Sensitivity of seven HIV subtyping tools differs among subtypes/recombinants in the Spanish cohort of naïve HIV-infected patients (CoRIS).

BACKGROUND: HIV-1 group M is classified into 9 subtypes and recombinants (CRFs/URFs). Variants other than subtype B (non-B) cause 90% of infections worldwide. HIV is often subtyped using automated tools instead of the gold-standard phylogenetic analysis. We evaluated the reliability of subtyping tools vs. phylogeny in a panel of HIV-1 pol sequences from the cohort of naïve patients of the HIV/AIDS Spanish Research Network (CoRIS).
METHODS: HIV-1 subtyping was performed using seven automated subtyping tools (Stanford, Geno2pheno, Rega, NCBI, EuResist, STAR, TherapyEdge) in HIV-1 pol sequences from 670 CoRIS patients previously subtyped by phylogeny (587 subtype B/83 non-B). Sensitivity with respect to phylogeny was assessed.
RESULTS: Most tools correctly classified subtype B, although up to 15% of non-B sequences were wrongly identified as B depending on the tool. For subtype B and CRF02_AG identification, Stanford/NCBI and Geno2pheno/Rega presented the highest/lowest sensitivities, respectively. EuResist and Geno2pheno correctly classified all 13 non-B "pure"subtypes at pol. The efficacy of all subtyping tools dropped clearly when identifying recombinants different from CRF02_AG. Only NCBI05, Rega and STAR identified URF, but with very low sensitivities. NCBI classified the highest number of subtypes B as non-B, and overestimated recombinants, especially when including references of 2009.
CONCLUSIONS: Automated tools are useful for subtype B identification, although they present serious limitations in classifying variants uncommon in developed regions, especially recombinants. Their sensitivity depends on the prevalence of non-B variants in the population, and decreases drastically when the frequency of recombinants increases. Furthermore, HIV-1 variant distribution differs according to the tool used.