Biology subjects

Farrell, A. G.

Publications and source records attributed to Farrell, A. G..

4 recordsLinked to original sources

bioRxiv2026

Defining the molecular interaction between influenza hemagglutinin and MHC-II

The hemagglutinin (HA) of some influenza viruses can interact with major histocompatibility complex class II (MHC-II), but how these proteins interact is unclear. Here we demonstrate that diverse H5 HAs can use MHC-II to enter cells, with avian MHC-II enabling more efficient entry than human MHC-II for most H5 HAs. To define the molecular interface, we use pseudovirus deep mutational scanning to measure how mutations to H5 HA affect its interaction with tufted duck MHC-II, and identify mutations that restrict HA to exclusively MHC-II or sialic acid receptors. We leverage identification of H5 HA mutations that increase binding to tufted duck MHC-II to determine a 4.8 [A] cryo-EM model of the complex. To support the structural model, we measure how all mutations to tufted duck MHC-II affect its interaction with H5 HA, and find the alpha chain is the dominant determinant but beta chain sites near the peptide-binding groove also contribute. To generalize these findings, we use deep mutational scanning to show that a H7 HA interacts with MHC-II similarly to H5 HA. Finally, we show that H1, H2, H3, and H9 HAs interact with avian or human MHC-II, although interactions vary among strains that evolved in different hosts.

microbiology↗

bioRxiv2023

Full-spike deep mutational scanning helps predict the evolutionary success of SARS-CoV-2 clades

SARS-CoV-2 variants acquire mutations in spike that promote immune evasion and impact other properties that contribute to viral fitness such as ACE2 receptor binding and cell entry. Knowledge of how mutations affect these spike phenotypes can provide insight into the current and potential future evolution of the virus. Here we use pseudovirus deep mutational scanning to measure how >9,000 mutations across the full XBB.1.5 and BA.2 spikes affect ACE2 binding, cell entry, or escape from human sera. We find that mutations outside the receptor-binding domain (RBD) have meaningfully impacted ACE2 binding during SARS-CoV-2 evolution. We also measure how mutations to the XBB.1.5 spike affect neutralization by serum from individuals who recently had SARS-CoV-2 infections. The strongest serum escape mutations are in the RBD at sites 357, 420, 440, 456, and 473--however, the antigenic impacts of these mutations vary across individuals. We also identify strong escape mutations outside the RBD; however many of them decrease ACE2 binding, suggesting they act by modulating RBD conformation. Notably, the growth rates of human SARS-CoV-2 clades can be explained in substantial part by the measured effects of mutations on spike phenotypes, suggesting our data could enable better prediction of viral evolution.

microbiology↗

bioRxiv2022

A pseudovirus system enables deep mutational scanning of the full SARS-CoV-2 spike

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 ~105 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.

microbiology↗

bioRxiv2022

Receptor binding domain (RBD) antibodies contribute more to SARS-CoV-2 neutralization when target cells express high levels of ACE2

Neutralization assays are experimental surrogates for the effectiveness of infection- or vaccine-elicited polyclonal antibodies and therapeutic monoclonal antibodies targeting SARS-CoV-2. However, the measured neutralization can depend on details of the experimental assay. Here we systematically assess how ACE2 expression in target cells affects neutralization by antibodies to different spike epitopes in lentivirus pseudovirus neutralization assays. For high ACE2-expressing target cells, receptor binding domain (RBD) antibodies account for nearly all neutralizing activity in polyclonal human sera. But for lower ACE2-expressing target cells, antibodies targeting regions outside the RBD make a larger (although still modest) contribution to serum neutralization. These serum-level results are mirrored for monoclonal antibodies: N-terminal domain (NTD) antibodies and RBD antibodies that do not compete for ACE2 binding incompletely neutralize on high ACE2-expressing target cells, but completely neutralize on cells with lower ACE2 expression. Our results show that ACE2 expression level in the target cells is an important experimental variable, and that high ACE2 expression emphasizes the role of a subset of RBD-directed antibodies.

immunology↗