Virome-wide detection of natural infection events and the associated antibody dynamics using longitudinal highly-multiplexed serology.

Current methods for detecting infections either require a sample collected from an actively infected site, are limited in the number of agents they can query, and/or yield no information on the immune response. Here we present an approach that uses temporally coordinated changes in highly-multiplexed antibody measurements from longitudinal blood samples to monitor infection events at sub-species resolution across the human virome. In a longitudinally-sampled cohort of South African adolescents representing >100 person-years, we identify >650 events across 48 virus species and observe strong epidemic effects, including high-incidence waves of Aichivirus A and the D68 subtype of Enterovirus D earlier than their widespread circulation was appreciated. In separate cohorts of adults who were sampled at higher frequency using self-collected dried blood spots, we show that such events temporally correlate with symptoms and transient inflammatory biomarker elevations, and observe the responding antibodies to persist for periods ranging from ≤1 week to >5 years. Our approach generates a rich view of viral/host dynamics, supporting novel studies in immunology and epidemiology.

COVID-19 vaccination elicits an evolving, cross-reactive antibody response to epitopes conserved with endemic coronavirus spike proteins.

The COVID-19 pandemic has triggered the first widespread vaccination campaign against a coronavirus. Many vaccinated subjects are previously naive to SARS-CoV-2; however, almost all have previously encountered other coronaviruses (CoVs), and the role of this immunity in shaping the vaccine response remains uncharacterized. Here, we use longitudinal samples and highly multiplexed serology to identify mRNA-1273 vaccine-induced antibody responses against a range of CoV Spike epitopes, in both phylogenetically conserved and non-conserved regions. Whereas reactivity to SARS-CoV-2 epitopes shows a delayed but progressive increase following vaccination, we observe distinct kinetics for the endemic CoV homologs at conserved sites in Spike S2: these become detectable sooner and decay at later time points. Using homolog-specific antibody depletion and alanine-substitution experiments, we show that these distinct trajectories reflect an evolving cross-reactive response that can distinguish rare, polymorphic residues within these epitopes. Our results reveal mechanisms for the formation of antibodies with broad reactivity against CoVs.

Epitope-resolved profiling of the SARS-CoV-2 antibody response identifies cross-reactivity with endemic human coronaviruses.

The SARS-CoV-2 proteome shares regions of conservation with endemic human coronaviruses (CoVs), but it remains unknown to what extent these may be cross-recognized by the antibody response. Here, we study cross-reactivity using a highly multiplexed peptide assay (PepSeq) to generate an epitope-resolved view of IgG reactivity across all human CoVs in both COVID-19 convalescent and negative donors. PepSeq resolves epitopes across the SARS-CoV-2 Spike and Nucleocapsid proteins that are commonly targeted in convalescent donors, including several sites also recognized in some uninfected controls. By comparing patterns of homologous reactivity between CoVs and using targeted antibody-depletion experiments, we demonstrate that SARS-CoV-2 elicits antibodies that cross-recognize pandemic and endemic CoV antigens at two Spike S2 subunit epitopes. We further show that these cross-reactive antibodies preferentially bind endemic homologs. Our findings highlight sites at which the SARS-CoV-2 response appears to be shaped by previous CoV exposures and which have the potential to raise broadly neutralizing responses.

An Early Pandemic Analysis of SARS-CoV-2 Population Structure and Dynamics in Arizona.

In December of 2019, a novel coronavirus, SARS-CoV-2, emerged in the city of Wuhan, China, causing severe morbidity and mortality. Since then, the virus has swept across the globe, causing millions of confirmed infections and hundreds of thousands of deaths. To better understand the nature of the pandemic and the introduction and spread of the virus in Arizona, we sequenced viral genomes from clinical samples tested at the TGen North Clinical Laboratory, the Arizona Department of Health Services, and those collected as part of community surveillance projects at Arizona State University and the University of Arizona. Phylogenetic analysis of 84 genomes from across Arizona revealed a minimum of 11 distinct introductions inferred to have occurred during February and March. We show that >80% of our sequences descend from strains that were initially circulating widely in Europe but have since dominated the outbreak in the United States. In addition, we show that the first reported case of community transmission in Arizona descended from the Washington state outbreak that was discovered in late February. Notably, none of the observed transmission clusters are epidemiologically linked to the original travel-related case in the state, suggesting successful early isolation and quarantine. Finally, we use molecular clock analyses to demonstrate a lack of identifiable, widespread cryptic transmission in Arizona prior to the middle of February 2020.IMPORTANCE As the COVID-19 pandemic swept across the United States, there was great differential impact on local and regional communities. One of the earliest and hardest hit regions was in New York, while at the same time Arizona (for example) had low incidence. That situation has changed dramatically, with Arizona now having the highest rate of disease increase in the country. Understanding the roots of the pandemic during the initial months is essential as the pandemic continues and reaches new heights. Genomic analysis and phylogenetic modeling of SARS-COV-2 in Arizona can help to reconstruct population composition and predict the earliest undetected introductions. This foundational work represents the basis for future analysis and understanding as the pandemic continues.