基于代谢流分析的砷暴露致肺损伤的毒性机制研究

Arsenic exposure is an environmental and public health problem worldwide, which is closely related to the high risk of lung cancer. However, the mechanism of pulmonary toxicity induced by arsenic exposure is still unclear, and the mechanism of toxicity based on small molecule metabolites has not been carried out as far as we know. In our previous work, a novel pseudotargeted cellular metabolomics method has been preliminary established based on gas chromatography – massspectrometry and liquid chromatography - mass spectrometry, which covers more than 800 metabolites involved in glucose metabolism, amino acid metabolism, tricarboxylic acid cycle, nucleotide metabolism and lipid metabolism, etc. It is expectation to investigate the mechanism of pulmonary toxicity induced by arsenic exposure from the perspective of cellular metabolic reprogramming. On the basis of on our previous work, a metabolic flux analysis method with high sensitivity and high coverage will be developed in combination with stable isotope labeling technology, to study the "panorama" and "dynamic" changes of metabolites in bronchial epithelial cells exposed to arsenic at different doses and times, and further reveal the cellular metabolic reprogramming induced by arsenic exposure. In combination with the changes of cell phenotype, a correlation would be established in arsenic exposure dose/time - effect - metabolic network changes, to elucidate the toxicological mechanism of lung injury induced by arsenic exposure. The effect and biological functions of the selected potential exposure biomarker will be clarified through the metabolic perturbation analysis of the isotope labelling method. The implementation of this project will provide a method for the early warning and intervention of lung injury related to arsenic exposure, and a new perspective for the investigation of the toxicological mechanism related to exposure.

砷暴露是世界性环境和公共卫生问题，与肺癌发病风险密切相关。砷暴露的肺毒性机制尚不清楚。申请人前期初步建立了基于GC-MS和LC-MS的细胞拟靶标分析方法，覆盖了糖代谢、氨基酸代谢、三羧酸循环、核苷酸代谢和脂质代谢等800多个代谢物，以期从砷暴露引起的细胞代谢重编程视角探讨其肺毒性机制。在此基础上，本项目拟与稳定同位素标记技术结合，发展高灵敏、高覆盖的代谢流分析新方法，研究不同剂量、时间砷暴露的支气管上皮细胞代谢物“全景”、“动态”变化过程，揭示砷暴露引起的细胞代谢重编程，与细胞表型变化结合，建立砷暴露剂量/时间-效应-代谢网络变化之间的准确关联，阐明砷暴露致肺损伤的毒性机制；筛选潜在暴露生物标志物，通过对其作同位素标记代谢扰动分析，明确其作用与生物功能。本研究可为砷暴露相关风险预警及干预提供手段，为暴露相关毒性机制研究提供新视角。

砷暴露是世界性环境和公共卫生问题，与肺癌发病风险密切相关。砷暴露的肺毒性机制尚不清楚。本项目从代谢重编程入手，考察砷暴露相关风险及潜在机制。首先，针对代谢物常规方法分析通量不足和无法反映动态调控信息问题，以生物样本为研究对象，构建了基于气相色谱-质谱联用的快速代谢组学方法和代谢流分析方法，实现生物样本高通量分析及细胞代谢物动态变化过程研究。然后，构建了长期砷暴露肺癌细胞模型，系统分析其表型变化，发现砷暴露导致肺癌细胞铂类耐药且迁移和侵袭能力增强；基于构建的代谢组学新方法开展细胞代谢重编程研究，发现砷暴露引起肺癌细胞全局性代谢扰动，与细胞表型变化结合，阐明了砷暴露致肺癌细胞铂类耐药及进展的潜在机制，涉及能量代谢紊乱、脂肪酸氧化增强、生物合成异常和氧化应激等；定位关键代谢通路变化，初步明确了其作用与生物功能。鉴于三氧化二砷（ATO）在肿瘤治疗中的作用，研究发现ATO干预导致肺癌细胞凋亡，其潜在机制与ATO干预后肺癌细胞的紊乱能量供应机制逆转及多胺代谢活跃等相关。最后，基于代谢分子间的关联关系，引入“相对表达逆转”来测量代谢物比率的浓度变化，构建了基于机器学习的差异代谢网络，在识别关键代谢网络信号方面具有潜力，筛选的网络标志物预测性能良好。本研究为砷暴露相关风险预警及干预提供了理论依据，为暴露相关毒性机制研究提供了新视角。