Determining factors of transmission and evolution of SARS-CoV-2 in populations at risk

National Institute Of Allergy And Infectious Diseases

Investigators

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Abstract

The major aspects of this project involve characterizing SARS-CoV-2 genetic diversity and microbial communities in the respiratory tract during infection. This involves analyzing samples from COVI19 positive subjects, and from model animal infections. Whole genome sequencing of SARS-CoV-2 has become crucial for epidemiology studies and to determine how the virus sweeps through various populations, with the transmission potential of new emerging variants. We have ongoing genomic epidemiology studies: one study includes a surveillance project of SARS-CoV-2 in the NIH worker population, where more than 1000 asymptomatic and symptomatic positive cases have been identified. The second is a set of collaborations with clinical and public health teams in the Dominican Republic and Haiti. For the DR/Haiti study, we are combining phylogenetics with travel history data, and are using the viral diversity information to determine the number of independent introductions into each of these countries that shutdown their borders and airports early in the pandemic. From a public health perspective, it will also enable an evaluation of how efficient border closings are in limiting the introduction of new variants. The Caribbean is a populous region (>40 million people in the island states) at the crossroads of many trade routes and visited by tourists from around the world, yet is drastically undersampled relative to Europe and North America. We analyzed samples from Haiti in Spring 2020, making this the biggest collection from a single Caribbean island in this time period studied so far. Although the number of specimens sequenced in this study nearly doubles the number of specimens available for the early pandemic in the region, the absolute number of samples is small compared to the scale of sequencing in other parts of the world. This increase is nevertheless sufficient to demonstrate that covid-19 was spreading among Caribbean islands in early 2020 and to show that at least one lineage was possibly introduced from the Caribbean into North America, where it sustained community submission over a period of several months. Since the first reported US introduction of SARS-CoV2 in Washington state on January 19, 2020, hotspots of the virus have arisen in all major US cities and areas. Sequencing of virus isolates from infected patients in these cities has helped to determine the number and origin of introduction events, and key amino acid changes that differentiate clades of the virus in circulation. While identification of new clades and lineages, and the associated viral consensus changes help in tracking spread of the virus, few studies have been done on the minority variants present in infected individuals. These minority variants could be seeding the emergence of new clades, thus identifying them early is of relevance for preparedness and to track transmission events. Errors made during replication that are not deleterious or lethal to the virus can lead to the generation of these minority variants. However, the identification of minority variants in SARS-CoV-2 sequence data is complicated by errors introduced during amplification and sequencing of the genome. To help delineate minority variants from introduced errors, we used simulated data to test the ability of 7 software packages to accurately call variants at a range of allele frequencies and coverage cutoffs. Using the results of these tests, we analyzed minority variants within the SARS-CoV-2 data in a sample set from Maryland and in more recent sequence data from clusters of transmission. Our data suggest that analysis of shared minority variants could help identify regions of the SARS-CoV-2 genome that are under increased selective pressure, as well as inform transmission chains and give insight into possible variant strain emergence. Roder et al. BioRXiv https://doi.org/10.1101/2021.05.05.442873 In our first study of the airway microbiome of COVID19 patients, we focused on the metagenomic and metatranscriptomic analysis of cross-sectional BAL samples collected from mechanically ventilated patients during the first wave of the pandemic in NYC. However, while these patients all had severe disease requiring intubation, the mortality rate was much lower in this cohort because only stable patients could undergo bronchoscopy. In a follow-up study, we are analyzing longitudinal samples from the first wave and from the second wave with approximately 70 patients for which 1-5 samples were collected up to 6 weeks follow-up. Samples from the first wave are from BAL, while samples from the 2nd wave are primarily tracheal aspirates, which allows us to analyze the microbiome for critically ill patients who could not undergo bronchoscopies. From the same cohort as well as from a cohort at Weil Cornell (PI: M. Salvatore), we are looking at how the virus evolves in immunocompromised patients. Since immunocompromise has become of particular interest as it allows to see what genetic space the virus can explore, we have initiated a study in May with Dr. Mehul Suthar (Emory) who collected virus from nasal turbinates of CD4CD8 T cell depleted mice. In an ongoing collaboration with Dr. James Musser (Houston Methodist), we used deep sequences of thousands of SARS-CoV-2 clinical samples to explore within-host diversity of the virus from a high-throughput viral surveillance program associated with a large hospital system. We find that, although the within-host diversity of the virus is overall low, there exists a sizable minority of individuals harboring high within-host diversity. These individuals are overrepresented among hospitalized patients compared to outpatients. The understanding that mutations accumulate more readily among the more severely ill reinforces the importance of transmission control in healthcare settings. It also suggests new avenues of research on differences between mutation accumulation dynamics in different types of patients. In a pandemic that has thus far been characterized by considerable heterogeneity in patient outcomes and transmission dynamics, our results suggest that it is worth further investigating heterogeneity in within-host viral population genetic changes. Mushegian et al Medrxiv https://doi.org/10.1101/2022.08.17.22278898