A de novo approach to inferring within-host fitness effects during untreated HIV-1 infection
Creators: name: Illingworth, Christopher J. R.
name: Raghwani, Jayna
name: Serwadda, David
name: Sewankambo, Nelson K.
name: Robb, Merlin L.
name: Eller, Michael A.
name: Redd, Andrew R.
name: Quinn, Thomas C.
name: Lythgoe, Katrina A.
Publisher: name: Apollo - University of Cambridge Repository
Year: 2020
Subjects: Research Article
Biology and life sciences
Ecology and environmental sciences
Medicine and health sciences

description: Funder: Isaac Newton Trust; funder-id: http://dx.doi.org/10.13039/501100004815
description: Funder: Li Ka Shing Foundation; funder-id: http://dx.doi.org/10.13039/100007421
description: Funder: Division of Intramural Research, National Institute of Allergy and Infectious Diseases; funder-id: http://dx.doi.org/10.13039/100006492
description: Funder: Helsingin Yliopisto; funder-id: http://dx.doi.org/10.13039/100007797
description: In the absence of effective antiviral therapy, HIV-1 evolves in response to the within-host environment, of which the immune system is an important aspect. During the earliest stages of infection, this process of evolution is very rapid, driven by a small number of CTL escape mutations. As the infection progresses, immune escape variants evolve under reduced magnitudes of selection, while competition between an increasing number of polymorphic alleles (i.e., clonal interference) makes it difficult to quantify the magnitude of selection acting upon specific variant alleles. To tackle this complex problem, we developed a novel multi-locus inference method to evaluate the role of selection during the chronic stage of within-host infection. We applied this method to targeted sequence data from the p24 and gp41 regions of HIV-1 collected from 34 patients with long-term untreated HIV-1 infection. We identify a broad distribution of beneficial fitness effects during infection, with a small number of variants evolving under strong selection and very many variants evolving under weaker selection. The uniquely large number of infections analysed granted a previously unparalleled statistical power to identify loci at which selection could be inferred to act with statistical confidence. Our model makes no prior assumptions about the nature of alleles under selection, such that any synonymous or non-synonymous variant may be inferred to evolve under selection. However, the majority of variants inferred with confidence to be under selection were non-synonymous in nature, and in most cases were have previously been associated with either CTL escape in p24 or neutralising antibody escape in gp41. We also identified a putative new CTL escape site (residue 286 in gag), and a region of gp41 (including residues 644, 648, 655 in env) likely to be associated with immune escape. Sites inferred to be under selection in multiple hosts have high within-host and between-host diversity although not all sites with high between-host diversity were inferred to be under selection at the within-host level. Our identification of selection at sites associated with resistance to broadly neutralising antibodies (bNAbs) highlights the need to fully understand the role of selection in untreated individuals when designing bNAb based therapies.