A5018606667- vaccines and immunoinformatics approaches
- CRISPR and Genetic Engineering
- HIV Research and Treatment
- SARS-CoV-2 and COVID-19 Research
- Influenza Virus Research Studies
- Respiratory viral infections research
- T-cell and B-cell Immunology
- Cell Image Analysis Techniques
- Gene Regulatory Network Analysis
- Immune Cell Function and Interaction
- Single-cell and spatial transcriptomics
- Viral Infections and Immunology Research
- Embedded Systems Design Techniques
- Explainable Artificial Intelligence (XAI)
- Monoclonal and Polyclonal Antibodies Research
- Malaria Research and Control
- RNA and protein synthesis mechanisms
- Virus-based gene therapy research
- Parvovirus B19 Infection Studies
- Evolutionary Algorithms and Applications
- Complement system in diseases
- HIV/AIDS drug development and treatment
- Viral Infectious Diseases and Gene Expression in Insects
- Bacterial Genetics and Biotechnology
University of Washington
2021-2025
Fred Hutch Cancer Center
2022-2024
Cape Town HVTN Immunology Laboratory / Hutchinson Centre Research Institute of South Africa
2023
University of California, Los Angeles
2020-2021
Ragon Institute of MGH, MIT and Harvard
2021
A major challenge in understanding SARS-CoV-2 evolution is interpreting the antigenic and functional effects of emerging mutations viral spike protein. Here, we describe a deep mutational scanning platform based on non-replicative pseudotyped lentiviruses that directly quantifies how large numbers impact antibody neutralization pseudovirus infection. We apply this to produce libraries Omicron BA.1 Delta spikes. These each contain ∼7,000 distinct amino acid context up ∼135,000 unique mutation...
Human influenza virus evolves to escape neutralization by polyclonal antibodies. However, we have a limited understanding of how the antigenic effects viral mutations vary across human population and this heterogeneity affects evolution. Here, use deep mutational scanning map hemagglutinin (HA) proteins two H3N2 strains, A/Hong Kong/45/2019 A/Perth/16/2009, affect serum from individuals variety ages. The HA on differ age groups in ways that can be partially rationalized terms exposure...
A crucial step towards engineering biological systems is the ability to precisely tune genetic response environmental stimuli. In case of Escherichia coli inducible promoters, our incomplete understanding relationship between sequence composition and gene expression hinders predictably control transcriptional responses. Here, we profile dynamics 8269 rationally designed, IPTG-inducible promoters that collectively explore individual combinatorial effects RNA polymerase LacI repressor binding...
A challenge in studying viral immune escape is determining how mutations combine to polyclonal antibodies, which can potentially target multiple distinct epitopes. Here we introduce a biophysical model of this process that partitions the total antibody activity by epitope and then quantifies each mutation affects against epitope. We develop software use deep mutational scanning data infer these properties for mixtures. validate using computationally simulated experiment demonstrate it...
Understanding the specificities of human serum antibodies that broadly neutralize HIV can inform prevention and treatment strategies. Here, we describe a deep mutational scanning system measure effects combinations mutations to envelope (Env) on neutralization by polyclonal serum. We first show this accurately map how all functionally tolerated Env affect monoclonal antibodies. then comprehensively set sera diverse strains target site engaging host receptor CD4. The neutralizing activities...
Vaccines and monoclonal antibodies targeting the respiratory syncytial virus (RSV) fusion protein (F) have recently begun to be widely used protect infants high-risk adults. Some other viral proteins evolve erode polyclonal antibody neutralization escape individual antibodies. However, little is known about how RSV F evolution affects Here we develop an experimental system for measuring titers against using pseudotyped lentiviral particles. This easily adaptable evaluate of relevant clinical...
ABSTRACT Human influenza virus evolves to escape neutralization by polyclonal antibodies. However, we have a limited understanding of how the antigenic effects viral mutations vary across human population, and this heterogeneity affects evolution. Here use deep mutational scanning map hemagglutinin (HA) proteins A/Hong Kong/45/2019 (H3N2) A/Perth/16/2009 strains affect serum from individuals variety ages. The HA on differ age groups in ways that can be partially rationalized terms exposure...
A major challenge in understanding SARS-CoV-2 evolution is interpreting the antigenic and functional effects of emerging mutations viral spike protein. Here we describe a new deep mutational scanning platform based on non-replicative pseudotyped lentiviruses that directly quantifies how large numbers impact antibody neutralization pseudovirus infection. We demonstrate this by making libraries Omicron BA.1 Delta spikes. These each contain ~7000 distinct amino-acid context up to ~135,000...
Abstract A crucial step towards engineering biological systems is the ability to precisely tune genetic response environmental stimuli. In case of Escherichia coli inducible promoters, our incomplete understanding relationship between sequence composition and gene expression hinders predictably control transcriptional responses. Here, we profile dynamics 8,269 rationally designed IPTG-inducible promoters that collectively explore individual combinatorial effects RNA polymerase LacI repressor...
Abstract A challenge in studying viral immune escape is determining how mutations combine to polyclonal antibodies, which can potentially target multiple distinct epitopes. Here we introduce a biophysical model of this process that partitions the total antibody activity by epitope, and then quantifies each mutation affects against epitope. We develop software use deep mutational scanning data infer these properties for mixtures. validate using computationally simulated experiment,...
Abstract A common workflow in single-cell RNA-seq analysis is to project the data a latent space, cluster cells that and identify sets of marker genes explain differences among discovered clusters. primary drawback this three-step procedure each step carried out independently, thereby neglecting effects nonlinear embedding inter-gene dependencies on selection genes. Here we propose an integrated deep learning framework, Adversarial Clustering Explanation (ACE), bundles all three steps into...
Understanding the specificities of human serum antibodies that broadly neutralize HIV can inform prevention and treatment strategies. Here we describe a deep mutational scanning system measure effects combinations mutations to envelope (Env) on neutralization by polyclonal serum. We first show this accurately map how all functionally tolerated Env affect monoclonal antibodies. then comprehensively set sera known target CD4-binding site diverse strains HIV. The neutralizing activities these...