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HIV-1 Tropism Determines Different Mutation Profiles in Proviral DNA.

ABSTRACT: In order to establish new infections HIV-1 particles need to attach to receptors expressed on the cellular surface. HIV-1 particles interact with a cell membrane receptor known as CD4 and subsequently with another cell membrane molecule known as a co-receptor. Two major different co-receptors have been identified: C-C chemokine Receptor type 5 (CCR5) and C-X-C chemokine Receptor type 4 (CXCR4) Previous reports have demonstrated cellular modifications upon HIV-1 binding to its co-receptors including gene expression modulations. Here we investigated the effect of viral binding to either CCR5 or CXCR4 co-receptors on viral diversity after a single round of reverse transcription. CCR5 and CXCR4 pseudotyped viruses were used to infect non-stimulated and stimulated PBMCs and purified CD4 positive cells. We adopted the SOLiD methodology to sequence virtually the entire proviral DNA from all experimental infections. Infections with CCR5 and CXCR4 pseudotyped virus resulted in different patterns of genetic diversification. CCR5 virus infections produced extensive proviral diversity while in CXCR4 infections a more localized substitution process was observed. In addition, we present pioneering results of a recently developed method for the analysis of SOLiD generated sequencing data applicable to the study of viral quasi-species. Our findings demonstrate the feasibility of viral quasi-species evaluation by NGS methodologies. We presented for the first time strong evidence for a host cell driving mechanism acting on the HIV-1 genetic variability under the control of co-receptor stimulation. Additional investigations are needed to further clarify this question, which is relevant to viral diversification process and consequent disease progression.

SUBMITTER: Nascimento-Brito S

PROVIDER: S-EPMC4587555 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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HIV-1 Tropism Determines Different Mutation Profiles in Proviral DNA.

Nascimento-Brito Sieberth S Paulo Zukurov Jean J Maricato Juliana T JT Volpini Angela C AC Salim Anna Christina M AC Araújo Flávio M G FM Coimbra Roney S RS Oliveira Guilherme C GC Antoneli Fernando F Janini Luiz Mário R LM

PloS one 20150928 9

In order to establish new infections HIV-1 particles need to attach to receptors expressed on the cellular surface. HIV-1 particles interact with a cell membrane receptor known as CD4 and subsequently with another cell membrane molecule known as a co-receptor. Two major different co-receptors have been identified: C-C chemokine Receptor type 5 (CCR5) and C-X-C chemokine Receptor type 4 (CXCR4) Previous reports have demonstrated cellular modifications upon HIV-1 binding to its co-receptors includ ...[more]

PMID: 26413773

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Project description:The Maraviroc Switch collaborative study (MARCH) is a study in aviremic patients on stable antiretroviral therapy and utilizes population-based sequencing of proviral DNA to determine HIV tropism and susceptibility to maraviroc. An external quality assessment (EQA) program was implemented to ensure competency in assessing the tropism of clinical samples conducted by MARCH laboratories (n = 14). The MARCH EQA has three prestudy phases assessing V3 loop sequencing and tropism determination using the bioinformatic algorithm geno2pheno, which generates a false-positive rate (FPR). DNA sequences with low FPRs are more likely to be from CXCR4-using (X4) viruses. Phase 1 of the EQA involved chromatogram interpretation. Phases 2, 2/3, and 3 involved patient and clonal samples. Clinical samples used in these phases were from treatment-experienced HIV-infected volunteers; 18/20 had viral loads of <50 copies/ml, and 10/15 were CXCR4-tropic on prior phenotyping. All samples were tested in triplicate, and any replicate with a geno2pheno FPR of <10% was designated X4. Performance was deemed adequate if ?2 R5 and ?1 X4 specimens were miscalled. For several clinical samples in the EQA, triplicate testing revealed marked DNA variability (FPR range, 0 to 96.7%). Therefore, a consensus-based approach was employed for each sample, i.e., a median FPR across laboratories was used to define sample tropism. Further sequencing analysis showed mixed viral populations in the clinical samples, explaining the differences in tropism predictions. All laboratories passed the EQA after achieving predefined competence thresholds in either of the phase 2 rounds. The use of clinical samples from patients resembling those who were likely to be screened in the MARCH, coupled with triplicate testing, revealed inherent DNA variability that might have been missed if single or duplicate testing and/or clonal samples alone were used. These data highlight the importance of intensive EQA of tropism laboratories before embarking on clinical studies. (This study has been registered at ClinicalTrials.gov under registration no. NCT01384682 [http://www.clinicaltrials.gov/ct2/show/study/NCT01384682?term=NCT01384682&rank=1].).

