Early Detection of Emerging SARS-CoV-2 Variants of Interest for Experimental Evaluation (preprint)

ABSTRACT

Since the beginning of the COVID-19 pandemic, SARS-CoV-2 has demonstrated its ability to rapidly and continuously evolve, leading to the emergence of thousands of different sequence variants, many with distinctive phenotypic properties. Fortunately, the broad availability of next generation sequencing (NGS) technologies across the globe has produced a wealth of SARS-CoV-2 genome sequences, offering a comprehensive picture of how this virus is evolving so that accurate diagnostics and reliable therapeutics for COVID-19 can be maintained. The millions of SARS-CoV-2 sequences deposited into genomic sequencing databases, including GenBank, BV-BRC, and GISAID are annotated with the dates and geographical regions of sample collection, and can be aligned to the Wuhan-Hu-1 reference genome to extract the constellation of nucleotide and amino acid substitutions. By aggregating these data into concise datasets, the spread of variants through space and time can be assessed. Variant tracking efforts have focused on the spike protein due to its critical role in viral tropism and antibody neutralization. To identify emerging variants of concern as early as possible, we developed a computational pipeline to process the genomic data from public databases and assign risk scores based on both epidemiological and functional parameters. Epidemiological dynamics are used to identify variants exhibiting substantial growth over time and across geographical regions. In addition, experimental data that quantify Spike protein regions critical for adaptive immunity are used to predict variants with consequential immunogenic or pathogenic impacts. These growth assessment and functional impact scores are combined to produce a Composite Score for any set of Spike substitutions detected. With this systematic approach to routinely score and rank emerging variants, we have established a method to identify threatening variants early and prioritize them for experimental evaluation.