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ORIGINAL RESEARCH article

Front. Public Health
Sec. Infectious Diseases: Epidemiology and Prevention
Volume 13 - 2025 | doi: 10.3389/fpubh.2025.1429464
This article is part of the Research Topic Novel Interventions for the Prevention and Control of Communicable Disease View all 12 articles

Molecular Network Analysis for Detecting HIV Transmission Clusters: Insights and Implications

Provisionally accepted
Yangyang Liu Yangyang Liu 1Lichun Hua Lichun Hua 2Wenqian Wu Wenqian Wu 3You Ge You Ge 4Wei Li Wei Li 5*Pingmin Wei Pingmin Wei 4*
  • 1 School of Public Health, Southeast University, Nanjing, China
  • 2 Department of Ultrasound Diagnostic, Children's Hospital of Nanjing Medical University, Nanjing, China
  • 3 Department of Emergency, Pediatric intensive care unit, Children' Hospital of Nanjing Medical University, Nanjing, China
  • 4 Department of Epidemiology and Health Statistics, School of Public Health, Southeast University, Nanjing, Jiangsu Province, China
  • 5 Department of clinical research center, Children’s hospital of Nanjing medical university, Nanjing, China

The final, formatted version of the article will be published soon.

    Objective In 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. Methods 89 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. Results In this investigation of 89 doublepositive 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. Conclusion For 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.

    Keywords: HIV-1, phylogeny, Molecular network, Molecular Epidemiology, Transmit

    Received: 08 May 2024; Accepted: 13 Jan 2025.

    Copyright: © 2025 Liu, Hua, Wu, Ge, Li and Wei. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence:
    Wei Li, Department of clinical research center, Children’s hospital of Nanjing medical university, Nanjing, China
    Pingmin Wei, Department of Epidemiology and Health Statistics, School of Public Health, Southeast University, Nanjing, Jiangsu Province, China

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