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

  1. Chunlin Wang1,3,
  2. Yumi Mitsuya1,3,
  3. Baback Gharizadeh2,
  4. Mostafa Ronaghi2, and
  5. Robert W. Shafer1,4
  1. 1 Division of Infectious Diseases, Department of Medicine, Stanford University, Stanford, California 94305, USA;
  2. 2 Stanford Genome Technology Center, Stanford University, Stanford, California 94305, USA
  1. 3 These authors contributed equally to this work.

Abstract

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.

Footnotes

  • 4 Corresponding author.

    4 E-mail rshafer{at}stanford.edu; fax (650) 725-2088.

  • [Supplemental material is available online at www.genome.org. The raw data from this study are available online at http://dbpartners.stanford.edu/454/pub.]

  • Article published online before print. Article and publication date are online at http://www.genome.org/cgi/doi/10.1101/gr.6468307

    • Received March 6, 2007.
    • Accepted April 27, 2007.
  • Freely available online through the Genome Research Open Access option.

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