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Wang YY, Xie L, Zhang WZ, Du XL, Li WG, Bia LL, Cui ZG, Wu Y, Lu JX. Application of a core genome sequence typing (cgMLST) pipeline for surveillance of Clostridioides difficile in China. Front Cell Infect Microbiol 2023; 13:1109153. [PMID: 36992688 PMCID: PMC10040748 DOI: 10.3389/fcimb.2023.1109153] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2022] [Accepted: 02/28/2023] [Indexed: 03/14/2023] Open
Abstract
IntroductionClostridioides difficile (C. difficile) is a nosocomial bacterial pathogen that causes antibiotic-associated diarrhea mediated by cellular exotoxins secreted into the intestine during bacterial growth. Multilocus sequence typing (MLST) and PCR ribotyping are the main molecular typing for C. difficile. Whole genome sequencing (WGS) core genome multilocus sequence typing (cgMLST) was developed for genetic evolution and outbreak investigation of C. difficile with higher precision and accuracy.MethodsA total of 699 whole (complete and draft) genome sequences of distinct C. difficile strains were used in this study to identify core gene set (2469 core genes) and the cgMLST scheme for the phylogeny analysis of C. difficile. This cgMLST pipeline was then carried the Chinese Pathogen Identification Net (China PIN) for surveillance of C. difficile in China. Within the China PIN, 195 WGS of C. difficile and an outbreak of CDI with 12 WGS of C. difficile were used to evaluate the cgMLST pipeline.ResultsThe result displayed that mostly tested C. difficile isolates could be successfully divided into 5 classic clades and the outbreak event was also successfully identified.DiscussionThe results are meaningful and offer a practicable pipeline for a national-wide surveillance of C. difficile in China.
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Affiliation(s)
- Yuan Yuan Wang
- State Key Laboratory of Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Lu Xie
- Research Center for Micro-Ecological Agent Engineering and Technology of Guangdong Province, Guangzhou, China
| | - Wen Zhu Zhang
- State Key Laboratory of Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Xiao li Du
- State Key Laboratory of Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Wen Ge Li
- State Key Laboratory of Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Lu Lu Bia
- State Key Laboratory of Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Zhi Gang Cui
- State Key Laboratory of Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Yuan Wu
- State Key Laboratory of Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
- Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Hangzhou, China
- *Correspondence: Yuan Wu,
| | - Jin Xing Lu
- State Key Laboratory of Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
- Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Hangzhou, China
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2
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Sun L, Zhuang H, Di L, Ling X, Yin Y, Wang Z, Chen M, Jiang S, Chen Y, Zhu F, Wang H, Ji S, Sun L, Wu D, Yu Y, Chen Y. Transmission and microevolution of methicillin-resistant Staphylococcus aureus ST88 strain among patients, healthcare workers, and household contacts at a trauma and orthopedic ward. Front Public Health 2023; 10:1053785. [PMID: 36699930 PMCID: PMC9868773 DOI: 10.3389/fpubh.2022.1053785] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2022] [Accepted: 12/19/2022] [Indexed: 01/11/2023] Open
Abstract
Background Surgical sites infections (SSIs) caused by Methicillin-resistant Staphylococcus aureus (MRSA) constitute a major clinical problem. Understanding the transmission mode of MRSA is important for its prevention and control. Aim We investigated the transmission mode of a MRSA outbreak in a trauma and orthopedic hospital ward. Methods Clinical data were collected from patients (n = 9) with MRSA infection in a trauma and orthopedic ward from January 1, 2015 to December 31, 2019. The wards (n = 18), patients (n = 48), medical staff (n = 23), and their households (n = 5) were screened for MRSA. The transmission mode of MRSA isolates was investigated using next-generation sequencing and phylogenetic analyses. The resistance genes, plasmids, and single-nucleotide variants of the isolates were analyzed to evaluate microevolution of MRSA isolates causing SSIs. The MRSA colonization-positive doctor was asked to suspend his medical activities to stop MRSA spread. Findings Nine MRSA infected patients were investigated, of which three patients were diagnosed with SSI and had prolonged hospitalization due to the persistent MRSA infection. After screening, MRSA isolates were not detected in environmental samples. The surgeon in charge of the patients with SSI caused by MRSA and his son were positive for MRSA colonization. The MRSA from the son was closely related to the isolates detected in MRSA-induced SSIs patients with 8-9 single-nucleotide variants, while ST88-MRSA isolates with three different spa types were detected in the surgeon's nasal cavity. Comparative genomic analysis showed that ST88-MRSA isolates acquired mutations in genes related to cell wall synthesis, colonization, metabolism, and virulence during their transmission. Suspending the medical activity of this surgeon interrupted the spread of MRSA infection in this ward. Conclusion Community-associated MRSA clones can invade hospitals and cause severe postoperative nosocomial infections. Further MRSA surveillance in the households of health workers may prevent the transition of MRSA from colonization to infection.
