Objectives: Low-capital-layout sequencing options from Oxford Nanopore Technologies (ONT) could assist in expanding HIV drug resistance testing to resource-limited settings. HIV drug resistance mutations often occur as mixtures, but current ONT pipelines provide a consensus sequence only. Moreover, there is no integrated pipeline that provides a drug resistance report from an ONT sequence file without intervention from skilled bioinformaticists. We therefore investigated Nano-RECall, which provides seamless drug resistance interpretation while requiring low-read coverage ONT sequence data from affordable Flongle or MinION flow cells and which provides mutation mixtures similar to Sanger Sequencing. Methods: We compared Sanger sequencing to ONT sequencing of the same HIV-1 subtype C polymerase chain reaction (PCR) amplicons, respectively using RECall and the novel Nano-RECall bioinformatics pipelines. Amplicons were from separate assays: (a) Applied Biosystems HIV-1 Genotyping Kit (ThermoFisher) spanning protease (PR) to reverse transcriptase (RT) (PR-RT) (n = 46) and (b) homebrew integrase (IN) (n = 21). The agreement between Sanger sequences and ONT sequences was assessed at nucleotide level, and at codon level for Stanford HIV drug resistance database mutations at an optimal ONT read depth of 400 reads only. Results: The average sequence similarity between ONT and Sanger sequences was 99.3% (95% CI: 99.1%-99.4%) for PR-RT and 99.6% (95% CI: 99.4%-99.7%) for INT. Drug resistance mutations did not differ for 21 IN specimens; 8 mutations were detected by both ONT-and Sanger sequencing. For the 46 PR and RT specimens, 245 mutations were detected by either ONT or Sanger, of these 238 (97.1%) were detected by both. Conclusions: The Nano-RECall pipeline, freely available as a downloadable application on a Windows computer, provides Sanger-equivalent HIV drug resistance interpretation. This novel pipeline combined with a simple workflow and multiplexing samples on ONT flow-cells would contribute to making HIV drug resistance sequencing feasible for resource-limited settings. K E Y W O R D S bioinformatics pipeline, codon-aware alignment, HIV drug resistance sequencing, homopolymer error, Oxford Nanopore Technology, sanger sequencing P. Richard Harrigan and Gert Uves van Zyl contributed equally to this work.
Introduction: Oxford Nanopore Technologies (ONT) offer sequencing with low-capital-layout sequencing options, which could assist in expanding HIV drug resistance testing to resource limited settings. However, sequence analysis remains time time-consuming and reliant on skilled personnel. Moreover, current ONT bioinformatic pipelines provide a single consensus sequence that is not equivalent to Sanger sequencing, as drug resistance is often detected in mixed populations. We have therefore investigated an integrated bioinformatic pipeline, Nano-RECall, for seamless drug resistance of low read coverage ONT sequence data from affordable Flongle or MinION flow cells. Methods: We compared Sanger sequencing to ONT sequencing of the same HIV-1 subtype C polymerase chain reaction (PCR) amplicons, respectively using RECall and the novel Nano-RECall bioinformatics pipelines. Amplicons were from separate assays a) Applied Biosystems HIV-1 Genotyping Kit (ThermoFisher) spanning protease (PR) to reverse transcriptase (RT) (PR-RT) (n=46) and b) homebrew integrase (IN) (n=21). We investigated optimal read-depth by assessing the coefficient of variation (CV) of nucleotide proportions for various read-depths; and between replicates of 400 reads. The agreement between Sanger sequences and ONT sequences were assessed at nucleotide level, and at codon level for Stanford HIV drug resistance database mutations. Results: The coefficient of variation of ONT minority variants plateaued after a read depth of 400-fold implying limited benefit of additional depth and replicates of 400 reads showed a CV of ~6 % for a representative position. The average sequence similarity between ONT and Sanger sequences was 99.3% (95% CI: 99.1-99.4%) for PR-RT and 99.6% (95% CI: 99.4-99.7%) for INT. Drug resistance mutations did not differ for 21 IN sequences; 16 mutations were detected by both ONT- and Sanger sequencing. For the 46 PR and RT sequences, 245 mutations were detected by either ONT or Sanger, of these 238 (97.1%) were detected by both. Conclusions: The Nano-RECall pipeline, freely available as a downloadable application on a Windows computer, provides Sanger-equivalent HIV drug resistance interpretation. This novel pipeline combined with a simple workflow and multiplexing samples on ONT flow-cells would contribute to making HIV drug resistance sequencing feasible for resource limited settings.
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