PuSH - Publikationsserver des Helmholtz Zentrums München: Understanding molecular formula assignment of Fourier transform ion cyclotron resonance mass spectrometry data of natural organic matter from a chemical point of view.

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Herzsprung, P.* ; Hertkorn, N. ; von Tümpling, W.* ; Harir, M. ; Friese, K.* ; Schmitt-Kopplin, P.

Understanding molecular formula assignment of Fourier transform ion cyclotron resonance mass spectrometry data of natural organic matter from a chemical point of view.

Anal. Bioanal. Chem. 406, 7977-7987 (2014)

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Open Access Green möglich sobald Postprint bei der ZB eingereicht worden ist.

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Formula assignment is one of the key challenges in evaluation of dissolved organic matter analyses using ultrahigh resolution mass spectrometry (FTICR MS). The number of possible solutions for elemental formulas grows exponentially with increasing nominal mass, especially when non-oxygen heteroatoms like N, S or P are considered. Until now, no definitive solution for finding the correct elemental formula has been given. For that reason an approach from the viewpoint of chemical feasibility was elucidated. To illustrate the new chemical formula assignment principle, a literature data set was used and evaluated by simplified chemical constraints. Only formulas containing a maximum of one sulphur and five nitrogen atoms were selected for further data processing. The resulting data table was then divided into mass peaks with unique component solutions (singlets, representing unequivocal formula assignments) and those with two or more solutions (multiple formula assignments, representing equivocal formula assignments). Based on a [double bond equivalent (DBE) versus the number of oxygen atoms (o)] frequency contour plot and a frequency versus [DBE minus o] diagram, a new assessment and decision strategy was developed to differentiate multiple formula assignments into chemically reliable and less reliable molecular formulas. Using this approach a considerable number of reliable components were identified within the equivocal part of the data set. As a control, a considerable proportion of the assigned formulas deemed to be reliable correspond to those which would have been obtained by CH 2 -based Kendrick mass defect analysis. We conclude that formula assignment in complex mixtures can be improved by group-wise decisions based on the frequency and the [DBE minus o] values of multiple formula assignments.

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