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Affiliation(s)
- Long Sun
- Department of Clinical Laboratory, Hangzhou Women's Hospital (Hangzhou Maternity and Child Health Care Hospital), Zhejiang, China
| | - Hemu Zhuang
- Department of Infectious Diseases, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China,Key Laboratory of Microbial Technology and Bioinformatics of Zhejiang Province, Hangzhou, Zhejiang, China,Regional Medical Center for National Institute of Respiratory Diseases, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Lingfang Di
- Department of Infectious Diseases, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China,Key Laboratory of Microbial Technology and Bioinformatics of Zhejiang Province, Hangzhou, Zhejiang, China,Regional Medical Center for National Institute of Respiratory Diseases, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China,Department of Clinical Laboratory, Tongxiang First People's Hospital, Tongxiang, Zhejiang, China
| | - Xia Ling
- Department of Infectious Diseases, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China,Key Laboratory of Microbial Technology and Bioinformatics of Zhejiang Province, Hangzhou, Zhejiang, China,Regional Medical Center for National Institute of Respiratory Diseases, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China,Blood Center of Zhejiang Province, Hangzhou, Zhejiang, China
| | - Yiping Yin
- Hospital Infection Control Office, Hospital of Zhejiang People's Armed Police, Zhejiang, China
| | - Zhengan Wang
- Department of Infectious Diseases, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China,Key Laboratory of Microbial Technology and Bioinformatics of Zhejiang Province, Hangzhou, Zhejiang, China,Regional Medical Center for National Institute of Respiratory Diseases, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Mengzhen Chen
- Department of Infectious Diseases, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China,Key Laboratory of Microbial Technology and Bioinformatics of Zhejiang Province, Hangzhou, Zhejiang, China,Regional Medical Center for National Institute of Respiratory Diseases, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Shengnan Jiang
- Department of Infectious Diseases, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China,Key Laboratory of Microbial Technology and Bioinformatics of Zhejiang Province, Hangzhou, Zhejiang, China,Regional Medical Center for National Institute of Respiratory Diseases, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Yiyi Chen
- Department of Infectious Diseases, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China,Key Laboratory of Microbial Technology and Bioinformatics of Zhejiang Province, Hangzhou, Zhejiang, China,Regional Medical Center for National Institute of Respiratory Diseases, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Feiteng Zhu
- Department of Infectious Diseases, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China,Key Laboratory of Microbial Technology and Bioinformatics of Zhejiang Province, Hangzhou, Zhejiang, China,Regional Medical Center for National Institute of Respiratory Diseases, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Haiping Wang
- Department of Infectious Diseases, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China,Key Laboratory of Microbial Technology and Bioinformatics of Zhejiang Province, Hangzhou, Zhejiang, China,Regional Medical Center for National Institute of Respiratory Diseases, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Shujuan Ji
- Department of Infectious Diseases, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China,Key Laboratory of Microbial Technology and Bioinformatics of Zhejiang Province, Hangzhou, Zhejiang, China,Regional Medical Center for National Institute of Respiratory Diseases, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Lu Sun
- Department of Infectious Diseases, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China,Key Laboratory of Microbial Technology and Bioinformatics of Zhejiang Province, Hangzhou, Zhejiang, China,Regional Medical Center for National Institute of Respiratory Diseases, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Dandan Wu
- Department of Infectious Diseases, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Yunsong Yu
