Development and evaluation of an oligonucleotide ligation assay for detection of drug resistance-associated mutations in the human immunodeficiency virus type 2 pol gene.
Jallow S., Kaye S., Schutten M., Brandin E., Albert J., McConkey SJ., Corrah T., Whittle H., Vanham G., Rowland-Jones S., Janssens W.
Human immunodeficiency virus type 2 (HIV-2) is naturally resistant to several antiretroviral drugs, including all of the non-nucleoside reverse transcriptase inhibitors and the entry inhibitor T-20, and may have reduced susceptibility to some protease inhibitors. These resistance properties make treatment of HIV-2 patients difficult, with very limited treatment options. Therefore, early detection of resistance mutations is important for understanding treatment failures and guiding subsequent therapy decisions. With the Global Fund Initiative, a substantial number of HIV-2 patients in West Africa will receive antiretroviral therapy. Therefore, development of cheaper and more sustainable resistance assays, such as the oligonucleotide ligation assay (OLA), is a priority. In this study, we designed oligonucleotide probes to detect the Q151M mutation, associated with phenotypic resistance to zidovudine, didanosine, zalcitabine, and stavudine, and the M184V mutation, associated with phenotypic resistance to lamivudine and emtricitabine, in HIV-2. The assay was successfully developed and evaluated with 122 samples from The Gambia, Guinea Bissau, The Netherlands, and Sweden. The overall sensitivity of the assay was 98.8%, with 99.2% for Q151M and 98.4% for M184V. OLA results were compared with sequencing to give high concordances of 98.4% (Q151M) and 97.5% (M184V). OLA demonstrated a higher sensitivity for detection of minor variants as a mixture of wild-type and mutant viruses in cases when sequencing detected only the major population. In conclusion, we have developed a simple, easy-to-use, and economical assay for genotyping of drug resistance in HIV-2 that is more sustainable for use in resource-poor settings than is consensus sequencing.