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

化学 化学计量学 图表 元素分析 生态化学计量学 分类 环境化学 生物系统 有机化学 人工智能 数学 计算机科学 统计 生物
作者
Albert Rivas‐Ubach,Yina Liu,Thomas S. Bianchi,Nikola Tolić,Christer Jansson,Ljiljana Paša‐Tolić
出处
期刊:Analytical Chemistry [American Chemical Society]
卷期号:90 (10): 6152-6160 被引量:229
标识
DOI:10.1021/acs.analchem.8b00529
摘要

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.
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