Abstract
MALDI-TOF mass spectrometry has been shown to be a rapid and reliable tool for identification of bacteria at the genus and species, and in some cases, strain levels. Commercially available and open source software tools have been developed to facilitate identification; however, no universal/standardized data analysis pipeline has been described in the literature. Here, we provide a comprehensive and detailed demonstration of bacterial identification procedures using a MALDI-TOF mass spectrometer. Mass spectra were collected from 15 diverse bacteria isolated from Kartchner Caverns, AZ, USA, and identified by 16S rDNA sequencing. Databases were constructed in BioNumerics 7.1. Follow-up analyses of mass spectra were performed, including cluster analyses, peak matching, and statistical analyses. Identification was performed using blind-coded samples randomly selected from these 15 bacteria. Two identification methods are presented: similarity coefficient-based and biomarker-based methods. Results show that both identification methods can identify the bacteria to the species level.
Original language | English (US) |
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Article number | e52064 |
Journal | Journal of Visualized Experiments |
Issue number | 95 |
DOIs | |
State | Published - Jan 2 2015 |
Keywords
- BioNumerics
- Biomarker
- Database
- Environmental Sciences
- Environmental bacteria
- Fingerprint
- Identification
- Issue 95
- MALDI-TOF mass spectrometry
- Similarity coefficient
ASJC Scopus subject areas
- Neuroscience(all)
- Chemical Engineering(all)
- Biochemistry, Genetics and Molecular Biology(all)
- Immunology and Microbiology(all)