Hillel Haim
University of Iowa, IA·Microbiology & Immunology
HIV drugs work, until the virus mutates around them. Because mutations arise randomly, the appearance of resistant virus is usually treated as unpredictable, so treatment choices are largely made by trial and error.
- Fields
Microbiology & Immunology
Medicine & Clinical Research
Genetics
- Topics
capsid protein
lenacapavir
antiviral resistance
- Grants
- 2 known grants, through Jun 2028
What they work on
- Build a deep mutational scanning system using replication-defective HIV-1 to measure, safely and at high throughput, how every amino acid substitution at each site of the capsid protein affects viral fitness and resistance to the capsid inhibitor lenacapavir.
- Optimize and benchmark the scanning measurements by assessing reproducibility across three independent biological replicates per site, comparing different cell types, and validating selected variants with conventional single-variant assays in replication-competent and replication-defective virus.
- Extend the platform to dual-site deep mutational scanning to resolve epistatic interactions, where one mutation's effect depends on another, among capsid residues linked to lenacapavir resistance.
- Test whether the rate of HIV-1 escape from broadly neutralizing antibodies is specific to each patient's virus swarm, using Env-expressing strains isolated from patient samples collected at different time points and in vitro escape experiments.
- Determine whether sequence-based models can forecast the rate and the site of envelope glycoprotein escape, and apply refined models to predict resistance rates observed in four clinical trials of broadly neutralizing antibodies.
- Establish whether resistant mutants emerge because of their pre-treatment fitness or their post-treatment replicative advantage, and compare fitness profiles at escape sites between circulating virus and latent virus induced to grow out from peripheral blood cells.
More about the research
Both projects here push against that assumption, arguing that the mutational options available to a given virus can be measured in advance. One project maps every possible mutation in the viral shell protein targeted by a new long-acting drug; the other asks whether the virus population in an individual patient carries a readable signature of how fast it will escape antibody therapy. Together they aim to make resistance something that can be anticipated rather than discovered after treatment fails.
Why it matters
Drug and antibody resistance limits how long HIV treatments keep working. A complete map of which capsid mutations confer resistance to lenacapavir, and how fit those mutants are, could help clinicians anticipate escape pathways and help chemists design follow-on capsid inhibitors. Measuring each patient's virus swarm for its propensity to escape a given antibody could lay the groundwork for personalized antiviral selection, matching people living with HIV to the agents their virus is least likely to escape.
Known grants
From NIH and NSF research grants. Labs often have other funding we can't see.
Closest labs
Masahiro Yamashita
Columbia University, NY·Microbiology & Immunology
Develop a high-throughput neutralization assay in which each HIV envelope (Env) variant in a lentiviral system carries a unique DNA barcode, allowing simultaneous tracking of hundreds of variants against ten broadly neutralizing antibodies targeting five gp120 sites.
Jeannette Tenthorey
University of California-San Francisco, CA·Microbiology & Immunology·Early-career
Build stable, high-complexity HIV-1 libraries containing all possible single missense mutations across the capsid, using new tools that overcome long-standing barriers to producing saturating mutant viral libraries.
Wei Li
University of Pittsburgh, PA·Microbiology & Immunology
Engineer soluble CD4 D1-domain variants with improved binding kinetics and isolate single-domain VH binders against CD4-induced epitopes on HIV envelope, combining computational structure design, phage display and time-resolved cryo-electron microscopy.
The school
University of Iowa: 32 labs on PI Pages, $703M a year on research, 418 research doctorates a year.
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