Improved HIV-1 Subtyping Accuracy Using near Full-Length Sequencing: A Comparison of Common Tools.

Area of Science:

• Virology
• Molecular Biology
• Bioinformatics

Background:

• Human Immunodeficiency Virus type 1 (HIV-1) exhibits extensive genetic diversity, including multiple subtypes and circulating recombinant forms (CRFs).
• Accurate HIV-1 subtyping is essential for effective treatment, vaccine development, and epidemiological surveillance.
• Partial genomic sequencing presents challenges for precise subtype classification due to HIV-1's genetic complexity.

Purpose of the Study:

• To evaluate the performance of four automated HIV-1 subtyping tools against molecular phylogenetic analysis (Mphy).
• To compare subtyping accuracy using different sequence lengths: protease-reverse transcriptase (PR-RT), pol, and near full-length (NFL) genomes.
• To assess the impact of sequencing depth on the detection of circulating recombinant forms (CRFs).

Main Methods:

• Generated sequences from 100 plasma samples using Next-Generation Sequencing (NGS) for PR-RT, pol, and NFL regions.
• Compared automated subtyping tool outputs (Stanford HIVdb, COMET, REGA, Geno2pheno) with Mphy (gold standard).
• Assessed concordance, sensitivity, and specificity across different sequence lengths and subtypes.

Main Results:

• NFL sequencing identified a higher proportion of CRFs (51.6%) than PR-RT and pol (44.1%), reclassifying 13 samples.
• Automated tools showed good concordance with Mphy for PR-RT and pol, especially for pure subtypes.
• Concordance decreased for NFL sequences, particularly for non-B subtypes and CRFs, with variable sensitivity but high specificity.

Conclusions:

• Whole genome or NFL sequencing significantly enhances the detection of complex HIV-1 CRFs.
• The accuracy of automated HIV-1 subtyping tools is influenced by sequence length and the completeness of reference databases.
• Optimizing sequencing strategies and database updates are critical for improving HIV-1 subtyping accuracy.