Identification of Methicillin-Resistant Staphylococcus Aureus From Methicillin-Sensitive Staphylococcus Aureus and Molecular Characterization in Quanzhou, China

Zhimin Bai; Min Chen; Qiaofa Lin; Ying Ye; Hongmei Fan; Kaizhen Wen; Jianxing Zeng; Donghong Huang; Wenfei Mo; Ying Lei; Zhijun Liao

doi:10.3389/fcell.2021.629681

Identification of Methicillin-Resistant Staphylococcus Aureus From Methicillin-Sensitive Staphylococcus Aureus and Molecular Characterization in Quanzhou, China

Front Cell Dev Biol. 2021 Jan 21:9:629681. doi: 10.3389/fcell.2021.629681. eCollection 2021.

Authors

Zhimin Bai^{1

2}, Min Chen^{1

3}, Qiaofa Lin¹, Ying Ye¹, Hongmei Fan¹, Kaizhen Wen², Jianxing Zeng², Donghong Huang⁴, Wenfei Mo¹, Ying Lei⁵, Zhijun Liao¹

Affiliations

¹ Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Fujian Medical University, Fuzhou, China.
² Department of Clinical Laboratory, Jinjiang Municipal Hospital, Jinjiang, China.
³ Microbiological Laboratory Sanming Center for Disease Control and Prevention, Sanming, China.
⁴ Department of Clinical Laboratory, The Second Affiliated Hospital of Fujian Medical University, Quanzhou, China.
⁵ Department of Clinical Laboratory, Quanzhou Women's and Children's Hospital, Quanzhou, China.

Abstract

To distinguish Methicillin-Resistant Staphylococcus aureus (MRSA) from Methicillin-Sensitive Staphylococcus aureus (MSSA) in the protein sequences level, test the susceptibility to antibiotic of all Staphylococcus aureus isolates from Quanzhou hospitals, define the virulence factor and molecular characteristics of the MRSA isolates. MRSA and MSSA Pfam protein sequences were used to extract feature vectors of 188D, n-gram and 400D. Weka software was applied to classify the two Staphylococcus aureus and performance effect was evaluated. Antibiotic susceptibility testing of the 81 Staphylococcus aureus was performed by the Mérieux Microbial Analysis Instrument. The 65 MRSA isolates were characterized by Panton-Valentine leukocidin (PVL), X polymorphic region of Protein A (spa), multilocus sequence typing test (MLST), staphylococcus chromosomal cassette mec (SCCmec) typing. After comparing the results of Weka six classifiers, the highest correctly classified rates were 91.94, 70.16, and 62.90% from 188D, n-gram and 400D, respectively. Antimicrobial susceptibility test of the 81 Staphylococcus aureus: Penicillin-resistant rate was 100%. No resistance to teicoplanin, linezolid, and vancomycin. The resistance rate of the MRSA isolates to clindamycin, erythromycin and tetracycline was higher than that of the MSSAs. Among the 65 MRSA isolates, the positive rate of PVL gene was 47.7% (31/65). Seventeen sequence types (STs) were identified among the 65 isolates, and ST59 was the most prevalent. SCCmec type III and IV were observed at 24.6 and 72.3%, respectively. Two isolates did not be typed. Twenty-one spa types were identified, spa t437 (34/65, 52.3%) was the most predominant type. MRSA major clone type of molecular typing was CC59-ST59-spa t437-IV (28/65, 43.1%). Overall, 188D feature vectors can be applied to successfully distinguish MRSA from MSSA. In Quanzhou, the detection rate of PVL virulence factor was high, suggesting a high pathogenic risk of MRSA infection. The cross-infection of CA-MRSA and HA-MRSA was presented, the molecular characteristics were increasingly blurred, HA-MRSA with typical CA-MRSA molecular characteristics has become an important cause of healthcare-related infections. CC59-ST59-spa t437-IV was the main clone type in Quanzhou, which was rare in other parts of mainland China.

Keywords: Staphylococcus aureus; antibiotic resistance; feature vector; machine learning; molecular characterization; virulence factor.