High-resolution profiling of pathways of escape for SARS-CoV-2 spike-binding antibodies.

Defining long-term protective immunity to SARS-CoV-2 is one of the most pressing questions of our time and will require a detailed understanding of potential ways this virus can evolve to escape immune protection. Immune protection will most likely be mediated by antibodies that bind to the viral entry protein, spike (S). Here, we used Phage-DMS, an approach that comprehensively interrogates the effect of all possible mutations on binding to a protein of interest, to define the profile of antibody escape to the SARS-CoV-2 S protein using coronavirus disease 2019 (COVID-19) convalescent plasma. Antibody binding was common in two regions, the fusion peptide and the linker region upstream of the heptad repeat region 2. However, escape mutations were variable within these immunodominant regions. There was also individual variation in less commonly targeted epitopes. This study provides a granular view of potential antibody escape pathways and suggests there will be individual variation in antibody-mediated virus evolution.

Deep mutational scanning reveals functional constraints and antibody-escape potential of Lassa virus glycoprotein complex.

Lassa virus is estimated to cause thousands of human deaths per year, primarily due to spillovers from its natural host, Mastomys rodents. Efforts to create vaccines and antibody therapeutics must account for the evolutionary variability of the Lassa virus's glycoprotein complex (GPC), which mediates viral entry into cells and is the target of neutralizing antibodies. To map the evolutionary space accessible to GPC, we used pseudovirus deep mutational scanning to measure how nearly all GPC amino-acid mutations affected cell entry and antibody neutralization. Our experiments defined functional constraints throughout GPC. We quantified how GPC mutations affected neutralization with a panel of monoclonal antibodies. All antibodies tested were escaped by mutations that existed among natural Lassa virus lineages. Overall, our work describes a biosafety-level-2 method to elucidate the mutational space accessible to GPC and shows how prospective characterization of antigenic variation could aid the design of therapeutics and vaccines.

phippery: a software suite for PhIP-Seq data analysis.

SUMMARY: We present the phippery software suite for analyzing data from phage display methods that use immunoprecipitation and deep sequencing to capture antibody binding to peptides, often referred to as PhIP-Seq. It has three main components that can be used separately or in conjunction: (i) a Nextflow pipeline, phip-flow, to process raw sequencing data into a compact, multidimensional dataset format and allows for end-to-end automation of reproducible workflows. (ii) a Python API, phippery, which provides interfaces for tasks such as count normalization, enrichment calculation, multidimensional scaling, and more, and (iii) a Streamlit application, phip-viz, as an interactive interface for visualizing the data as a heatmap in a flexible manner. AVAILABILITY AND IMPLEMENTATION: All software packages are publicly available under the MIT License. The phip-flow pipeline: https://github.com/matsengrp/phip-flow. The phippery library: https://github.com/matsengrp/phippery. The phip-viz Streamlit application: https://github.com/matsengrp/phip-viz.

Detailed analysis of antibody responses to SARS-CoV-2 vaccination and infection in macaques.

Macaques are a commonly used model for studying immunity to human viruses, including for studies of SARS-CoV-2 infection and vaccination. However, it is unknown whether macaque antibody responses resemble the response in humans. To answer this question, we employed a phage-based deep mutational scanning approach (Phage-DMS) to compare which linear epitopes are targeted on the SARS-CoV-2 Spike protein in convalescent humans, convalescent (re-infected) rhesus macaques, mRNA-vaccinated humans, and repRNA-vaccinated pigtail macaques. We also used Phage-DMS to determine antibody escape pathways within each epitope, enabling a granular comparison of antibody binding specificities at the locus level. Overall, we identified some common epitope targets in both macaques and humans, including in the fusion peptide (FP) and stem helix-heptad repeat 2 (SH-H) regions. Differences between groups included a response to epitopes in the N-terminal domain (NTD) and C-terminal domain (CTD) in vaccinated humans but not vaccinated macaques, as well as recognition of a CTD epitope and epitopes flanking the FP in convalescent macaques but not convalescent humans. There was also considerable variability in the escape pathways among individuals within each group. Sera from convalescent macaques showed the least variability in escape overall and converged on a common response with vaccinated humans in the SH-H epitope region, suggesting highly similar antibodies were elicited. Collectively, these findings suggest that the antibody response to SARS-CoV-2 in macaques shares many features with humans, but with substantial differences in the recognition of certain epitopes and considerable individual variability in antibody escape profiles, suggesting a diverse repertoire of antibodies that can respond to major epitopes in both humans and macaques. Differences in macaque species and exposure type may also contribute to these findings.

