The Evolutionary Analysis of Emerging Low Frequency HIV-1 CXCR4 Using Variants through Time—An Ultra-Deep Approach

Abstract

Large-scale parallel pyrosequencing produces unprecedented quantities of sequence data. However, when generated from viral populations current mapping software is inadequate for dealing with the high levels of variation present, resulting in the potential for biased data loss. In order to apply the 454 Life Sciences' pyrosequencing system to the study of viral populations, we have developed software for the processing of highly variable sequence data. Here we demonstrate our software by analyzing two temporally sampled HIV-1 intra-patient datasets from a clinical study of maraviroc. This drug binds the CCR5 coreceptor, thus preventing HIV-1 infection of the cell. The objective is to determine viral tropism (CCR5 versus CXCR4 usage) and track the evolution of minority CXCR4-using variants that may limit the response to a maraviroc-containing treatment regimen. Five time points (two prior to treatment) were available from each patient. We first quantify the effects of divergence on initial read k-mer mapping and demonstrate the importance of utilizing population-specific template sequences in relation to the analysis of next-generation sequence data. Then, in conjunction with coreceptor prediction algorithms that infer HIV tropism, our software was used to quantify the viral population structure pre- and post-treatment. In both cases, low frequency CXCR4-using variants (2.5–15%) were detected prior to treatment. Following phylogenetic inference, these variants were observed to exist as distinct lineages that were maintained through time. Our analysis, thus confirms the role of pre-existing CXCR4-using virus in the emergence of maraviroc-insensitive HIV. The software will have utility for the study of intra-host viral diversity and evolution of other fast evolving viruses, and is available from http://www.bioinf.manchester.ac.uk/segminator/.

Primer ID Validates Template Sampling Depth and Greatly Reduces the Error Rate of Next-Generation Sequencing of HIV-1 Genomic RNA Populations

“…The Primer ID approach provides information about initial template sampling, providing the denominator in estimating relative abundance. A standard approach to sequencing viral RNA is to randomly fragment larger PCR amplicons before sequencing and align the sequencing reads with a template sequence (28). With this approach it is difficult to do linkage analysis (due to PCR recombination and the fragmentation) and estimate allelic frequencies (due to PCR amplification skewing, PCR resampling, and PCR and sequencing errors).…”

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

“…Thus, PCR errors, including nucleotide misincorporation by the polymerase, PCR recombination, and PCR resampling, may alter diversity as well as skew the allelic frequen-cies (29,30). Second, in some approaches, the amplicons are first sheared before sequencing, and the sequencing reads are aligned with a reference sequence (41). With this approach, it is difficult to perform linkage analysis and estimate allelic frequencies.…”

Sensitive Cell-Based Assay for Determination of Human Immunodeficiency Virus Type 1 Coreceptor Tropism

“…Following the sorting of reads by barcode into sample-derived data sets, the reads were mapped and aligned to the corresponding reference sequence (i.e., global V3 sequence for each sample) using Segminator II (37). Within this software, reads spanning the V3 loop were extracted, truncated, translated, and assembled for genotyping (24,38).…”