Abstract
Ion mobility spectrometry coupled to multi capillary columns (MCC/IMS) combines highly sensitive spectrometry with a rapid separation technique. MCC\IMS is widely used for biomedical breath analysis. The identification of molecules in such a complex sample necessitates a reference database. The existing IMS reference databases are still in their infancy and do not allow to actually identify all analytes. With a gas chromatograph coupled to a mass selective detector (GC/MSD) setup in parallel to a MCC/IMS instrumentation we may increase the accuracy of automatic analyte identification. To overcome the time-consuming manual evaluation and comparison of the results of both devices, we developed a software tool MIMA (MS-IMS-Mapper), which can computationally generate analyte layers for MCC/IMS spectra by using the corresponding GC/MSD data. We demonstrate the power of our method by successfully identifying the analytes of a seven-component mixture. In conclusion, the main contribution of MIMA is a fast and easy computational method for assigning analyte names to yet un-assigned signals in MCC/IMS data. We believe that this will greatly impact modern MCC/IMS-based biomarker research by "giving a name" to previously detected disease-specific molecules.
| Original language | English |
|---|---|
| Pages (from-to) | 95-101 |
| Number of pages | 7 |
| Journal | International Journal for Ion Mobility Spectrometry |
| Volume | 17 |
| Issue number | 2 |
| DOIs | |
| State | Published - Jun 2014 |
| Externally published | Yes |
Keywords
- Analyte identification
- Automation
- Gas chromatography/mass selective detector (GC/MSD)
- Layer
- Multi-capillary column ion mobility spectrometry (MCC/IMS)
- Volatile organic compounds (VOCs)
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