Genomic sequencing reveals unique pattern of SARS-CoV-2 Epsilon emergence in Alaska

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In a recent study posted to the medRxiv* pre-print server, researchers used genomic sequencing to examine severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genomes from Alaska, United States (US), between December 2020 and June 2021.

Study: Founder effect contributes to the unique pattern of SARS-CoV-2 variant B.1.1.519 emergence in Alaska. Image Credit: Paranyu/Shutterstock
Study: Founder effect contributes to the unique pattern of SARS-CoV-2 variant B.1.1.519 emergence in Alaska. Image Credit: Paranyu/Shutterstock

This news article was a review of a preliminary scientific report that had not undergone peer-review at the time of publication. Since its initial publication, the scientific report has now been peer reviewed and accepted for publication in a Scientific Journal. Links to the preliminary and peer-reviewed reports are available in the Sources section at the bottom of this article. View Sources

During this period, Alaska witnessed a surge in coronavirus disease 2019 (COVID-19) cases due to the SARS-CoV-2 lineage B.1.1.519 (Epsilon), and a founder effect contributed to the unique pattern of B.1.1.519 emergence and dissemination in Alaska.

Background

Several studies have suggested that geographic and sociodemographic factors contribute to the emergence, evolution, and transmission of SARS-CoV-2 variants globally.

Despite being the largest state in the US by area, Alaska has the lowest population density and has unique community dynamics compared to the contiguous US states (lower 48). While its two economic regions are densely populated and highly intersected, its rural areas are sporadically populated and reachable by water or air transportation.

It is approximately 800 km from the lower 48, so the researchers explored how different was Alaska’s pattern of SARS-CoV-2 variant emergence. Expectedly, they observed prominent differences in the prevalence of the SARS-CoV-2 Epsilon variant between Alaska and the lower 48 in early 2021.

About the study

In the current study, researchers downloaded 2,323 SARS-CoV-2 genomic sequences available on the Global Initiative on Sharing Avian Influenza Data (GISAID), and starting February 2022, they analyzed these sequences to increase genomic surveillance of SARS-CoV-2 variants as part of the Alaska SARS-CoV-2 Sequencing Consortium. The serum samples for these sequences were collected by the authorities of the Alaska Division of Public Health (AKDPH) and volunteers of the University of Alaska between 29 November 2020 and 26 June 2021 in Alaska, US.

For the lower 48, the research team gathered 1,331,799 sequences from GenBank, including Pangolin assignment, geolocation, and isolate for all the samples; additionally, they filtered out cases from Hawaii, Alaska, and other US territories to limit study comparisons to the lower 48. They used the Centers for Disease and Control and Prevention (CDC) COVID-19 data tracker site for gathering daily case data with a mean of seven days.

The study presented an estimate of the prevalence of the following SARS-CoV-2 lineages - B.1.617.2 and AY sublineages (Delta), B.1.525 (Eta), B.1.1.519, B.1.427/429 (Epsilon), B.1.617.1 (Kappa), C.37 (Lambda), B.1.526 (Iota), B.1.621 (Mu), B.1.351 (Beta), B.1.1.7 (Alpha), and P.1 (Gamma) in Alaska compared to the lower 48.

The SARS-CoV-2 variant prevalence data were computed for each week during the study period and compared to prevalence rates in other geographical locations, especially the lower 48.

The researchers used the Nextclade version 1.13.2 to determine the number of the amino acid (AA) mutations in the SARS-CoV-2 spike (S) glycoprotein. The Wilcoxon test was used to identify the differences in AA mutations between the emerging sublineages and lineages.

Study findings

The analysis of genomic data from outbreak.info, a sequence repository of GISAID, showed that Epsilon was highly prevalent worldwide in early March 2021, a month before Alaska’s peak prevalence. Notably, this variant was detected in sequencing data from Alaska five weeks after its detection in the US, i.e., in December 2020.

By the end of January 2021, Alpha and Epsilon had emerged and were being steadily detected in the US sequencing data, thus, 5% of sequenced cases in the lower 48 were due to Alpha by this time. However, at this time, Alaska had only one case of Alpha and no cases of Epsilon. In February 2022, Epsilon constituted 10.4% of Alaska’s SARS-CoV-2 sequences; such high prevalence rates also point at temporal and spatial heterogeneity in sequencing data.

Epsilon reached a peak prevalence of 77.9% in Alaska, five weeks after attaining the peak in the lower 48. Epsilon comprised a high percentage of sequenced cases from January to March 2021 in the Interior economic region of Alaska, 360 miles away from its another large economic region, the Anchorage-Mat Su.

By the end of February, Epsilon accounted for 37.8% and 10.5% of sequenced cases in the Anchorage-Mat Su and the Interior regions, respectively. By April 2021, the proportions of Epsilon sequenced cases in the Interior and the Anchorage-Mat Su regions were 77.2% and 72.6%, respectively. After attaining a peak on April 4, 2021, the prevalence of Epsilon in May decreased to 74.1% and 38.8% for the Interior and Anchorage-Mat Su regions, respectively.

The study revealed that the mutations in the SARS-CoV-2 genomes (from Alaska) occurred in a clockwise manner. The Wilcoxon test results suggested that Epsilon had more AA substitutions in the S protein than lineages detected in Alaska before its peak prevalence. Therefore, it had a competitive advantage over pre-peak circulating lineages; however, genomes sequenced after its peak prevalence were assigned to Alpha and Delta, having more AA mutations than Epsilon. This finding indicates that both Alpha and Delta had a selective advantage that allowed them to replace Epsilon in Alaska, a phenomenon also previously observed across Alpha and Delta waves in the USA.

The founder effect reduced the genetic diversity from a founding SARS-CoV-2 lineage that helps it outcompete its previously circulating lineage(s) because the founding population had a selective advantage, thus explaining how Epsilon likely emerged and became dominant in Alaska. In other US states, especially the lower 48, the same trend was not observed. This was most likely because Alpha, which could potentially outcompete Epsilon, had already established itself within the population.

At a country level, for instance, in Mexico, Epsilon was first detected in November 2020, about three months before its detection in Alaska. Thereafter, Epsilon rapidly outcompeted existing variants to become the dominant variant in Mexico comprising 51.5% of sequenced genomes by January 2021.

Conclusions

The stud demonstrated the importance of robust genomic sequencing efforts to examine the distinctive and unique patterns of SARS-CoV- 2 variant emergence and transmission. Further, the study highlighted how founder effects influenced the observed regional differences in the circulating SARS-CoV-2 lineages in Alaska.

Overall, the study data could prove beneficial in informing public health decisions when SARS-CoV-2 will become endemic in Alaska and globally.

This news article was a review of a preliminary scientific report that had not undergone peer-review at the time of publication. Since its initial publication, the scientific report has now been peer reviewed and accepted for publication in a Scientific Journal. Links to the preliminary and peer-reviewed reports are available in the Sources section at the bottom of this article. View Sources

Source:
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Article Revisions

  • May 12 2023 - The preprint preliminary research paper that this article was based upon was accepted for publication in a peer-reviewed Scientific Journal. This article was edited accordingly to include a link to the final peer-reviewed paper, now shown in the sources section.
Neha Mathur

Written by

Neha Mathur

Neha is a digital marketing professional based in Gurugram, India. She has a Master’s degree from the University of Rajasthan with a specialization in Biotechnology in 2008. She has experience in pre-clinical research as part of her research project in The Department of Toxicology at the prestigious Central Drug Research Institute (CDRI), Lucknow, India. She also holds a certification in C++ programming.

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