Viruses (Jan 2023)

Prediction of Coreceptor Tropism in HIV-1 Subtype C in Botswana

  • Kenanao Kotokwe,
  • Sikhulile Moyo,
  • Melissa Zahralban-Steele,
  • Molly Pretorius Holme,
  • Pinkie Melamu,
  • Catherine Kegakilwe Koofhethile,
  • Wonderful Tatenda Choga,
  • Terence Mohammed,
  • Tapiwa Nkhisang,
  • Baitshepi Mokaleng,
  • Dorcas Maruapula,
  • Tsotlhe Ditlhako,
  • Ontlametse Bareng,
  • Patrick Mokgethi,
  • Corretah Boleo,
  • Joseph Makhema,
  • Shahin Lockman,
  • Max Essex,
  • Manon Ragonnet-Cronin,
  • Vlad Novitsky,
  • Simani Gaseitsiwe,
  • PANGEA Consortium

DOI
https://doi.org/10.3390/v15020403
Journal volume & issue
Vol. 15, no. 2
p. 403

Abstract

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It remains unknown whether the C-C motif chemokine receptor type 5 (CCR5) coreceptor is still the predominant coreceptor used by Human Immunodeficiency Virus-1 (HIV-1) in Botswana, where the HIV-1 subtype C predominates. We sought to determine HIV-1C tropism in Botswana using genotypic tools, taking into account the effect of antiretroviral treatment (ART) and virologic suppression. HIV-1 gp120 V3 loop sequences from 5602 participants were analyzed for viral tropism using three coreceptor use predicting algorithms/tools: Geno2pheno, HIV-1C Web Position-Specific Score Matrices (WebPSSM) and the 11/25 charge rule. We then compared the demographic and clinical characteristics of people living with HIV (PLWH) harboring R5- versus X4-tropic viruses using χ2 and Wilcoxon rank sum tests for categorical and continuous data analysis, respectively. The three tools congruently predicted 64% of viruses as either R5-tropic or X4-tropic. Geno2pheno and the 11/25 charge rule had the highest concordance at 89%. We observed a significant difference in ART status between participants harboring X4- versus R5-tropic viruses. X4-tropic viruses were more frequent among PLWH receiving ART (χ2 test, p = 0.03). CCR5 is the predominant coreceptor used by HIV-1C strains circulating in Botswana, underlining the strong potential for CCR5 inhibitor use, even in PLWH with drug resistance. We suggest that the tools for coreceptor prediction should be used in combination.

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