Competition-driven eco-evolutionary feedback reshapes bacteriophage lambda's fitness landscape and enables speciation.

A major challenge in evolutionary biology is explaining how populations navigate rugged fitness landscapes without getting trapped on local optima. One idea illustrated by adaptive dynamics theory is that as populations adapt, their newly enhanced capacities to exploit resources alter fitness payoffs and restructure the landscape in ways that promote speciation by opening new adaptive pathways. While there have been indirect tests of this theory, to our knowledge none have measured how fitness landscapes deform during adaptation, or test whether these shifts promote diversification. Here, we achieve this by studying bacteriophage [Formula: see text], a virus that readily speciates into co-existing receptor specialists under controlled laboratory conditions. We use a high-throughput gene editing-phenotyping technology to measure [Formula: see text]'s fitness landscape in the presence of different evolved-[Formula: see text] competitors and find that the fitness effects of individual mutations, and their epistatic interactions, depend on the competitor. Using these empirical data, we simulate [Formula: see text]'s evolution on an unchanging landscape and one that recapitulates how the landscape deforms during evolution. [Formula: see text] heterogeneity only evolves in the shifting landscape regime. This study provides a test of adaptive dynamics, and, more broadly, shows how fitness landscapes dynamically change during adaptation, potentiating phenomena like speciation by opening new adaptive pathways.

Competition-driven eco-evolutionary feedback reshapes bacteriophage lambda's fitness landscape and enables speciation.

A major challenge in evolutionary biology is explaining how populations navigate rugged fitness landscapes without getting trapped on local optima. One idea illustrated by adaptive dynamics theory is that as populations adapt, their newly enhanced capacities to exploit resources alter fitness payoffs and restructure the landscape in ways that promote speciation by opening new adaptive pathways. While there have been indirect tests of this theory, none have measured how fitness landscapes deform during adaptation, or test whether these shifts promote diversification. Here, we achieve this by studying bacteriophage λ, a virus that readily speciates into co-existing receptor specialists under controlled laboratory conditions. We used a high-throughput gene editing-phenotyping technology to measure λ's fitness landscape in the presence of different evolved-λ competitors and found that the fitness effects of individual mutations, and their epistatic interactions, depend on the competitor. Using these empirical data, we simulated λ's evolution on an unchanging landscape and one that recapitulates how the landscape deforms during evolution. λ heterogeneity only evolved in the shifting landscape regime. This study provides a test of adaptive dynamics, and, more broadly, shows how fitness landscapes dynamically change during adaptation, potentiating phenomena like speciation by opening new adaptive pathways.

Enhanced ER proteostasis and temperature differentially impact the mutational tolerance of influenza hemagglutinin.

We systematically and quantitatively evaluate whether endoplasmic reticulum (ER) proteostasis factors impact the mutational tolerance of secretory pathway proteins. We focus on influenza hemaggluttinin (HA), a viral membrane protein that folds in the host's ER via a complex pathway. By integrating chemical methods to modulate ER proteostasis with deep mutational scanning to assess mutational tolerance, we discover that upregulation of ER proteostasis factors broadly enhances HA mutational tolerance across diverse structural elements. Remarkably, this proteostasis network-enhanced mutational tolerance occurs at the same sites where mutational tolerance is most reduced by propagation at fever-like temperature. These findings have important implications for influenza evolution, because influenza immune escape is contingent on HA possessing sufficient mutational tolerance to evade antibodies while maintaining the capacity to fold and function. More broadly, this work provides the first experimental evidence that ER proteostasis mechanisms define the mutational tolerance and, therefore, the evolution of secretory pathway proteins.

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 HA's 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.

How single mutations affect viral escape from broad and narrow antibodies to H1 influenza hemagglutinin.

Influenza virus can 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 there was strong pressure to do so. Here, we map all single amino-acid mutations that increase resistance to broad antibodies to H1 hemagglutinin. 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 to hemagglutinin's receptor-binding site the same way it escapes narrow strain-specific antibodies: via single mutations with huge effects. In contrast, broad antibodies to hemagglutinin's stalk only select mutations with small effects. Therefore, among the antibodies we examine, breadth is an imperfect indicator of the potential for viral escape via single mutations. Antibodies targeting the H1 hemagglutinin stalk are quantifiably harder to escape than the other antibodies tested here.

phydms: software for phylogenetic analyses informed by deep mutational scanning.

It has recently become possible to experimentally measure the effects of all amino-acid point mutations to proteins using deep mutational scanning. These experimental measurements can inform site-specific phylogenetic substitution models of gene evolution in nature. Here we describe software that efficiently performs analyses with such substitution models. This software, phydms, can be used to compare the results of deep mutational scanning experiments to the selection on genes in nature. Given a phylogenetic tree topology inferred with another program, phydms enables rigorous comparison of how well different experiments on the same gene capture actual natural selection. It also enables 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. As data from deep mutational scanning experiments become increasingly widespread, phydms will facilitate quantitative comparison of the experimental results to the actual selection pressures shaping evolution in nature.

