Explanatory signal interpretation and metabolite identification strategies for nominal mass FIE-MS metabolite fingerprints.
Flow injection electrospray mass spectrometry (FIE-MS) metabolite fingerprinting is widely used as a 'first pass' screen for compositional differences, where discrimination between samples can be achieved without any preconceptions. Powerful data analysis algorithms can be used to select and rank FIE-MS fingerprint variables highly explanatory of the biological problem under investigation. We describe how to create a species-specific FIE-MS/MS(n) metabolite database and how to then query the database to predict the identity of highly significant variables within FIE-MS fingerprints. The protocol details how to interpret m/z signals within the explanatory variable list based on a correlation analysis in conjunction with an investigation of mathematical relationships regarding (de)protonated molecular ions, salt adducts, neutral losses and dimeric associations routinely observed in FIE-MS fingerprints. Although designed for use by biologists/analytical chemists, collaboration with data-mining experts is generally advised. The protocol is applicable in any areas of bioscience research involving FIE-MS fingerprinting.
Overy
David P
DP
Institute of Biological Sciences, Aberystwyth University, Aberystwyth, Ceredigion, SY23 3DA, UK.
Enot
David P
DP
Tailliart
Kathleen
K
Jenkins
Helen
H
Parker
David
D
Beckmann
Manfred
M
Draper
John
J
D000465:Algorithms; D019295:Computational Biology / Q000379:methods*; D016208:Databases, Factual; D008660:Metabolism; D021241:Spectrometry, Mass, Electrospray Ionization / Q000379:methods*