Mass differences in metabolome analyses of untargeted direct infusion ultra-high resolution MS data

Ultra-high resolution mass spectrometers (UHR MS) including Fourier Transform ion cyclotron resonance (FT-ICR MS) and Orbitrap mass analyzers produce data of ever more increasing mass accuracy, resolution and information content. In its comparably long history of analyses on complex mixtures such as petroleum or natural organic matter, UHR-MS scientists have developed methods for mining and analysis of homologous hydrocarbon series, repetitive elemental compositional units that are characteristic for the chemistry of diverse complex organic matrices. The science of metabolomics considered the use of UHR-MS for the analysis of complete sets of metabolites since its infancy. However, the peculiarities of this type of UHR analytical instrumentation and the data it produces did not yet become a widely accepted source of biologically relevant information. This book chapter aims to assist the readers in their assessment of the great value that UHR-MS analyzers can produce for their own research. This book chapter's first section accordingly provides a short introduction into the history of metabolomics and attempts to gauge where UHR-MS is to be positioned amidst the various sub-classifications of metabolomic research. The second section then proceeds with introducing mass differences as the major means of mass spectrometric quality assessment, just to extend their use for the visual and computational localization of homologous molecular series and molecular formula assignment. After a review of major mass-difference based technologies in m/. z signal identification, ". Mass difference networks in the visualization and secondary analysis of UHR-MS data" section continues to line out the methods that are central for a systems biological analysis of metabolomic data. The chapter finishes by embedding mass differences into the context of the introduced methods and an example on their use for mining the chemical meaning of unknown metabolic features.