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A major challenge in understanding SARS-CoV-2 evolution is interpreting the antigenic and functional effects of emerging mutations in the viral spike protein. Here we describe a new deep mutational scanning platform based on non-replicative pseudotyped lentiviruses that directly quantifies how large numbers of spike mutations impact antibody neutralization and pseudovirus infection. We demonstrate this new platform by making libraries of the Omicron BA.1 and Delta spikes. These libraries each contain ~7000 distinct amino-acid mutations in the context of up to ~135,000 unique mutation combinations. We use these libraries to map escape mutations from neutralizing antibodies targeting the receptor binding domain, N-terminal domain, and S2 subunit of spike. Overall, this work establishes a high-throughput and safe approach to measure how ~'10 to the 5' combinations of mutations affect antibody neutralization and spike-mediated infection. Notably, the platform described here can be extended to the entry proteins of many other viruses.

Ancestral sequence reconstruction (ASR) is a still-burgeoning method that has revealed many key mechanisms of molecular evolution. One criticism of the approach is an inability to validate its algorithms within a biological context as opposed to a computer simulation. Here we build an experimental phylogeny using the gene of a single red fluorescent protein to address this criticism. The evolved phylogeny consists of 19 operational taxonomic units (leaves) and 17 ancestral bifurcations (nodes) that display a wide variety of fluorescent phenotypes. The 19 leaves then serve as ‘modern' sequences that we subject to ASR analyses using various algorithms and to benchmark against the known ancestral genotypes and ancestral phenotypes. We confirm computer simulations that show all algorithms infer ancient sequences with high accuracy, yet we also reveal wide variation in the phenotypes encoded by incorrectly inferred sequences. Specifically, Bayesian methods incorporating rate variation significantly outperform the maximum parsimony criterion in phenotypic accuracy. Subsampling of extant sequences had minor effect on the inference of ancestral sequences.

A challenge in studying viral immune escape is determining how mutations combine to escape polyclonal antibodies, which can potentially target multiple distinct viral epitopes. Here we introduce a biophysical model of this process that partitions the total polyclonal antibody activity by epitope, and then quantifies how each viral mutation affects the antibody activity against each epitope. We develop software that can use deep mutational scanning data to infer these properties for polyclonal antibody mixtures. We validate this software using a computationally simulated deep mutational scanning experiment, and demonstrate that it enables the prediction of escape by arbitrary combinations of mutations. The software described in this paper is available at https://jbloomlab.github.io/polyclonal.

No abstract

A challenge in studying viral immune escape is determining how mutations combine to escape polyclonal antibodies, which can . potentially target multiple distinct viral epitopes. Here we introduce a biophysical model of this process that partitions the total polyclonal antibody activity by epitope, and then quantifies how each viral mutation affects the antibody activity against each epitope. We develop software that can use deep mutational scanning data to infer these properties for polyclonal antibody mixtures. We validate this software using a computationally simulated deep mutational scanning experiment, and demonstrate that it enables the prediction of escape by arbitrary combinations of mutations. The software described in this paper is available at https://jbloomlab.github.io/polyclonal .

Ancestral sequence reconstruction provides a unique platform for investigating the molecular evolution of single gene products and recently has shown success in engineering advanced biological therapeutics. To date, the coevolution of proteins within complexes and protein–protein interactions is mostly investigated in silico via proteomics and/or within single-celled systems. Herein, ancestral sequence reconstruction is used to investigate the molecular evolution of 2 proteins linked not only by stabilizing association in circulation but also by their independent roles within the primary and secondary hemostatic systems of mammals. Using sequence analysis and biochemical characterization of recombinant ancestral von Willebrand factor (VWF) and coagulation factor VIII (FVIII), we investigated the evolution of the essential macromolecular FVIII/VWF complex. Our data support the hypothesis that these coagulation proteins coevolved throughout mammalian diversification, maintaining strong binding affinities while modulating independent and distinct hemostatic activities in diverse lineages.

Orthologous proteins contain sequence disparity guided by natural selection. In certain cases, species-specific protein functionality predicts pharmacological enhancement, such as greater specific activity or stability. However, immunological barriers generally preclude use of nonhuman proteins as therapeutics, and difficulty exists in the identification of individual sequence determinants among the overall sequence disparity. Ancestral sequence reconstruction (ASR) represents a platform for the prediction and resurrection of ancient gene and protein sequences. Recently, we demonstrated that ASR can be used as a platform to facilitate the identification of therapeutic protein variants with enhanced properties. Specifically, we identified coagulation factor VIII (FVIII) variants with improved specific activity, biosynthesis, stability, and resistance to anti-human FVIII antibody–based inhibition. In the current study, we resurrected a panel of ancient mammalian coagulation factor IX (FIX) variants with the goal of identifying improved pharmaceutical candidates. One variant (An96) demonstrated 12-fold greater FIX activity production than human FIX. Addition of the R338L Padua substitution further increased An96 activity, suggesting independent but additive mechanisms. after adeno-associated virus 2 (AAV2)/8-FIX gene therapy, 10-fold greater plasma FIX activity was observed in hemophilia B mice administered AAV2/8-An96–Padua as compared with AAV2/8-human FIX–Padua. Furthermore, phenotypic correction conferred by the ancestral variant was confirmed using a saphenous vein bleeding challenge and thromboelastography. Collectively, these findings validate the ASR drug discovery platform as well as identify an ancient FIX candidate for pharmaceutical development.