| 气相色谱-质谱联用结合代谢组学方法研究不同极化状态下小胶质细胞的代谢差异 |
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| 引用本文： | 王彦,俞仲望,陈思,李玲,朱臻宇.气相色谱-质谱联用结合代谢组学方法研究不同极化状态下小胶质细胞的代谢差异[J].药学实践杂志,2015,33(3):226-230. |
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| 作者姓名： | 王彦 俞仲望 陈思 李玲 朱臻宇 |
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| 作者单位： | 第二军医大学 药学院药物分析学教研室, 上海 200433,第二军医大学 基础部神经生物教研室, 上海 200433,第二军医大学 药学院药物分析学教研室, 上海 200433,第二军医大学 药学院分析测试中心, 上海 200433,第二军医大学 药学院分析测试中心, 上海 200433 |
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| 基金项目： | 国家自然科学基金(81273474,31100765) |
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| 摘 要： | 目的 运用代谢组学方法阐明经典激活型(M1型)、选择活化型(M2型)和静息态小胶质细胞的代谢差异。方法 将体外培养小鼠小胶质细胞系(BV2)细胞,分为M1组、M2组和静息态组,用实时荧光定量聚合酶链反应(qRT-PCR)检测特异性mRNA的表达差异以确定细胞极化状态,采用基于气相色谱-质谱联用(GC-MS)技术的代谢组学方法阐明代谢变化。结果 发现M1型与静息态细胞的差异代谢物15个,M2型与静息态细胞的差异代谢物15个。结论 通过代谢组学方法可以找到小胶质细胞极化的差异代谢物,并解释其可能的极化机制,为神经退行性疾病的防治提供了理论依据。
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| 关 键 词： | 气相色谱-质谱联用 代谢组学 小胶质细胞 实时定量PCR |
| 收稿时间： | 2014/12/2 0:00:00 |
| 修稿时间： | 2015/3/17 0:00:00 |
Comparative analysis of different states of polarized BV2 cells by GC-MS combined with metabonomic technology |
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| WANG Yan,YU Zhongwang,CHEN Si,LI Ling and ZHU Zhenyu.Comparative analysis of different states of polarized BV2 cells by GC-MS combined with metabonomic technology[J].The Journal of Pharmaceutical Practice,2015,33(3):226-230. |
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| Authors: | WANG Yan YU Zhongwang CHEN Si LI Ling and ZHU Zhenyu |
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| Institution: | Second Military Medical University, Department of Pharmaceutical Analysis, School of Pharmacy, Shanghai 200433, China,Second Military Medical University Institute of Neuroscience and Key Laboratory of Molecular Neurobiology of the Ministry of Education, College of Basic Medical Science, Shanghai 200433, China,Second Military Medical University, Department of Pharmaceutical Analysis, School of Pharmacy, Shanghai 200433, China,Second Military Medical University Pharmaceutical Analysis Center, School of Pharmacy, Shanghai 200433, China and Second Military Medical University Pharmaceutical Analysis Center, School of Pharmacy, Shanghai 200433, China |
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| Abstract: | Objective To analyze the different metabolites of the classical activated(M1), alternatively activated(M2) and resting BV2 cells by metabolomics method. Methods The mRNAs of several potential biomarkers were determined by real-time PCR analyses to confirm the state of BV2 cells. Static GC-MS combined with metabolomics technology was used to analyze the metabolic changes. Results There were 15 biomarkers identified between the M1 group and the resting group, and 15 biomarkers were found in the M2 group and the resting group. Conclusion The present study provides an effective way to reveal the mechanism of the polarization of BV2 cell, and it might provide a theoretical basis to prevent or treat the neurodegenerative diseases. |
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| Keywords: | GC-MS metabonomic microglia cell RT-PCR |
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