Design of a companion bioinformatic tool to detect the emergence and geographical distribution of SARS-CoV-2 Spike protein genetic variants

Abstract

Background: Tracking the genetic variability of Severe Acute Respiratory Syndrome CoronaVirus 2 (SARS-CoV-2) is a crucial challenge. Mainly to identify target sequences in order to generate robust vaccines and neutralizing monoclonal antibodies, but also to track viral genetic temporal and geographic evolution and to mine for variants associated with reduced or increased disease severity. Several online tools and bioinformatic phylogenetic analyses have been released, but the main interest lies in the Spike protein, which is the pivotal element of current vaccine design, and in the Receptor Binding Domain, that accounts for most of the neutralizing the antibody activity.

Methods: Here, we present an open-source bioinformatic protocol, and a web portal focused on SARS-CoV-2 single mutations and minimal consensus sequence building as a companion vaccine design tool. Furthermore, we provide immunogenomic analyses to understand the impact of the most frequent RBD variations.

Results: Results on the whole GISAID sequence dataset at the time of the writing (October 2020) reveals an emerging mutation, S477N, located on the central part of the Spike protein Receptor Binding Domain, the Receptor Binding Motif. Immunogenomic analyses revealed some variation in mutated epitope MHC compatibility, T-cell recognition, and B-cell epitope probability for most frequent human HLAs.

Conclusions: This work provides a framework able to track down SARS-CoV-2 genomic variability.

Keywords: Bioinformatic workflow; COVID mutations; Docker; SARS-CoV-2 genome; SARS-CoV-2 mutation; SARS-CoV-2 vaccine.

Fig. 1

a Workflow of the Covid-Miner package. The execution is fully automatized and encapsulated in a Docker container. b LolliPlot representation of SARS-CoV-2 variants at 1% frequency for the whole SARS-CoV-2 genome and from 0.5 to 10% for the Spike protein locus, showing the most frequent RBD variants at codon 447 (7%) and 439 (0.7%). c Barplot from occurrences of most frequent RBD variations

Fig. 2

a Heatmap of Receptor Binding Domain variants geographical distribution by normalized frequency. Countries with low occurrences of RBD variants (less than 5) were removed. b Multiple Correspondence Analysis (MCA) of Country-RBD variant association. c Evolution of S447N and N439K in space and time. Y-axis represents the relative frequency of that mutation in every country isolate set for each month. X-axis: months in 2020, as annotated in GISAID sequences. Every bar is annotated with absolute counts

Fig. 3

a Heatmap representing T-cell immunogenicity scores for wild-type and mutated RBD epitopes. b Screenshot of covid-miner web portal homepage. c Donut plot of RBD mutational impact of overall sequences and September 2020 sequences. d Location of the most frequent RBD mutated amino acids N439 and S477