pointing to potentially novel biomarkers to monitor reservoir activity.

Numerous studies have identified similarities in blood transcriptomic signatures of tuberculosis (TB) phenotypes between mice and humans, including type 1 interferon production and innate immune cell activation. However, murine infection pathophysiology is distinct from human disease. We hypothesized that this is partly due to differences in the relative importance of biological pathways across species. To address this animal-to-human gap, we applied a systems modeling framework, Translatable Components Regression, to identify the axes of variation in the preclinical data most relevant to human TB disease state. Among the pathways our cross-species model pinpointed as highly predictive of human TB phenotype was the infection-induced unfolded protein response. To validate this mechanism, we confirmed that this cellular stress pathway modulates immune functions in Mycobacterium tuberculosis-infected mouse macrophages. Our work demonstrates how systems-level computational models enhance the value of animal studies for elucidating complex human pathophysiology. [ABSTRACT FROM AUTHOR]

Cancer is a manifestation of dysfunctional cell states. It emerges from an interplay of intrinsic and extrinsic factors that disrupt cellular dynamics, including genetic and epigenetic alterations, as well as the tumor microenvironment. This complexity can make it challenging to infer molecular causes for treating the disease. This may be addressed by system-wide computer models of cells, as they allow rapid generation and testing of hypotheses that would be too slow or impossible to perform in the laboratory and clinic. However, so far, such models have been impeded by both experimental and computational limitations. In this perspective, we argue that they can now be achieved using deep learning algorithms to integrate omics data and prior knowledge of molecular networks. Such models would have many applications in precision oncology, e.g., for identifying drug targets and biomarkers, predicting resistance mechanisms and toxicity effects of drugs, or simulating cell-cell interactions in the microenvironment. [ABSTRACT FROM AUTHOR]

Multi-cellular biological systems, including the immune system, are highly complex, dynamic, and adaptable. Systems biologists aim to understand such complexity at a quantitative level. However, these ambitious efforts are often limited by access to a variety of high-density intra-, extra- and multi-cellular measurements resolved in time and space and across a variety of perturbations. The advent of automation, OMICs and single-cell technologies now allows high dimensional multi-modal data acquisition from the same biological samples multiplexed at scale (multi-OMICs). As a result, systems biologists -theoretically- have access to more data than ever. However, the mathematical frameworks and computational tools needed to analyze and interpret such data are often still nascent, limiting the biological insights that can be obtained without years of computational method development and validation. More pressingly, much of the data sits in silos in formats that are incomprehensible to other scientists or machines limiting its value to the vaster scientific community, especially the computational biologists tasked with analyzing these vast amounts of data in more nuanced ways. With the rapid development and increasing interest in using artificial intelligence (AI) for the life sciences, improving how biologic data is organized and shared is more pressing than ever for scientific progress. Here, we outline a practical approach to multi-modal data management and FAIR sharing, which are in line with the latest US and EU funders' data sharing policies. This framework can help extend the longevity and utility of data by allowing facile use and reuse, accelerating scientific discovery in the biomedical sciences. [ABSTRACT FROM AUTHOR]

IntroductionTargeted cancer therapeutics have demonstrated more limited clinical efficacy than anticipated, due to both intrinsic and acquired drug resistance. Underlying mechanisms have been largely attributed to genetic changes, but a substantial proportion of resistance observations remain unexplained by genomic properties. Emerging evidence shows that receptor tyrosine kinase (RTK) reprogramming is a major alternative process causing targeted drug resistance, separate from genetic alterations. Hence, the contributions of mechanisms leading to this process need to be more rigorously assessed.MethodsTo parse contributions of multiple mechanisms to RTK reprogramming, we have developed a quantitative multi-receptor and multi-mechanistic experimental framework and kinetic model.ResultsWe find that RTK reprogramming mechanisms are disparate among RTKs and nodes of intervention in the MAPK pathway. Mek inhibition induces increased Axl and Her2 levels in triple negative breast cancer (TNBC) cells while Met and EGFR levels remain unchanged, with Axl and Her2 sharing re-wiring through increased synthesis and differing secondary contributing mechanisms. While three Mek inhibitors exhibited mechanistic similarity, three Erk inhibitors elicited effects different from the Mek inhibitors and from each other, with MAPK pathway target-specific effects correlating with Erk subcellular localization. Furthermore, we find that Mek inhibitor-induced RTK reprogramming occurs through both BET bromodomain dependent and independent mechanisms, motivating combination treatment with BET and Axl inhibition to overcome RTK reprogramming.ConclusionsOur findings suggest that RTK reprogramming occurs through multiple mechanisms in a MAPK pathway target-specific manner, highlighting the need for comprehensive resistance mechanism profiling strategies during pharmacological development.

