State Key Laboratory of Radiation Medicine and Protection, School of Radiation Medicine and Protection, Soochow University, Suzhou, 215123, China.
Department of Public Health Surveillance and Evaluation, Shandong Center for Disease Control and Prevention, Jinan, 250014, China.
Sci Rep. 2024 May 21;14(1):11524. doi: 10.1038/s41598-024-62501-5.
The biological mechanisms triggered by low-dose exposure still need to be explored in depth. In this study, the potential mechanisms of low-dose radiation when irradiating the BEAS-2B cell lines with a Cs-137 gamma-ray source were investigated through simulations and experiments. Monolayer cell population models were constructed for simulating and analyzing distributions of nucleus-specific energy within cell populations combined with the Monte Carlo method and microdosimetric analysis. Furthermore, the 10 × Genomics single-cell sequencing technology was employed to capture the heterogeneity of individual cell responses to low-dose radiation in the same irradiated sample. The numerical uncertainties can be found both in the specific energy distribution in microdosimetry and in differential gene expressions in radiation cytogenetics. Subsequently, the distribution of nucleus-specific energy was compared with the distribution of differential gene expressions to guide the selection of differential genes bioinformatics analysis. Dose inhomogeneity is pronounced at low doses, where an increase in dose corresponds to a decrease in the dispersion of cellular-specific energy distribution. Multiple screening of differential genes by microdosimetric features and statistical analysis indicate a number of potential pathways induced by low-dose exposure. It also provides a novel perspective on the selection of sensitive biomarkers that respond to low-dose radiation.
低剂量暴露引发的生物学机制仍需要深入探究。本研究通过模拟和实验,探讨了 Cs-137γ射线源辐照 BEAS-2B 细胞系时低剂量辐射的潜在机制。通过蒙特卡罗方法和微剂量分析,构建了单层细胞群体模型,用于模拟和分析细胞群体中核特异性能量的分布。此外,还采用了 10×基因组单细胞测序技术,在同一辐照样本中捕获低剂量辐射对单个细胞反应的异质性。数值不确定性既存在于微剂量学中的特定能量分布中,也存在于辐射细胞遗传学中的差异基因表达中。随后,将核特异性能量分布与差异基因表达分布进行比较,以指导差异基因生物信息学分析的选择。在低剂量时,剂量不均匀性显著,剂量增加对应于细胞特异性能量分布的离散度降低。通过微剂量特征和统计分析对差异基因进行多次筛选,表明低剂量暴露诱导了多个潜在途径。这也为选择对低剂量辐射有反应的敏感生物标志物提供了新的视角。