Biology subjects

Doud, M. B.

Publications and source records attributed to Doud, M. B..

4 recordsLinked to original sources

bioRxiv2018

Deep mutational scanning of hemagglutinin helps predict evolutionary fates of human H3N2 influenza variants

Human influenza virus rapidly accumulates mutations in its major surface protein hemagglutinin (HA). The evolutionary success of influenza virus lineages depends on how these mutations affect HAs functionality and antigenicity. Here we experimentally measure the effects on viral growth in cell culture of all single amino-acid mutations to the HA from a recent human H3N2 influenza virus strain. We show that mutations that are measured to be more favorable for viral growth are enriched in evolutionarily successful H3N2 viral lineages relative to mutations that are measured to be less favorable for viral growth. Therefore, despite the well-known caveats about cell-culture measurements of viral fitness, such measurements can still be informative for understanding evolution in nature. We also compare our measurements for H3 HA to similar data previously generated for a distantly related H1 HA, and find substantial differences in which amino acids are preferred at many sites. For instance, the H3 HA has less disparity in mutational tolerance between the head and stalk domains than the H1 HA. Overall, our work suggests that experimental measurements of mutational effects can be leveraged to help understand the evolutionary fates of viral lineages in nature -- but only when the measurements are made on a viral strain similar to the ones being studied in nature.\n\nSignificance StatementA key goal in the study of influenza virus evolution is to forecast which viral strains will persist and which ones will die out. Here we experimentally measure the effects of all amino-acid mutations to the hemagglutinin protein from a human H3N2 influenza strain on viral growth in cell culture. We show that these measurements have utility for distinguishing among viral strains that do and do not succeed in nature. Overall, our work suggests that new high-throughput experimental approaches may be useful for understanding virus evolution in nature.

evolutionary biology↗

bioRxiv2017

Quantifying the ease of viral escape from broad and narrow antibodies to influenza hemagglutinin

Influenza virus can completely escape most antibodies with single mutations. However, rare antibodies broadly neutralize many viral strains. It is unclear how easily influenza virus might escape such antibodies if it was under strong pressure to do so. Here we map all single amino-acid mutations that increase resistance to broad antibodies targeting an H1 hemagglutinin. Crucially, our approach not only identifies antigenic mutations but also quantifies their effect sizes. All antibodies select mutations, but the effect sizes vary widely. The virus can escape a broad antibody that targets residues in hemagglutinins receptor-binding site the same way it escapes narrow strain-specific antibodies: via single mutations with huge effects. In contrast, broad antibodies targeting hemagglutinins stalk only select mutations with small effects. Therefore, among the antibodies we have examined, breadth is an imperfect indicator of the potential for viral escape via single mutations. Broadly neutralizing antibodies targeting the H1 hemagglutinin stalk are quantifiably harder to escape than the other antibodies tested here.

microbiology↗

bioRxiv2017

phydms: Software for phylogenetic analyses informed by deep mutational scanning

BackgroundThe evolution of protein-coding genes can be quantitatively modeled using phylogenetic methods. Recently, it has been shown that high-throughput experimental measurements of mutational effects made via deep mutational scanning can inform site-specific phylogenetic substitution models of gene evolution. However, there is currently no software tailored for such analyses.\n\nResultsWe describe software that efficiently performs phylogenetic analyses with substitution models informed by deep mutational scanning. This software, phydms, is [~]100-fold faster than existing programs that accommodate such substitution models. It can be used to compare the results of deep mutational scanning experiments to the selection on genes in nature. For instance, phydms enables rigorous comparison of how well different experiments on the same gene describe natural selection. It also enables the re-scaling of deep mutational scanning data to account for differences in the stringency of selection in the lab and nature. Finally, phydms can identify sites that are evolving differently in nature than expected from experiments in the lab.\n\nConclusionsThe phydms software makes it easy to use phylogenetic substitution models informed by deep mutational scanning experiments. As data from such experiments becomes increasingly widespread, phydms will facilitate quantitative comparison of the experimental results to the actual selection pressures shaping evolution in nature.

evolutionary biology↗

bioRxiv2016

Complete mapping of viral escape from neutralizing antibodies

Identifying viral mutations that confer escape from antibodies is crucial for understanding the interplay between immunity and viral evolution. Here we quantify how every amino-acid mutation to influenza hemagglutinin affects neutralization by monoclonal antibodies targeting several antigenic regions. Our approach involves creating all replication-competent protein variants of the virus, selecting these variants with antibody, and using deep sequencing to identify enriched mutations. These high-throughput measurements are predictive of the effects of individual mutations in traditional neutralization assays. At many residues, only some of the possible mutations escape from an antibody. For instance, at a single residue targeted by two different antibodies, we identify some mutations that escape both antibodies and other mutations that escape only one or the other. Therefore, our approach maps how viruses can escape antibodies with mutation-level sensitivity, and shows that only some mutations at antigenic residues actually alter antigenicity.

microbiology↗