Timothy J.C. Tan

This study identifies a cross-reactive germline antibody that can be evolved to neutralize multiple SARS-CoV-2 variants through targeted somatic mutations.

This study shows that antibodies against influenza virus neutralize by interacting with the viral membrane, and disrupting these interactions reduces their effectiveness.

This study identifies three IGHV3-23 antibodies targeting influenza HA stem, showing that non-neutralizing antibodies with enhanced Fc-mediated effector functions offer better in vivo protection than a potent neutralizer.

This study uses deep mutational scanning to analyze the functional impact of NEP mutations in influenza A virus, revealing pleiotropic effects on viral replication and host adaptation.

This study compares the ability of seasonal H1N1 and H3N2 influenza A viruses to antagonize interferon induction and signaling at the single-cell level, finding differences in their IFN antagonism potential.

This study uses deep mutational scanning to analyze the SARS-CoV-2 spike fusion peptide, identifying mutations affecting viral entry and antibody resistance.

This study identifies S2 domain mutations in SARS-CoV-2 spike that reduce binding to antibodies, showing antigenic drift in this region and its impact on vaccine efficacy.

This study shows that natural variation in neuraminidase activity affects the evolutionary potential of hemagglutinin in seasonal H1N1 influenza viruses.

This study identifies sequence constraints for IGHV1-69 antibodies targeting influenza HA stem, showing light chain and CDR H3 sequences coordinate HA stem specificity.

This study curates a dataset of influenza HA antibodies and develops an explainable language model to predict antibody specificity, identifying and validating HA stem antibodies.