Schwartz Ashley V, Sant Karilyn E, George Uduak Z
Computational Science Research Center, San Diego State University, San Diego, CA 92182, USA.
Department of Mathematics and Statistics, San Diego State University, San Diego, CA 92182, USA.
J Xenobiot. 2023 Jun 16;13(2):284-297. doi: 10.3390/jox13020021.
Embryogenesis is a well-coordinated process relying on precise cues and environmental signals that direct spatiotemporal embryonic patterning. Quite often, when one error in this process occurs, others tend to co-occur. We posit that investigating the co-occurrence of these abnormalities over time would yield additional information about the mode of toxicity for chemicals. Here, we use the environmental contaminant tris(4-chlorophenyl)methanol (TCPMOH) as a model toxicant to assess the relationship between exposures and co-occurrence of developmental abnormalities in zebrafish embryos. We propose a dynamic network modeling approach to study the co-occurrence of abnormalities, including pericardial edema, yolk sac edema, cranial malformation, spinal deformity, delayed/failed swim bladder inflation, and mortality induced by TCPMOH exposure. TCPMOH-exposed samples revealed increased abnormality co-occurrence when compared to controls. The abnormalities were represented as nodes in the dynamic network model. Abnormalities with high co-occurrence over time were identified using network centrality scores. We found that the temporal patterns of abnormality co-occurrence varied between exposure groups. In particular, the high TCPMOH exposure group experienced abnormality co-occurrence earlier than the low exposure group. The network model also revealed that pericardial and yolk sac edema are the most common critical nodes among all TCPMOH exposure levels, preceding further abnormalities. Overall, this study introduces a dynamic network model as a tool for assessing developmental toxicology, integrating structural and temporal features with a concentration response.
胚胎发生是一个协调良好的过程，依赖于精确的线索和环境信号来指导时空胚胎模式形成。通常，当这个过程中出现一个错误时，其他错误往往也会同时出现。我们假设，随着时间的推移研究这些异常的同时出现情况，将产生有关化学物质毒性模式的更多信息。在这里，我们使用环境污染物三（4-氯苯基）甲醇（TCPMOH）作为模型毒物，来评估斑马鱼胚胎暴露与发育异常同时出现之间的关系。我们提出一种动态网络建模方法来研究异常的同时出现情况，包括心包水肿、卵黄囊水肿、颅骨畸形、脊柱畸形、鳔充气延迟/失败以及TCPMOH暴露引起的死亡率。与对照组相比，暴露于TCPMOH的样本显示异常同时出现的情况增加。这些异常在动态网络模型中表示为节点。使用网络中心性得分识别随时间同时出现频率高的异常。我们发现，暴露组之间异常同时出现的时间模式有所不同。特别是，高TCPMOH暴露组比低暴露组更早出现异常同时出现的情况。网络模型还显示，心包和卵黄囊水肿是所有TCPMOH暴露水平中最常见的关键节点，先于进一步的异常出现。总体而言，本研究引入了一种动态网络模型作为评估发育毒理学的工具，将结构和时间特征与浓度反应相结合。
