Minimizing Next-Generation Sequencing Errors for HIV Drug Resistance Testing

Abstract

Next-generation sequencing prototypes for the routine diagnosis of resistance to antiretrovirals approved for the treatment of HIV infection are now being used in many clinical diagnostic laboratories. As some of the next-generation sequencing platforms may be a source of errors, it is necessary to improve the currently available protocols and implement bioinformatic tools that may help to correctly identify the presence of resistance mutations with clinical impact. Several studies have addressed these issues in recent years. Some of them are mainly focused on improving protocols for decreasing the magnitude of errors during the polymerase change reaction. Other studies propose specific bioinformatic tools, able to reach both a 93-98% reduction of indels (insertions/deletions) and a sensitivity and specificity close to 100% in single nucleotide polymorphism variant calling. The implementation of new protocols and bioinformatic tools improving the accuracy of next-generation sequencing results must be considered for a correct analysis of HIV resistance mutations for making clinical decisions. This review summarizes the most relevant data available for the optimization of next-generation sequencing applied to HIV resistance testing.