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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.

T215 revertant mutations such as T215C/D/E/S that evolve from the nucleoside reverse transcriptase (RT) inhibitor mutations T215Y/F have been found in about 3% of human immunodeficiency virus type 1 (HIV-1) isolates from newly diagnosed HIV-1-infected persons. We used a newly developed sequencing method—ultradeep pyrosequencing (UDPS; 454 Life Sciences)—to determine the frequency with which T215Y/F or other RT inhibitor resistance mutations could be detected as minority variants in samples from untreated persons that contain T215 revertants ("revertant" samples) compared with samples from untreated persons that lack such revertants ("control" samples). Among the 22 revertant and 29 control samples, UDPS detected a mean of 3.8 and 4.8 additional RT amino acid mutations, respectively. In 6 of 22 (27%) revertant samples and in 4 of 29 control samples (14%; P = 0.4), UDPS detected one or more RT inhibitor resistance mutations. T215Y or T215F was not detected in any of the revertant or control samples; however, 4 of 22 revertant samples had one or more T215 revertants that were detected by UDPS but not by direct PCR sequencing. The failure to detect viruses with T215Y/F in the 22 revertant samples in this study may result from the overwhelming replacement of transmitted T215Y variants by the more fit T215 revertants or from the primary transmission of a T215 revertant in a subset of persons with T215 revertants. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]