Genomic Detection of the Emerging, Highly Pathogenic HIV-1 Subtype D in Bahia, Northeast Brazil

Viruses. 2023 Jul 29;15(8):1650. doi: 10.3390/v15081650.

Abstract

(1) Background: The HIV subtype D is generally associated with a faster decline in CD4+ T cell counts, a higher viral load, and a faster progression to AIDS. However, it is still poorly characterized in Brazil. In this study, we used genomics and epidemiological data to investigate the transmission dynamics of HIV subtype D in the state of Bahia, Northeast Brazil. (2) Methods: To achieve this goal, we obtained four novel HIV-1 subtype D partial pol genome sequences using the Sanger method. To understand the emergence of this novel subtype in the state of Bahia, we used phylodynamic analysis on a dataset comprising 3704 pol genome sequences downloaded from the Los Alamos database. (3) Results: Our analysis revealed three branching patterns, indicating multiple introductions of the HIV-1 subtype D in Brazil from the late 1980s to the late 2000s and a single introduction event in the state of Bahia. Our data further suggest that these introductions most likely originated from European, Eastern African, Western African, and Southern African countries. (4) Conclusion: Understanding the distribution of HIV-1 viral strains and their temporal dynamics is crucial for monitoring the real-time evolution of circulating subtypes and recombinant forms, as well as for designing novel diagnostic and vaccination strategies. We advocate for a shift to active surveillance, to ensure adequate preparedness for future epidemics mediated by emerging viral strains.

Keywords: HIV-1 subtype D; genomic surveillance; phylodynamics.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Brazil / epidemiology
  • Databases, Factual
  • Genomics
  • HIV Seropositivity*
  • HIV-1* / genetics
  • Humans

Grants and funding

This research was funded by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior—Brasil (CAPES) [Finance Code 001, R.K.], Fundação de Amparo à Pesquisa do Estado da Bahia (FAPESB, grant APP0032/2016, R.K.), Brazilian National Council for Scientific and Technological Development (CNPq, grant 65083/2015-8, L.A.S.), and Fonds voor Wetenschappelijk Onderzoek Vlaanderen (grant G0A0621N, J.W.). MG is funded by PON “Ricerca e Innovazione” 2014–2020. None of the funding organizations had any role in the study design, data collection, data interpretation, or writing of this report.