Predicting the Landscape of Recombination Using Deep Learning.

Accurately inferring the genome-wide landscape of recombination rates in natural populations is a central aim in genomics, as patterns of linkage influence everything from genetic mapping to understanding evolutionary history. Here, we describe recombination landscape estimation using recurrent neural networks (ReLERNN), a deep learning method for estimating a genome-wide recombination map that is accurate even with small numbers of pooled or individually sequenced genomes. Rather than use summaries of linkage disequilibrium as its input, ReLERNN takes columns from a genotype alignment, which are then modeled as a sequence across the genome using a recurrent neural network. We demonstrate that ReLERNN improves accuracy and reduces bias relative to existing methods and maintains high accuracy in the face of demographic model misspecification, missing genotype calls, and genome inaccessibility. We apply ReLERNN to natural populations of African Drosophila melanogaster and show that genome-wide recombination landscapes, although largely correlated among populations, exhibit important population-specific differences. Lastly, we connect the inferred patterns of recombination with the frequencies of major inversions segregating in natural Drosophila populations.

Deep mutational scanning reveals functional constraints and antigenic variability of Lassa virus glycoprotein complex.

Lassa virus is estimated to cause thousands of human deaths per year, primarily due to spillovers from its natural host, Mastomys rodents. Efforts to create vaccines and antibody therapeutics must account for the evolutionary variability of Lassa virus's glycoprotein complex (GPC), which mediates viral entry into cells and is the target of neutralizing antibodies. To map the evolutionary space accessible to GPC, we use pseudovirus deep mutational scanning to measure how nearly all GPC amino-acid mutations affect cell entry and antibody neutralization. Our experiments define functional constraints throughout GPC. We quantify how GPC mutations affect neutralization by a panel of monoclonal antibodies and show that all antibodies are escaped by mutations that exist among natural Lassa virus lineages. Overall, our work describes a biosafety-level-2 method to elucidate the mutational space accessible to GPC and shows how prospective characterization of antigenic variation could aid design of therapeutics and vaccines.

Age-dependent heterogeneity in the antigenic effects of mutations to influenza hemagglutinin.

Human influenza virus evolves to escape neutralization by polyclonal antibodies. However, we have a limited understanding of how the antigenic effects of viral mutations vary across the human population and how this heterogeneity affects virus evolution. Here, we use deep mutational scanning to map how mutations to the hemagglutinin (HA) proteins of two H3N2 strains, A/Hong Kong/45/2019 and A/Perth/16/2009, affect neutralization by serum from individuals of a variety of ages. The effects of HA mutations on serum neutralization differ across age groups in ways that can be partially rationalized in terms of exposure histories. Mutations that were fixed in influenza variants after 2020 cause greater escape from sera from younger individuals compared with adults. Overall, these results demonstrate that influenza faces distinct antigenic selection regimes from different age groups and suggest approaches to understand how this heterogeneous selection shapes viral evolution.

Automatic Differentiation is no Panacea for Phylogenetic Gradient Computation.

Gradients of probabilistic model likelihoods with respect to their parameters are essential for modern computational statistics and machine learning. These calculations are readily available for arbitrary models via "automatic differentiation" implemented in general-purpose machine-learning libraries such as TensorFlow and PyTorch. Although these libraries are highly optimized, it is not clear if their general-purpose nature will limit their algorithmic complexity or implementation speed for the phylogenetic case compared to phylogenetics-specific code. In this paper, we compare six gradient implementations of the phylogenetic likelihood functions, in isolation and also as part of a variational inference procedure. We find that although automatic differentiation can scale approximately linearly in tree size, it is much slower than the carefully implemented gradient calculation for tree likelihood and ratio transformation operations. We conclude that a mixed approach combining phylogenetic libraries with machine learning libraries will provide the optimal combination of speed and model flexibility moving forward.

