Automated sequence analysis and editing software for HIV drug resistance testing.

Area of Science:

• Virology
• Bioinformatics
• Public Health

Background:

• Emergence of HIV drug resistance is a major challenge in resource-limited settings.
• Effective monitoring of treatment efficacy and HIV drug resistance is critical.
• Lack of low-cost, context-appropriate technologies hinders resistance testing in these areas.

Purpose of the Study:

• To develop automated sequence analysis and editing software for high-throughput sequencing.
• To support HIV drug resistance monitoring in resource-limited settings through the ART-A consortium.

Main Methods:

• The ART-A Software was designed for automatic processing and editing of ABI chromatograms or FASTA files from HIV-1 isolates.
• The software performs basecalling, quality value assignment, sequence alignment, consensus inference, HIV typing, and translation to amino acids.
• It identifies and reports insertions/deletions, stop codons, ambiguities, and mixed calls, with results exportable to Excel.

Main Results:

• Automated analysis demonstrated high accuracy, with discrepancies of 0.69% at the nucleotide level and 0.57% at the amino acid level compared to manual analysis.
• Analysis of 1624 PR-RT sequences across three labs showed minimal discordances at major resistance mutations (4.83% for PR, 6.18% for RT).
• The software effectively highlights positions requiring attention for resistance mutations.

Conclusions:

• The ART-A Software is a valuable, time-saving tool for pre-analyzing HIV and viral quasispecies sequences.
• It enhances efficiency in high-throughput laboratories, particularly in resource-limited settings.
• The software aids in identifying critical positions for monitoring drug resistance and treatment efficacy.