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Structurally-related alkaloids were analyzed by electrospray ionization/multiple stage mass spectrometry (ESI/MS(n)) at varying collision energies to demonstrate a conceptual algorithm, precursor ion fingerprinting (PIF). PIF is a new approach for interpreting and library-searching ESI mass spectra predicated on the precursor ions of structurally-related compounds and their matching product ion spectra. Multiple-stage mass spectra were compiled and constructed into "spectral trees" that illustrated the compounds' product ion spectra in their respective mass spectral stages. The precursor ions of these alkaloids were characterized and their spectral trees incorporated into an MS(n) library. These data will be used to construct a universal, searchable, and transferable library of MS(n) spectra. In addition, PIF will generate a proposed structural arrangement utilizing previously characterized ion structures, which will assist in the identification of unknown compounds.

Metabolomics, along with other “omics” approaches, is rapidly becoming one of the major approaches aimed at understanding the organization and dynamics of metabolic networks. Mass spectrometry is often a technique of choice for metabolomics studies due to its high sensitivity, reproducibility and wide dynamic range. High resolution mass spectrometry (HRMS) is a widely practiced technique in analytical and bioanalytical sciences. It offers exceptionally high resolution and the highest degree of structural confirmation. Many metabolomics studies have been conducted using HRMS over the past decade. In this review, we will explore the latest developments in Fourier transform mass spectrometry (FTMS) and Orbitrap based metabolomics technology, its advantages and drawbacks for using in metabolomics and lipidomics studies, and development of novel approaches for processing HRMS data.

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Model organisms are an essential component of biological and biomedical research that can be used to study specific biological processes. These organisms are in part selected for facile experimental study. However, just as importantly, intensive study of a small number of model organisms yields important synergies as discoveries in one area of science for a given organism shed light on biological processes in other areas, even for other organisms. Furthermore, the extensive knowledge bases compiled for each model organism enable systems-level understandings of these species, which enhance the overall biological and biomedical knowledge for all organisms, including humans. Building upon extensive genomics research, we argue that the time is now right to focus intensively on model organism metabolomes. We propose a grand challenge for metabolomics studies of model organisms: to identify and map all metabolites onto metabolic pathways, to develop quantitative metabolic models for model organisms, and to relate organism metabolic pathways within the context of evolutionary metabolomics, i.e., phylometabolomics. These efforts should focus on a series of established model organisms in microbial, animal and plant research.