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.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
1秒前
杨浩天发布了新的文献求助10
1秒前
hayin发布了新的文献求助10
1秒前
xwhite完成签到,获得积分10
1秒前
xiaoyan发布了新的文献求助10
2秒前
qiqi发布了新的文献求助20
2秒前
www完成签到,获得积分10
2秒前
2秒前
DARLING002完成签到,获得积分10
2秒前
cy0824给cy0824的求助进行了留言
2秒前
黑马发布了新的文献求助10
3秒前
ty完成签到,获得积分20
3秒前
vv完成签到,获得积分10
3秒前
小蘑菇应助joyux采纳,获得10
3秒前
4秒前
熙春茶完成签到 ,获得积分10
4秒前
4秒前
4秒前
4秒前
小蘑菇应助栖浔采纳,获得10
4秒前
wanguangliang发布了新的文献求助30
4秒前
5秒前
健忘的迎梅完成签到,获得积分10
5秒前
5秒前
5秒前
6秒前
6秒前
7秒前
bin完成签到,获得积分20
7秒前
传奇3应助淡定宛白采纳,获得10
8秒前
8秒前
阿诺发布了新的文献求助10
8秒前
shunee发布了新的文献求助10
9秒前
9秒前
感动水杯发布了新的文献求助10
10秒前
超级的逊发布了新的文献求助10
10秒前
11秒前
11秒前
天天快乐应助落无痕采纳,获得10
11秒前
11秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Earth System Geophysics 1000
Bioseparations Science and Engineering Third Edition 1000
Lloyd's Register of Shipping's Approach to the Control of Incidents of Brittle Fracture in Ship Structures 1000
BRITTLE FRACTURE IN WELDED SHIPS 1000
Entre Praga y Madrid: los contactos checoslovaco-españoles (1948-1977) 1000
Encyclopedia of Materials: Plastics and Polymers 800
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 纳米技术 有机化学 物理 生物化学 化学工程 计算机科学 复合材料 内科学 催化作用 光电子学 物理化学 电极 冶金 遗传学 细胞生物学
热门帖子
关注 科研通微信公众号,转发送积分 6114249
求助须知:如何正确求助?哪些是违规求助? 7942675
关于积分的说明 16467890
捐赠科研通 5238726
什么是DOI,文献DOI怎么找? 2799065
邀请新用户注册赠送积分活动 1780712
关于科研通互助平台的介绍 1652931