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- Garcia-Knight, MA, et al.
(författare)
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Viral Evolution and Cytotoxic T Cell Restricted Selection in Acute Infant HIV-1 Infection
- 2016
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Ingår i: Scientific reports. - : Springer Science and Business Media LLC. - 2045-2322. ; 6, s. 29536-
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Tidskriftsartikel (refereegranskat)abstract
- Antiretroviral therapy-naive HIV-1 infected infants experience poor viral containment and rapid disease progression compared to adults. Viral factors (e.g. transmitted cytotoxic T- lymphocyte (CTL) escape mutations) or infant factors (e.g. reduced CTL functional capacity) may explain this observation. We assessed CTL functionality by analysing selection in CTL-targeted HIV-1 epitopes following perinatal infection. HIV-1 gag, pol and nef sequences were generated from a historical repository of longitudinal specimens from 19 vertically infected infants. Evolutionary rate and selection were estimated for each gene and in CTL-restricted and non-restricted epitopes. Evolutionary rate was higher in nef and gag vs. pol, and lower in infants with non-severe immunosuppression vs. severe immunosuppression across gag and nef. Selection pressure was stronger in infants with non-severe immunosuppression vs. severe immunosuppression across gag. The analysis also showed that infants with non-severe immunosuppression had stronger selection in CTL-restricted vs. non-restricted epitopes in gag and nef. Evidence of stronger CTL selection was absent in infants with severe immunosuppression. These data indicate that infant CTLs can exert selection pressure on gag and nef epitopes in early infection and that stronger selection across CTL epitopes is associated with favourable clinical outcomes. These results have implications for the development of paediatric HIV-1 vaccines.
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- Pond, SLK, et al.
(författare)
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HyPhy 2.5-A Customizable Platform for Evolutionary Hypothesis Testing Using Phylogenies
- 2020
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Ingår i: Molecular biology and evolution. - : Oxford University Press (OUP). - 1537-1719 .- 0737-4038. ; 37:1, s. 295-299
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Tidskriftsartikel (refereegranskat)abstract
- HYpothesis testing using PHYlogenies (HyPhy) is a scriptable, open-source package for fitting a broad range of evolutionary models to multiple sequence alignments, and for conducting subsequent parameter estimation and hypothesis testing, primarily in the maximum likelihood statistical framework. It has become a popular choice for characterizing various aspects of the evolutionary process: natural selection, evolutionary rates, recombination, and coevolution. The 2.5 release (available from www.hyphy.org) includes a completely re-engineered computational core and analysis library that introduces new classes of evolutionary models and statistical tests, delivers substantial performance and stability enhancements, improves usability, streamlines end-to-end analysis workflows, makes it easier to develop custom analyses, and is mostly backward compatible with previous HyPhy releases.
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