2 research outputs found
Moving beyond the van Krevelen Diagram: A New Stoichiometric Approach for Compound Classification in Organisms
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
Moving beyond the van Krevelen Diagram: A New Stoichiometric Approach for Compound Classification in Organisms
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