莱州湾抗生素抗性基因季节分布特征及影响因素分析

Analysis of Seasonal Distribution Patterns and Influencing Factors of Antibiotic Resistance Genes in Laizhou Bay

  • 摘要: 本研究通过宏基因组测序技术对2022年莱州湾枯水期(5月)、丰水期(8月)的水体和沉积物样品进行分析,揭示其抗生素抗性基因(Antibiotic Resistance Genes, ARGs)的季节分布特征及其影响因素。共鉴定出19 534条311种ARGs序列,涉及到抗Elfamycin类、氟喹诺酮类、氨基糖苷类等28类抗生素;将样品按照鉴出的ARGs种类数由大到小排序为:丰水期水体、枯水期水体、枯水期沉积物、丰水期沉积物。按照ARGs相对丰度由大到小排序为:丰水期沉积物、枯水期沉积物、丰水期水体、枯水期水体。ARGs的分布与pH、盐度等多种环境要素显著相关。此外,部分ARGs的分布与质粒、整合子、插入序列(Insertion Sequence, IS)等可移动遗传元件(Mobile Genetic Elements, MGEs)存在显著相关性,且ARGs与MGEs的相关性存在季节差异。对宏基因组组装得到的MAGs(Metagenome-Assembled Genomes)进一步分析表明,水体中ARGs的宿主主要隶属于假单胞菌门(Pseudomonadota)和拟杆菌门(Bacteroidota),沉积物中ARGs的宿主主要隶属于假单胞菌门和脱硫菌门(Desulfobacterota)。本研究获得的ARGs季节分布特征为该区域环境治理和生态风险评估提供了科学数据。

     

    Abstract: This study analyzed water and sediment samples collected from Laizhou Bay during the dry season (May) and wet season (August) of 2022 using metagenomic sequencing technology, to explore the seasonal distribution characteristics and influencing factors of antibiotic resistance genes (ARGs). A total of 19,534 sequences belonging to 311 ARG subtypes were identified, covering 28 classes of antibiotics including Elfamycin, fluoroquinolones and aminoglycosides. In terms of the number of detected ARG subtypes, the ranking was wet season water>dry season water>dry season sediment>wet season sediment. As for the relative abundance of ARGs, the order was wet season sediment>dry season sediment>wet season water>dry season water. The distribution of ARGs was significantly correlated with multiple environmental factors such as pH and salinity. Moreover, some ARGs showed significant correlations with mobile genetic elements (MGEs) including plasmids, integrons and insertion sequences (IS), and such correlations varied across seasons. Further analysis on metagenome-assembled genomes (MAGs) indicated that ARG hosts in water were mainly affiliated with Pseudomonadota and Bacteroidota, while those in sediments primarily belonged to Pseudomonadota and Desulfobacterota. The findings on seasonal distribution of ARGs in this study can provide scientific data for environmental management and ecological risk assessment in this region.

     

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