A Follow-Up of the Multicenter Collaborative Study on HIV-1 Drug Resistance and Tropism Testing Using 454 Ultra Deep Pyrosequencing

Background: Ultra deep sequencing is of increasing use not only in research but also in diagnostics. For implementation of ultra deep sequencing assays in clinical laboratories for routine diagnostics, intra- and inter-laboratory testing are of the utmost importance. Methods: A multicenter study was conducted to validate an updated assay design for 454 Life Sciences’ GS FLX Titanium system targeting protease/reverse transcriptase (RTP) and env (V3) regions to identify HIV-1 drug-resistance mutations and determine co-receptor use with high sensitivity. The study included 30 HIV-1 subtype B and 6 subtype non-B samples with viral titers (VT) of 3,940–447,400 copies/mL, two dilution series (52,129–1,340 and 25,130–734 copies/mL), and triplicate samples. Amplicons spanning PR codons 10–99, RT codons 1–251 and the entire V3 region were generated using barcoded primers. Analysis was performed using the GS Amplicon Variant Analyzer and geno2pheno for tropism. For comparison, population sequencing was performed using the ViroSeq HIV-1 genotyping system. Results: The median sequencing depth across the 11 sites was 1,829 reads per position for RTP (IQR 592–3,488) and 2,410 for V3 (IQR 786–3,695). 10 preselected drug resistant variants were measured across sites and showed high inter-laboratory correlation across all sites with data (P20% were missed, variants 2–10% were detected at most sites (even at low VT), and variants 1–2% were detected by some sites. All mutations detected by population sequencing were also detected by UDS. Conclusions: This assay design results in an accurate and reproducible approach to analyze HIV-1 mutant spectra, even at variant frequencies well below those routinely detectable by population sequencing

A Follow-Up of the Multicenter Collaborative Study on HIV-1 Drug Resistance and Tropism Testing Using 454 Ultra Deep Pyrosequencing

Ultra deep sequencing is of increasing use not only in research but also in diagnostics. For implementation of ultra deep sequencing assays in clinical laboratories for routine diagnostics, intra- and inter-laboratory testing are of the utmost importance. 5A multicenter study was conducted to validate an updated assay design for 454 Life Sciences' GS FLX Titanium system targeting protease/reverse transcriptase (RTP) and env (V3) regions to identify HIV-1 drug-resistance mutations and determine co-receptor use with high sensitivity. The study included 30 HIV-1 subtype B and 6 subtype non-B samples with viral titers (VT) of 3,940-447,400 copies/mL, two dilution series (52,129-1,340 and 25,130-734 copies/mL), and triplicate samples. Amplicons spanning PR codons 10-99, RT codons 1-251 and the entire V3 region were generated using barcoded primers. Analysis was performed using the GS Amplicon Variant Analyzer and geno2pheno for tropism. For comparison, population sequencing was performed using the ViroSeq HIV-1 genotyping system. The median sequencing depth across the 11 sites was 1,829 reads per position for RTP (IQR 592-3,488) and 2,410 for V3 (IQR 786-3,695). 10 preselected drug resistant variants were measured across sites and showed high inter-laboratory correlation across all sites with data (P20% were missed, variants 2-10% were detected at most sites (even at low VT), and variants 1-2% were detected by some sites. All mutations detected by population sequencing were also detected by UDS. This assay design results in an accurate and reproducible approach to analyze HIV-1 mutant spectra, even at variant frequencies well below those routinely detectable by population sequencing

Minimum information for reporting next generation sequence genotyping (MIRING): Guidelines for reporting HLA and KIR genotyping via next generation sequencing

AbstractThe development of next-generation sequencing (NGS) technologies for HLA and KIR genotyping is rapidly advancing knowledge of genetic variation of these highly polymorphic loci. NGS genotyping is poised to replace older methods for clinical use, but standard methods for reporting and exchanging these new, high quality genotype data are needed. The Immunogenomic NGS Consortium, a broad collaboration of histocompatibility and immunogenetics clinicians, researchers, instrument manufacturers and software developers, has developed the Minimum Information for Reporting Immunogenomic NGS Genotyping (MIRING) reporting guidelines. MIRING is a checklist that specifies the content of NGS genotyping results as well as a set of messaging guidelines for reporting the results. A MIRING message includes five categories of structured information – message annotation, reference context, full genotype, consensus sequence and novel polymorphism – and references to three categories of accessory information – NGS platform documentation, read processing documentation and primary data. These eight categories of information ensure the long-term portability and broad application of this NGS data for all current histocompatibility and immunogenetics use cases. In addition, MIRING can be extended to allow the reporting of genotype data generated using pre-NGS technologies. Because genotyping results reported using MIRING are easily updated in accordance with reference and nomenclature databases, MIRING represents a bold departure from previous methods of reporting HLA and KIR genotyping results, which have provided static and less-portable data. More information about MIRING can be found online at miring.immunogenomics.org

Drug resistance mutation detection in limiting dilution series.

<p>Two HIV-1 subtype B samples were used for the dilution series (A, samples 40–44; B, samples 45–49). The four groups shown in the histogram are based on the median frequency of each drug resistance mutation in its respective <i>undiluted</i> sample: >20% (white bars), 10–20% (bright grey bars), 2–10% (dark grey bars), and 1–2% (black bars). The means and standard deviations are given of the percentage of sites reporting drug-resistance mutations in these categories. The number of mutations in each category is represented by n.</p

Triplicate sample analysis.

<p>A set of three samples was measured in triplicate at each of the 11 sites. Variant percentages measured in the triplicate samples are shown for each mutation.</p