Development of a Dynamic Network Model to Identify Temporal Patterns of Structural Malformations in Zebrafish Embryos Exposed to a Model Toxicant, Tris(4-chlorophenyl)methanol.

IF 6.8 Q1 TOXICOLOGY
Ashley V Schwartz, Karilyn E Sant, Uduak Z George
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引用次数: 0

Abstract

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.

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一个动态网络模型的发展,以确定斑马鱼胚胎结构畸形的时间模式暴露于模型毒物,Tris(4-氯苯)甲醇。
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胚胎的时空模式。通常,当这个过程中出现一个错误时,其他错误往往会同时出现。我们假设,随着时间的推移,调查这些异常的共同发生将产生关于化学品毒性模式的额外信息。在这里,我们使用环境污染物三(4-氯苯)甲醇(TCPMOH)作为模型毒物来评估暴露与斑马鱼胚胎共同发生发育异常之间的关系。我们提出了一种动态网络建模方法来研究TCPMOH暴露引起的异常共发生,包括心包水肿、卵黄囊水肿、颅畸形、脊柱畸形、延迟/失败的鳔膨胀和死亡率。与对照组相比,暴露于tcpmoh的样本显示异常发生率增加。这些异常被表示为动态网络模型中的节点。随着时间的推移,使用网络中心性评分来识别高发生率的异常。我们发现,在不同的暴露组中,异常共现的时间模式有所不同。特别是高TCPMOH暴露组比低TCPMOH暴露组更早出现异常共现。网络模型还显示,在所有TCPMOH暴露水平中,心包和卵黄囊水肿是最常见的关键节点,在进一步异常之前。总的来说,本研究引入了一个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。
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来源期刊
CiteScore
5.30
自引率
1.70%
发文量
21
审稿时长
10 weeks
期刊介绍: The Journal of Xenobiotics publishes original studies concerning the beneficial (pharmacology) and detrimental effects (toxicology) of xenobiotics in all organisms. A xenobiotic (“stranger to life”) is defined as a chemical that is not usually found at significant concentrations or expected to reside for long periods in organisms. In addition to man-made chemicals, natural products could also be of interest if they have potent biological properties, special medicinal properties or that a given organism is at risk of exposure in the environment. Topics dealing with abiotic- and biotic-based transformations in various media (xenobiochemistry) and environmental toxicology are also of interest. Areas of interests include the identification of key physical and chemical properties of molecules that predict biological effects and persistence in the environment; the molecular mode of action of xenobiotics; biochemical and physiological interactions leading to change in organism health; pathophysiological interactions of natural and synthetic chemicals; development of biochemical indicators including new “-omics” approaches to identify biomarkers of exposure or effects for xenobiotics.
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