- Department of Infectious Diseases, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China,Key Laboratory of Microbial Technology and Bioinformatics of Zhejiang Province, Hangzhou, Zhejiang, China,Regional Medical Center for National Institute of Respiratory Diseases, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China,Yunsong Yu ✉
| | - Yan Chen
- Department of Infectious Diseases, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China,Key Laboratory of Microbial Technology and Bioinformatics of Zhejiang Province, Hangzhou, Zhejiang, China,Regional Medical Center for National Institute of Respiratory Diseases, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China,*Correspondence: Yan Chen ✉
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Current molecular approach for diagnosis of MRSA: a meta-narrative review. Drug Target Insights 2022; 16:88-96. [PMID: 36761068 PMCID: PMC9906022 DOI: 10.33393/dti.2022.2522] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2022] [Accepted: 12/31/2022] [Indexed: 01/19/2023] Open
Abstract
Introduction: Detection and diagnosis of methicillin-resistant Staphylococcus aureus (MRSA) are important in ensuring a correct and effective treatment, further reducing its spread. A wide range of molecular approaches has been used for the diagnosis of antimicrobial resistance (AMR) in MRSA. This review aims to study and appraise widely used molecular diagnostic methods for detecting MRSA. Methods: This meta-narrative review was performed by searching PubMed using the following search terms: (molecular diagnosis) AND (antimicrobial resistance) AND (methicillin-resistant Staphylococcus aureus). Studies using molecular diagnostic techniques for the detection of MRSA were included, while non-English language, duplicates and non-article studies were excluded. After reviewing the libraries and a further manual search, 20 studies were included in this article. RAMESES publication standard for narrative reviews was used for this synthesis. Results: A total of 20 full papers were reviewed and appraised in this synthesis, consisting of PCR technique (n = 7), deoxyribonucleic acid (DNA) Microarray (n = 1), DNA sequencing (n = 2), Xpert MRSA/SA BC assay (n = 2), matrix-assisted laser desorption/ionization-time of flight (MALDI-TOF) (n = 2), MLST (n = 4), SCCmec typing (n = 1) and GENECUBE (n = 1). Discussion: Different diagnostic methods used to diagnose MRSA have been studied in this review. This study concludes that PCR has been extensively used due to its higher sensitivity and cost-effectiveness in the past five years
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Szymanek-Majchrzak K, Młynarczyk G. Genomic Insights of First ermB-Positive ST338-SCC mecV T/CC59 Taiwan Clone of Community-Associated Methicillin-Resistant Staphylococcus aureus in Poland. Int J Mol Sci 2022; 23:ijms23158755. [PMID: 35955887 PMCID: PMC9369149 DOI: 10.3390/ijms23158755] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2022] [Revised: 07/31/2022] [Accepted: 08/04/2022] [Indexed: 11/16/2022] Open
Abstract
We report the first Polish representative of community-associated methicillin-resistant Staphylococcus aureus (CA-MRSA), lukS/F-PV-positive, encoding the ermB gene, as a genetic determinant of constitutive resistance to macrolides, lincosamides, and streptogramin B antibiotics, cMLS-B. This is the first detection of the CA-MRSA strain responsible for nosocomial infection in the Warsaw Clinical Hospital. Resistance to β-lactams associates with a composite genetic element, SCCmec cassette type VT (5C2&5). We assigned the strain to sequence type ST338 (single-locus variant of ST59), clonal complex CC59, spa-type t437, and agr-type I. Genomic-based comparison was designated SO574/12 as an international Taiwan clone, which has been so far described mainly in the Asia-Pacific region. The ermB gene locates on the chromosome within the 14,690 bp mobile element structure, i.e., the MESPM1-like structure, which also encodes aminoglycoside- and streptothricin-resistance genes. The MESPM1-like structure is a composite transposon containing Tn551, flanked by direct repeats of IS1216V insertion sequences, which probably originates from Enterococcus. The ermB is preceded by the 273 bp regulatory region that contains the regulatory 84 bp ermBL ORF, encoding the 27 amino acid leader peptides. The latest research suggests that a new leader peptide, ermBL2, also exists in the ermB regulatory region. Therefore, the detailed function of ermBL2 requires further investigations.
