Massively parallel pyrosequencing highlights minority variants in the HIV-1 env quasispecies deriving from lymphomonocyte sub-populations

Abstract

Background: Virus-associated cell membrane proteins acquired by HIV-1 during budding may give information on the cellular source of circulating virions. In the present study, by applying immunosorting of the virus and of the cells with antibodies targeting monocyte (CD36) and lymphocyte (CD26) markers, it was possible to directly compare HIV-1 quasispecies archived in circulating monocytes and T lymphocytes with that present in plasma virions originated from the same cell types. Five chronically HIV-1 infected patients who underwent therapy interruption after prolonged HAART were enrolled in the study. The analysis was performed by the powerful technology of ultra-deep pyrosequencing after PCR amplification of part of the env gene, coding for the viral glycoprotein (gp) 120, encompassing the tropism-related V3 loop region. V3 amino acid sequences were used to establish heterogeneity parameters, to build phylogenetic trees and to predict co-receptor usage.

Tracking the Evolution of MultipleIn VitroHepatitis C Virus Replicon Variants under Protease Inhibitor Selection Pressure by 454 Deep Sequencing

“…At every passage, cell viability was scored microscopically, and cells were harvested, total RNA was extracted, and the protease domain of the NS3 gene was sequenced using standard Sanger population sequencing. For reasons of clarity, we will here limit our analysis to the six amino acid positions (41,43,80,155,156, and 168) in NS3 known to affect binding and activity of macrocyclic NS3 protease inhibitors (20,21,24). Different resistance profiles were observed in the low-concentration (100 nM) and high-concentration (1,000 nM) experiments (Fig.…”

“…3. Codon frequencies at six key amino NS3 acid positions (41,43,80,155,156, and 168; indicated by 1 to 6, respectively) of selection experiment with stepwise-increasing TMC380765 concentrations (A and B) or in the absence of NS3/4A inhibitor (C), as determined by 454 GS-FLX shotgun (A) or 454 GS-FLX amplicon (B and C) deep sequencing. Frequencies of individual amino acids were calculated as the number of sequence reads per specific codon divided by the total number of reads at that codon position.…”

“…The recent development of deep sequencing technologies may facilitate a better understanding of the genetic composition and natural evolution of viral quasispecies in the presence of antiviral drugs (30,34,54). Indeed, studies of HIV suggest that these more-sensitive sequencing technologies detect additional minority variants for both treatment-naive and treatment-experienced patients which could impact the clinical outcome of antiretroviral therapy and may provide important information for treatment planning (2,23,41,46). TMC380765 ( Fig.…”

MHC influences infection with parasites and winter survival in the root vole Microtus oeconomus

“…In 454 sequencing, artefacts generated repeatedly through 1 bp indels in homopolymer tracts are especially common, with approximately a 1 % error rate. As the frequency of a given artefact per amplicon may be considerable (Rozera et al 2009), we excluded all sequences with indels. The probability of obtaining more than two identical substitution-type artefacts per amplicon is negligibly low (Galan et al 2010), so we also removed sequences that occurred in a single copy or in only two copies.…”

Phylogenetic Analysis of Population-Based and Deep Sequencing Data to Identify Coevolving Sites in the nef Gene of HIV-1

“…For rapidly evolving RNA viruses, this limited read length can nonetheless suffice to render an informative sample of sequence diversity within a narrowly defined portion of the genome, that is, "deep sequencing." As a result, the massively parallel pyrosequencing (MPP) platform distributed by Roche/454 Life Sciences, which offers the longest mean read length (100-450 bp) at the expense of a reduced throughput capacity (≈10 5 reads), has been adopted by many investigators in HIV research (Hoffmann et al 2007;Wang, Ciuffi, et al 2007;Wang, Mitsuya, et al 2007;Rozera et al 2009), where NGS is most often used to detect minority variants in the virus population. Although such data might carry a sufficiently strong phylogenetic signal to infer within-host evolutionary processes such as sequence coevolution, this application has only begun to be pursued (Campbell et al 2008;Tsibris et al 2009).…”