基于液相色谱-质谱联用技术的心肌缺血大鼠血清和心肌组织代谢组学

doi:10.3724/SP.J.1123.2019.07019

色谱 ›› 2020, Vol. 38 ›› Issue (2): 206-211.DOI: 10.3724/SP.J.1123.2019.07019

基于液相色谱-质谱联用技术的心肌缺血大鼠血清和心肌组织代谢组学

尹春园¹^,², 孙明谦¹, 金龙¹, 林力¹, 苗兰¹, 刘建勋¹^,^*()

¹ 中国中医科学院西苑医院基础医学研究所, 中药药理北京市重点实验室, 北京 100091
² 北京中医药大学, 北京 100029

收稿日期:2019-07-15 出版日期:2020-02-08 发布日期:2020-12-10
通讯作者: 刘建勋
作者简介:刘建勋.Tel:(010)62835601, E-mail:liujx0324@sina.com
基金资助:
国家重点基础研究发展计划("973"计划)(2015CB554405);国家自然科学基金(81872992);国家自然科学基金(81673587);国家自然科学基金(81803770)

Rat serum and heart tissue metabolomics in myocardial ischemia based on liquid chromatography-mass spectrometry

YIN Chunyuan¹^,², SUN Mingqian¹, JIN Long¹, LIN Li¹, MIAO Lan¹, LIU Jianxun¹^,^*()

¹ Beijing Key Laboratory of Pharmacology of Chinese Materia Medica, Institute of Basic Medical Sciences of Xiyuan Hospital, China Academy of Chinese Medical Sciences, Beijing 100091, China
² Beijing University of Chinese Medicine, Beijing 100029, China

Received:2019-07-15 Online:2020-02-08 Published:2020-12-10
Contact: LIU Jianxun
Supported by:
National Basic Research Program of China ("973" Program)(2015CB554405);National Natural Science Foundation of China(81872992);National Natural Science Foundation of China(81673587);National Natural Science Foundation of China(81803770)

摘要/Abstract

摘要：

采用异丙肾上腺素诱导心肌缺血大鼠模型，使用液相色谱-质谱法检测血清和心肌中的内源性成分，应用软件对已鉴定的40余种目标成分进行靶向提取，用主成分分析（PCA）、有监督偏最小二乘法判别分析（PLS-DA）对代谢组学数据进行多维度统计分析，筛选潜在生物标志物。与对照组相比，在心肌缺血模型组大鼠血清、组织中检测出18个差异代谢物，涉及精氨酸和脯氨酸代谢、甘氨酸、丝氨酸和苏氨酸代谢、谷氨酰胺和谷氨酸代谢、牛磺酸和亚牛磺酸代谢等多条代谢通路。代谢产物可作为心肌缺血研究中的重要标志物，该研究结果有助于揭示心肌缺血的发病机制，可为临床疾病诊断提供思路。

关键词: 液相色谱-质谱, 生物标志物, 代谢组学, 心肌缺血

Abstract:

A rat model with isoproterenol (ISO)-induced myocardial ischemia was obtained. Liquid chromatography-mass spectrometry (LC-MS)was conducted on the serum and heart tissue metabolites of normal and model rats. Principal component analysis (PCA) and differentiation analysis of supervised partial least-squares method (PLS-DA) were applied to the metabolomics data for multidimensional statistical analysis, and the resulting biomarkers were screened. Compared with the normal group, 18 different endogenous metabolites in plasma and tissues were detected, including the products of arginine and proline metabolism; glycine, serine, and threonine metabolism; glutamine and glutamate metabolism; and taurine and hypotaurine metabolism. These metabolites can be used as important biomarkers for myocardial ischemia. The results of this study can help reveal the pathogenesis of myocardial ischemia and aid clinical diagnosis.

Key words: liquid chromatography-mass spectrometry (LC-MS), biomarkers, metabolomics, myocardial ischemia

尹春园, 孙明谦, 金龙, 林力, 苗兰, 刘建勋. 基于液相色谱-质谱联用技术的心肌缺血大鼠血清和心肌组织代谢组学[J]. 色谱, 2020, 38(2): 206-211.