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Zhuang H, Zhu F, Lan P, Ji S, Sun L, Chen Y, Wang Z, Jiang S, Zhang L, Zhu Y, Jiang Y, Chen Y, Yu Y. A random forest model based on core genome allelic profiles of MRSA for penicillin plus potassium clavulanate susceptibility prediction. Microb Genom 2021; 7. [PMID: 34554083 PMCID: PMC8715440 DOI: 10.1099/mgen.0.000610] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023] Open
Abstract
Treatment failure of methicillin-resistant Staphylococcus aureus (MRSA) infections remains problematic in clinical practice because therapeutic options are limited. Penicillin plus potassium clavulanate combination (PENC) was shown to have potential for treating some MRSA infections. We investigated the susceptibility of MRSA isolates and constructed a drug susceptibility prediction model for the phenotype of the PENC. We determined the minimum inhibitory concentration of PENC for MRSA (n=284) in a teaching hospital (SRRSH-MRSA). PENC susceptibility genotypes were analysed using a published genotyping scheme based on the mecA sequence. mecA expression in MRSA isolates was analysed by qPCR. We established a random forest model for predicting PENC-susceptible phenotypes using core genome allelic profiles from cgMLST analysis. We identified S2-R isolates with susceptible mecA genotypes but PENC-resistant phenotypes; these isolates expressed mecA at higher levels than did S2 MRSA (2.61 vs 0.98, P<0.05), indicating the limitation of using a single factor for predicting drug susceptibility. Using the data of selected UK-sourced MRSA (n=74) and MRSA collected in a previous national survey (NA-MRSA, n=471) as a training set, we built a model with accuracies of 0.94 and 0.93 for SRRSH-MRSA and UK-sourced MRSA (n=287, NAM-MRSA) validation sets. The AUROC of this model for SRRSH-MRSA and NAM-MRSA was 0.96 and 0.97. Although the source of the training set data affects the scope of application of the prediction model, our data demonstrated the power of the machine learning approach in predicting susceptibility from cgMLST results.
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Affiliation(s)
- Hemu Zhuang
- Department of Infectious Diseases, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine; Key Laboratory of Microbial Technology and Bioinformatics of Zhejiang Province; Regional Medical Center for National Institute of Respiratory Diseases, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, PR China
| | - Feiteng Zhu
- Department of Infectious Diseases, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine; Key Laboratory of Microbial Technology and Bioinformatics of Zhejiang Province; Regional Medical Center for National Institute of Respiratory Diseases, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, PR China
| | - Peng Lan
- Department of Infectious Diseases, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine; Key Laboratory of Microbial Technology and Bioinformatics of Zhejiang Province; Regional Medical Center for National Institute of Respiratory Diseases, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, PR China
| | - Shujuan Ji
- Department of Infectious Diseases, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine; Key Laboratory of Microbial Technology and Bioinformatics of Zhejiang Province; Regional Medical Center for National Institute of Respiratory Diseases, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, PR China
| | - Lu Sun
- Department of Infectious Diseases, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine; Key Laboratory of Microbial Technology and Bioinformatics of Zhejiang Province; Regional Medical Center for National Institute of Respiratory Diseases, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, PR China
| | - Yiyi Chen
- Department of Infectious Diseases, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine; Key Laboratory of Microbial Technology and Bioinformatics of Zhejiang Province; Regional Medical Center for National Institute of Respiratory Diseases, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, PR China
| | - Zhengan Wang
