Maan Kiran, Baghel Ruchi, Bakhshi Radhika, Dhariwal Seema, Tyagi Ritu, Rana Poonam
Metabolomics Research Facility, Institute of Nuclear Medicine and Allied Sciences (INMAS), DRDO, S. K Mazumdar Road, Timarpur, Delhi-54, India.
Department of Biomedical Sciences, Shaheed Rajguru College of Applied Sciences for Women, University of Delhi, Delhi, India.
Mol Omics. 2022 Mar 28;18(3):214-225. doi: 10.1039/d1mo00399b.
The increasing threat of nuclear terrorism or radiological accident has made high throughput radiation biodosimetry a requisite for the immediate response for triage. Owing to detection of subtle alterations in biological pathways before the onset of clinical conditions, metabolomics has become an important tool for studying biomarkers and the related mechanisms for radiation induced damage. Here, we have attempted to combine two detection techniques, LC-MS and H NMR spectroscopy, to obtain a comprehensive metabolite profile of urine at 24 h following lethal (7.5 Gy) and sub-lethal (5 Gy) irradiation in mice. Integrated data analytics using multiblock-OPLSDA (MB-OPLSDA), correlation networking and pathway analysis was used to identify metabolic disturbances associated with radiation exposure. MB-OPLSDA revealed better clustering and separation of irradiated groups compared with controls without overfitting (-value of CV-ANOVA: 1.5 × 10). Metabolites identified through MB-OPLSDA, namely, taurine, creatine, citrate and 2-oxoglutarate, were found to be dose independent markers and further support and validate our earlier findings as potential radiation injury biomarkers. Integrated analysis resulted in the enhanced coverage of metabolites and better correlation networking in energy, taurine, gut flora, L-carnitine and nucleotide metabolism observed post irradiation in urine. Our study thus emphasizes the major advantage of using the two detection techniques along with integrated analysis for better detection and comprehensive understanding of disturbed metabolites in biological pathways.
核恐怖主义或放射性事故带来的威胁与日俱增,这使得高通量辐射生物剂量测定成为进行伤员分类紧急应对的一项必要手段。由于能够在临床症状出现之前检测到生物途径中的细微变化,代谢组学已成为研究生物标志物以及辐射诱导损伤相关机制的重要工具。在此,我们尝试结合液相色谱-质谱联用(LC-MS)和核磁共振氢谱(H NMR)两种检测技术,以获取小鼠在接受致死剂量(7.5 Gy)和亚致死剂量(5 Gy)照射后24小时尿液的综合代谢物谱。运用多块正交偏最小二乘判别分析(MB-OPLSDA)、关联网络分析和通路分析进行综合数据分析,以识别与辐射暴露相关的代谢紊乱。与未出现过拟合的对照组相比,MB-OPLSDA显示出受照射组有更好的聚类和分离效果(CV-ANOVA的p值:1.5×10)。通过MB-OPLSDA鉴定出的代谢物,即牛磺酸、肌酸、柠檬酸盐和2-氧代戊二酸,被发现是与剂量无关的标志物,进一步支持和验证了我们之前关于潜在辐射损伤生物标志物的研究结果。综合分析使代谢物的覆盖范围得以扩大,且在照射后尿液中观察到的能量、牛磺酸、肠道菌群、左旋肉碱和核苷酸代谢方面有更好的关联网络。因此,我们的研究强调了结合使用这两种检测技术以及综合分析的主要优势,以便更好地检测和全面理解生物途径中受干扰的代谢物。