Rapid Identification of Anaerobes by CE,MALDI-TOF-MS and HPLC-Nano-MS/MS approaches

碩士 === 慈濟大學 === 醫學生物技術研究所 === 98 === Abstract The rapid and precise identification of bacterial pathogens is significant for the patient supervision and initiation of appropriate antibiotic therapy in the early stages of infection. Recently, CE and mass spectrometry has been used widely as a diagnos...

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Bibliographic Details
Main Authors: Che -wei Liu, 劉哲瑋
Other Authors: Anren-Hu
Format: Others
Language:zh-TW
Published: 2010
Online Access:http://ndltd.ncl.edu.tw/handle/90760795583045050342
Description
Summary:碩士 === 慈濟大學 === 醫學生物技術研究所 === 98 === Abstract The rapid and precise identification of bacterial pathogens is significant for the patient supervision and initiation of appropriate antibiotic therapy in the early stages of infection. Recently, CE and mass spectrometry has been used widely as a diagnostic tool in separation and identification of microbial mixtures. Furthermore, most of the human normal flora is composed of anaerobic bacteria and can infect deep wounds, deep tissues, internal organs and also inflict occasionally life-threatening disease. In the present investigation, we performed two analytical approaches for rapid identification of pathogens. At first, we present an off-line coupling of capillary electrophoresis (CE) to matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) approach for fast identification of anaerobes. In this study, we successfully separated and collected several anaerobic pathogens like Fusobacterium nucleatum, Bacteroides fragilis, Prevotella bivia, Clostridium sporgenes, Clostridium difficile and Porphyromonas gingivalis from clinical specimens performing CE and then analyzed by MALDI-TOF mass spectrometry. Different pathogens were further identified shortly through protein fingerprinting approach. On the other hand, we performed HPLC-Nanospray-MS/MS analysis for identification of anaerobic pathogens. This technique is most useful for microbial identification because of its sensitivity, high throughput capacity and it is readily amenable to automation. Here, we developed a new method to identify bacteria based on data-dependent tandem mass spectrometry. We used Bioworks browser with SEQUEST search engine combined NCBI BLAST proteome database, followed ranking peptide by its score and found specific unique peptide of the bacterium to identify unknown pathogen. In conclusion, both the approaches allow the rapid and efficient separation and analyzed the pathogens within one day. Moreover it was easy, faster and almost automated and offer clear advantages over conventional methods. Furthermore, the offline coupled CE-MALDI-TOF-MS approach allows reinvestigation of the collected fractions by other methods following the mass spectrometric analysis.