Biology subjects

Hilton, S. K.

Publications and source records attributed to Hilton, S. K..

8 recordsLinked to original sources

bioRxiv2020

Robustness of phylogenetic inference to model misspecification caused by pairwise epistasis

Likelihood-based phylogenetic inference posits a probabilistic model of character state change along branches of a phylogenetic tree. These models typically assume statistical independence of sites in the sequence alignment. This is a restrictive assumption that facilitates computational tractability, but ignores how epistasis, the effect of genetic background on mutational effects, influences the evolution of functional sequences. We consider the effect of using a misspecified site-independent model on the accuracy of Bayesian phylogenetic inference in the setting of pairwise-site epistasis. Previous work has shown that as alignment length increases, tree reconstruction accuracy also increases. Here, we present a simulation study demonstrating that accuracy increases with alignment size even if the additional sites are epistatically coupled. We introduce an alignment-based test statistic that is a diagnostic for pair-wise epistasis and can be used in posterior predictive checks.

evolutionary biology↗

bioRxiv2020

High-resolution mapping of the neutralizing and binding specificities of polyclonal rabbit serum elicited by HIV Env trimer immunization

Mapping the epitope specificities of polyclonal serum is critical to rational vaccine design. However, most high-resolution mapping approaches involve isolating and characterizing individual monoclonal antibodies, which incompletely defines the full polyclonal response. Here we use two complementary approaches to directly map the specificities of the neutralizing and binding antibodies of polyclonal anti-HIV-1 sera from rabbits immunized with BG505 Env SOSIP trimers. To map the neutralizing specificity, we used mutational antigenic profiling to determine how all amino-acid mutations in Env affected viral neutralization. To map the binding specificity, we used electron microscopy polyclonal epitope mapping (EMPEM) to directly visualize the Fabs in serum bound to Env trimers. Mutational antigenic profiling showed that the dominant neutralizing specificities were the C3/V5 and/or 241/289 glycan hole epitopes, which were generally only a subset of the more diverse binding specificities mapped with EMPEM. Additional differences between binding and neutralization reflected antigenicity differences between virus and soluble Env trimer. Further, mutational antigenic profiling was able to refine epitope specificity in residue-level detail directly from sera, revealing subtle differences across rabbits. Together, mutational antigenic profiling and EMPEM allow for a holistic view of the binding and neutralizing specificity of polyclonal sera and could be used to finely evaluate and guide vaccine design.

microbiology↗

bioRxiv2020

Complete mapping of mutations to the SARS-CoV-2 spike receptor-binding domain that escape antibody recognition

Antibodies targeting the SARS-CoV-2 spike receptor-binding domain (RBD) are being developed as therapeutics and make a major contribution to the neutralizing antibody response elicited by infection. Here, we describe a deep mutational scanning method to map how all amino-acid mutations in the RBD affect antibody binding, and apply this method to 10 human monoclonal antibodies. The escape mutations cluster on several surfaces of the RBD that broadly correspond to structurally defined antibody epitopes. However, even antibodies targeting the same RBD surface often have distinct escape mutations. The complete escape maps predict which mutations are selected during viral growth in the presence of single antibodies, and enable us to design escape-resistant antibody cocktails-including cocktails of antibodies that compete for binding to the same surface of the RBD but have different escape mutations. Therefore, complete escape-mutation maps enable rational design of antibody therapeutics and assessment of the antigenic consequences of viral evolution.

microbiology↗

bioRxiv2020

Deep mutational scanning of SARS-CoV-2 receptor binding domain reveals constraints on folding and ACE2 binding

The receptor binding domain (RBD) of the SARS-CoV-2 spike glycoprotein mediates viral attachment to ACE2 receptor, and is a major determinant of host range and a dominant target of neutralizing antibodies. Here we experimentally measure how all amino-acid mutations to the RBD affect expression of folded protein and its affinity for ACE2. Most mutations are deleterious for RBD expression and ACE2 binding, and we identify constrained regions on the RBDs surface that may be desirable targets for vaccines and antibody-based therapeutics. But a substantial number of mutations are well tolerated or even enhance ACE2 binding, including at ACE2 interface residues that vary across SARS-related coronaviruses. However, we find no evidence that these ACE2-affinity enhancing mutations have been selected in current SARS-CoV-2 pandemic isolates. We present an interactive visualization and open analysis pipeline to facilitate use of our dataset for vaccine design and functional annotation of mutations observed during viral surveillance.