Jointly modeling deep mutational scans identifies shifted mutational effects among SARS-CoV-2 spike homologs.

Deep mutational scanning (DMS) is a high-throughput experimental technique that measures the effects of thousands of mutations to a protein. These experiments can be performed on multiple homologs of a protein or on the same protein selected under multiple conditions. It is often of biological interest to identify mutations with shifted effects across homologs or conditions. However, it is challenging to determine if observed shifts arise from biological signal or experimental noise. Here, we describe a method for jointly inferring mutational effects across multiple DMS experiments while also identifying mutations that have shifted in their effects among experiments. A key aspect of our method is to regularize the inferred shifts, so that they are nonzero only when strongly supported by the data. We apply this method to DMS experiments that measure how mutations to spike proteins from SARS-CoV-2 variants (Delta, Omicron BA.1, and Omicron BA.2) affect cell entry. Most mutational effects are conserved between these spike homologs, but a fraction have markedly shifted. We experimentally validate a subset of the mutations inferred to have shifted effects, and confirm differences of > 1,000-fold in the impact of the same mutation on spike-mediated viral infection across spikes from different SARS-CoV-2 variants. Overall, our work establishes a general approach for comparing sets of DMS experiments to identify biologically important shifts in mutational effects.

Elevated binding and functional antibody responses to SARS-CoV-2 in infants versus mothers.

Infant antibody responses to viral infection can differ from those in adults. However, data on the specificity and function of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibodies in infants, and direct comparisons between infants and adults are limited. We characterized antibody binding and functionality in convalescent plasma from postpartum women and their infants infected with SARS-CoV-2 from a vaccine-naïve prospective cohort in Nairobi, Kenya. Antibody titers against SARS-CoV-2 Spike, receptor binding domain and N-terminal domain, and Spike-expressing cell-surface staining levels were significantly higher in infants than in mothers. Plasma antibodies from mothers and infants bound to similar regions of the Spike S2 subunit, including the fusion peptide (FP) and stem helix-heptad repeat 2. However, infants displayed higher antibody levels and more consistent antibody escape pathways in the FP region compared to mothers. Finally, infants had significantly higher levels of antibody-dependent cellular cytotoxicity (ADCC), though, surprisingly, neutralization titers between infants and mothers were similar. These results suggest infants develop distinct SARS-CoV-2 binding and functional antibody repertoires and reveal age-related differences in humoral immunity to SARS-CoV-2 infection that could be relevant to protection and COVID-19 disease outcomes.

Elevated binding and functional antibody responses to SARS-CoV-2 in infants versus mothers.

Infant antibody responses to viral infection can differ from those in adults. However, data on the specificity and function of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibodies in infants, and direct comparisons between infants and adults are limited. Here, we characterize antibody binding and functionality against Wuhan-Hu-1 (B lineage) strain SARS-CoV-2 in convalescent plasma from 36 postpartum women and 14 of their infants infected with SARS-CoV-2 from a vaccine-naïve prospective cohort in Nairobi, Kenya. We find significantly higher antibody titers against SARS-CoV-2 Spike, receptor binding domain and N-terminal domain, and Spike-expressing cell-surface staining levels in infants versus mothers. Plasma antibodies from mothers and infants bind to similar regions of the Spike S2 subunit, including the fusion peptide (FP) and stem helix-heptad repeat 2. However, infants display higher antibody levels and more consistent antibody escape pathways in the FP region compared to mothers. Finally, infants have significantly higher levels of antibody-dependent cellular cytotoxicity (ADCC), though, surprisingly, Spike pseudovirus neutralization titers between infants and mothers are similar. These results suggest infants develop distinct SARS-CoV-2 binding and functional antibody activities and reveal age-related differences in humoral immunity to SARS-CoV-2 infection that could be relevant to protection and COVID-19 disease outcomes.

