Identification and Characterization of Clostridium difficile Sequence Type 37 Genotype by Matrix-Assisted Laser Desorption Ionization – Time of Flight Mass Spectrometry
Year: 2018
Type: article
Abstract: ABSTRACT Clostridium difficile multilocus sequence type 37 (ST37), which mainly corresponds to ribotype 017, has been a dominant genotype circulating in China. In this study, we report the use of matrix-assisted laser desorption ionization–time of flight mass spectrometry (MALDI-TOF MS) to analyze and characterize 204 C. difficile clinical isolates, including 49 ST37 and 155 non-ST37 isolates collected in China and other countries. The distributions of two major protein peaks ( m/z 3,242 and 3,286) were significantly different between ST37 and non-ST37 prototype strains and clinical isolates. This difference was reproducible when analysis was performed on different colonies in different runs. This finding was repeated and confirmed by both bioMérieux Vitek MS and Bruker Microflex LT systems on isolates recovered from a variety of geographic regions worldwide. The combination of the two peaks was present in 47 of 49 ST37 isolates, resulting in a sensitivity of 95.9%. In contrast, the peak combination was absent in 153 of 155 non-ST37 isolates, resulting in a specificity of 98.7%. Our results suggest that MALDI-TOF MS is a rapid and reliable tool to identify C. difficile genotype ST37. Work is in progress to characterize the two molecules having peaks at m/z 3,242 and 3,286, which appear to be specific to C. difficile genotype ST37.
Source: Journal of Clinical Microbiology
DOI: 10.1128/jcm.01990-17
Institutions: Hebei Medical University, Second Hospital of Hebei Medical University, Chinese Center For Disease Control and Prevention, National Institute for Communicable Disease Control and Prevention, State Key Laboratory of Infectious Disease Prevention and Control, Memorial Sloan Kettering Cancer Center, bioMérieux (France), bioMérieux (United States), Zhejiang Center for Disease Control and Prevention, Capital Medical University, Beijing Tian Tan Hospital, Cornell University, Weill Cornell Medicine
Language: English
Subfield: Clinical Biochemistry
Domain: Life Sciences
Open Access status: green
Award: Cancer Center Support Grant
OpenAlex ID: W2790098157
