High-affinity, neutralizing antibodies to SARS-CoV-2 can be made in the absence of T follicular helper cells (preprint)

T follicular helper (Tfh) cells are the conventional drivers of protective, germinal center (GC)-based antiviral antibody responses. However, loss of Tfh cells and GCs has been observed in patients with severe COVID-19. As T cell-B cell interactions and immunoglobulin class switching still occur in these patients, non-canonical pathways of antibody production may be operative during SARS-CoV-2 infection. We found that both Tfh-dependent and -independent antibodies were induced against SARS-CoV-2 as well as influenza A virus. Tfh-independent responses were mediated by a population we call lymph node (LN)-Th1 cells, which remain in the LN and interact with B cells outside of GCs to promote high-affinity but broad-spectrum antibodies. Strikingly, antibodies generated in the presence and absence of Tfh cells displayed similar neutralization potency against homologous SARS-CoV-2 as well as the B.1.351 variant of concern. These data support a new paradigm for the induction of B cell responses during viral infection that enables effective, neutralizing antibody production to complement traditional GCs and even compensate for GCs damaged by viral inflammation.

Immunogenic Amino Acid Motifs and Linear Epitopes of COVID-19 mRNA Vaccines (preprint)

Reverse vaccinology is an evolving approach for improving vaccine effectiveness and minimizing adverse responses by limiting immunizations to critical epitopes. Towards this goal, we sought to identify immunogenic amino acid motifs and linear epitopes of the SARS-CoV-2 spike protein that elicit IgG in COVID-19 mRNA vaccine recipients. Paired pre/post vaccination samples from N=20 healthy adults, and post-vaccine samples from an additional N=13 individuals were used to immunoprecipitate IgG targets expressed by a bacterial display random peptide library, and preferentially recognized peptides were mapped to the spike primary sequence. The data identify several distinct amino acid motifs recognized by vaccine-induced IgG, a subset of those targeted by IgG from natural infection, which may mimic 3-dimensional conformation (mimotopes). Dominant linear epitopes were identified in the C-terminal domains of the S1 and S2 subunits (aa 558-569, 627-638, and 1148-1159) which have been previously associated with SARS-CoV-2 neutralization in vitro and demonstrate identity to bat coronavirus and SARS-CoV, but limited homology to non-pathogenic human coronavirus. The identified COVID-19 mRNA vaccine epitopes should be considered in the context of variants, immune escape and vaccine and therapy design moving forward.

High-resolution mapping and characterization of epitopes in COVID-19 patients (preprint)

Fine scale delineation of epitopes recognized by the antibody response to SARS-CoV-2 infection will be critical to understanding disease heterogeneity and informing development of safe and effective vaccines and therapeutics. The Serum Epitope Repertoire Analysis (SERA) platform leverages a high diversity random bacterial display library to identify epitope binding specificities with single amino acid resolution. We applied SERA broadly, across human, viral and viral strain proteomes in multiple cohorts with a wide range of outcomes from SARS-CoV-2 infection. We identify dominant epitope motifs and profiles which effectively classify COVID-19, distinguish mild from severe disease, and relate to neutralization activity. We identify a repertoire of epitopes shared by SARS-CoV-2 and endemic human coronaviruses and determine that a region of amino acid sequence identity shared by the SARS-CoV-2 furin cleavage site and the host protein ENaC-alpha is a potential cross-reactive epitope. Finally, we observe decreased epitope signal for mutant strains which points to reduced antibody response to mutant SARS-CoV-2. Together, these findings indicate that SERA enables high resolution of antibody epitopes that can inform data-driven design and target selection for COVID-19 diagnostics, therapeutics and vaccines.

Triple Combination Nitazoxanide, Ribavirin, and Hydroxychloroquine results in the multiplicative reduction of in vitro SARS-CoV-2 viral replication (preprint)

Background: An immediate unmet medical need exists to test and develop existing approved drugs against SARS-COV-2. Despite many efforts, very little progress has been made regarding finding low-cost oral medicines that can be made widely available worldwide to address the global pandemic. Methods: We sought to examine if a triple combination of nitazoxanide (using its active metabolite tizoxanide), ribavirin, and hydroxychloroquine would lead to a multiplicative effects on viral replication of SARS-COV-2 resulting in a significant reduction of virus yield using VERO E6 cells as a model of viral replication. Results: Virus yield measured in PFU/ml was ~ 2 logs lower with triple combination versus either drug alone, resulting in the prolongation of time to peak cytopathic effects (CPE). The time to produce 50% CPE increased from 2.8 days for viral controls versus 5.3 days for triple combination therapy. Finally, for each 1-log reduction in virus yield 24 hours post-infection, there was an additional 0.7-day delay in onset of CPE. Conclusions: A triple combination of tizoxanide, ribavirin, and hydroxychloroquine produced a reduction in SARS-COV-2 viral replication in Vero E6 cells, warranting exploration in additional cell lines as well as human clinical trials.

Massively parallel interrogation of protein fragment secretability using SECRiFY reveals features influencing secretory system transit (preprint)

While transcriptome- and proteome-wide technologies to assess processes in protein biogenesis are now widely available, we still lack global approaches to assay post-ribosomal biogenesis events, in particular those occurring in the eukaryotic secretory system. We here developed a method, SECRiFY, to simultaneously assess the secretability of >105 protein fragments by two yeast species, S. cerevisiae and P. pastoris, using custom fragment libraries, surface display and a sequencing-based readout. Screening human proteome fragments with a median size of 50 - 100 amino acids, we generated datasets that enable datamining into protein features underlying secretability, revealing a striking role for intrinsic disorder and chain flexibility. SECRiFY is the first methodology that generates sufficient amounts of annotated data for advanced machine learning methods to deduce secretability predictors. The finding that secretability is indeed a learnable feature of protein sequences is of significant impact in the broad area of recombinant protein expression and de novo protein design.

Pharmacologic profiling reveals lapatinib as a novel antiviral against SARS-CoV-2 in vitro (preprint)

The emergence of SARS-CoV-2 virus has resulted in a worldwide pandemic, but an effective antiviral therapy has yet to be discovered. To improve treatment options, we conducted a high-throughput drug repurposing screen to uncover compounds that block the viral activity of SARS-CoV-2. A minimally pathogenic human betacoronavirus (OC43) was used to infect physiologically-relevant human pulmonary fibroblasts (MRC5) to facilitate rapid antiviral discovery in a preclinical model. Comprehensive profiling was conducted on more than 600 compounds, with each compound arrayed at 10 dose points (ranging from 20 M to 1 nM). Our screening revealed several FDA-approved agents that act as novel antivirals that block both OC43 and SARS-CoV-2 viral replication, including lapatinib, doramapimod, and 17-AAG. Importantly, lapatinib inhibited SARS-CoV-2 replication by over 50,000-fold without any toxicity and at doses readily achievable in human tissues. Further, both lapatinib and doramapimod could be combined with remdesivir to dramatically improve antiviral activity in cells. These findings reveal novel treatment options for people infected with SARS-CoV-2 that can be readily implemented during the pandemic.