Identification and evaluation of cycling yeast metabolites in two-dimensional comprehensive gas chromatography–time-of-flight-mass spectrometry data

A yeast metabolome exhibiting oscillatory behavior was analyzed using comprehensive two-dimensional gas chromatography–time-of-flight-mass spectrometry (GC × GC–TOF-MS) and in-house developed data analysis software methodology, referred to as a signal ratio method (Sratio method). In this study, 44 identified unique metabolites were found to exhibit cycling, with a depth-of-modulation amplitude greater than three. After the initial locations are found using the Sratio software, and identified preliminarily using ChromaTOF software, the refined mass spectra and peak volumes were subsequently obtained using parallel factor analysis (PARAFAC). The peak volumes provided by PARAFAC deconvolution provide a measurement of the cycling depth-of-modulation amplitude that is more accurate than the initial Sratio information (which serves as a rapid screening procedure to find the cycling metabolites while excluding peaks that do not cycle). The Sratio reported is a rapid method to determine the depth-of-modulation while not constraining the search to specific cycling frequencies. The phase delay of the cycling metabolites ranged widely in relation to the oxygen consumption cycling pattern.