- Department of Infectious Diseases, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine; Key Laboratory of Microbial Technology and Bioinformatics of Zhejiang Province; Regional Medical Center for National Institute of Respiratory Diseases, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, PR China
| | - Shengnan Jiang
- Department of Infectious Diseases, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine; Key Laboratory of Microbial Technology and Bioinformatics of Zhejiang Province; Regional Medical Center for National Institute of Respiratory Diseases, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, PR China
| | - Linyue Zhang
- Department of Infectious Diseases, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine; Key Laboratory of Microbial Technology and Bioinformatics of Zhejiang Province; Regional Medical Center for National Institute of Respiratory Diseases, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, PR China
| | - Yiwei Zhu
- Department of Infectious Diseases, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine; Key Laboratory of Microbial Technology and Bioinformatics of Zhejiang Province; Regional Medical Center for National Institute of Respiratory Diseases, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, PR China
| | - Yan Jiang
- Department of Infectious Diseases, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine; Key Laboratory of Microbial Technology and Bioinformatics of Zhejiang Province; Regional Medical Center for National Institute of Respiratory Diseases, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, PR China
| | - Yan Chen
- Department of Infectious Diseases, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine; Key Laboratory of Microbial Technology and Bioinformatics of Zhejiang Province; Regional Medical Center for National Institute of Respiratory Diseases, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, PR China
| | - Yunsong Yu
- Department of Infectious Diseases, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine; Key Laboratory of Microbial Technology and Bioinformatics of Zhejiang Province; Regional Medical Center for National Institute of Respiratory Diseases, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, PR China
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Jin Y, Zhou W, Yin Z, Zhang S, Chen Y, Shen P, Ji J, Chen W, Zheng B, Xiao Y. The genetic feature and virulence determinant of highly virulent community-associated MRSA ST338-SCCmec Vb in China. Emerg Microbes Infect 2021; 10:1052-1064. [PMID: 33823746 PMCID: PMC8183566 DOI: 10.1080/22221751.2021.1914516] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Abstract
ST59 is the predominant pathotype of community-associated methicillin-resistant Staphylococcus aureus (CA-MRSA) in China. As a variant of ST59, there is relatively little known about the detailed information of ST338. To address this issue, here, we described thirteen ST338 CA-MRSA strains isolated from severe bloodstream infection cases, and focused on their epidemiology, genetic features and virulence potential. Phylogenetic analysis showed the earliest isolated strain of this study is likely a predecessor of recent ST338 lineage (after year of 2014). Furthermore, the phylogenetic reconstruction and time estimation suggested that ST338 evolved from ST59 in 1991. Notably, the carrying patten of virulence factors of all ST338 strains were similar, and the genomic islands νSaα, νSaγ and SaPI and the core virulence factors like hla and psm were detected in ST338 isolates. However, all ST338 isolates lacked some adhesion factors such as clfA, clfB, eap, cna and icaD. Additionally, among these ST338 strains, one PVL-negative ST338 isolate was detected. Experiment on mice nose and human alveolar epithelial cell showed that the nasal colonization ability of ST338 was weaker than that of CA-MRSA MW2. In a mouse bloodstream infection model and skin infection model, PVL+ and PVL− strains had the similar virulence, which was dependent on upregulation of toxin genes rather than the presence of mobile genetic elements such as ΦSa2 carrying PVL. Our findings provide important insight into the epidemiology and pathogenicity of the novel and highly virulent ST338-SCCmec Vb clone.