Age-dependent heterogeneity in the antigenic effects of mutations to influenza hemagglutinin.

Human influenza virus evolves to escape neutralization by polyclonal antibodies. However, we have a limited understanding of how the antigenic effects of viral mutations vary across the human population, and how this heterogeneity affects virus evolution. Here we use deep mutational scanning to map how mutations to the hemagglutinin (HA) proteins of the A/Hong Kong/45/2019 (H3N2) and A/Perth/16/2009 (H3N2) strains affect neutralization by serum from individuals of a variety of ages. The effects of HA mutations on serum neutralization differ across age groups in ways that can be partially rationalized in terms of exposure histories. Mutations that fixed in influenza variants after 2020 cause the greatest escape from sera from younger individuals. Overall, these results demonstrate that influenza faces distinct antigenic selection regimes from different age groups, and suggest approaches to understand how this heterogeneous selection shapes viral evolution.

Comprehensive characterization of the antibody responses to SARS-CoV-2 Spike protein finds additional vaccine-induced epitopes beyond those for mild infection.

Background: Control of the COVID-19 pandemic will rely on SARS-CoV-2 vaccine-elicited antibodies to protect against emerging and future variants; an understanding of the unique features of the humoral responses to infection and vaccination, including different vaccine platforms, is needed to achieve this goal. Methods: The epitopes and pathways of escape for Spike-specific antibodies in individuals with diverse infection and vaccination history were profiled using Phage-DMS. Principal component analysis was performed to identify regions of antibody binding along the Spike protein that differentiate the samples from one another. Within these epitope regions, we determined potential sites of escape by comparing antibody binding of peptides containing wild-type residues versus peptides containing a mutant residue. Results: Individuals with mild infection had antibodies that bound to epitopes in the S2 subunit within the fusion peptide and heptad-repeat regions, whereas vaccinated individuals had antibodies that additionally bound to epitopes in the N- and C-terminal domains of the S1 subunit, a pattern that was also observed in individuals with severe disease due to infection. Epitope binding appeared to change over time after vaccination, but other covariates such as mRNA vaccine dose, mRNA vaccine type, and age did not affect antibody binding to these epitopes. Vaccination induced a relatively uniform escape profile across individuals for some epitopes, whereas there was much more variation in escape pathways in mildly infected individuals. In the case of antibodies targeting the fusion peptide region, which was a common response to both infection and vaccination, the escape profile after infection was not altered by subsequent vaccination. Conclusions: The finding that SARS-CoV-2 mRNA vaccination resulted in binding to additional epitopes beyond what was seen after infection suggests that protection could vary depending on the route of exposure to Spike antigen. The relatively conserved escape pathways to vaccine-induced antibodies relative to infection-induced antibodies suggests that if escape variants emerge they may be readily selected for across vaccinated individuals. Given that the majority of people will be first exposed to Spike via vaccination and not infection, this work has implications for predicting the selection of immune escape variants at a population level. Funding: This work was supported by NIH grants AI138709 (PI JMO) and AI146028 (PI FAM). JMO received support as the Endowed Chair for Graduate Education (FHCRC). The research of FAM was supported in part by a Faculty Scholar grant from the Howard Hughes Medical Institute and the Simons Foundation. Scientific Computing Infrastructure at Fred Hutch was funded by ORIP grant S10OD028685.

