Beyond monoisotopic accurate mass spectrometry: ancillary techniques for identifying unknown features in non-targeted discovery analysis. (15th November 2018)

• Record Type: Journal Article
• Authors: Pleil, Joachim D; Wallace, M Ariel Geer; McCord, James
• Is Part Of: Journal of breath research. Volume 13:Number 1(2019:Mar.)
• Publication Date: 2018-11-15
• Subjects: accurate mass -- monoisotopic mass -- compound identification -- chemical features -- high resolution MS -- isotope ratios -- mass fragments; Volatile organic compounds -- Analysis -- Periodicals; Clinical chemistry -- Periodicals; Bad breath -- Periodicals; Bad breath -- Treatment -- Periodicals; Bad breath -- Diagnosis -- Periodicals; 616.0756
• DOI: 10.1088/1752-7163/aae8c3
• Languages: English
• ISSNs: 1752-7155

Abstract

Abstract: High-resolution mass spectrometry (HR-MS) is an important tool for performing non-targeted analysis for investigating complex organic mixtures in human or environmental media. This perspective demonstrates HR-MS compound identification strategies using atom counting, isotope ratios, and fragmentation pattern analysis based on 'exact' or 'accurate' mass, which allows analytical distinction among mass fragments with the same integer mass, but with different atomic constituents of the original molecules. Herein, HR-MS technology is shown to narrow down the identity of unknown compounds for specific examples, and ultimately inform future analyses when these compounds reoccur. Although HR-MS is important for all biological media, this is particularly critical for new methods and instrumentation invoking exhaled breath condensate, particles, and aerosols. In contrast to standard breath gas-phase analyses where 1 mass unit (Da) resolution is generally sufficient, the condensed phase breath media are particularly vulnerable to errors in compound identification because the larger organic non-volatile molecules can form identical integer mass fragments from different atomic constituents which then require high-resolution mass analyses to tell them apart.