Species-Specific Bacteria Identification Using Differential Mobility Spectrometry and Bioinformatics Pattern Recognition

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• 作者：Marianna Shnayderman ; Brian Mansfield ; Ping Yip ; Heather A. Clark ; Melissa D. Krebs ; Sarah J. Cohen ; Julie E. Zeskind ; Edward T. Ryan ; Henry L. Dorkin ; Michael V. Callahan ; Thomas O. Stair ; Jeffrey A.
• 刊名：Analytical Chemistry
• 出版年：2005
• 出版时间：September 15, 2005
• 年：2005
• 卷：77
• 期：18
• 页码：5930 - 5937
• 全文大小：573K
• 年卷期：v.77,no.18(September 15, 2005)
• ISSN：1520-6882

文摘

As bacteria grow and proliferate, they release a variety ofvolatile compounds that can be profiled and used forspeciation, providing an approach amenable to diseasediagnosis through quick analysis of clinical cultures aswell as patient breath analysis. As a practical alternativeto mass spectrometry detection and whole cell pyrolysisapproaches, we have developed methodology that involvesdetection via a sensitive, micromachined differentialmobility spectrometer (microDMx), for sampling headspace gases produced by bacteria growing in liquidculture. We have applied pattern discovery/recognitionalgorithms (ProteomeQuest) to analyze headspace gasspectra generated by microDMx to reliably discern multiple species of bacteria in vitro: Escherichia coli,Bacillus subtilis, Bacillus thuringiensis, and Mycobacterium smegmatis. The overall accuracy for identifying volatile profiles of a species within the 95% confidenceinterval for the two highest accuracy models evolved wasbetween 70.4 and 89.3% based upon the coordinatedexpression of between 5 and 11 features. These encouraging in vitro results suggest that the microDMx technology, coupled with bioinformatics data analysis, has potential for diagnosis of bacterial infections.