Jesse D. Bloom

The paper measures how mutations in influenza HA affect function, stability, and antibody neutralization, showing epistasis enables antigenic change but cannot overcome pleiotropic costs that restrict evolutionary trajectories.

This study uses deep mutational scanning to identify functional and antigenic effects of mutations in rabies glycoprotein, revealing escape mutations for antibodies and constrained regions for vaccine development.

This study maps escape mutations from antibodies 10-1074 and 3BNC117 against HIV Envs from two strains, showing differences in mutation effects between strains.

This study compares neutralizing antibody specificities between recently infected infants and immune-imprinted adults, finding distinct targeting of SARS-CoV-2 spike domains.

This study uses deep mutational scanning to analyze how mutations in the Nipah virus receptor-binding protein affect function, receptor binding, and antibody escape, revealing constrained regions and limited antigenic variation in natural strains.

The paper designs bispecific antibodies that retain neutralization activity against multiple SARS-CoV-2 variants, including Omicron subvariants.

The paper quantifies neutralizing antibody responses to influenza strains using sera collected in 2024-2025 to inform vaccine-strain selection for 2025.

This study uses deep mutational scanning to analyze H5 hemagglutinin mutations and their impact on pandemic risk factors in influenza viruses.

This study develops a high-throughput sequencing-based neutralization assay to measure antibody titers against multiple influenza strains and finds that vaccination effects vary by individual and prior vaccination history.

This study identifies molecular mechanisms of FCoV-23 pathogenicity, including receptor usage and biotype switching, and identifies a cross-reactive antibody for therapeutic development.

This study compares IgG antibody responses from SARS-CoV-2 infection, vaccination, and hybrid immunity, finding that hybrid immunity retains the imprint of the initial exposure and enhances antibody breadth and affinity.

The paper maps how HA mutations affect neutralization by serum from different age groups, showing age-dependent antigenic effects and implications for viral evolution.

dms-viz provides a web-based tool for visualizing mutation-based data in the context of 3D protein structures, improving the interpretation of mutation effects on protein function.

This study characterizes structural and genetic diversity in MUC5AC and MUC5B using long-read sequencing, revealing haplotype variation and evolutionary patterns across human and nonhuman primate populations.

This study uses deep mutational scanning to assess how mutations in SARS-CoV-2 spike proteins affect ACE2 binding, cell entry, and serum escape, linking these effects to clade growth rates.

This study identifies how single mutations in Zika virus envelope protein affect neutralization by broadly and narrowly specific antibodies, finding that broad antibodies are harder to escape.

This study identifies two antibodies that neutralize all SARS-CoV-2 variants by locking the spike protein in a down conformation, showing a novel mechanism and potential for prophylaxis.

The paper develops a method to identify mutations with shifted effects across DMS experiments on SARS-CoV-2 spike homologs, finding some mutations show >1,000-fold differences in impact across variants.

The paper analyzes metagenomic data from the Huanan Seafood Market to assess the relationship between SARS-CoV-2 reads and animal species, finding no consistent correlation between viral reads and susceptible species.

The paper designs and characterizes trivalent miniprotein binders that neutralize SARS-CoV-2 variants with low pM IC50 values and provide prophylactic and therapeutic protection in mice.

dms-view is a web-based tool for visualizing DMS data in the context of 3-D protein structures and natural sequence variation.

alignparse is a Python package that parses complex features from long-read sequencing data by aligning reads to user-defined target sequences and extracting specified features.

The paper derives equations to calculate multiplet frequency in single-cell RNA sequencing when cell types are mixed in arbitrary proportions, assuming Poisson cell loading.

This study uses single-cell RNA sequencing to show extreme variation in viral gene transcript production among infected cells, with some cells producing over half their mRNA from virus.

This paper develops a deep mutational scanning framework to map functional missense variants in human genes and applies it to four proteins, identifying pathogenic variants and showing scalability to disease genes.