Abstract
We have developed a metabolic profiling experimental scheme based on a direct-infusion method on a Fourier Transform Ion Cyclotron Resonance Mass Spectrometry (FT-ICR MS). The metabolic profiling scheme was designed for metabolome classification and marker metabolite identification, correcting considerable analytical errors intrinsically associated with the high-resolution analyses with FT-ICR MS under unpredictable ion suppression effects in the analytical cell. The scheme consists of 1) optimization of the analysis conditions for reproducible data correction among each MS scan, 2) development of a data analysis tool (Dmass) for automatic mass-error correction, 3) multivariate analyses for metabolome clarification among different samples, 4) identification of marker metabolite candidates through a database (KNApSAcK) search using accurate mass values, and 5) structural analyses for the candidate compounds by MSMS technique. We discuss the application of our experimental scheme for an integrated data analysis of metabolomics and transcriptomics for Arabidopsis suspension cells under different culture conditions.