When SARS-CoV-2 ­ the virus that causes COVID-19 ­ infects our bodies, our immune system reacts by producing small molecules called antibodies that stick to a part of the virus called the spike protein. Vaccines are thought to work by triggering the production of similar antibodies without causing disease. Some of the most effective antibodies against SARS-CoV-2 bind a specific area of the spike protein called the 'receptor binding domain' or RBD. When SARS-CoV-2 evolves it creates a challenge for our immune system: mutations, which are changes in the virus's genetic code, can alter the shape of its spike protein, meaning that existing antibodies may no longer bind to it as effectively. This lowers the protection offered by past infection or vaccination, which makes it harder to tackle the pandemic. As it stands, it is not clear which mutations to the virus's genetic code can affect antibody binding, especially to portions outside the RBD. To complicate things further, the antibodies people produce in response to mild infection, severe infection, and vaccination, while somewhat overlapping, exhibit some differences. Studying these differences could help minimize emergence of mutations that allow the virus to 'escape' the antibody response. A phage display library is a laboratory technique in which phages (viruses that infect bacteria) are used as a 'repository' for DNA fragments that code for a specific protein. The phages can then produce the protein (or fragments of it), and if the protein fragments bind to a target, it can be easily detected. Garrett, Galloway et al. exploited this technique to study how different portions of the SARS-CoV-2 spike protein were bound by antibodies. They made a phage library in which each phage encoded a portion of the spike protein with different mutations, and then exposed the different versions of the protein to antibodies from people who had experienced prior infection, vaccination, or both. The experiment showed that antibodies produced during severe infection or after vaccination bound to similar parts of the spike protein, while antibodies from people who had experienced mild infection targeted fewer areas. Garrett, Galloway et al. also found that mutations that affected the binding of antibodies produced after vaccination were more consistent than mutations that interfered with antibodies produced during infection. While these results show which mutations are most likely to help the virus escape existing antibodies, this does not mean that the virus will necessarily evolve in that direction. Indeed, some of the mutations may be impossible for the virus to acquire because they interfere with the virus's ability to spread. Further studies could focus on revealing which of the mutations detected by Garrett, Galloway et al. are most likely to occur, to guide vaccine development in that direction. To help with this, Garrett, Galloway et al. have made the data accessible to other scientists and the public using a web tool.

Efficient ancestry and mutation simulation with msprime 1.0.

Stochastic simulation is a key tool in population genetics, since the models involved are often analytically intractable and simulation is usually the only way of obtaining ground-truth data to evaluate inferences. Because of this, a large number of specialized simulation programs have been developed, each filling a particular niche, but with largely overlapping functionality and a substantial duplication of effort. Here, we introduce msprime version 1.0, which efficiently implements ancestry and mutation simulations based on the succinct tree sequence data structure and the tskit library. We summarize msprime's many features, and show that its performance is excellent, often many times faster and more memory efficient than specialized alternatives. These high-performance features have been thoroughly tested and validated, and built using a collaborative, open source development model, which reduces duplication of effort and promotes software quality via community engagement.

Comprehensive characterization of the antibody responses to SARS-CoV-2 Spike protein after infection and/or vaccination.

BACKGROUND: Control of the COVID-19 pandemic will rely on SARS-CoV-2 vaccine-elicited antibodies to protect against emerging and future variants; an understanding of the unique features of the humoral responses to infection and vaccination, including different vaccine platforms, is needed to achieve this goal. METHODS: The epitopes and pathways of escape for Spike-specific antibodies in individuals with diverse infection and vaccination history were profiled using Phage-DMS. Principal component analysis was performed to identify regions of antibody binding along the Spike protein that differentiate the samples from one another. Within these epitope regions we determined potential escape mutations by comparing antibody binding of peptides containing wildtype residues versus peptides containing a mutant residue. RESULTS: Individuals with mild infection had antibodies that bound to epitopes in the S2 subunit within the fusion peptide and heptad-repeat regions, whereas vaccinated individuals had antibodies that additionally bound to epitopes in the N- and C-terminal domains of the S1 subunit, a pattern that was also observed in individuals with severe disease due to infection. Epitope binding appeared to change over time after vaccination, but other covariates such as mRNA vaccine dose, mRNA vaccine type, and age did not affect antibody binding to these epitopes. Vaccination induced a relatively uniform escape profile across individuals for some epitopes, whereas there was much more variation in escape pathways in in mildly infected individuals. In the case of antibodies targeting the fusion peptide region, which was a common response to both infection and vaccination, the escape profile after infection was not altered by subsequent vaccination. CONCLUSIONS: The finding that SARS-CoV-2 mRNA vaccination resulted in binding to additional epitopes beyond what was seen after infection suggests protection could vary depending on the route of exposure to Spike antigen. The relatively conserved escape pathways to vaccine-induced antibodies relative to infection-induced antibodies suggests that if escape variants emerge, they may be readily selected for across vaccinated individuals. Given that the majority of people will be first exposed to Spike via vaccination and not infection, this work has implications for predicting the selection of immune escape variants at a population level. FUNDING: This work was supported by NIH grants AI138709 (PI Overbaugh) and AI146028 (PI Matsen). Julie Overbaugh received support as the Endowed Chair for Graduate Education (FHCRC). The research of Frederick Matsen was supported in part by a Faculty Scholar grant from the Howard Hughes Medical Institute and the Simons Foundation. Scientific Computing Infrastructure at Fred Hutch was funded by ORIP grant S10OD028685.

