Related Experiment Video
Updated: Jun 27, 2026
An Affordable HIV-1 Drug Resistance Monitoring Method for Resource Limited Settings
Published on: March 30, 2014
Acquired HIV-1 Drug Resistance and Molecular Transmission Networks in Zhongwei, Ningxia, China
Youping Duan1, Subinuer Mutalifu1, Ziyang Luo1
1College of Public Health, Ningxia Medical University, Yinchuan 750004, China.
Objective:
This retrospective cross-sectional study aimed to characterize HIV-1 genotypes, assess drug resistance, and analyze molecular transmission networks in Zhongwei City to inform prevention strategies.
Methods:
Plasma samples were collected from antiretroviral therapy (ART)-treated patients (2007-2024) with viral load ≥ 200 copies/mL. HIV-1 pol was amplified by nested PCR; successful sequences were genotyped by maximum likelihood (ML) (IQ-TREE, TVM+F+I+G4, 1000 bootstrap). Drug resistance (DR) was interpreted using Stanford HIV Drug Resistance Database (HIVDB) v9.0; detected mutations represent acquired drug resistance (ADR). Pairwise genetic distances (GD) (TN93 model) were calculated; transmission networks were constructed in Cytoscape 3.10.3.
Results:
75 sequences were obtained. Males (84.00%), and heterosexual transmission (64.00%) predominated. CRF07_BC (46.67%) and CRF01_AE (38.67%) were the major subtypes; the overall ADR rate was 40.00%, mainly NNRTIs-associated (30.67% of all participants, including 16.00% single-class NNRTIs and 14.67% dual-class NRTIs-NNRTIs). Network inclusion rate was 40.00% of the 75 sequences; CRF07_BC showed higher betweenness centrality (p = 0.028), while CRF01_AE and CRF85_BC showed higher closeness centrality (p < 0.001). Occupation significantly affected network enrollment (p ≤ 0.05).
Conclusion:
HIV-1 subtypes are diverse with high ADR. CRF07_BC may act as a transmission bridge, whereas CRF01_AE and CRF85_BC exhibit faster potential spread. Baseline DR testing and network-guided interventions are recommended.
