Biology subjects

Herbeck, J.

Publications and source records attributed to Herbeck, J..

3 recordsLinked to original sources

bioRxiv2023

Directional predictions of HIV transmission with optimised genomics in cohorts of serodiscordant couples

Viral genetic information from people living with HIV can deepen our understanding of the infections epidemiology at many scales. To better understand the potentials and limits of tools that utilise such information, we show the performance of two representative tools (HIV-TRACE and phyloscanner) in describing HIV transmission dynamics, with different types of genetic data, and compare with previous findings. The samples were collected from three cohort studies in Sub-Saharan Africa and were deep sequenced to produce both short Illumina reads and long PacBio reads. By comparing phyloscanners performance with short and long reads, we show that long reads provide improved phylogenetic resolution for the classic transmission topology in joint within-host trees. Our pipeline accurately predicted the direction of transmission 88%-92% of the time. We also show that the timing of sample collection plays an important role in the reconstruction of directionality using deep sequencing data. Consensus sequences were also generated and used as HIV-TRACE input to show different patterns of clustering sensitivity and specificity for data from different genomic regions or the entire genome. Finally, we discuss adjusting expectations about sensitivity and specificity of different types of sequence data, considering rapid pathogen evolution, and highlight the potentials of high within-host phylogenetic resolution in HIV. In conclusion, viral genetic data collected and presented differently could greatly influence our ability to describe the underlying dynamics. Methods for source attribution analysis have reached levels of superior accuracy. However, residual uncertainty emphasizes sequence analysis alone cannot conclusively prove linkage at the individual level. ImportanceUnderstanding HIV transmission dynamics is key to designing effective HIV testing and prevention strategies. By using different sequencing techniques on well-characterised cohorts, we were able to evaluate the effect of genetic data resolution on the accuracy of identifying likely transmission pairs and the direction of transmission within pairs. We find that the longer reads generated by PacBio sequencing are more suitable for transmission analyses.

genomics↗

bioRxiv2022

Optimized phylogenetic clustering of HIV-1 sequence data for public health applications

Clusters of genetically similar infections suggest rapid transmission and may indicate priorities for public health action or reveal underlying epidemiological processes. However, clusters often require user-defined thresholds and are sensitive to non-epidemiological factors, such as non-random sampling. Consequently the ideal threshold for public health applications varies substantially across settings. Here, we show a method which selects optimal thresholds for phylogenetic (subset tree) clustering based on population. We evaluated this method on HIV-1 pol datasets (n = 14,221 sequences) from four sites in USA (Tennessee, Seattle), Canada (Northern Alberta) and China (Beijing). Clusters were defined by tips descending from an ancestral node (with a minimum bootstrap support of 95%) through a series of branches, each with a length below a given threshold. Next, we used pplacer to graft new cases to the fixed tree by maximum likelihood. We evaluated the effect of varying branch-length thresholds on cluster growth as a count outcome by fitting two Poisson regression models: a null model that predicts growth from cluster size, and an alternative model that includes mean collection date as an additional covariate. The alternative model was favoured by AIC across most thresholds, with optimal (greatest difference in AIC) thresholds ranging 0.007-0.013 across sites. The range of optimal thresholds was more variable when re-sampling 80% of the data by location (IQR 0.008 - 0.016, n = 100 replicates). Our results use prospective phylogenetic cluster growth and suggest that there is more variation in effective thresholds for public health than those typically used in clustering studies.

bioinformatics↗

bioRxiv2017

HIV population-level adaptation can rapidly diminish the impact of a partially effective vaccine

Development of an HIV vaccine is essential to ending the HIV/AIDS pandemic. However, vaccines can result in the emergence and spread of vaccine-resistant strains. Indeed, analyses of breakthrough infections in the HIV vaccine trial RV144 identified HIV genotypes with differential rates of transmission in vaccine and placebo recipients. We hypothesized that, for HIV vaccination programs based on partially effective vaccines similar to RV144, HIV adaptation will diminish the expected vaccine impact. Using two HIV epidemic models, we simulated large-scale vaccination programs and, critically, included HIV strain diversity with respect to the vaccine response. We show here that rapid population-level viral adaptation can lead to decreased overall vaccine efficacy and substantially fewer infections averted by vaccination, when comparing scenarios with and without viral evolution (depending on vaccination coverage, vaccine efficacy against the sensitive allele, and the initial resistant allele frequency). Translating this to the epidemic in South Africa, a scenario with 70% vaccination coverage may result in 250,000 new infections within 10 years of vaccine rollout that are due solely to HIV adaptation, all else being equal. These findings suggest that approaches to HIV vaccine development, program implementation, and epidemic modeling may require attention to viral evolutionary responses to vaccination.

evolutionary biology↗