Login / Signup

Deep sequencing of near full-length HIV-1 genomes from plasma identifies circulating subtype C and infrequent occurrence of AC recombinant form in Southern India.

Shuba Varshini AlampalliMichael M ThomsonRaghavan SampathkumarKarthi SivaramanAnto Jesuraj U K JChirag DharGeorge D SouzaNeil BerryAnnapurna Vyakarnam
Published in: PloS one (2017)
India has the third largest number of HIV-1-infected individuals accounting for approximately 2.1 million people, with a predominance of circulating subtype C strains and a low prevalence of subtype A and A1C and BC recombinant forms, identified over the past two decades. Recovery of near full-length HIV-1 genomes from a plasma source coupled with advances in next generation sequencing (NGS) technologies and development of universal methods for amplifying whole genomes of HIV-1 circulating in a target geography or population provides the opportunity for a detailed analysis of HIV-1 strain identification, evolution and dynamics. Here we describe the development and implementation of approaches for HIV-1 NGS analysis in a southern Indian cohort. Plasma samples (n = 20) were obtained from HIV-1-confirmed individuals living in and around the city of Bengaluru. Near full-length genome recovery was obtained for 9 Indian HIV-1 patients, with recovery of full-length gag and env genes for 10 and 2 additional subjects, respectively. Phylogenetic analyses indicate the majority of sequences to be represented by subtype C viruses branching within a monophyletic clade, comprising viruses from India, Nepal, Myanmar and China and closely related to a southern African cluster, with a low prevalence of the A1C recombinant form also present. Development of algorithms for bespoke recovery and analysis at a local level will further aid clinical management of HIV-1 infected Indian subjects and delineate the progress of the HIV-1 pandemic in this and other geographical regions.
Keyphrases
  • hiv infected
  • antiretroviral therapy
  • hiv positive
  • human immunodeficiency virus
  • hiv testing
  • hiv aids
  • hepatitis c virus
  • men who have sex with men
  • dna methylation
  • machine learning
  • coronavirus disease
  • single cell