Alphaviruses are emerging public health threats. Broadly reactive anti-alphavirus monoclonal antibodies (mAbs) have been shown to be protective in mouse models of infection. However, the antibody characteristics that promote in vivo efficacy and dependency on Fc effector functions remain ill defined. Here, we used two vaccine-elicited, broadly reactive, anti-alphavirus mAbs, SKT05 and SKT20, to establish correlates of mAb-mediated protection during Venezuelan equine encephalitis virus (VEEV) challenge. SKT20 required Fc effector functions to prevent lethality. The necessity of Fc effector functions for SKT20 was dose dependent and related to mAb binding potency and pseudovirus neutralization rather than epitope specificity. In contrast, survival mediated by SKT05 when given prophylactically was independent of Fc effector functions and rather was linked to early viral control through egress inhibition. However, control of virus replication and spread with SKT05 at later time points was Fc dependent. Therapeutic administration of SKT05 required Fc effector functions only at 3 days after infection. These findings extended to additional in vivo infection models with alternative VEEV subtypes and with chikungunya virus. Collectively, this study identified binding potency and pseudoviral neutralization as correlates for in vivo efficacy of mAbs and demonstrated that Fc-dependent mechanisms can be leveraged for development of therapeutic mAbs against emerging alphaviruses.

Infection with the β-coronavirus SARS-CoV-2 typically generates strong virus-specific antibody production. Antibody responses against novel features of SARS-CoV-2 proteins require naïve B cell activation, but there is a growing appreciation that conserved regions are recognized by pre-existing memory B cells (MBCs) generated by endemic coronaviruses. The current study investigated the role of pre-existing cross-reactive coronavirus memory in the antibody response to the viral spike (S) and nucleocapsid (N) proteins following SARS-CoV-2 infection. The breadth of reactivity of circulating antibodies, plasmablasts, and MBCs was analyzed. Acutely infected subjects generated strong IgG responses to the S protein, including the novel receptor binding domain, the conserved S2 region, and to the N protein. The response included reactivity to the S of endemic β-coronaviruses and, interestingly, to the N of an endemic α-coronavirus. Both mild and severe infection expanded IgG MBC populations reactive to the S of SARS-CoV-2 and endemic β-coronaviruses. Avidity of S-reactive IgG antibodies and MBCs increased after infection. Overall, findings indicate that the response to the S and N of SARS-CoV-2 involves pre-existing MBC activation and adaptation to novel features of the proteins, along with the potential of imprinting to shape the response to SARS-CoV-2 infection.

Background Many tools exist to perform a rigorous pathway analysis, though traditional gene set enrichment analysis remains among the most common. While useful for many applications, one common situation where it is less so is the metabolic profiling of bulk omics datasets. Rate limiting steps in more linear pathways are the main determinant of flux through these pathways, but differential expression of the enzymes that catalyze these steps is usually not differentially weighted in pathway analysis. Fluximplied was built to perform pathway analysis with rate limiting steps in mind to assess the implied flux through a number of well validated metabolic pathways. Results A database of rate limiting steps and their associated pathway was constructed. Using publicly available human RNA sequencing data from liver, putamen, and adipose tissue, fluximplied generally corroborated the pathway analysis. When comparing two CD8 T cell subsets from mouse lung, our algorithm confirmed previous findings that were not found previously. Conclusion Fluximplied is an accessible tool for pathway analysis which is intended to assist the user with hypothesis generation. Unlike traditional approaches to pathway analysis, it specifically queries a database of rate limiting steps in order to infer flux through canonical metabolic pathways.