HIV-specific broadly neutralizing antibodies (bNAbs) confer protection after passive immunization, but the immunological mechanisms that drive their development are poorly understood. Structural features of bNAbs indicate that they originate from extensive germinal center (GC) selection, which relies on persistent GC activity. However, why a fraction of infected individuals are able to successfully drive more effective affinity maturation is unclear. Delivery of antigens in the form of antibody-immune complexes (ICs), which bind to complement receptors (CRs) or Fc receptors (FcRs) on follicular dendritic cells, represents an effective mechanism for antigen delivery to the GC. We sought to define whether IC-FcR or CR interactions differ among individuals who develop bNAb responses to HIV. Enhanced Fc effector functions and FcR/CR interactions, via altered Fc glycosylation profiles, were observed among individuals with neutralizing antibody responses to HIV compared with those without neutralizing antibody activity. Moreover, both polyclonal neutralizer ICs and monoclonal IC mimics of neutralizer antibodies induced higher antibody titers, higher-avidity antibodies, and expanded GC B cell reactions after immunization of mice via accelerated antigen deposition within B cell follicles in a complement-dependent manner. Thus, these data point to a direct role for altered Fc profile/complement interactions in shaping the maturation of the humoral immune response, providing insights into how GC activity may be enhanced to drive affinity maturation in next-generation vaccine approaches.

Introduction The introduction of Bacillus Calmette Guerin (BCG) as a vaccine contributed significantly to tuberculosis (TB) control, which has threatened global health for millennia. As the only vaccine approved for [...], Heterogeneity in human immune responses is difficult to model in standard laboratory mice. To understand how host variation affects Bacillus Calmette Guerin-induced (BCG-induced) immunity against Mycobacterium tuberculosis, we studied 24 unique collaborative cross (CC) mouse strains, which differ primarily in the genes and alleles they inherit from founder strains. The CC strains were vaccinated with or without BCG and challenged with aerosolized M. tuberculosis. Since BCG protects only half of the CC strains tested, we concluded that host genetics has a major influence on BCG-induced immunity against M. tuberculosis infection, making it an important barrier to vaccine- mediated protection. Importantly, BCG efficacy is dissociable from inherent susceptibility to tuberculosis (TB). T cell immunity was extensively characterized to identify components associated with protection that were stimulated by BCG and recalled after M. tuberculosis infection. Although considerable diversity is observed, BCG has little impact on the composition of T cells in the lung after infection. Instead, variability is largely shaped by host genetics. BCG-elicited protection against TB correlated with changes in immune function. Thus, CC mice can be used to define correlates of protection and to identify vaccine strategies that protect a larger fraction of genetically diverse individuals instead of optimizing protection for a single genotype.

ObjectiveGiven the emerging appreciation for the role of antibody-dependent effector functions and IgG subclass distribution among spontaneous controllers of HIV, we sought to determine whether antibody-associated features diverged in early HIV infection between patients who ultimately became controllers versus those who became progressors.MethodsIgG was purified from plasma from nine acutely infected patients who subsequently controlled HIV spontaneously (controllers) and 10 acutely infected individuals who did not control viremia (progressors). Antibody profiles were compared at weeks 4, 12, 24 and 48 postinfection. Levels of clade B gp120-specific, gp140-specific and gp41-specific IgG antibody subclasses were measured. In addition, gp120-specific antibody-dependent cellular phagocytosis, rapid fluorescent antibody-dependent cellular cytotoxicity and antibody-dependent cellular viral inhibition were all assessed.ResultsAlthough no single antibody-related measurement was significantly associated with long-term HIV control, combinations of antibody-associated variables were able to accurately differentiate controllers and progressors. In contrast to controllers, progressors showed greater dynamic changes in gp120-specific subclass selection profiles, with increasing levels of Env-specific IgG2 antibodies and losses in Env-specific IgG3 antibodies. Moreover, progressors, but not controllers, lost antibody-dependent cellular viral inhibition function over time. Together, these results highlight changes in IgG subclass selection profiles in progressive, but not controlled, HIV infection.ConclusionThis study suggests that the temporal variation and maintenance of Env-specific IgG subclasses during acute HIV infection are predictive of eventual disease control. The maintenance of gp120-specific and gp140-specific IgG3 may contribute to control of disease in spontaneous controllers. Thus, strategies to induce stable IgG3 responses may preserve control of the viral reservoir.

Ectodomain shedding of cell-surface precursor proteins by metalloproteases generates important cellular signaling molecules. Of importance for disease is the release of ligands that activate the EGFR, such as TGFα, which is mostly carried out by ADAM17 [a member of the A-disintegrin and metalloprotease (ADAM) domain family]. EGFR ligand shedding has been linked to many diseases, in particular cancer development, growth and metastasis, as well as resistance to cancer therapeutics. Excessive EGFR ligand release can outcompete therapeutic EGFR inhibition or the inhibition of other growth factor pathways by providing bypass signaling via EGFR activation. Drugging metalloproteases directly have failed clinically because it indiscriminately affected shedding of numerous substrates. It is therefore essential to identify regulators for EGFR ligand cleavage. Here, integration of a functional shRNA genomic screen, computational network analysis, and dedicated validation tests succeeded in identifying several key signaling pathways as novel regulators of TGFα shedding in cancer cells. Most notably, a cluster of genes with NFκB pathway regulatory functions was found to strongly influence TGFα release, albeit independent of their NFκB regulatory functions. Inflammatory regulators thus also govern cancer cell growth-promoting ectodomain cleavage, lending mechanistic understanding to the well-known connection between inflammation and cancer.Implications: Using genomic screens and network analysis, this study defines targets that regulate ectodomain shedding and suggests new treatment opportunities for EGFR-driven cancers. Mol Cancer Res; 16(1); 147-61. ©2017 AACR.