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Affiliation(s)
- Ye Jin
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, People's Republic of China
| | - Wangxiao Zhou
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, People's Republic of China
| | - Zhidong Yin
- Department of Pathology, The Second Affiliated Hospital of Zhejiang University College of Medicine, Hangzhou, People's Republic of China
| | - Shuntian Zhang
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, People's Republic of China
| | - Yunbo Chen
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, People's Republic of China
| | - Ping Shen
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, People's Republic of China
| | - Jinru Ji
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, People's Republic of China
| | - Weiwei Chen
- Department of Laboratory Medicine, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, People's Republic of China
| | - Beiwen Zheng
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, People's Republic of China
| | - Yonghong Xiao
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, People's Republic of China
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Chen Y, Sun L, Ba X, Jiang S, Zhuang H, Zhu F, Wang H, Lan P, Shi Q, Wang Z, Chen Y, Shi K, Ji S, Jiang Y, Holmes MA, Yu Y. Epidemiology, evolution and cryptic susceptibility of methicillin-resistant Staphylococcus aureus in China: a whole-genome-based survey. Clin Microbiol Infect 2021; 28:85-92. [PMID: 34022399 DOI: 10.1016/j.cmi.2021.05.024] [Citation(s) in RCA: 35] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2020] [Revised: 05/08/2021] [Accepted: 05/11/2021] [Indexed: 01/19/2023]
Abstract
OBJECTIVES The aim of this study was to investigate the genomic epidemiology of methicillin-resistant Staphylococcus aureus (MRSA) in China to identify predominant lineages and their associations with clinical data and antimicrobial resistance profiles. METHODS We performed a national prevalence study of patients with S. aureus infections in 22 tertiary hospitals in China from 2015 to 2017. Clinical data from patients and the antimicrobial phenotypes were collected for each isolate. Genome sequencing was performed on a proportion of isolates and a phylogenetic analysis was undertaken. Genotypic and phenotypic β-lactam susceptibilities were compared. RESULTS A total of 1900 patients with S. aureus infections were included, of which 40% involved MRSA. Community-associated MRSA (CA-MRSA) infections were 24% of the total isolates. Genomic data showed that more than three-quarters of the MRSA were from three dominant lineages CC239 (25%, 116/471), CC5 (21%, 96/471) and CC59 (33%, 154/471) with CC59 accounting for more than half of the CA-MRSA isolates. Penicillin susceptibility genomic features were observed in 53% (251/470) of MRSA, including almost all of the CC59 (152/154) lineage, and 96% (242/251) of these isolates demonstrated in vitro susceptibility to penicillin or amoxicillin combined with clavulanic acid. Phylogenetic analysis indicated that the CC59 lineage can be divided into six lineages with all Asian CC59 isolates likely arising from an ancestral Mainland China lineage. CONCLUSIONS This study showed a high prevalence of CA-MRSA in China, largely due to the widespread presence of CC59. As almost all isolates in this lineage possess genetic variants leading to increased β-lactam susceptibility, we suggest that to improve antibiotic stewardship combinations of penicillins and β-lactamase inhibitors should be included in the antibiotic susceptibility testing panels used to inform treatment decisions and research undertaken on this combination therapy.
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Affiliation(s)
- Yan Chen
- Department of Infectious Diseases, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China; Key Laboratory of Microbial Technology and Bioinformatics of Zhejiang Province, Hangzhou, Zhejiang, China; Regional Medical Center for National Institute of Respiratory Diseases, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Lu Sun
- Department of Infectious Diseases, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China; Key Laboratory of Microbial Technology and Bioinformatics of Zhejiang Province, Hangzhou, Zhejiang, China; Regional Medical Center for National Institute of Respiratory Diseases, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Xiaoliang Ba
- Department of Veterinary Medicine, University of Cambridge, Cambridge, UK
| | - Shengnan Jiang
- Department of Infectious Diseases, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China; Key Laboratory of Microbial Technology and Bioinformatics of Zhejiang Province, Hangzhou, Zhejiang, China; Regional Medical Center for National Institute of Respiratory Diseases, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Hemu Zhuang
- Department of Infectious Diseases, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China; Key Laboratory of Microbial Technology and Bioinformatics of Zhejiang Province, Hangzhou, Zhejiang, China; Regional Medical Center for National Institute of Respiratory Diseases, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Feiteng Zhu
- Department of Infectious Diseases, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China; Key Laboratory of Microbial Technology and Bioinformatics of Zhejiang Province, Hangzhou, Zhejiang, China; Regional Medical Center for National Institute of Respiratory Diseases, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Haiping Wang
