Secondary structure of the SARS-CoV-2 genome is predictive of nucleotide substitution frequency (preprint)

Accurate estimation of the effects of mutations on SARS-CoV-2 viral fitness can inform public-health responses such as vaccine development and predicting the impact of a new variant; it can also illuminate biological mechanisms including those underlying the emergence of variants of concern. Recently, Lan et al reported a high-quality model of SARS-CoV-2 secondary structure and its underlying dimethyl sulfate (DMS) reactivity data. I investigated whether secondary structure can explain some variability in the frequency of observing different nucleotide substitutions across millions of patient sequences in the SARS-CoV-2 phylogenetic tree. Nucleotide basepairing was compared to the estimated mutational fitness of substitutions, a measurement of the difference between observed and expected substitution frequency that is correlated with other estimates of viral fitness. This comparison revealed that secondary structure is often predictive of substitution frequency, with significant decreases in substitution frequencies at basepaired positions. Focusing on the mutational fitness of C[->]T, the most common type of substitution, I describe C[->]T substitutions at basepaired positions that characterize major SARS-CoV-2 variants; such mutations may have a greater impact on fitness than appreciated when considering substitution frequency alone.

A critical reexamination of recovered SARS-CoV-2 sequencing data (preprint)

SARS-CoV-2 genomes collected at the onset of the Covid-19 pandemic are valuable because they could help understand how the virus entered the human population. In 2021, Jesse Bloom reported on the recovery of a sequencing dataset that had been removed from the NCBI SRA database at the request of the data generators, a scientific team at Wuhan University. Bloom suggested that the data may have been removed in order to obfuscate the origin of SARS-CoV-2, questioning the generating authors\' statements that the samples had been collected on and after January 30, 2020. Here, we show that sample collection dates were published in 2020 together with the sequencing data, and match the dates given by the authors in 2021. We examine mutations in these sequences and confirm that they are entirely consistent with the previously known genetic diversity of SARS-CoV-2 of late January 2020. Finally, we explain how an apparent phylogenetic rooting paradox described by Bloom was resolved by subsequent analysis. Our reanalysis demonstrates that allegations of cover-up or metadata manipulation were unwarranted.

Genetic tracing of market wildlife and viruses at the epicenter of the COVID-19 pandemic (preprint)

Zoonotic spillovers of viruses have occurred through the animal trade worldwide. The start of the COVID-19 pandemic was traced epidemiologically to the Huanan Wholesale Seafood Market, the site with the most reported wildlife vendors in the city of Wuhan, China. Here, we analyze publicly available qPCR and sequencing data from environmental samples collected in the Huanan market in early 2020. We demonstrate that the SARS-CoV-2 genetic diversity linked to this market is consistent with market emergence, and find increased SARS-CoV-2 positivity near and within a particular wildlife stall. We identify wildlife DNA in all SARS-CoV-2 positive samples from this stall. This includes species such as civets, bamboo rats, porcupines, hedgehogs, and one species, raccoon dogs, known to be capable of SARS-CoV-2 transmission. We also detect other animal viruses that infect raccoon dogs, civets, and bamboo rats. Combining metagenomic and phylogenetic approaches, we recover genotypes of market animals and compare them to those from other markets. This analysis provides the genetic basis for a short list of potential intermediate hosts of SARS-CoV-2 to prioritize for retrospective serological testing and viral sampling.

Predicted binding interface between coronavirus nsp3 and nsp4 (preprint)

Double membrane vesicles (DMVs) in coronavirus-infected cells feature pores that span both membranes. DMV pores were observed to have six-fold symmetry and include the nsp3 protein. Co-expression of SARS-CoV nsp3 and nsp4 induces DMV formation, and elements of nsp3 and nsp4 have been identified that are essential for membrane disruption. I describe a predicted luminal binding interface between nsp3 and nsp4 that is membrane-associated, conserved in SARS-CoV-2 during the COVID-19 pandemic and in diverse coronaviruses, and stable in molecular dynamics simulation. Combined with structure predictions for the full-length nsp4 monomer and cryo-EM data, this suggests a DMV pore model in which nsp4 spans both membranes with nsp3 and nsp4 inserted into the same bilayer. This approach may be able to identify additional protein-protein interactions between coronavirus proteins.