空气传播的微生物,正在出现的全球健康威胁,吸引了广泛的研究。然而,很少有人关注空气中病原体的季节性分布,特别是它们与抗生素抗性基因(ARGs)的关联。为此,连续采集南昌4个季节每日2周的PM2.5样本,并基于高通量测序筛选人-人病原体。结果表明,南昌市PM2.5中存在20个病原类群,冬季病原体相对丰度最高(5.84%),其次是夏季(3.51%),秋季(2.66%),和春季(1.80%)。尽管四个季节共有一半以上的病原分类群,相似性分析表明,致病群落是按季节形成的(r=0.16,p<0.01)。共现网络分析揭示了每个季节病原体之间的显着相互作用。此外,一些优势病原体,如志贺菌假单胞菌,脆弱拟杆菌,大肠埃希菌-志贺菌为中心病原菌。此外,PICRUSt2预测PM2.5中有35个高危ARG亚型,病原体与这些ARGs呈强烈正相关。甚至一些病原体,比如志贺菌,脆弱拟杆菌,气单胞菌,柠檬酸杆菌,可能是多重耐药病原体,包括β-内酰胺,氨基糖苷类,氯霉素和多重耐药性,等。空气污染物和气象条件均对空气传播病原菌的季节变化有贡献(r=0.15,p<0.01),尤其是CO,O3、PM2.5、温度和相对湿度。这项研究进一步加深了我们对空气传播病原体的理解,并强调了它们与ARGs的关联。
Airborne microorganisms, an emerging global health threat, have attracted extensive studies. However, few attentions have been paid to the seasonal distribution of airborne pathogens, in particular their associations with antibiotic resistance genes (ARGs). To this end, two-week daily PM2.5 samples were consecutively collected from Nanchang in four seasons, and the human-to-human pathogens were screened based on high-throughput sequencing. The results showed that there were 20 pathogenic taxa in PM2.5 in Nanchang, and the highest relative abundance of pathogens was observed in winter (5.84%), followed by summer (3.51%), autumn (2.66%), and spring (1.80%). Although more than half of pathogenic taxa were shared by the four seasons, the analysis of similarities showed that pathogenic community was shaped by season (r = 0.16, p < 0.01). Co-occurrence network analysis disclosed significant interactions among pathogens in each season. Moreover, some dominant pathogens such as Plesiomonas shigelloides, Bacteroides fragilis, and Escherichia-Shigella were hub pathogens. In addition, PICRUSt2 predicted that there were 35 high-risk ARG subtypes in PM2.5, and the pathogens had strongly positive correlations with these ARGs. Even some pathogens like Plesiomonas shigelloides, Bacteroides fragilis, Aeromonas, Citrobacter, may be multi-drug resistant pathogens, including beta-lactam, aminoglycosides, chloramphenicol and multi-drug resistances, etc. Both air pollutants and meteorological conditions contributed to the seasonal variation of airborne pathogenic bacteria (r = 0.15, p < 0.01), especially CO, O3, PM2.5, temperature and relative humidity. This study furthers our understanding of airborne pathogens and highlights their associations with ARGs.