Identifying viral mutations that confer escape from antibodies is crucial for understanding the interplay between immunity and viral evolution. We describe a high-throughput approach to quantify the selection that monoclonal antibodies exert on all single amino-acid mutations to a viral protein. This approach, mutational antigenic profiling, involves creating all replication-competent protein variants of a virus, selecting with antibody, and using deep sequencing to identify enriched mutations. We use mutational antigenic profiling to comprehensively identify mutations that enable influenza virus to escape four monoclonal antibodies targeting hemagglutinin, and validate key findings with neutralization assays. We find remarkable mutation-level idiosyncrasy in antibody escape: for instance, at a single residue targeted by two antibodies, some mutations escape both antibodies while other mutations escape only one or the other. Because mutational antigenic profiling rapidly maps all mutations selected by an antibody, it is useful for elucidating immune specificities and interpreting the antigenic consequences of viral genetic variation.

Many viruses evolve rapidly, and this evolution sometimes enables them to escape antibodies that would otherwise neutralize their infectivity. An important aspect of studying this evolution is determining which viral mutations can mediate antibody escape. The classic way of identifying such mutations is to select or test them one by one. However, a vast number of possible mutations can be made to a virus. For instance, there are over 10,000 single amino-acid mutations that can be made to the most abundant surface protein of influenza virus, hemagglutinin. This is too many to test one by one, and so all previous studies of antibody escape have examined just a fraction of the possible amino-acid mutations to any given viral protein. Here we describe a new approach to quantify the selection that an antibody exerts on all these mutations in a single experiment. This approach enables us to reproducibly and sensitively identify mutations that affect antibody neutralization—for instance, at individual sites in hemagglutinin, we can distinguish which of several different mutations have the largest effect on antibody escape. The ability to completely map viral escape from antibodies opens the door to much more detailed characterization of viral antigenic evolution.

Funding: This work was supported by grants R01GM102198 and R01AI127893 from the NIGMS and NIAID of the NIH to JDB and grants 1R01AI113047 and 1R01AI108686 from the NIAID of the NIH to SEH. The research of JDB was also supported in part by a Faculty Scholar grant from the Howard Hughes Medical Institute and the Simons Foundation. MBD was supported in part by training grant T32AI083203 from the NIAID of the NIH. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Data Availability: Deep sequencing data has been deposited at the Sequence Read Archive under BioSample accession SAMN05789126. S2 File contains an iPython notebook (and a static HTML version of this notebook) that performs all analyses of deep sequencing data. Processed deep sequencing data and all computer code can also be found at https://github.com/mbdoud/mutational_antigenic_profiling . Logo plots of the differential selection by each antibody spanning the entire gene, averaged across the replicate libraries, are provided in S3 Fig, S4 Fig, S5 Fig, and S6 Fig. Files providing the mutation differential selection values, averaged across the replicate libraries for each antibody at each concentration tested, are in S3 File.

Copyright: © 2017 Doud et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Here we use massively parallel experiments to rapidly map all single amino-acid mutations to HA that enable influenza virus to escape from four neutralizing antibodies. Our approach involves imposing antibody selection on virus libraries generated from all amino-acid point mutants of HA, and using deep sequencing to quantify the selection on every mutation in the context of actual replication-competent virus. The resulting comprehensive map of antibody escape reveals remarkable mutation-level idiosyncrasy for each antibody: for instance, at many residues only some of the possible amino-acid mutations confer escape, and two antibodies targeting the same residue elicit unique profiles of escape mutations. Mutational antigenic profiling therefore enables complete and high-resolution mapping of viral antibody escape mutations.

A complete structural definition of the interface between an antibody and antigen can be obtained using methods such as X-ray crystallography. However, obtaining such structures remains non-trivial, particularly since viral surface proteins are often heavily glycosylated [ 19 ] and sometimes conformationally heterogeneous [ 20 ]. In addition, structural definitions do not reveal which mutations actually escape antibody neutralization. Mutations at only a subset of the residues in the antibody-antigen interface actually disrupt binding [ 21 – 24 ], a “hot spot” phenomenon observed in protein-protein interfaces more generally [ 25 – 27 ].

Another approach is to individually test antibody binding or neutralization for each member of a panel of viral variants. However, there are ∼10 4 single amino-acid mutants to a 500-residue viral protein, so individually creating and testing all of them is a daunting task. Therefore, even the most ambitious such studies limit themselves to a small fraction of the possible point mutations, such as by only testing mutations to alanine [ 13 – 15 ]. But as the current work will underscore, the antigenic effect of mutating a residue to one amino acid can be poorly predictive of the effects of mutating the same residue to another amino acid. Furthermore, the difficulty in individually generating and testing large numbers of viral variants means that such studies often use simpler assays (e.g., hemagglutination-inhibition, pseudovirus neutralization, or protein binding) that can be imperfect surrogates for how well a mutation enables a replication-competent virus to escape antibody neutralization [ 16 – 18 ].