YIN Chunyuan, SUN Mingqian, JIN Long, LIN Li, MIAO Lan, LIU Jianxun. Rat serum and heart tissue metabolomics in myocardial ischemia based on liquid chromatography-mass spectrometry[J]. Chinese Journal of Chromatography, 2020, 38(2): 206-211.

图/表 5

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Group	CK/(U/L)	LDH/(U/L)	CK-MB/(U/L)
CK: creatine kinase; LDH: lactate dehydrogenase; CK-MB: creatine kinase isoenzyme MB. ** Compared with control group, p＜0.01.
Control group	463±130	548±210	603±157
Model group	743±139^**	680±267	1167±243^**

Group	CK/(U/L)	LDH/(U/L)	CK-MB/(U/L)
CK: creatine kinase; LDH: lactate dehydrogenase; CK-MB: creatine kinase isoenzyme MB. ** Compared with control group, p＜0.01.
Control group	463±130	548±210	603±157
Model group	743±139^**	680±267	1167±243^**

No.	m/z	Biomarker	Pathways	Trend^*
No.	m/z	Biomarker	Pathways	Serum	Heart tissue
* Change trend compared with control group.
1	89.09	alanine	alanine, aspartate and glutamate metabolism	↑
2	175.19	citrulline	arginine and proline metabolism	↑
3	113.12	creatinine	arginine and proline metabolism	↓
4	131.13	hydroxyproline	arginine and proline metabolism	↓	↑
5	132.16	ornithine	arginine and proline metabolism	↑	↑
6	161.20	L-carnitine	carnitine synthesis	↑
7	117.15	betaine	glycine, serine and threonine metabolism	↓	↑
8	75.07	glycine	glycine, serine and threonine metabolism		↑
9	146.14	glutamine	glutamine and glutamate metabolism	↓	↓
10	147.13	glutamate	glutamine and glutamate metabolism	↓
11	105.09	serine	glutamine and glutamate metabolism		↑
12	188.22	n6-acetyl-L-lysine	lysine degradation		↓
13	297.33	5′-methylthioadenosine	methionine metabolism		↑
14	111.10	cytosine	pyrimidine metabolism		↑
15	376.36	riboflavin	riboflavin metabolism	↓	↑
16	125.15	taurine	taurine and hypotaurine metabolism	↓	↓
17	117.15	indole	tryptophan metabolism	↓
18	117.15	valine	valine, leucine and isoleucine degradation		↓

No.	m/z	Biomarker	Pathways	Trend^*
No.	m/z	Biomarker	Pathways	Serum	Heart tissue
* Change trend compared with control group.
1	89.09	alanine	alanine, aspartate and glutamate metabolism	↑
2	175.19	citrulline	arginine and proline metabolism	↑
3	113.12	creatinine	arginine and proline metabolism	↓
4	131.13	hydroxyproline	arginine and proline metabolism	↓	↑
5	132.16	ornithine	arginine and proline metabolism	↑	↑
6	161.20	L-carnitine	carnitine synthesis	↑
7	117.15	betaine	glycine, serine and threonine metabolism	↓	↑
8	75.07	glycine	glycine, serine and threonine metabolism		↑
9	146.14	glutamine	glutamine and glutamate metabolism	↓	↓
10	147.13	glutamate	glutamine and glutamate metabolism	↓
11	105.09	serine	glutamine and glutamate metabolism		↑
12	188.22	n6-acetyl-L-lysine	lysine degradation		↓
13	297.33	5′-methylthioadenosine	methionine metabolism		↑
14	111.10	cytosine	pyrimidine metabolism		↑
15	376.36	riboflavin	riboflavin metabolism	↓	↑
16	125.15	taurine	taurine and hypotaurine metabolism	↓	↓
17	117.15	indole	tryptophan metabolism	↓
18	117.15	valine	valine, leucine and isoleucine degradation		↓

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基于液相色谱-质谱联用技术的心肌缺血大鼠血清和心肌组织代谢组学

Rat serum and heart tissue metabolomics in myocardial ischemia based on liquid chromatography-mass spectrometry

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