Molecular network analysis for detecting HIV transmission clusters: insights and implications - Liu, Yangyang; Hua, Lichun; Wu, Wenqian; Ge, You; Li, Wei; Wei, Pingmin (Frontiers in Public Health, 2025)
ObjectiveIn order to improve knowledge of HIV transmission dynamics and guide preventive and control strategies, this work uses molecular cluster analysis to objectively detect clusters of HIV genetic sequence similarity.Methods89 HIV-positive couples provided blood samples, and plasma was separated for pol region gene sequence amplification. Furthermore, analyzed HIV-1 pol fragment sequences from Nanjing patients between 2015 and 2019. HYPHY and Cytoscape were used to generate and illustrate molecular networks.ResultsIn this investigation of 89 double-positive pairs, it was discovered that the pairwise gene distance approach properly detected 82.02% of positive couples at an ideal gene distance of 0.014 substitution/loci. With an accuracy of 86.25%, the optimal parameter for the phylogenetic tree and gene distance approach was 90 + 0.045 substitution/loci. A molecular network was built for the Nanjing samples (2015–2019) using the optimum threshold of the previous technique. This network had 487 sequences with one misconnected cluster. There were 565 sequences in the network created by the latter approach that were not incorrectly connected.ConclusionFor HIV research, molecular cluster analysis provides novel insights. It helps with preventive and control methods by objectively identifying clusters with comparable genetic sequences, which enhances our knowledge of HIV transmission. Further developments will increase its importance for HIV/AIDS research and worldwide prevention.