PLoS ONE (Jan 2013)

Phylogenetic relatedness of circulating HIV-1C variants in Mochudi, Botswana.

  • Vladimir Novitsky,
  • Hermann Bussmann,
  • Andrew Logan,
  • Sikhulile Moyo,
  • Erik van Widenfelt,
  • Lillian Okui,
  • Mompati Mmalane,
  • Jeannie Baca,
  • Lauren Buck,
  • Eleanor Phillips,
  • David Tim,
  • Mary Fran McLane,
  • Quanhong Lei,
  • Rui Wang,
  • Joseph Makhema,
  • Shahin Lockman,
  • Victor DeGruttola,
  • M Essex

DOI
https://doi.org/10.1371/journal.pone.0080589
Journal volume & issue
Vol. 8, no. 12
p. e80589

Abstract

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BackgroundDetermining patterns of HIV transmission is increasingly important for the most efficient use of modern prevention interventions. HIV phylogeny can provide a better understanding of the mechanisms underlying HIV transmission networks in communities.MethodsTo reconstruct the structure and dynamics of a local HIV/AIDS epidemic, the phylogenetic relatedness of HIV-1 subtype C env sequences obtained from 785 HIV-infected community residents in the northeastern sector of Mochudi, Botswana, during 2010-2013 was estimated. The genotyping coverage was estimated at 44%. Clusters were defined based on relatedness of HIV-1C env sequences and bootstrap support of splits.ResultsThe overall proportion of clustered HIV-1C env sequences was 19.1% (95% CI 17.5% to 20.8%). The proportion of clustered sequences from Mochudi was significantly higher than the proportion of non-Mochudi sequences that clustered, 27.0% vs. 14.7% (p = 5.8E-12; Fisher exact test). The majority of clustered Mochudi sequences (90.1%; 95% CI 85.1% to 93.6%) were found in the Mochudi-unique clusters. None of the sequences from Mochudi clustered with any of the 1,244 non-Botswana HIV-1C sequences. At least 83 distinct HIV-1C variants, or chains of HIV transmission, in Mochudi were enumerated, and their sequence signatures were reconstructed. Seven of 20 genotyped seroconverters were found in 7 distinct clusters.ConclusionsThe study provides essential characteristics of the HIV transmission network in a community in Botswana, suggests the importance of high sampling coverage, and highlights the need for broad HIV genotyping to determine the spread of community-unique and community-mixed viral variants circulating in local epidemics. The proposed methodology of cluster analysis enumerates circulating HIV variants and can work well for surveillance of HIV transmission networks. HIV genotyping at the community level can help to optimize and balance HIV prevention strategies in trials and combined intervention packages.