SARS-CoV-2 Antibody Binding and Neutralization in Dried Blood Spot Eluates and Paired Plasma.

Wide-scale assessment of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-specific antibodies is critical to understanding population seroprevalence, correlates of protection, and the longevity of vaccine-elicited responses. Most SARS-CoV-2 studies characterize antibody responses in plasma/sera. While reliable and broadly used, these samples pose several logistical restrictions, such as requiring venipuncture for collection and a cold chain for transportation and storage. Dried blood spots (DBS) overcome these barriers as they can be self-collected by fingerstick and mailed and stored at ambient temperature. Here, we evaluate the suitability of DBS for SARS-CoV-2 antibody assays by comparing several antibody responses between paired plasma and DBS from SARS-CoV-2 convalescent and vaccinated individuals. We found that DBS not only reflected plasma antibody binding by enzyme-linked immunosorbent assay (ELISA) and epitope profiles using phage display, but also yielded SARS-CoV-2 neutralization titers that highly correlated with paired plasma. Neutralization measurement was further streamlined by adapting assays to a high-throughput 384-well format. This study supports the adoption of DBS for numerous SARS-CoV-2 binding and neutralization assays. IMPORTANCE Plasma and sera isolated from venous blood represent conventional sample types used for the evaluation of SARS-CoV-2 antibody responses after infection or vaccination. However, collection of these samples is invasive and requires trained personnel and equipment for immediate processing. Once collected, plasma and sera must be stored and shipped at cold temperatures. To define the risk of emerging SARS-CoV-2 variants and the longevity of immune responses to natural infection and vaccination, it will be necessary to measure various antibody features in populations around the world, including in resource-limited areas. A sampling method that is compatible with these settings and is suitable for a variety of SARS-CoV-2 antibody assays is therefore needed to continue to understand and curb the COVID-19 pandemic.

Epitope profiling reveals binding signatures of SARS-CoV-2 immune response in natural infection and cross-reactivity with endemic human CoVs.

A major goal of current severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccine efforts is to elicit antibody responses that confer protection. Mapping the epitope targets of the SARS-CoV-2 antibody response is critical for vaccine design, diagnostics, and development of therapeutics. Here, we develop a pan-coronavirus phage display library to map antibody binding sites at high resolution within the complete viral proteomes of all known human-infecting coronaviruses in patients with mild or moderate/severe coronavirus disease 2019 (COVID-19). We find that the majority of immune responses to SARS-CoV-2 are targeted to the spike protein, nucleocapsid, and ORF1ab and include sites of mutation in current variants of concern. Some epitopes are identified in the majority of samples, while others are rare, and we find variation in the number of epitopes targeted between individuals. We find low levels of SARS-CoV-2 cross-reactivity in individuals with no exposure to the virus and significant cross-reactivity with endemic human coronaviruses (CoVs) in convalescent sera from patients with COVID-19.

Macaque-human differences in SARS-CoV-2 Spike antibody response elicited by vaccination or infection.

