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An antigenic atlas of HIV-1 escape from broadly neutralizing antibodies

Adam S. Dingens, Dana Arenz, Haidyn Weight, Julie Overbaugh, and Jesse D. Bloom

The manuscript accompanying this analysis has been published in to Immunity as An antigenic atlas of HIV-1 escape from broadly neutralizing antibodies distinguishes functional and structural epitopes.

We performed mutational antigenic profiling of a panel of bnAbs using the BG505.T332N mutant Env libraries, first described and characterized in Haddox, Dingens et al 2018. The triplicate mutant libraries examined here correspond to the three BG505 replicates in this paper. Replicates annotated with an additional letter (i.e. "rep 1b") were done on an independent day and have their own mock selected control.

The fraction surviving statistic used in this analysis is explained in detail here, and the computation of differential selection (computed here but not discussed in the paper) is described here. The barcoded subamplicon Illumina sequencing approach is described in detail here. Our first mutational antigenic profiling analysis of escape from PGT151 using the BF520 env libraries was published here in June 2017, and this original analysis is located in this ipython notebook.

We use dms_tools2 to analyze these data. This notebook processes the Illumina deep sequencing data software package, and then analyzes the selection in the context of the antibody. Experiments and analysis performed by Adam Dingens in the Bloom lab in 2017-2018.

Organization

The mutational antigenic profiling analysis is performed by the iPython notebook analysis_notebook.ipynb.

Subdirectories:

• ./results/ is generated by analysis_notebook.ipynb. It contains the codoncounts, fraction surviving, fration surviving above average, and differential selection data in individual directories. However, the easiest way to get median selection metrics for each antibody is from File S3.

• ./results/FASTQ_files/ contains the input Illumina deep sequencing data. This file is generated by analysis_notebook.ipynb, which downloads the sequencing files from the Sequence Read Archive.

• ./data/ contains all input data needed to run analysis_notebook.ipynb). Files are described in the iPython notebok when used.

Results and Conclusions

All of the results are breifly detailed in the analysis_notebook.ipynb notebook; click on this notebook to see the results.