Divergent transmission dynamics and drug resistance evolution of HIV-1 CRF01_AE and CRF07_BC in Tianjin, China (2013-2022)

Abstract

Background: Tianjin, a major hub in northern China, faces rising HIV-1 infections dominated by CRF01_AE and CRF07_BC. This study elucidated their divergent transmission patterns and drug resistance dynamics to guide targeted interventions.

Methods: This study included samples identified as CRF01_AE and CRF07_BC subtypes through various methods between 2013 and 2022. BEAST software was used to examine the spatiotemporal transmission patterns of these subtypes in Tianjin. By integrating HIV-TRACE, we constructed high-risk transmission clusters and identified drug resistance mutations (DRMs) based on the Stanford HIV Drug Resistance Database. Finally, the birth-death skyline serial (BDSKY) model was employed to dynamically assess the effective reproductive number (Re) of both subtypes to predict future transmission dynamics.

Results: CRF01_AE might be introduced in 1988 from Henan and Zhejiang, forming multiple small clusters (< 10 nodes) and spreading through both heterosexual and men who have sex with men (MSM) in Tianjin, while CRF07_BC from Chongqing and Guizhou, et al. in 2004, experiencing explosive local transmission and forming a large cluster of 170 nodes primarily among MSM under 30 years old (P < 0.05). Phylogenetic analysis indicated that CRF01_AE has a significantly higher evolutionary rate (2.08 × 10⁻³ vs. 1.48 × 10⁻³ substitutions/site/year, P < 0.05), while CRF07_BC demonstrates a greater cluster formation capacity (56.6% vs. 37.1%, P < 0.05). CRF01_AE showed a higher mutation occurrence rate (5.18% vs. 2.49%, P < 0.05), particularly with non-nucleoside reverse transcriptase inhibitor (NNRTI) associated mutations (e.g., K101E). Although CRF07_BC had a lower resistance burden, the emergence of K103E mutations suggests a need for vigilance regarding potential decreases in sensitivity to newer NNRTIs. BDSKY modeling revealed that the Re for CRF01_AE dropped below 1 after 2016, whereas CRF07_BC's Re remains above 1, indicating that the risk of transmission still exists.

Conclusion: Subtype-specific strategies are critical: intensified resistance monitoring for CRF01_AE and cluster-focused interventions for CRF07_BC, particularly among young MSM.

Keywords: DRMs; HIV-1; Phylodynamic analysis; Transmission dynamics.

Fig. 1

a, b MCC trees and map of geographic location transition based on CRF01_AE and CRF07_BC sequences in this study. Purple areas indicate Tianjin strains in this study. c, d Red arrows indicate decisive rates with BF ≥ 1000; orange arrows indicate very strongly supported rate with 100 ≤ BF < 1000; blue arrows indicate strongly supported rates with10 ≤ BF < 100

Fig. 2

Annual clustering proportion of CRF01_AE and CRF07_BC

Fig. 3

The annual variation trend of subtypes and prevalence of SDRMs

Fig. 4

Frequency (case) and characteristic of SDRMs. The color depth of the orange blocks represents different levels of drug resistance. The lightest block indicates “susceptible,” and the levels of resistance increase as follows: Potential Low-level Resistance, Low-Level Resistance, Intermediate Resistance, and High-Level Resistance

Fig. 5

Median of the Re of different subtypes and their HPD intervals. The red line represents the reference value 1