The subtracks of this track show mutations that lead to escape from monoclonal antibodies obtained from different studies:
For the Bloom lab data, we show just a summary of the data. Fully detailed structural visualizations are available from the authors via dms-view for the 10 monoclonal antibodies.
and the 4 treatment antibodies.Features are labeled with the nucleotide and protein coordinates and the name of the antibody. Click a feature or mouse-over a feature to show these annotations.
Scores represent the "escape fraction" (discussed at length in the Methods of the paper) which "represent the fraction of a given variant that escape antibody binding, and should in principle range from 0 to 1."
A higher score indicates a greater level of escape.
Each subtrack contains all the scores representing mutations to a particular amino acid (each annotation is a Spike codon). For instance the A subtrack measures the escape fraction for a particular antibody if the annotated amino acid is mutated to alanine (if the wildtype amino acid is A, then the score is 0). The "total" subtracks represent the sum of all escape fractions for all amino acid changes at a position. The "max" subtracks are the escape fraction for the amino acid substitution with the greatest escape fraction.
"Note that the magnitude of the measured effects of mutations on antibody escape depends on the antibody concentration and the flow cytometry gates applied, meaning that the escape fractions are comparable across sites for any given antibody, but are not precisely comparable among antibodies without external calibration."
Visualizations of the data are available from the authors here.
10 Antibodies: Table S1 from Starr et al, was downloaded and parsed into bedGraph format.
21 Antibodies: Table 2 from Liu et al 2020, was copied manually and converted to bedGraph format.
4 Antibodies: Data was downloaded from the jbloomlab Github file and parsed into bedGraph format using the total and maximum values.
The raw data can be explored interactively with the Table Browser, or combined with other datasets in the Data Integrator tool.
Please refer to our mailing list archives for questions, or our Data Access FAQ for more information.
Greaney AJ, Starr TN, Gilchuk P, Zost SJ, Binshtein E, Loes AN, Hilton SK, Huddleston J, Eguia R, Crawford KHD et al. Complete Mapping of Mutations to the SARS-CoV-2 Spike Receptor-Binding Domain that Escape Antibody Recognition. Cell Host Microbe. 2020 Nov 19;. PMID: 33259788; PMC: PMC7676316
Zhuoming Liu, Laura A. VanBlargan, Paul W. Rothlauf, Louis-Marie Bloyet, Rita E. Chen, Spencer Stumpf, Haiyan Zhao, John M. Errico, Elitza S. Theel, Ali H. Ellebedy, Daved H. Fremont, Michael S. Diamond, Sean P. J. Whelan Landscape analysis of escape variants identifies SARS-CoV-2 spike mutations that attenuate monoclonal and serum antibody neutralization. Biorxiv. 2020
Starr TN, Greaney AJ, Addetia A, Hannon WW, Choudhary MC, Dingens AS, Li JZ, Bloom JD. Prospective mapping of viral mutations that escape antibodies used to treat COVID-19. bioRxiv. 2020 Dec 1;. PMID: 33299993; PMC: PMC7724661