Detection of Inferred CCR5- and CXCR4-Using HIV-1 Variants and Evolutionary Intermediates Using Ultra-Deep Pyrosequencing

Abstract

The emergence of CXCR4-using human immunodeficiency virus type 1 (HIV-1) variants is associated with accelerated disease progression. CXCR4-using variants are believed to evolve from CCR5-using variants, but due to the extremely low frequency at which transitional intermediate variants are often present, the kinetics and mutational pathways involved in this process have been difficult to study and are therefore poorly understood. Here, we used ultra-deep sequencing of the V3 loop of the viral envelope in combination with the V3-based coreceptor prediction tools PSSMNSI/SI and geno2pheno[coreceptor] to detect HIV-1 variants during the transition from CCR5- to CXCR4-usage. We analyzed PBMC and serum samples obtained from eight HIV-1-infected individuals at three-month intervals up to one year prior to the first phenotypic detection of CXCR4-using variants in the MT-2 assay. Between 3,482 and 10,521 reads were generated from each sample. In all individuals, V3 sequences of predicted CXCR4-using HIV-1 were detected at least three months prior to phenotypic detection of CXCR4-using variants in the MT-2 assay. Subsequent analysis of the genetic relationships of these V3 sequences using minimum spanning trees revealed that the transition in coreceptor usage followed a stepwise mutational pathway involving sequential intermediate variants, which were generally present at relatively low frequencies compared to the major predicted CCR5- and CXCR4-using variants. In addition, we observed differences between individuals with respect to the number of predicted CXCR4-using variants, the diversity among major predicted CCR5-using variants, and the presence or absence of intermediate variants with discordant phenotype predictions. These results provide the first detailed description of the mutational pathways in V3 during the transition from CCR5- to CXCR4-usage in natural HIV-1 infection.

Deep Sequencing of the HIV-1 env Gene Reveals Discrete X4 Lineages and Linkage Disequilibrium between X4 and R5 Viruses in the V1/V2 and V3 Variable Regions

“…Several previously reported studies used deep sequencing to predict HIV-1 coreceptor usage by sequencing of the HIV-1 env V3 region (26,(45)(46)(47)(48). Most of those studies used 454 sequencing, which was limited by homopolymer errors and relative low throughput compared to the Illumina or IonTorrent platform (25).…”

“…EPD PCR is time-consuming and labor-intensive, making it challenging to analyze more than a few dozen viral genomes per sample (20)(21)(22), which limits the depth of sampling of viral genomes when assessing the complexity of the viral population. Recently, viral population studies have started to incorporate deep-sequencing or next-generation sequencing (NGS) technologies that have the capacity to greatly extend the depth of sampling (12,(23)(24)(25)(26)(27)(28). However, conventional approaches using NGS in HIV-1 population studies have serious limitations in representing an accurate sampling of the original viral population.…”

Sensitive Deep-Sequencing-Based HIV-1 Genotyping Assay To Simultaneously Determine Susceptibility to Protease, Reverse Transcriptase, Integrase, and Maturation Inhibitors, as Well as HIV-1 Coreceptor Tropism

“…In the case of deep sequencing V3 sequences, reads spanning amino acid positions 1 to 35 in the V3 region (HXB2 7110 to 7217) were extracted and truncated for HIV-1 coreceptor tropism determination using Geno2Pheno (27) with an FPR of 3.5%, based on optimized cutoffs for determining HIV-1 coreceptor usage, as previously described (36,63,80). Deep sequencing V3 sequences usually spanned 105 nucleotides (35 amino acids), with some minor discrepancies associated with natural HIV-1 variation (81,82), which led to V3 sequences with an open reading frame of 96, 99, 102, 108, or 111 nucleotides, all starting and ending with a cysteine codon, i.e., TG(T/ C). V3 reads with stop codons (TGA, TAA, or TAG) and/or where the nucleotide length was not a multiple of 3 (e.g., 101, 103, 104, and 106), mostly associated with naturally or methodology (PCR or sequencing)-induced insertions and/or deletions, were not included in the analysis.…”

Ultradeep Sequencing Analysis of Population Dynamics of Virus Escape Mutants in RNAi-Mediated Resistant Plants

“…On the other hand, next-generation sequencing (NGS) techniques can generate massive amounts of genetic data, which can be used to detect variants at much lower frequencies (Wang et al 2007;Eriksson et al 2008;Solmone et al 2009;Cordey et al 2010;Eckerle et al 2010;Murcia et al 2010;Zagordi et al 2010;Willerth et al 2010;Bunnik et al 2011;Guo et al 2011;Wrigth et al 2011). In this study, we have generated tens of millions of short reads with Illumina sequencing to obtain an unprecedented ultradeep coverage of amiR targets in the TuMV genome, thus characterizing in great detail the genetic composition of TuMV lineages evolving in WT and 10-4 plants at different time points during the experimental evolution process and right after the first successful infection of 12-4-resistant plants.…”