The classic approach for identifying such mutations is to select individual viral mutants that are resistant to neutralization by antibodies. For instance, escape-mutant selections with a panel of monoclonal antibodies were used to broadly define major antigenic regions of influenza HA [ 10 – 12 ]. However, each such selection typically only identifies one of potentially many mutations that escape an antibody, with a strong bias towards whichever mutations happen to be prevalent in the initial viral stock. Therefore, escape-mutant selections provide an incomplete picture of the ways that a virus can escape an antibody.

Host immunity drives the evolution of many viruses. For instance, potent immunity against influenza virus is provided by antibodies against hemagglutinin (HA), the virus’s most abundant surface protein [ 1 ]. Unfortunately, these antibodies also select amino-acid substitutions in the HA of human seasonal influenza A virus at a rate of over two per year [ 2 , 3 ]. This rapid evolution degrades the effectiveness of anti-influenza immunity, and is a major reason why humans are repeatedly re-infected over their lifetimes. Extensive antigenic variation is also a hallmark of several other medically relevant viruses, most prominently HIV. Efforts to induce immunity to such viruses must therefore account for antigenic variation, either by targeting vaccines against current circulating viral strains [ 4 , 5 ] or developing methods to administer [ 6 , 7 ] or elicit [ 8 , 9 ] antibodies that recognize a broad range of strains. An important component of these efforts is identifying which viral mutations escape neutralization by specific antibodies.

Results

Complete mapping of escape mutations from four monoclonal antibodies We next extended the mutational antigenic profiling to three more antibodies. We performed selections with each antibody at concentrations at which the virus libraries retained 0.1 to 0.4% of their infectivity (S1 Table). Each antibody exerted strong selection at a small number of residues in HA. Fig 4A shows site differential selection across HA, while Fig 4B uses logo plots to show detailed mutation-level selection at some key positions in the antibody epitopes. We again performed three full biological replicates with each antibody, and the results were again highly reproducible among replicates (S1 Fig). PPT PowerPoint slide

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larger image TIFF original image Download: Fig 4. Mutational antigenic profiling of four antibodies. (A) Each antibody exerts a different profile of selection on HA. (B) Zoomed in view of some of the most strongly selected sites for each antibody. The wild-type amino acid is shown under the logoplots. Sites where mutations were selected in classical escape-mutant selections [11, 12] are underlined. Logoplots spanning all of HA are in S3, S4, S5 and S6 Figs. (C) The selection from each antibody visualized on HA’s structure (PDB 1RVX [54]). Each site is colored from white to red based on the differential selection for the most strongly selected mutation at that site. Red indicates strong differential selection. All structures show trimeric HA in the same orientation (the epitope is visible for two of the three monomers for H17-L19, H17-L7, and H18-S415). See S2 Fig for a zoomed-in structural view. The y-axis scale is set separately for each antibody; since the measured strength of differential selection depends on the concentration / potency of the antibody and the mutational tolerance of the viral epitope, it was impossible to precisely standardize selection strength across antibodies. The scale bar in each logo plot shows the letter height for a mutation with differential selection of 8 (a 256-fold enrichment). The data for each antibody is the average across three biological replicates. https://doi.org/10.1371/journal.ppat.1006271.g004 For each antibody, the sites of strongest differential selection were clustered in surface-exposed patches on HA’s structure that are presumably within the antibody-binding footprint (Fig 4C and S2 Fig). The four antibodies target three antigenic regions: H17-L19 targets Ca2, H17-L10 targets Ca1, and H17-L7 and H18-S415 both target Cb [11, 12]. As expected, H17-L19 and H17-L10 exert strong selection on entirely distinct sets of residues, but H17-L7 and H18-S415 exert selection on similar sets of residues in the Cb antigenic region. For three of the antibodies, the strongly selected residues are within short contiguous stretches of primary amino-acid sequence, but for H17-L10 the strongly selected residues are distributed across 70 residues of HA’s primary sequence. Overall, these results show that mutational antigenic profiling can comprehensively identify the selection imposed by diverse antibodies.