microbiology↗

bioRxiv2020

dms-view: Interactive visualization tool for deep mutational scanning data

Summary and PurposeThe high-throughput technique of deep mutational scanning (DMS) has recently made it possible to experimentally measure the effects of all amino-acid mutations to a protein (Fowler and Fields 2014). Over the past five years, this technique has been used to study dozens of different proteins (Esposito et al. 2019) and answer a variety of research questions. For example, DMS has been used for protein engineering (Wrenbeck, Faber, and Whitehead 2017), understanding the human immune response to viruses (Lee et al. 2019), and interpreting human variation in a clinical setting (Starita et al. 2017; Gelman et al. 2019). Accompanying this proliferation of DMS studies has been the development of software tools (Bloom 2015; Rubin et al. 2017) and databases (Esposito et al. 2019) for data analysis and sharing. However, for many purposes it is important to also integrate and visualize the DMS data in the context of other information, such as the 3-D protein structure or natural sequence-variation data. Here we describe dms-view (https://dms-view.github.io/), a flexible, web-based, interactive visualization tool for DMS data. dms-view is written in JavaScript and D3, and links site-level and mutation-level DMS data to a 3-D protein structure. The user can interactively select sites of interest to examine the DMS measurements in the context of the protein structure. dms-view tracks the input data and user selections in the URL, making it possible to save specific views of interactively generated visualizations to share with collaborators or to support a published study. Importantly, dms-view takes a flexible input data file so users can easily visualize their own DMS data in the context of protein structures of their choosing, and also incorporate additional information such amino-acid frequencies in natural alignments.

bioinformatics↗

bioRxiv2018

Modeling site-specific amino-acid preferences deepens phylogenetic estimates of viral divergence

Molecular phylogenetics is often used to estimate the time since the divergence of modern gene sequences. For highly diverged sequences, such phylogenetic techniques sometimes estimate surprisingly recent divergence times. In the case of viruses, independent evidence indicates that the estimates of deep divergence times from molecular phylogenetics are sometimes too recent. This discrepancy is caused in part by inadequate models of purifying selection leading to branch-length underestimation. Here we examine the effect on branch-length estimation of using models that incorporate experimental measurements of purifying selection. We find that models informed by experimentally measured site-specific amino-acid preferences estimate longer deep branches on phylogenies of influenza virus hemagglutinin. This lengthening of branches is due to more realistic stationary states of the models, and is mostly independent of the branch-length-extension from modeling site-to-site variation in amino-acid substitution rate. The branch-length extension from experimentally informed site-specific models is similar to that achieved by other approaches that allow the stationary state to vary across sites. However, the improvements from all of these site-specific but time-homogeneous and site-independent models are limited by the fact that a proteins amino-acid preferences gradually shift as it evolves. Overall, our work underscores the importance of modeling site-specific amino-acid preferences when estimating deep divergence times--but also shows the inherent limitations of approaches that fail to account for how these preferences shift over time.

evolutionary biology↗

bioRxiv2017

Mapping mutational effects along the evolutionary landscape of HIV envelope

The immediate evolutionary space accessible to HIV is largely determined by how single amino-acid mutations affect fitness. These mutational effects can shift as the virus evolves. However, the prevalence of such shifts in mutational effects remains unclear. Here we quantify the effects on viral growth of all amino-acid mutations to two HIV envelope (Env) proteins that differ at >100 residues. Most mutations similarly affect both Envs, but the amino-acid preferences of a minority of sites have clearly shifted. These shifted sites usually prefer a specific amino acid in one Env, but tolerate many amino acids in the other. Surprisingly, shifts are only slightly enriched at sites that have substituted between the Envs -- and many occur at residues that do not even contact substitutions. Therefore, long-range epistasis can unpredictably shift Env's mutational tolerance during HIV evolution, although the amino-acid preferences of most sites are conserved between moderately diverged viral strains.

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↗