Empowering SARS-CoV-2 Genomics Surveillance in Missouri with Data Analytics and Integration Portals

Introduction and Background

The coronavirus disease 2019 (COVID-19) caused by SARS-CoV-2 that emerged in late 2019, has spread rapidly across the world and was declared as global pandemic by the Word Health Organization (WHO) on March 11, 2020. Since then, it has ravaged many countries worldwide resulting in an exponential increase in infection rate and mortality.

Like other RNA viruses, SARS-CoV-2 continues to develop genomic changes affecting its transmission capacity, COVID-19 clinical severity, and viral response to therapeutics. The ongoing surge of progressively more infectious SARS-CoV-2 variants seen worldwide continues to have a significant impact on population health.¹ The Centers for Disease Control’s SARS-CoV-2 genomic surveillance program provides state level estimates of variant proportions, but reporting is delayed nearly one month and does not provide the level of granularity needed for local estimates. For those reasons, public health response to emerging new virus variants could be delayed and less efficient.

To overcome this limitation, and to allow for targeted sampling and sequencing of cases of particular clinical or epidemiological significance, our team developed a new Genomics Surveillance Architecture to better understand prevalence of existing variants and to quickly identify emergence of new SARS-CoV-2 variants in Missouri. This architecture allows us to streamline acquisition, processing, analysis and evaluation of sequencing data from SARS-CoV-2 positive samples in a timely manner and enables local or regional estimates of infection prevalence. We implemented a bioinformatics end-to-end data analysis pipeline for SARS-CoV-2 variants and a COVID-19 Genomics Surveillance Data Portal for tracking information at the University of Missouri (MU), in close collaboration with Missouri Department of Health and Senior Services (MDHSS) and Missouri State Public Health Laboratory (MSPHL).

Genomics Surveillance Data Analytics

The SARS-CoV-2 positive samples collected through the MDHSS COVID-19 surveillance are sequenced by MSPHL using Illumina sequencing technology and the raw sequence reads shared via Illumina’s BaseSpace platform. The data analysis pipeline at MU runs on high-performance computing (HPC) Linux clusters and starts the analysis with automated data downloads and quality checks. It further completes assembly of the consensus sequence, variant identification for every sample in the batch, generates a summary table and surveillance report after integrating all results, incorporates the data into the COVID-19 Genomics Surveillance Data Portal, and later submits sequences to GISAID database (Figure 1). We use several widely utilized open-source tools for the analysis, such as FastQC for the raw sequence reads quality checks, Seqclean for the reads filtering, BWA for reads alignments, Pangolin for lineage classification, Nextclade for mutation calling and clade classification, and Nextstrain for the phylogenetic tree and cluster analysis. All the analyzed SARS-CoV-2 sample sequences with greater than 90% genome coverage from all batches processed in a week are then submitted to the GISAID database.

Figure 1.

SARS-CoV-2 Genomics Surveillance Architecture and tools incorporated into the bioinformatics data analysis pipeline.

Genomics Surveillance Data Portal

Variants of concern (VOCs) and variants of interest (VOIs), as defined by CDC, are actively monitored in our pipeline to estimate local prevalence in Missouri. Since the establishment of the Genomic Surveillance Architecture in January 2021, the Alpha variant (B.1.1.7) emerged as a dominant SARS-CoV-2 variant in Missouri through April 2021, followed by the Delta variant dominance (B.1.617.2) until December 2021, with its first detection in Missouri as early as March 2021. The Delta variant wave was followed by the emergence of the Omicron variant (B.1.1.529) with an estimated 10-fold increase in infectivity compared to the ancestral strain, and 2.8 times higher infectiousness than the Delta variant.² Omicron quickly became completely dominant in Missouri since its emergence in December 2021 and continues to the present date (Figure 2).

Figure 2.

Weekly trends of variants of concern (VOCs) by sample collection date, February 2021–April 2022.

Evolutionary relationship between variants identified from 6,818 SARS-CoV-2 positive samples sequenced by MSPHL between March 2020 and March 2022 is demonstrated by the phylogenetic tree (Figure 3). The 20I (Alpha, V1), 21A (Delta), and 21M (Omicron) are three significant clusters which emerged during the sequencing period, with the Omicron variants being the most divergent with a high number of mutations compared to Alpha and Delta variants.

Figure 3.

Phylogenetic tree of the SARS-CoV-2 variants (n=6,818), March 2020–March 2022.

Summary

The SARS-CoV-2 Genomics Surveillance Architecture and COVID-19 Genomics Surveillance Data Portal is an exemplar of the interdisciplinary partnerships needed to establish a successful genomics surveillance program capable of providing timely identification of virus variants essential to informed decision-making and proper public health response.

Funding Statement

This work is supported by funding from Missouri Department of Health and Senior Services (MDHSS)-Contract #AOC21380080.