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开发一种自动形态测量方法以评估斑马鱼暴露于环境化学物质后的血管结局。

Development of an Automated Morphometric Approach to Assess Vascular Outcomes following Exposure to Environmental Chemicals in Zebrafish.

作者信息

Zhong Xiali, Chen Junzhou, Zhang Zhuyi, Zhu Qicheng, Ji Di, Ke Weijian, Niu Congying, Wang Can, Zhao Nan, Chen Wenquan, Jia Kunkun, Liu Qian, Song Maoyong, Liu Chunqiao, Wei Yanhong

机构信息

Guangdong Provincial Key Laboratory of Food, Nutrition and Health, Department of Toxicology, School of Public Health, Sun Yat-sen University, Guangzhou, China.

School of Intelligent Systems Engineering, Shenzhen Campus of Sun Yat-sen University, Shenzhen, China.

出版信息

Environ Health Perspect. 2024 May;132(5):57001. doi: 10.1289/EHP13214. Epub 2024 May 3.

DOI:10.1289/EHP13214
PMID:38701112
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11068156/
Abstract

BACKGROUND

Disruptions in vascular formation attributable to chemical insults is a pivotal risk factor or potential etiology of developmental defects and various disease settings. Among the thousands of chemicals threatening human health, the highly concerning groups prevalent in the environment and detected in biological monitoring in the general population ought to be prioritized because of their high exposure risks. However, the impacts of a large number of environmental chemicals on vasculature are far from understood. The angioarchitecture complexity and technical limitations make it challenging to analyze the entire vasculature efficiently and identify subtle changes through a high-throughput assay.

OBJECTIVES

We aimed to develop an automated morphometric approach for the vascular profile and assess the vascular morphology of health-concerning environmental chemicals.

METHODS

High-resolution images of the entire vasculature in zebrafish were collected using a high-content imaging platform. We established a deep learning-based quantitative framework, ECA-ResXUnet, combined with MATLAB to segment the vascular networks and extract features. Vessel scores based on the rates of morphological changes were calculated to rank vascular toxicity. Potential biomarkers were identified by vessel-endothelium-gene-disease integrative analysis.

RESULTS

Whole-trunk blood vessels and the cerebral vasculature in larvae exposed to 150 representative chemicals were automatically segmented as comparable to human-level accuracy, with sensitivity and specificity of 95.56% and 95.81%, respectively. Chemical treatments led to heterogeneous vascular patterns manifested by 31 architecture indexes, and the common cardinal vein (CCV) was the most affected vessel. The antipsychotic medicine haloperidol, flame retardant 2,2-bis(chloromethyl)trimethylenebis[bis(2-chloroethyl) phosphate], and -butylphenyl diphenyl phosphate ranked as the top three in vessel scores. Pesticides accounted for the largest group, with a vessel score of , characterized by a remarkable inhibition of subintestinal venous plexus and delayed development of CCV. Multiple-concentration evaluation of nine per- and polyfluoroalkyl substances (PFAS) indicated a low-concentration effect on vascular impairment and a positive association between carbon chain length and benchmark concentration. Target vessel-directed single-cell RNA sequencing of cells from larvae treated with , perfluorohexanesulfonic acid, or benzylbutyl phthalate, along with vessel-endothelium-gene-disease integrative analysis, uncovered potential associations with vascular disorders and identified biomarker candidates.

DISCUSSION

This study provides a novel paradigm for phenotype-driven screenings of vascular-disrupting chemicals by converging morphological and transcriptomic profiles at a high-resolution level, serving as a powerful tool for large-scale toxicity tests. Our approach and the high-quality morphometric data facilitate the precise evaluation of vascular effects caused by environmental chemicals. https://doi.org/10.1289/EHP13214.

摘要

背景

化学损伤引起的血管形成破坏是发育缺陷和各种疾病状态的关键风险因素或潜在病因。在数千种威胁人类健康的化学物质中,由于其高暴露风险,在环境中普遍存在且在普通人群的生物监测中被检测到的高度关注的化学物质组应被优先考虑。然而,大量环境化学物质对脉管系统的影响远未得到了解。血管结构的复杂性和技术限制使得通过高通量检测有效地分析整个脉管系统并识别细微变化具有挑战性。

目的

我们旨在开发一种用于血管轮廓的自动形态测量方法,并评估与健康相关的环境化学物质的血管形态。

方法

使用高内涵成像平台收集斑马鱼整个脉管系统的高分辨率图像。我们建立了一个基于深度学习的定量框架ECA-ResXUnet,并结合MATLAB对血管网络进行分割并提取特征。计算基于形态变化率的血管评分以对血管毒性进行排名。通过血管内皮基因疾病综合分析确定潜在的生物标志物。

结果

暴露于150种代表性化学物质的幼虫的全躯干血管和脑血管被自动分割,其准确性可与人类水平相媲美,灵敏度和特异性分别为95.56%和95.81%。化学处理导致由31个结构指标表现出的异质血管模式,并且共同主静脉(CCV)是受影响最严重的血管。抗精神病药物氟哌啶醇、阻燃剂2,2-双(氯甲基)三亚甲基双[双(2-氯乙基)磷酸酯]和磷酸丁基苯基二苯基酯在血管评分中排名前三。农药占比最大,血管评分为 ,其特征是对肠下静脉丛有显著抑制作用且CCV发育延迟。对9种全氟和多氟烷基物质(PFAS)的多浓度评估表明低浓度对血管损伤有影响,并且碳链长度与基准浓度之间呈正相关。对用全氟己烷磺酸或邻苯二甲酸苄丁酯处理的幼虫的细胞进行靶向血管定向单细胞RNA测序,以及血管内皮基因疾病综合分析,揭示了与血管疾病的潜在关联并确定了生物标志物候选物。

讨论

本研究通过在高分辨率水平上融合形态学和转录组学特征,为表型驱动的血管破坏化学物质筛选提供了一种新的范例,是大规模毒性测试的有力工具。我们的方法和高质量的形态测量数据有助于精确评估环境化学物质引起的血管效应。https://doi.org/10.1289/EHP13214。

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