Mathematical models based on ordinary differential equations (ODE) that describe the population dynamics of viruses and infected cells have been an essential tool to characterize and quantify viral infection dynamics. Although an important aspect of viral infection is the dynamics of viral spread, which includes transmission by cell-free virions and direct cell-to-cell transmission, models used so far ignored cell-to-cell transmission completely, or accounted for this process by simple mass-action kinetics between infected and uninfected cells. In this study, we show that the simple mass-action approach falls short when describing viral spread in a spatially-defined environment. Using simulated data, we present a model extension that allows correct quantification of cell-to-cell transmission dynamics within a monolayer of cells. By considering the decreasing proportion of cells that can contribute to cell-to-cell spread with progressing infection, our extension accounts for the transmission dynamics on a single cell level while still remaining applicable to standard population-based experimental measurements. While the ability to infer the proportion of cells infected by either of the transmission modes depends on the viral diffusion rate, the improved estimates obtained using our novel approach emphasize the need to correctly account for spatial aspects when analyzing viral spread.

Chronic hepatitis B virus (HBV) infection remains a global health care problem, as we lack sufficient curative treatment options. Elucidating the dynamics of HBV infection and treatment response at the molecular level could facilitate the development of novel, more effective HBV antivirals.

The hepatitis C virus (HCV) is capable of spreading within a host by two different transmission modes: cell-free and cell-to-cell. However, the contribution of each of these transmission mechanisms to HCV spread is unknown. To dissect the contribution of these different transmission modes to HCV spread, we measured HCV lifecycle kinetics and used an in vitro spread assay to monitor HCV spread kinetics after a low multiplicity of infection in the absence and presence of a neutralizing antibody that blocks cell-free spread. By analyzing these data with a spatially explicit mathematical model that describes viral spread on a single-cell level, we quantified the contribution of cell-free, and cell-to-cell spread to the overall infection dynamics and show that both transmission modes act synergistically to enhance the spread of infection. Thus, the simultaneous occurrence of both transmission modes represents an advantage for HCV that may contribute to viral persistence. Notably, the relative contribution of each viral transmission mode appeared to vary dependent on different experimental conditions and suggests that viral spread is optimized according to the environment. Together, our analyses provide insight into the spread dynamics of HCV and reveal how different transmission modes impact each other.

The pandemic of COVID-19 caused by SARS-CoV-2 infection continues to spread around the world. Vaccines that elicit protective immunity have reduced infection and mortality, however new viral variants are arising that may evade vaccine-induced immunity or cause disease in individuals who are unable to develop robust vaccine-induced responses. Investigating the role of viral variants in causing severe disease, evading vaccine-elicited immunity, and infecting vulnerable individuals is important for developing strategies to control the pandemic. Here, we report fourteen breakthrough infections of SARS-CoV-2 in vaccinated individuals with symptoms ranging from asymptomatic/mild (6/14) to severe disease (8/14). High viral loads with a median Ct value of 19.6 were detected in the nasopharyngeal specimens from subjects regardless of disease severity. Sequence analysis revealed four distinct virus lineages, including alpha and gamma variants of concern. Immunosuppressed individuals were more likely to be hospitalized after infection (p = 0.047), however no specific variant was associated with severe disease. Our results highlight the high viral load that can occur in asymptomatic breakthrough infections and the vulnerability of immunosuppressed individuals to post-vaccination infections by diverse variants of SARS-CoV-2.

Understanding the magnitude of responses to vaccination during the ongoing SARS-CoV-2 pandemic is essential for ultimate mitigation of the disease. Here, we describe a cohort of 102 subjects (70 COVID-19-naïve, 32 COVID-19-experienced) who received two doses of one of the mRNA vaccines (BNT162b2 (Pfizer–BioNTech) and mRNA-1273 (Moderna)). We document that a single exposure to antigen via infection or vaccination induces a variable antibody response which is affected by age, gender, race, and co-morbidities. In response to a second antigen dose, both COVID-19-naïve and experienced subjects exhibited elevated levels of anti-spike and SARS-CoV-2 neutralizing activity; however, COVID-19-experienced individuals achieved higher antibody levels and neutralization activity as a group. The COVID-19-experienced subjects exhibited no significant increase in antibody or neutralization titer in response to the second vaccine dose (i.e., third antigen exposure). Finally, we found that COVID-19-naïve individuals who received the Moderna vaccine exhibited a more robust boost response to the second vaccine dose (p = 0.004) as compared to the response to Pfizer–BioNTech. Ongoing studies with this cohort will continue to contribute to our understanding of the range and durability of responses to SARS-CoV-2 mRNA vaccines.

The pandemic of SARS-CoV-2 is characterized by the emergence of new variants of concern (VOCs) that supplant previous waves of infection. Here, we describe our investigation of the lineages and host-specific mutations identified in a particularly vulnerable population of predominantly older and immunosuppressed SARS-CoV-2-infected patients seen at our medical center in Chicago during the transition from the Delta to Omicron wave. We compare two primer schemes, ArticV4.1 and VarSkip2, used for short read amplicon sequencing, and describe our strategy for bioinformatics analysis that facilitates identifying lineage-associated mutations and host-specific mutations that arise during infection. This study illustrates the ongoing evolution of SARS-CoV-2 VOCs in our community and documents novel constellations of mutations that arise in individual patients. The ongoing evaluation of the evolution of SARS-CoV-2 during this pandemic is important for informing our public health strategies.