- Department of Infectious Diseases, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China; Key Laboratory of Microbial Technology and Bioinformatics of Zhejiang Province, Hangzhou, Zhejiang, China; Regional Medical Center for National Institute of Respiratory Diseases, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Peng Lan
- Department of Infectious Diseases, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China; Key Laboratory of Microbial Technology and Bioinformatics of Zhejiang Province, Hangzhou, Zhejiang, China; Regional Medical Center for National Institute of Respiratory Diseases, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Qiucheng Shi
- Department of Clinical Laboratory, The Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Centre for Child Health, Zhejiang, China
| | - Zhengan Wang
- Department of Infectious Diseases, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China; Key Laboratory of Microbial Technology and Bioinformatics of Zhejiang Province, Hangzhou, Zhejiang, China; Regional Medical Center for National Institute of Respiratory Diseases, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Yiyi Chen
- Department of Infectious Diseases, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China; Key Laboratory of Microbial Technology and Bioinformatics of Zhejiang Province, Hangzhou, Zhejiang, China; Regional Medical Center for National Institute of Respiratory Diseases, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Keren Shi
- Department of Infectious Diseases, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China; Key Laboratory of Microbial Technology and Bioinformatics of Zhejiang Province, Hangzhou, Zhejiang, China; Regional Medical Center for National Institute of Respiratory Diseases, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Shujuan Ji
- Department of Infectious Diseases, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China; Key Laboratory of Microbial Technology and Bioinformatics of Zhejiang Province, Hangzhou, Zhejiang, China; Regional Medical Center for National Institute of Respiratory Diseases, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Yan Jiang
- Department of Infectious Diseases, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China; Key Laboratory of Microbial Technology and Bioinformatics of Zhejiang Province, Hangzhou, Zhejiang, China; Regional Medical Center for National Institute of Respiratory Diseases, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Mark A Holmes
- Department of Veterinary Medicine, University of Cambridge, Cambridge, UK.
| | - Yunsong Yu
- Department of Infectious Diseases, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China; Key Laboratory of Microbial Technology and Bioinformatics of Zhejiang Province, Hangzhou, Zhejiang, China; Regional Medical Center for National Institute of Respiratory Diseases, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China.
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Abstract
Streptococcus mutans is one of the primary pathogens responsible for the development of dental caries. Recent whole-genome sequencing (WGS)-based core genome multilocus sequence typing (cgMLST) approaches have been employed in epidemiological studies of specific human pathogens. However, this approach has not been reported in studies of S. mutans Here, we therefore developed a cgMLST scheme for S. mutans We surveyed 199 available S. mutans genomes as a means of identifying cgMLST targets, developing a scheme that incorporated 594 targets from the S. mutans UA159 reference genome. Sixty-eight sequence types (STs) were identified in this cgMLST scheme (cgSTs) in 80 S. mutans isolates from 40 children that were sequenced in this study, compared to 35 STs identified by multilocus sequence typing (MLST). Fifty-six cgSTs (82.35%) were associated with a single isolate based on our cgMLST scheme, which is significantly higher than in the MLST scheme (11.43%). In addition, 58.06% of all MLST profiles with ≥2 isolates were further differentiated by our cgMLST scheme. Topological analyses of the maximum likelihood phylogenetic trees revealed that our cgMLST scheme was more reliable than the MLST scheme. A minimum spanning tree of 145 S. mutans isolates from 10 countries developed based upon the cgMLST scheme highlighted the diverse population structure of S. mutans This cgMLST scheme thus offers a new molecular typing method suitable for evaluating the epidemiological distribution of this pathogen and has the potential to serve as a benchmark for future global studies of the epidemiological nature of dental caries.IMPORTANCE Streptococcus mutans is regarded as a major pathogen responsible for the onset of dental caries. S. mutans can transmit among people, especially within families. In this study, we established a new epidemiological approach to S. mutans classification. This approach can effectively differentiate among closely related isolates and offers superior reliability relative to that of the traditional MLST molecular typing method. As such, it has the potential to better support effective public health strategies centered around this bacterium that are aimed at preventing and treating dental caries.
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