@article{Yao2026, 
author = {Chengcheng Yao and Liusheng Lei and Wenyan Wang and Lan Jiang and Wenshan Yang and Yaqi Sheng and Zishu Liu and Xun Qian},
title = {Global intI1 abundance quantifies livestock antimicrobial-resistance risk},
year = {2026},
journal = {Environmental Science and Ecotechnology},
volume = {33},
keywords = {Class 1 integrons, Antimicrobial resistance, Genetic indicator, Livestock farming, One health},
url = {https://www.sciopen.com/article/10.1016/j.ese.2026.100759},
doi = {10.1016/j.ese.2026.100759},
abstract = {Livestock farming environments are major reservoirs of antimicrobial resistance (AMR), yet scalable genetic indicators that quantitatively capture AMR risk remain limited. The class 1 integrase gene intI1 is a hallmark of class 1 integrons (CL1s), which couple gene capture with horizontal transfer capacity and have emerged as leading candidates. However, their suitability as a direct proxy for livestock-associated AMR risk has not been rigorously tested at scale. Here we show that the abundance of intI1 functions as a robust quantitative indicator of livestock-associated AMR risk. Using a custom Class 1 Integrase Database expanded by 63.5% and integrating 4017 livestock metagenomes, 9625 livestock-derived isolate genomes, and approximately 1.2 million human clinical isolate genomes, we demonstrate that intI1 abundance tracks host- and geography-dependent risk patterns, that livestock CL1s carry compact, conserved resistance-cassette arrays matching clinical spectra, and that nearly all are plasmid-borne, with their efficient dissemination facilitated by Tn402, ISCR, and IS110 family elements. A random-forest model trained on these data predicts global intI1 abundance and associated risk with high accuracy (R2 = 0.93), revealing persistent hotspots across Asia, sub-Saharan Africa, and South America over two decades. These findings establish intI1 as a practical, single-platform proxy that can be incorporated into One Health surveillance and early-warning systems.}
}