MHRP researchers recently published findings from a study comparing HIV gene and genome sequence analyses to help inform strategies to best estimate the timing of HIV infection.
Bethany Dearlove, a bioinformatics analyst in the Viral Genetics section at MHRP was the lead author of the paper, titled, “Factors influencing estimates of HIV-1 infection timing using BEAST,” published earlier this month in PLOS Computational Biology.
Researchers used a statistical modeling platform called Bayesian evolutionary analysis sampling trees (BEAST), to compare genome-based and gene-specific Bayesian phylogenetic analyses to investigate how certain factors impact estimates of the infection dates in an acute HIV-1 infection cohort, RV217. They analyzed HIV-1 sequences sampled one week, one month and six months after HIV-1 diagnosis in 39 individuals.
Previously, genetic data from three time periods during early infection were analyzed in the RV217 cohort. The study found that the eclipse phase lasted around one week in individuals.
The study found that all but the longest genes are near-clones during acute infection, meaning they provide little information helpful for dating purposes. Single-founder variants showed the infection eclipse phase lasting between one to two weeks. The eclipse phase is the time elapsed between cell infection and the start of virus production, and precise timing of the HIV eclipse phase has historically been difficult. The study approach could be used to narrow the date of suspected infection in ongoing clinical trials for the prevention of HIV-1 infection.
The study was possible due to valuable samples from MHRP’s RV217 prospective acute infection cohort. RV217 began in 2009 and prospectively followed a group of high-risk volunteers in East Africa and Thailand, tracking HIV status and characterizing progression through the acute stages of HIV infection. Most importantly, the RV217 study design restricted the plausible window of infection due to twice-weekly HIV RNA tests. Volunteers were enrolled before they became infected, and when they were diagnosed, researchers were able to capture samples from the earliest days of HIV infection, before these individuals developed antibodies against HIV.
PLoS Comput Biol. 2021 Feb 1;17(2):e1008537. doi: 10.1371/journal.pcbi.1008537.