Genotyping Characteristics of Human Fecal Escherichia coli and Their Association with Multidrug Resistance in Miyun District, Beijing

IF 3 3区医学 Q2 ENVIRONMENTAL SCIENCES

Biomedical and Environmental Sciences Pub Date : 2023-05-01 DOI:10.3967/bes2023.050

ZHANG Wei Wei , ZHU Xiao Lin , DENG Le Le , HAN Ya Jun , LI Zhuo Wei , WANG Jin Long , CHEN Yong Liang , WANG Ao Lin , TIAN Er Li , CHENG Bin , XU Lin Hua , CHEN Yi Cong , TIAN Li Li , HE Guang Xue

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引用次数: 0

Abstract

Objective

To explore the genotyping characteristics of human fecal Escherichia coli (E. coli) and the relationships between antibiotic resistance genes (ARGs) and multidrug resistance (MDR) of E. coli in Miyun District, Beijing, an area with high incidence of infectious diarrheal cases but no related data.

Methods

Over a period of 3 years, 94 E. coli strains were isolated from fecal samples collected from Miyun District Hospital, a surveillance hospital of the National Pathogen Identification Network. The antibiotic susceptibility of the isolates was determined by the broth microdilution method. ARGs, multilocus sequence typing (MLST), and polymorphism trees were analyzed using whole-genome sequencing data (WGS).

Results

This study revealed that 68.09% of the isolates had MDR, prevalent and distributed in different clades, with a relatively high rate and low pathogenicity. There was no difference in MDR between the diarrheal (49/70) and healthy groups (15/24).

Conclusion

We developed a random forest (RF) prediction model of TEM.1 + baeR + mphA + mphB + QnrS1 + AAC.3-IId to identify MDR status, highlighting its potential for early resistance identification. The causes of MDR are likely mobile units transmitting the ARGs. In the future, we will continue to strengthen the monitoring of ARGs and MDR, and increase the number of strains to further verify the accuracy of the MDR markers.

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北京市密云区人粪便大肠杆菌的基因分型特征及其与多药耐药性的关系

目的探讨北京市密云区人粪便大肠杆菌（E.coli）的基因分型特征及其与多药耐药性（MDR）的关系。方法在3年的时间里，从国家病原菌鉴定网监测医院密云区医院采集的粪便样本中分离出94株大肠杆菌。采用肉汤微量稀释法测定分离株对抗生素的敏感性。利用全基因组测序数据（WGS）对ARGs、MLST和多态树进行分析。结论我们建立了TEM.1+baeR+mphA+mphB+QnrS1+AAC.3-IId的随机森林（RF）预测模型来识别MDR状态，突出了其早期耐药性鉴定的潜力。MDR的原因可能是传输ARG的移动单元。未来，我们将继续加强对ARGs和MDR的监测，并增加菌株数量，以进一步验证MDR标志物的准确性。

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来源期刊

Biomedical and Environmental Sciences 环境科学-公共卫生、环境卫生与职业卫生

CiteScore

2.60

自引率

8.60%

发文量

2170

审稿时长

1.0 months

期刊介绍： Biomedical and Environmental Sciences (BES) is a peer-reviewed journal jointly established by the Chinese Center for Disease Control and Prevention (China CDC) and the Coulston International Corporation (CIC), USA in 1988, and is published monthly by Elsevier. It is indexed by SCI, PubMed, and CA. Topics covered by BES include infectious disease prevention, chronic and non-communicable disease prevention, disease control based on preventive medicine, and public health theories. It also focuses on the health impacts of environmental factors in people''s daily lives and work, including air quality, occupational hazards, and radiation hazards. Article types considered for publication include original articles, letters to the editor, reviews, research highlights, and policy forum.