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Characterizing Bacterial Volatiles using Secondary Electrospray Ionization Mass Spectrometry (SESI-MS)

Secondary electrospray ionization mass spectrometry (SESI-MS) is a method developed for the rapid detection of volatile compounds, without the need for sample pretreatment. The method was first described by Fenn and colleagues(1) and has been applied to the detection of illicit drugs(2) and explosiv...

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Detalles Bibliográficos
Autores principales: Bean, Heather D., Zhu, Jiangjiang, Hill, Jane E.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MyJove Corporation 2011
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3197037/
https://www.ncbi.nlm.nih.gov/pubmed/21694687
http://dx.doi.org/10.3791/2664
Descripción
Sumario:Secondary electrospray ionization mass spectrometry (SESI-MS) is a method developed for the rapid detection of volatile compounds, without the need for sample pretreatment. The method was first described by Fenn and colleagues(1) and has been applied to the detection of illicit drugs(2) and explosives(3-4), the characterization of skin volatiles(5), and the analysis of breath(6-7). SESI ionization occurs by proton transfer reactions between the electrospray solution and the volatile analyte, and is therefore suitable for the analysis of hetero-organic molecules, just as in traditional electrospray ionization (ESI). However, unlike standard ESI, the proton transfer process of SESI occurs in the vapor phase rather than in solution (Fig. 1), and therefore SESI is best suited for detecting organic volatiles and aerosols. We are expanding the use of SESI-MS to the detection of bacterial volatiles as a method for bacterial identification and characterization(8). We have demonstrated that SESI-MS volatile fingerprinting, combined with a statistical analysis method, can be used to differentiate bacterial genera, species, and mixed cultures in a variety of growth media.(8) Here we provide the steps for obtaining bacterial volatile fingerprints using SESI-MS, including the instrumental parameters that should be optimized to ensure robust bacterial identification and characterization.