Dai Rongchen, Wu Hanting, Liu Guiming, Shen Linlai, Geng Yuanyuan, Zhang Shu, Zhou Haijian, Jiang Canran, Gong Jie, Fan Xin, Ji Conghua
School of Public Health, Zhejiang Chinese Medical University, Hangzhou, Zhejiang, China.
Beijing Agro-Biotechnology Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing, China.
Front Microbiol. 2023 Mar 9;14:1089474. doi: 10.3389/fmicb.2023.1089474. eCollection 2023.
To evaluate the population structure of environmental bacteria and fungi in three different types of medical institutions and the potential risks due to antibiotic resistance during the coronavirus disease 2019 (COVID-19) pandemic.
One hundred twenty-six environmental surface samples were collected from three medical institutions during the COVID-19 pandemic. A total of 6,093 and 13,514 representative sequences of 16S and ITS ribosomal RNA (rRNA) were obtained by amplicon sequencing analysis. The functional prediction was performed using the Phylogenetic Investigation of Communities by Reconstruction of Unobserved States tool based on the Greengenes database and the FAPROTAX database.
On environmental surfaces in three medical institutions during the COVID-19 pandemic, Firmicutes (51.6%) and Bacteroidetes (25%) were the dominant bacteria, while Ascomycota (39.4%) and Basidiomycota (14.2%) were the dominant fungi. A number of potential bacterial and fungal pathogens were successfully identified by the metagenomic approach. Furthermore, compared with the bacterial results, the fungi showed a generally closer Bray Curtis distance between samples. The overall ratio of Gram-negative bacteria to Gram-positive bacteria was about 3:7. The proportion of stress-tolerant bacteria in medical institutions A, B and C reached 88.9, 93.0 and 93.8%, respectively. Anaerobic bacteria accounted for 39.6% in outdoor environments, 77.7% in public areas, 87.9% in inpatient areas and 79.6% in restricted areas. Finally, the β-Lactam resistance pathway and polymyxin resistance pathway were revealed through functional prediction.
We described the microbial population structure changes in three different types of medical institutions using the metagenomic approach during the COVID-19 pandemic. We found that the disinfection measures performed by three healthcare facilities may be effective on the "ESKAPE" pathogens, but less effective on fungal pathogens. Moreover, emphasis should be given to the prevention and control of β-lactam and polymyxin antibiotics resistance bacteria during the COVID-19 pandemic.
评估三种不同类型医疗机构中环境细菌和真菌的种群结构，以及2019年冠状病毒病（COVID-19）大流行期间抗生素耐药性带来的潜在风险。
在COVID-19大流行期间，从三家医疗机构采集了126份环境表面样本。通过扩增子测序分析获得了总共6093条和13514条16S和ITS核糖体RNA（rRNA）的代表性序列。使用基于Greengenes数据库和FAPROTAX数据库的未观察状态重建群落系统发育调查工具进行功能预测。
在COVID-19大流行期间，三家医疗机构的环境表面上，厚壁菌门（51.6%）和拟杆菌门（25%）是主要细菌，而子囊菌门（39.4%）和担子菌门（14.2%）是主要真菌。通过宏基因组学方法成功鉴定出许多潜在的细菌和真菌病原体。此外，与细菌结果相比，真菌在样本之间显示出总体上更接近的Bray Curtis距离。革兰氏阴性菌与革兰氏阳性菌的总体比例约为3:7。医疗机构A、B和C中耐应激细菌的比例分别达到88.9%、93.0%和93.8%。厌氧菌在室外环境中占39.6%，在公共区域占77.7%，在住院区域占87.9%，在限制区域占79.6%。最后，通过功能预测揭示了β-内酰胺耐药途径和多粘菌素耐药途径。
我们使用宏基因组学方法描述了COVID-19大流行期间三种不同类型医疗机构中微生物种群结构的变化。我们发现，三家医疗机构执行的消毒措施可能对“ESKAPE”病原体有效，但对真菌病原体效果较差。此外，在COVID-19大流行期间应重视β-内酰胺和多粘菌素抗生素耐药菌的防控。