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. 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.

Deep mutational scanning identifies sites in influenza nucleoprotein that affect viral inhibition by MxA.

The innate-immune restriction factor MxA inhibits influenza replication by targeting the viral nucleoprotein (NP). Human influenza virus is more resistant than avian influenza virus to inhibition by human MxA, and prior work has compared human and avian viral strains to identify amino-acid differences in NP that affect sensitivity to MxA. However, this strategy is limited to identifying sites in NP where mutations that affect MxA sensitivity have fixed during the small number of documented zoonotic transmissions of influenza to humans. Here we use an unbiased deep mutational scanning approach to quantify how all single amino-acid mutations to NP affect MxA sensitivity in the context of replication-competent virus. We both identify new sites in NP where mutations affect MxA resistance and re-identify mutations known to have increased MxA resistance during historical adaptations of influenza to humans. Most of the sites where mutations have the greatest effect are almost completely conserved across all influenza A viruses, and the amino acids at these sites confer relatively high resistance to MxA. These sites cluster in regions of NP that appear to be important for its recognition by MxA. Overall, our work systematically identifies the sites in influenza nucleoprotein where mutations affect sensitivity to MxA. We also demonstrate a powerful new strategy for identifying regions of viral proteins that affect inhibition by host factors.

Accurate Measurement of the Effects of All Amino-Acid Mutations on Influenza Hemagglutinin.

Influenza genes evolve mostly via point mutations, and so knowing the effect of every amino-acid mutation provides information about evolutionary paths available to the virus. We and others have combined high-throughput mutagenesis with deep sequencing to estimate the effects of large numbers of mutations to influenza genes. However, these measurements have suffered from substantial experimental noise due to a variety of technical problems, the most prominent of which is bottlenecking during the generation of mutant viruses from plasmids. Here we describe advances that ameliorate these problems, enabling us to measure with greatly improved accuracy and reproducibility the effects of all amino-acid mutations to an H1 influenza hemagglutinin on viral replication in cell culture. The largest improvements come from using a helper virus to reduce bottlenecks when generating viruses from plasmids. Our measurements confirm at much higher resolution the results of previous studies suggesting that antigenic sites on the globular head of hemagglutinin are highly tolerant of mutations. We also show that other regions of hemagglutinin-including the stalk epitopes targeted by broadly neutralizing antibodies-have a much lower inherent capacity to tolerate point mutations. The ability to accurately measure the effects of all influenza mutations should enhance efforts to understand and predict viral evolution.

Site-Specific Amino Acid Preferences Are Mostly Conserved in Two Closely Related Protein Homologs.

Evolution drives changes in a protein's sequence over time. The extent to which these changes in sequence lead to shifts in the underlying preference for each amino acid at each site is an important question with implications for comparative sequence-analysis methods, such as molecular phylogenetics. To quantify the extent that site-specific amino acid preferences shift during evolution, we performed deep mutational scanning on two homologs of human influenza nucleoprotein with 94% amino acid identity. We found that only a modest fraction of sites exhibited shifts in amino acid preferences that exceeded the noise in our experiments. Furthermore, even among sites that did exhibit detectable shifts, the magnitude tended to be small relative to differences between nonhomologous proteins. Given the limited change in amino acid preferences between these close homologs, we tested whether our measurements could inform site-specific substitution models that describe the evolution of nucleoproteins from more diverse influenza viruses. We found that site-specific evolutionary models informed by our experiments greatly outperformed nonsite-specific alternatives in fitting phylogenies of nucleoproteins from human, swine, equine, and avian influenza. Combining the experimental data from both homologs improved phylogenetic fit, partly because measurements in multiple genetic contexts better captured the evolutionary average of the amino acid preferences for sites with shifting preferences. Our results show that site-specific amino acid preferences are sufficiently conserved that measuring mutational effects in one protein provides information that can improve quantitative evolutionary modeling of nearby homologs.

Unexpected fold in the circumsporozoite protein target of malaria vaccines.

Circumsporozoite (CS) protein is the major surface component of Plasmodium falciparum sporozoites and is essential for host cell invasion. A vaccine containing tandem repeats, region III, and thrombospondin type-I repeat (TSR) of CS is efficacious in phase III trials but gives only a 35% reduction in severe malaria in the first year postimmunization. We solved crystal structures showing that region III and TSR fold into a single unit, an "αTSR" domain. The αTSR domain possesses a hydrophobic pocket and core, missing in TSR domains. CS binds heparin, but αTSR does not. Interestingly, polymorphic T-cell epitopes map to specialized αTSR regions. The N and C termini are unexpectedly close, providing clues for sporozoite sheath organization. Elucidation of a unique structure of a domain within CS enables rational design of next-generation subunit vaccines and functional and medicinal chemical investigation of the conserved hydrophobic pocket.