基于代谢学和转录学的多omics集成揭示了辐射诱导的改变路径网络和潜在机制
Kiran Maan1,2, Ruchi Baghel1, Seema Dhariwal1
1Metabolomics Research Facility, Institute of Nuclear Medicine and Allied Sciences (INMAS), DRDO, Delhi, India.
NPJ systems biology and applications
|September 9, 2023
概括
这项研究整合了暴露于辐射的小鼠的多omics数据,揭示了新陈代谢和免疫反应的显著变化. 欧米克集成为了解辐射效应和识别生物标志物提供了一个强大的工具.
科学领域:
- 生物医学研究的研究.
- 辐射生物学 辐射生物学
- 系统生物学 系统生物学
背景情况:
- 多omics技术正在推动生物医学研究.
- 在辐射研究中,omics方法正在出现,用于生物标志物发现.
- 了解对辐射的生物反应对于分拣管理至关重要.
研究的目的:
- 通过综合的多组学方法,全面了解全身辐射 (TBI) 后的生物过程.
- 用转录学,代谢学和脂质学来识别辐射暴露的生物标志物.
- 探索对辐射的反应中的综合途径和分子相互作用.
主要方法:
- 来自暴露于1 Gy (低剂量) 和7.5 Gy (高剂量) TBI 的小鼠血液的组合多组分析 (转录组学,代谢组学,脂组学).
- 多变量分析用于组划分.
- 联合路径分析和STITCH互动用于路径和网络分析.
- 基因本体学和BioPAN用于途径预测.
主要成果:
- 通过多变量分析,高剂量 (HD) 辐射暴露与对照组明确划分.
- 在氨基酸,脂胆 (PC),脂乙醇胺 (PE),卡尼丁和特定基因 (例如,No2,Hmgcs2,Oxct2a) 中观察到显著的失调.
- 综合途径分析揭示了氨基酸,碳水化合物,脂质,核酸和脂肪酸代谢的变化,以及引起的免疫反应.
- 脂肪酸代谢途径基因 (Elovl5,Elovl6,Fads2) 在HD组中被特别预测.
结论:
- 综合的多学科方法提供了对TBI后的生物过程和分子相互作用的更深入理解.
- 这项研究代表了综合奥米克在辐射代谢学中的新应用.
- 奥米克集成是阐明辐射研究中的机制和相互作用的宝贵工具.
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