Ebmeyer Stefan, Kristiansson Erik, Larsson D G Joakim
Center for Antibiotic Resistance Research in Gothenburg (CARe), SE-40530 Göteborg, Sweden; Department of Infectious Diseases, Institute of Biomedicine, University of Gothenburg, SE-41346 Göteborg, Sweden.
Center for Antibiotic Resistance Research in Gothenburg (CARe), SE-40530 Göteborg, Sweden; Department of Mathematical Sciences, Chalmers University of Technology and the University of Gothenburg, SE-41296 Göteborg, Sweden.
Environ Int. 2025 Apr;198:109374. doi: 10.1016/j.envint.2025.109374. Epub 2025 Mar 15.
Understanding in which environments and under what conditions chromosomal antibiotic resistance genes (ARGs) acquire increased mobility is crucial to effectively mitigate their emergence in and dissemination among pathogens. In order to identify the conditions and environments facilitating these processes, it is valuable to know from which bacterial species mobile ARGs were mobilized initially, before their dissemination to other species. In this study, we used data generated from > 1.5 million publicly available bacterial genome assemblies to train a random forest classifier to identify the origins of mobile genes. Analysis of the models' predictions revealed the previously unknown origins of 12 mobile ARG groups, which confer resistance to 4 different classes of antibiotics. This included ARGs conferring resistance to tetracyclines, an antibiotic class for which, to the best of our knowledge, no recent origins of ARGs have previously been convincingly demonstrated. All identified origin species in this study are known opportunistic pathogens, and some are the origin of multiple mobile ARGs. An analysis of public metagenomes from different sources indicates that most of the origin species are particularly abundant in municipal wastewaters, a few were highly abundant in animal feces and three were most common in environments polluted with waste from antibiotic manufacturing. This study highlights environments where these origin species thrive and where there is a need for limiting antibiotic selection pressures.
了解染色体抗生素抗性基因（ARGs）在哪些环境和条件下获得更高的移动性，对于有效减少它们在病原体中的出现和传播至关重要。为了确定促进这些过程的条件和环境，在移动ARGs传播到其他物种之前，了解它们最初是从哪些细菌物种中被转移出来的是很有价值的。在本研究中，我们使用了超过150万个公开可用的细菌基因组组装数据来训练一个随机森林分类器，以识别移动基因的起源。对模型预测的分析揭示了12个移动ARG组的先前未知起源，这些组赋予了对4种不同类别的抗生素的抗性。这包括赋予对四环素抗性的ARGs，据我们所知，对于这类抗生素，此前尚未令人信服地证明ARGs有近期的起源。本研究中所有确定的起源物种都是已知的机会性病原体，有些是多种移动ARGs的起源。对来自不同来源的公共宏基因组的分析表明，大多数起源物种在城市污水中特别丰富，少数在动物粪便中高度丰富，还有三种在受抗生素生产废物污染的环境中最为常见。这项研究突出了这些起源物种大量繁殖的环境以及需要限制抗生素选择压力的地方。
