Viral Population Estimation Using Pyrosequencing

The diversity of virus populations within single infected hosts presents a major difficulty for the natural immune response as well as for vaccine design and antiviral drug therapy. Recently developed pyrophosphate-based sequencing technologies (pyrosequencing) can be used for quantifying this diversity by ultra-deep sequencing of virus samples. We present computational methods for the analysis of such sequence data and apply these techniques to pyrosequencing data obtained from HIV populations within patients harboring drug-resistant virus strains. Our main result is the estimation of the population structure of the sample from the pyrosequencing reads. This inference is based on a statistical approach to error correction, followed by a combinatorial algorithm for constructing a minimal set of haplotypes that explain the data. Using this set of explaining haplotypes, we apply a statistical model to infer the frequencies of the haplotypes in the population via an expectation–maximization (EM) algorithm. We demonstrate that pyrosequencing reads allow for effective population reconstruction by extensive simulations and by comparison to 165 sequences obtained directly from clonal sequencing of four independent, diverse HIV populations. Thus, pyrosequencing can be used for cost-effective estimation of the structure of virus populations, promising new insights into viral evolutionary dynamics and disease control strategies.</p

Viral population estimation using pyrosequencing

The diversity of virus populations within single infected hosts presents a major difficulty for the natural immune response as well as for vaccine design and antiviral drug therapy. Recently developed pyrophosphate based sequencing technologies (pyrosequencing) can be used for quantifying this diversity by ultra-deep sequencing of virus samples. We present computational methods for the analysis of such sequence data and apply these techniques to pyrosequencing data obtained from HIV populations within patients harboring drug resistant virus strains. Our main result is the estimation of the population structure of the sample from the pyrosequencing reads. This inference is based on a statistical approach to error correction, followed by a combinatorial algorithm for constructing a minimal set of haplotypes that explain the data. Using this set of explaining haplotypes, we apply a statistical model to infer the frequencies of the haplotypes in the population via an EM algorithm. We demonstrate that pyrosequencing reads allow for effective population reconstruction by extensive simulations and by comparison to 165 sequences obtained directly from clonal sequencing of four independent, diverse HIV populations. Thus, pyrosequencing can be used for cost-effective estimation of the structure of virus populations, promising new insights into viral evolutionary dynamics and disease control strategies.Comment: 23 pages, 13 figure

Characterization of mutation spectra with ultra-deep pyrosequencing: Application to HIV-1 drug resistance

The detection of mutant spectra within a population of microorganisms is critical for the management of drug-resistant infections. We performed ultra-deep pyrosequencing to detect minor sequence variants in HIV-1 protease and reverse transcriptase (RT) genes from clinical plasma samples. We estimated empirical error rates from four HIV-1 plasmid clones and used them to develop a statistical approach to distinguish authentic minor variants from sequencing errors in eight clinical samples. Ultra-deep pyrosequencing detected an average of 58 variants per sample compared with an average of eight variants per sample detected by conventional direct-PCR dideoxynucleotide sequencing. In the clinical sample with the largest number of minor sequence variants, all 60 variants present in ≥3% of genomes and 20 of 35 variants present in <3% of genomes were confirmed by limiting dilution sequencing. With appropriate analysis, ultra-deep pyrosequencing is a promising method for characterizing genetic diversity and detecting minor yet clinically relevant variants in biological samples with complex genetic populations

Human Immunodeficiency Virus Type 1 Isolates with the Reverse Transcriptase (RT) Mutation Q145M Retain Nucleoside and Nonnucleoside RT Inhibitor Susceptibility▿

Q145M, a mutation in a conserved human immunodeficiency virus type 1 reverse transcriptase (RT) region, was reported to decrease susceptibility to multiple RT inhibitors. We report that Q145M and other Q145 mutations do not emerge with RT inhibitors nor decrease RT inhibitor susceptibility. Q145M should not, therefore, be considered an RT inhibitor resistance mutation

N88D facilitates the co-occurrence of D30N and L90M and the development of multidrug resistance in HIV type 1 protease following nelfinavir treatment failure

Nelfinavir was once one of the most commonly used protease inhibitors (PIs). To investigate the genetic mechanisms of multidrug resistance in protease isolates with the primary nelfinavir resistance mutation D30N, we analyzed patterns of protease mutations in 582 viruses with D30N from 460 persons undergoing HIV-1 genotypic resistance testing at Stanford University Hospital from 1997 to 2005. Three patterns of mutational associations were identified. First, D30N was positively associated with N88D but negatively associated with N88S. Second, D30N and L90M were negatively associated except in the presence of N88D, which facilitated the co-occurrence of D30N and L90M. Third, D30N+N88D+L90M formed a stable genetic backbone for the accumulation of additional protease inhibitor (PI) resistance mutations. In 16 patients having isolates with more than one combination of mutations at positions 30, 88, and 90, all exhibited one of the steps in the following progression: D30N--\u3eD30N+N88D--\u3eD30N+N88D+L90M--\u3eD30N+N88D+L90M+(L33F+/-I84V or M46I/L+/-I54V). Although nelfinavir is now used less frequently than other PIs, the well-delineated mutational pathway we describe is likely to influence patterns of cross-resistance in viruses from persons who experience virologic failure while receiving this PI