Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
5509511 | Clinica Chimica Acta | 2017 | 6 Pages |
Abstract
Biochemical methods such as metabolite testing and serotyping are traditionally used in clinical microbiology laboratories to identify and categorize microorganisms. Due to the large variety of bacteria, identifying representative metabolites is tedious, while raising high-quality antisera or antibodies unique to specific biomarkers used in serotyping is very challenging, sometimes even impossible. Although serotyping is a certified approach for differentiating bacteria such as E. coli and Salmonella at the subspecies level, the method is tedious, laborious, and not practical during an infectious disease outbreak. Mass spectrometry (MS) platforms, especially matrix assisted laser desorption and ionization-time of flight mass spectrometry (MALDI-TOF-MS), have recently become popular in the field of bacterial identification due to their fast speed and low cost. In the past few years, we have used liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based approaches to solve various problems hindering serotyping and have overcome some insufficiencies of the MALDI-TOF-MS platform. The current article aims to review the characteristics, advantages, and disadvantages of MS-based platforms over traditional approaches in bacterial identification and categorization.
Keywords
PMFBALDHBMRMTFAACNMALDI-TOFmatrix-assisted laser desorption ionization-time-of-flightCLSILPSFDAPFGE2,5-dihydroxybenzoic acidLC-MS/MSm/zCHCAPeptide mass fingerprintingAcetonitrileTrifluoroacetic acidFormic acidPulse field gel electrophoresisSDS-PAGESodium dodecyl sulfate polyacrylamide gel electrophoresisLosFood and Drug AdministrationMass spectrometryLiquid chromatography-tandem mass spectrometrybronchoalveolar lavageLipooligosaccharidesLipopolysaccharidesClinical and Laboratory Standards Institutemultiple reaction monitoringpolymerase chain reactionPCRhigh performance liquid chromatographyHPLC
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Authors
Angela Sloan, Gehua Wang, Keding Cheng,