Macaques are a commonly used model for studying immunity to human viruses, including for studies of SARS-CoV-2 infection and vaccination. However, it is unknown whether macaque antibody responses recapitulate, and thus appropriately model, the response in humans. To answer this question, we employed a phage-based deep mutational scanning approach (Phage-DMS) to compare which linear epitopes are targeted on the SARS-CoV-2 Spike protein in humans and macaques following either vaccination or infection. We also used Phage-DMS to determine antibody escape pathways within each epitope, enabling a granular comparison of antibody binding specificities at the locus level. Overall, we identified some common epitope targets in both macaques and humans, including in the fusion peptide (FP) and stem helix-heptad repeat 2 (SH-H) regions. Differences between groups included a response to epitopes in the N-terminal domain (NTD) and C-terminal domain (CTD) in vaccinated humans but not vaccinated macaques, as well as recognition of a CTD epitope and epitopes flanking the FP in convalescent macaques but not convalescent humans. There was also considerable variability in the escape pathways among individuals within each group. Sera from convalescent macaques showed the least variability in escape overall and converged on a common response with vaccinated humans in the SH-H epitope region, suggesting highly similar antibodies were elicited. Collectively, these findings suggest that the antibody response to SARS-CoV-2 in macaques shares many features with humans, but with substantial differences in the recognition of certain epitopes and considerable individual variability in antibody escape profiles, suggesting a diverse repertoire of antibodies that can respond to major epitopes in both humans and macaques.

A Few Stickleback Suffice for the Transport of Alleles to New Lakes.

Threespine stickleback populations provide a striking example of local adaptation to divergent habitats in populations that are connected by recurrent gene flow. These small fish occur in marine and freshwater habitats throughout the Northern Hemisphere, and in numerous cases the smaller freshwater populations have been established "de novo" from marine colonists. Independently evolved freshwater populations exhibit similar phenotypes that have been shown to derive largely from the same standing genetic variants. Geographic isolation prevents direct migration between the freshwater populations, strongly suggesting that these shared locally adaptive alleles are transported through the marine population. However it is still largely unknown how gene flow, recombination, and selection jointly impact the standing variation that might fuel this adaptation. Here we use individual-based, spatially explicit simulations to determine the levels of gene flow that best match observed patterns of allele sharing among habitats in stickleback. We aim to better understand how gene flow and local adaptation in large metapopulations determine the speed of adaptation and re-use of standing genetic variation. In our simulations we find that repeated adaptation uses a shared set of alleles that are maintained at low frequency by migration-selection balance in oceanic populations. This process occurs over a realistic range of intermediate levels of gene flow that match previous empirical population genomic studies in stickleback. Examining these simulations more deeply reveals how lower levels of gene flow leads to slow, independent adaptation to different habitats, whereas higher levels of gene flow leads to significant mutation load - but an increased probability of successful population genomic scans for locally adapted alleles. Surprisingly, we find that the genealogical origins of most freshwater adapted alleles can be traced back to the original generation of marine individuals that colonized the lakes, as opposed to subsequent migrants. These simulations provide deeper context for existing studies of stickleback evolutionary genomics, and guidance for future empirical studies in this model. More broadly, our results support existing theory of local adaptation but extend it by more completely documenting the genealogical history of adaptive alleles in a metapopulation.

High resolution profiling of pathways of escape for SARS-CoV-2 spike-binding antibodies.

Defining long-term protective immunity to SARS-CoV-2 is one of the most pressing questions of our time and will require a detailed understanding of potential ways this virus can evolve to escape immune protection. Immune protection will most likely be mediated by antibodies that bind to the viral entry protein, Spike (S). Here we used Phage-DMS, an approach that comprehensively interrogates the effect of all possible mutations on binding to a protein of interest, to define the profile of antibody escape to the SARS-CoV-2 S protein using COVID-19 convalescent plasma. Antibody binding was common in two regions: the fusion peptide and linker region upstream of the heptad repeat region 2. However, escape mutations were variable within these immunodominant regions. There was also individual variation in less commonly targeted epitopes. This study provides a granular view of potential antibody escape pathways and suggests there will be individual variation in antibody-mediated virus evolution.