In Silico analysis of Dolutegravir resistance mutations within the HIV-1 pol gene among isolates from Sub-Saharan Africa

Abstract

Dolutegravir (DTG) has become the cornerstone of first-line antiretroviral therapy across Sub-Saharan Africa, yet large-scale genotypic surveillance of DTG resistance in the region remains limited. This study used an in silico approach to determine the prevalence and molecular epidemiology of DTG-associated integrase resistance mutations among HIV-1 isolates from Sub-Saharan Africa. A total of 303 HIV-1 pol gene sequences encoding the integrase region were retrieved from NCBI GenBank, drawn from six countries (Uganda, Zambia, Malawi, Zimbabwe, Côte d'Ivoire, and Burkina Faso). Resistance mutations were identified using the Stanford HIVDB Sierra algorithm, subtypes were assigned using the REGA Subtyping Tool, genetic associations were tested using PLINK logistic regression and principal component analysis, and phylogenetic relationships were reconstructed using maximum likelihood (IQ-TREE2). DTG-associated resistance mutations were detected in 24.4% of sequences, with E138K (15.8%), G118R (13.5%), and R263K (6.3%) most prevalent, and the E138K+G118R dual pathway dominant. Resistance prevalence varied significantly by country (χ²=14.02, p=0.016) but not by subtype (χ²=6.86, p=0.144). PLINK identified nine integrase positions significantly associated with resistance, all within the catalytic core domain. Phylogenetic analysis demonstrated that resistant sequences were dispersed across all lineages, indicating convergent, independent acquisition of resistance rather than transmission of a single resistant strain. These findings reinforce the need for sustained INSTI resistance surveillance in Sub-Saharan Africa and demonstrate the value of in silico methods, integrating population-genomic and phylogenetic approaches, for monitoring HIV drug resistance in resource-limited settings.