Deciphering the chemical composition of Ganoderma lucidum from different geographical origins by mass spectrometry molecular networking coupled with multivariate analysis

化学成分 多元统计 多元分析 化学 偏最小二乘回归 线性判别分析 灵芝 灵芝 代谢组学 化学成分 传统医学 数学 统计 色谱法 食品科学 医学 有机化学
作者
Jia Liu,Guobao Chen,Junhui Yang,Leilei Sheng,Xue-xiao Tang,Xiao Zhang,Haibing Hua
出处
期刊:Biomedical Chromatography [Wiley]
卷期号:37 (1) 被引量:2
标识
DOI:10.1002/bmc.5506
摘要

Ganoderma lucidum is a medicinal fungus that has been widely used in China and many Asian countries for thousands of years. This once rare macrofungus has now been artificially cultivated in a number of regions in China. However, detailed knowledge of its composition across different geographical origins is still lacking, as are analytical methods for comprehensive profiling of the diverse phytochemicals contained in G. lucidum. In this work, an on-demand strategy based on high-resolution MS and molecular networking is applied for natural product characterization, which led to the identification of 84 constituents in G. lucidum. Moreover, multivariate analysis, including hierarchical cluster analysis and orthogonal partial least squares-discriminant analysis, was used to analyze the (dis)similarity of the G. lucidum samples collected from the three main production areas (i.e., Jilin, Henan and Shandong Province). The results revealed a significant variation in the chemical composition of samples from different provinces. Marker constituents corresponding to the differentiation were then screened in terms of the variable importance in projection value, P-value and fold change. A total of 24 constituents were identified as geoherbalism markers, such as ganoderenic acid A for Henan, ganolucidic acid B for Jilin and ganodernoid D for Shandong. This proof-of-concept application demonstrates that combining MS molecular networking with meticulous multivariate analysis can provide a sensitive and comprehensive analytical approach for the quality assessment of traditional Chinese medicine ingredients. This study also suggests that the bioactivity and efficacy from different origins should be further evaluated considering the large difference in chemical compositions.
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
刚刚
2秒前
4秒前
orixero应助kyJYbs采纳,获得10
4秒前
LLJ发布了新的文献求助10
5秒前
小犁牛完成签到 ,获得积分10
6秒前
无限的葶发布了新的文献求助30
7秒前
xt_489完成签到,获得积分10
7秒前
CodeCraft应助一笑而过采纳,获得10
7秒前
李橘子发布了新的文献求助10
9秒前
Akim应助专注的问筠采纳,获得10
10秒前
彭于晏应助枫月流年采纳,获得10
13秒前
无限的葶完成签到,获得积分20
13秒前
天天发布了新的文献求助10
15秒前
LLJ完成签到,获得积分10
16秒前
阡陌完成签到 ,获得积分10
20秒前
姜汁树完成签到 ,获得积分10
21秒前
英姑应助silent采纳,获得10
22秒前
菠萝吹雪完成签到,获得积分10
22秒前
小白发布了新的文献求助10
23秒前
24秒前
bkagyin应助喜悦怀亦采纳,获得30
25秒前
27秒前
27秒前
Orangeade发布了新的文献求助10
28秒前
32秒前
ding应助科研通管家采纳,获得10
35秒前
wanci应助科研通管家采纳,获得10
35秒前
zmnzmnzmn应助科研通管家采纳,获得10
35秒前
35秒前
小二郎应助科研通管家采纳,获得10
35秒前
zmnzmnzmn应助科研通管家采纳,获得10
35秒前
科研通AI5应助科研通管家采纳,获得10
35秒前
zmnzmnzmn应助科研通管家采纳,获得10
35秒前
wanci应助科研通管家采纳,获得10
35秒前
上官若男应助科研通管家采纳,获得10
35秒前
HEIKU应助科研通管家采纳,获得10
35秒前
35秒前
35秒前
35秒前
高分求助中
【此为提示信息,请勿应助】请按要求发布求助,避免被关 20000
Continuum Thermodynamics and Material Modelling 2000
Encyclopedia of Geology (2nd Edition) 2000
105th Edition CRC Handbook of Chemistry and Physics 1600
Maneuvering of a Damaged Navy Combatant 650
Периодизация спортивной тренировки. Общая теория и её практическое применение 310
Mixing the elements of mass customisation 300
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 物理 生物化学 纳米技术 计算机科学 化学工程 内科学 复合材料 物理化学 电极 遗传学 量子力学 基因 冶金 催化作用
热门帖子
关注 科研通微信公众号,转发送积分 3778901
求助须知:如何正确求助?哪些是违规求助? 3324431
关于积分的说明 10218443
捐赠科研通 3039495
什么是DOI,文献DOI怎么找? 1668204
邀请新用户注册赠送积分活动 798591
科研通“疑难数据库(出版商)”最低求助积分说明 758440