A tool for high-throughput prediction of molecular formulas and identification of isotopic peaks from large-scale mass spectrometry data

Abstract

Most plant metabolites are uncharacterized, even in well-analyzed plant species. High-accuracy measurement of mass values by state-of-the-art mass spectrometers such as Fourier transform ion cyclotron resonance mass spectrometers allows prediction of possible molecular formulas for each metabolite. As a first step in comprehensive metabolite identification from mass spectrometry data, here we have developed a computational tool for high-throughput prediction of molecular formulas and identification of isotopic peaks. The program generates all possible formulas for each mass value under given parameters. To reduce calculation time, monophosphate, diphosphate, triphosphate and bisulfate groups are regarded as monovalent units during formula generation. Prediction of isotopic peaks associated with each metabolite also facilitates reduction in the number of possible formulas. The tool implements these procedures for all mass values from a set of mass spectrometry data. The tool facilitates subsequent annotation of metabolites, which can be integrated with metabolome databases.