Comparison to traditional neutralization assays The results above were obtained using experiments that examined tens of thousands of viral variants in parallel. How do these high-throughput measurements compare to the antigenic effects of mutations measured by traditional low-throughput methods? To address this question, we tested some of our key findings with neutralization assays on individual viral mutants. To do this, we used site-directed mutagenesis to introduce single amino-acid mutations into the HA gene, generated viruses by reverse genetics, and performed GFP-based neutralization assays [39]. A clear observation from the mutational antigenic profiling is that at some residues, only a few of the possible amino-acid mutations are strongly selected by any given antibody, concordant with prior work showing that a limited number of mutations are sufficient for antigenic drift [40]. For instance, at HA residue 154, the H17-L19 antibody exerts strong selection only for mutations H154E and H154D, both of which introduce a negatively charged amino acid (Figs 4B and 5A; residues are numbered sequentially beginning at the N-terminal methionine, other numbering schemes are in S1 File). We generated viruses carrying the H154E mutation or a mutation to alanine (H154A), which mutational antigenic profiling did not find to be under differential selection. Neutralization assays confirmed that the H154E mutant completely escaped at all antibody concentrations tested, while the H154A mutant was as sensitive to antibody as wild-type (Fig 5A). Therefore, a more limited method such as alanine scanning would not have identified residue 154 as a site of escape mutations. This finding demonstrates the importance of assaying all amino-acid mutations if the goal is to comprehensively map sites of escape. PPT PowerPoint slide

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larger image TIFF original image Download: Fig 5. Comparison of the selection measured by mutational antigenic profiling with the antigenic effects of mutations in traditional neutralization assays on individual viral mutants. In each panel, the logo plot shows the results of the mutational antigenic profiling at the sites of mutations chosen for testing, and the graph shows the results of the neutralization assays. There is excellent concordance between whether a mutation is strongly selected in the mutational antigenic profiling and whether it has an effect in the neutralization assay. In many cases, only some of the amino-acid mutations at a site strongly affect neutralization by a given antibody—and the mutational antigenic profiling reliably distinguishes between mutations that do and do not have an effect. The antibodies in each panel are: (A) H17-L19, (B) H17-L10, (C) H17-L7, (D) H18-S415. https://doi.org/10.1371/journal.ppat.1006271.g005 Another example of mutation-level sensitivity is HA residue 148, where antibody H17-L19 only selects for mutations to serine and threonine (Fig 4B). Both the V148T and V148S mutations introduce a motif (N-X-S/T) that potentially leads to glycosylation of the asparagine at site 146. To confirm that only some mutations at site 148 enable escape, we generated the V148T mutant as well as another mutant (V148R) that does not introduce a glycosylation motif. As expected, V148T dramatically reduced the virus’s sensitivity to the antibody, whereas V148R only had a small effect (Fig 5A). The mutational antigenic profiling suggests similar mutation-level sensitivity in escape from antibody H17-L10. At residue 234, there is strong differential selection only for mutations to the positively charged amino-acid residues lysine and arginine (Fig 4B). We generated a virus carrying one of these mutations (P234K) as well as a virus carrying another mutation at the same residue (P234V) that was not under differential selection. Neutralization assays confirmed that the P234K mutation escaped H17-L10, while the P234V mutation caused no change in antibody sensitivity (Fig 5B). Interestingly, in HA’s structure, site 234 is on a neighboring protomer relative to all the other mutations strongly selected by H17-L10 (S2 Fig). Our finding that escape mutations from H17-L10 cross the HA trimer interface is consistent with the fact that this antibody only recognizes trimeric HA [41]. Escape mutations at such epitopes are discernible because mutational antigenic profiling uses actual viruses that display intact HA; such conformational epitopes might not be properly displayed in the modified forms of viral glycoproteins often used in other high-throughput methods such as phage and yeast display. Overall, these results indicate the power of mutational antigenic profiling to map residues where only a few specific amino-acid mutations lead to escape from antibody. Because this approach examines HA in its native context on influenza virions, it can comprehensively map escape mutations even in complex conformational epitopes.

Unique repertoires of escape mutations from two antibodies targeting the same site in HA Two of the antibodies used in our study (H17-L7 and H18-S415) target the same antigenic region of HA, with residue 89 under strong selection from both antibodies (Fig 5C and 5D). Do these antibodies select the same or different amino-acid mutations at this residue? The mutational antigenic profiling suggests that both antibodies select mutations to negatively charged amino acids (P89D and P89E; Fig 5C and 5D). However, each antibody also selects a unique set of additional mutations, such as P89Y for H17-L7 and P89T for H18-S415. We generated viruses containing the P89D, P89Y, or P89T mutations and tested their sensitivity to both antibodies using neutralization assays. In agreement with the mutational antigenic profiling, the P89D mutant escaped both antibodies, but P89Y only escaped from H17-L7 and P89T only escaped from H18-S415 (Fig 5C and 5D). Thus, when two antibodies target the same site, there can be both common and antibody-specific routes of escape. Characterizing antibody escape at the level of protein sites therefore only provides a partial picture of antigenicity. A complete understanding of escape requires consideration of every mutation at every site.