Rendon, G. | bioRxiv Science

bioRxiv2022

Within-host evolutionary dynamics and tissue compartmentalization during acute SARS-CoV-2 infection

The global evolution of SARS-CoV-2 depends in part upon the evolutionary dynamics within individual hosts with varying immune histories. To characterize the within-host evolution of acute SARS-CoV-2 infection, we deep sequenced saliva and nasal samples collected daily from immune and unvaccinated individuals early during infection. We show that longitudinal sampling facilitates high-confidence genetic variant detection and reveals evolutionary dynamics missed by less-frequent sampling strategies. Within-host dynamics in both naive and immune individuals appeared largely stochastic; however, we identified clear mutational hotspots within the viral genome, consistent with selection and differing between naive and immune individuals. In rare cases, minor genetic variants emerged to frequencies sufficient for forward transmission. Finally, we detected significant genetic compartmentalization of virus between saliva and nasal swab sample sites in many individuals. Altogether, these data provide a high-resolution profile of within-host SARS-CoV-2 evolutionary dynamics.

microbiology↗

bioRxiv2018

Illumina-based sequencing framework for accurate detection and mapping of influenza virus defective interfering particle-associated RNAs

The mechanisms and consequences of defective interfering particle (DIP) formation during influenza virus infection remain poorly understood. The development of next generation sequencing (NGS) technologies has made it possible to identify large numbers of DIP-associated sequences, providing a powerful tool to better understand their biological relevance. However, NGS approaches pose numerous technical challenges including the precise identification and mapping of deletion junctions in the presence of frequent mutation and base-calling errors, and the potential for numerous experimental and computational artifacts. Here we detail an Illumina-based sequencing framework and bioinformatics pipeline capable of generating highly accurate and reproducible profiles of DIP-associated junction sequences. We use a combination of simulated and experimental control datasets to optimize pipeline performance and demonstrate the absence of significant artifacts. Finally, we use this optimized pipeline to generate a high-resolution profile of DIP-associated junctions produced during influenza virus infection and demonstrate how this data can provide insight into mechanisms of DIP formation. This work highlights the specific challenges associated with NGS-based detection of DIP-associated sequences, and details the computational and experimental controls required for such studies.

microbiology↗