A biophysical model of viral escape from polyclonal antibodies

Abstract

A challenge in studying viral immune escape is determining how mutations combine to escape polyclonal antibodies, which can . potentially target multiple distinct viral epitopes. Here we introduce a biophysical model of this process that partitions the total polyclonal antibody activity by epitope, and then quantifies how each viral mutation affects the antibody activity against each epitope. We develop software that can use deep mutational scanning data to infer these properties for polyclonal antibody mixtures. We validate this software using a computationally simulated deep mutational scanning experiment, and demonstrate that it enables the prediction of escape by arbitrary combinations of mutations. The software described in this paper is available at https://jbloomlab.github.io/polyclonal .

A pseudovirus system enables deep mutational scanning of the full SARS-CoV-2 spike

“…All the tested mutations exhibited neutralization phenotypes consistent with those measured in the deep mutational scanning. Furthermore, the neutralization assay IC50 values correlated well with those predicted by our biophysical model (Yu et al, 2022) parameterized by the deep mutational scanning data (Figure 4F).…”

“…We first mapped escape from LY-CoV1404, applying the approach in Figure 3B to our three independent BA.1 libraries, and performing a technical replicate for one library. We used a biophysical model to decompose the measurements for spike variants in our libraries (some of which are multiply mutated) into escape scores for individual mutations (Yu et al, 2022). These mutation escape scores correlated well among technical and biological replicates (Figure 4A).…”

“…We use additional concentrations as it helps us to cover a greater dynamic concentration range in cases where the exact IC 99 value is difficult to determine. Also, the use of multiple concentrations enables more precise mutation-escape predictions by the biophysical model used to decompose single-mutation effects (Yu et al, 2022). For LY-CoV1404 starting concentration was 0.654 μg/ml, for CC9.104 - 68 μg/ml, for CC67.105 - 52.5 μg/ml.…”

“…To deconvolve mutation-level escape values from the measured 𝑝 " (𝑐) values for the variants (which often contain multiple mutations) at multiple concentrations, we used the approach implemented in polyclonal software package (https://jbloomlab.github.io/polyclonal/) (Yu et al, 2022), constraining the fits to a single epitope (since we are only analyzing monoclonal antibodies). This analysis yields a mutation-level escape score for each observed variant (the 𝛽 -,* values in the nomenclature of the polyclonal package) which will be zero for mutations that have no effect on antibody escape, and >0 for mutations that mediate antibody escape.…”

“…These are the values plotted in the heat maps shown in the antibody escape figures in this paper; the line plots show site-level summaries of these values (eg, the sum of the escape values at each site). Note that the polyclonal models (Yu et al, 2022) can use the escape values inferred from the deep mutational scanning to predict the non-neutralized fraction for arbitrary mutants, and we correlated those measurements with the IC50 values measured by standard neutralization assays in the antibody escape figures in this paper. For all antibodies we had replicate measurements (multiple libraries, and in some cases technical replicates of the same library), and the final reported values are the average (median) across these replicates.…”