Project description:BACKGROUND:The coreceptor tropism testing should be conducted prior to commencing a regimen containing a CCR5 antagonist for treatment of HIV-1 infection. For aviremic patients on long antiretroviral therapy, proviral DNA is often used instead of viral RNA in genotypic tropism testing. However, the tropism predictions from RNA and DNA are sometimes different. We examined the cause of the discrepancies between HIV-1 tropism predictions based on viral RNA and proviral DNA. METHODS:The nucleotide sequence of the env C2V3C3 region was determined using pair samples of plasma RNA and peripheral blood mononuclear cell DNA from 50 HIV-1 subtype B-infected individuals using population-based sequencing. The samples with discrepant tropism assessments between RNA and DNA were further analyzed using deep sequencing, followed by phylogenetic analysis. The tropism was assessed using the algorithm geno2pheno with a false-positive rate cutoff of 10 %. RESULTS:In population-based sequencing, five of 50 subjects showed discrepant tropism predictions between their RNA and DNA samples: four exhibited R5 tropism in RNA and X4 tropism in DNA, while one exhibited the opposite pattern. In the deep sequencing and phylogenetic analysis, three subjects had single clusters comprising of RNA- and DNA-derived sequences that were a mixture of R5 and X4 sequences. The other two subjects had two and three distinct phylogenetic clusters of sequences, respectively, each of which was dominated by R5 or X4 sequences; sequences of the R5-dominated cluster were mostly found in RNA, while sequences of the X4-dominated cluster were mostly in DNA. CONCLUSIONS:Some of HIV-1 tropism discrepancies between viral RNA and proviral DNA seem to be caused by phylogenetically distinct clusters which resides in plasma and cells in different frequencies. Our findings suggest that the tropism testing using PBMC DNA or deep sequencing may be required when the viral load is not suppressed or rebounds in the course of a CCR5 antagonist-containing regimen.

Project description:BACKGROUND:Using HIV proviral DNA as a template may be suitable for initial detection of transmitted drug resistance mutations (TDRMs) as it is easy to handle and less expensive compared to RNA. However, existing literatures which are mainly focused on HIV-1B subtypes DNA extracted from PBMCs revealed controversial findings ranging from the detection of significantly lower or higher mutations in proviral DNA compared to historic viral RNA. Thus, to verify whether viral RNA or proviral DNA has improved sensitivity in detecting transmitted genotypic drug resistance mutations paired viral RNA and proviral DNA (which is directly extracted from stored whole blood) samples were tested from Ethiopian antiretroviral naive HIV-1C infected subjects. METHODS:In the present comparative study the frequency of TDR mutations was assessed in paired samples of viral RNA and proviral DNA (extracted directly from stored whole blood) of HIV-1C infected treatment naïve patients and interpreted using the 2009 WHO drug resistance surveillance mutation lists, Stanford University drug resistance data base and International Antiviral Society-USA mutation lists. RESULTS:High agreement in rate of TDR between the two compartments was observed using the WHO mutation lists. While mutations G190A and E138A were concurrently found in both compartments, others such as G73S on PR and A62V, M184I, M230I on RT were identified in proviral DNA only. All signature mutations seen in viral RNA were not missed in proviral DNA. CONCLUSIONS:The concordance of major genotype drug resistance mutation between RNA and proviral DNA in treatment naïve patients suggests that proviral DNA might be an alternative approaches for an initial assessment of drug resistance prior to initiation of antiretroviral therapy using the WHO mutations lists in resource-limited countries. However, the clinical importance of TDRMs observed only in proviral DNA in terms of being a risk factor for virologic failure and whether they limit future treatment options needs additional investigation using more sensitive sequencing approaches such as Next Generation Sequencing (NGS).

Dataset Information

HIV-1 Tropism Determines Different Mutation Profiles in Proviral DNA.

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HIV-1 Tropism Determines Different Mutation Profiles in Proviral DNA.

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