Research Article: Evolution of HIV-1 within untreated individuals and at the population scale in Uganda

Date Published: July 27, 2018

Publisher: Public Library of Science

Author(s): Jayna Raghwani, Andrew D. Redd, Andrew F. Longosz, Chieh-Hsi Wu, David Serwadda, Craig Martens, Joseph Kagaayi, Nelson Sewankambo, Stephen F. Porcella, Mary K. Grabowski, Thomas C. Quinn, Michael A. Eller, Leigh Anne Eller, Fred Wabwire-Mangen, Merlin L. Robb, Christophe Fraser, Katrina A. Lythgoe, Philippe Lemey.


HIV-1 undergoes multiple rounds of error-prone replication between transmission events, resulting in diverse viral populations within and among individuals. In addition, the virus experiences different selective pressures at multiple levels: during the course of infection, at transmission, and among individuals. Disentangling how these evolutionary forces shape the evolution of the virus at the population scale is important for understanding pathogenesis, how drug- and immune-escape variants are likely to spread in populations, and the development of preventive vaccines. To address this, we deep-sequenced two regions of the HIV-1 genome (p24 and gp41) from 34 longitudinally-sampled untreated individuals from Rakai District in Uganda, infected with subtypes A, D, and inter-subtype recombinants. This dataset substantially increases the availability of HIV-1 sequence data that spans multiple years of untreated infection, in particular for different geographical regions and viral subtypes. In line with previous studies, we estimated an approximately five-fold faster rate of evolution at the within-host compared to the population scale for both synonymous and nonsynonymous substitutions, and for all subtypes. We determined the extent to which this mismatch in evolutionary rates can be explained by the evolution of the virus towards population-level consensus, or the transmission of viruses similar to those that establish infection within individuals. Our findings indicate that both processes are likely to be important.

Partial Text

Infection by HIV-1 is lifelong, and characterized by ongoing viral replication, and consequently the virus can undergo hundreds of rounds of replication between transmission events. This, combined with error-prone viral replication during reverse transcription, means that the viruses an individual transmits to a recipient are unlikely to be identical to those that initially infected them. A firm understanding of how evolution proceeds during the course of infection within an individual, and how this corresponds to evolution of the virus at the population scale, is therefore required to understand how selection acts at the point of transmission. This is important for vaccine design, and understanding how the virus evolves at the epidemiological scale.

Using cryopreserved samples from individuals longitudinally sampled before the availability of universal treatment in the Rakai District of Uganda, we have substantially increased the number of individuals for which deep-sequenced data is available for HIV-1 during the course of untreated infection. The main subtypes represented in this HIV-1 cohort are A and D, rather than subtype B, which predominates in the more frequently studied European and North American cohorts. As well as analyzing this within-host sequence data, we also utilized publicly available population consensus sequences from Uganda, enabling us to directly compare rates of viral evolution at both the within-individual and population scales in the same population and for the same regions of the genome.