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van Krevelen diagrams (O/C vs H/C ratios of elemental formulas) have been widely used in studies to obtain an estimation of the main compound categories present in environmental samples. However, the limits defining a specific compound category based solely on O/C and H/C ratios of elemental formulas have never been accurately listed or proposed to classify metabolites in biological samples. Furthermore, while O/C vs H/C ratios of elemental formulas can provide an overview of the compound categories, such classification is inefficient because of the large overlap among different compound categories along both axes. We propose a more accurate compound classification for biological samples analyzed by high-resolution mass spectrometry based on an assessment of the C/H/O/N/P stoichiometric ratios of over 130 000 elemental formulas of compounds classified in 6 main categories: lipids, peptides, amino sugars, carbohydrates, nucleotides, and phytochemical compounds (oxy-aromatic compounds). Our multidimensional stoichiometric compound classification (MSCC) constraints showed a highly accurate categorization of elemental formulas to the main compound categories in biological samples with over 98% of accuracy representing a substantial improvement over any classification based on the classic van Krevelen diagram. This method represents a signficant step forward in environmental research, especially ecological stoichiometry and eco-metabolomics studies, by providing a novel and robust tool to improve our understanding of the ecosystem structure and function through the chemical characterization of biological samples. [ABSTRACT FROM AUTHOR]

Ultrahigh resolution mass spectrometry, such as Fourier transform ion cyclotron resonance mass spectrometry (FT ICR MS), can resolve thousands of molecular ions in complex organic matrices. A Compound Identification Algorithm (CIA) was previously developed for automated elemental formula assignment for natural organic matter (NOM). In this work, we describe software Formularity with a user-friendly interface for CIA function and newly developed search function Isotopic Pattern Algorithm (IPA). While CIA assigns elemental formulas for compounds containing C, H, O, N, S, and P, IPA is capable of assigning formulas for compounds containing other elements. We used halogenated organic compounds (HOC), a chemical class that is ubiquitous in nature as well as anthropogenic systems, as an example to demonstrate the capability of Formularity with IPA. A HOC standard mix was used to evaluate the identification confidence of IPA. Tap water and HOC spike in Suwannee River NOM were used to assess HOC identification in complex environmental samples. Strategies for reconciliation of CIA and IPA assignments were discussed. Software and sample databases with documentation are freely available. [ABSTRACT FROM AUTHOR]