To identify vascular disruptor compounds (VDCs), this study utilized an in vivo zebrafish embryo vascular model in conjunction with a mouse endothelial cell model to screen a subset of the U.S. Environmental Protection Agency (EPA) ToxCast Phase I chemical inventory. In zebrafish, 161 compounds were screened and 34 were identified by visual inspection as VDCs, of which 28 were confirmed as VDCs by quantitative image analysis. Testing of the zebrafish VDCs for their capacity to inhibit endothelial tube formation in the murine yolk-sac-derived endothelial cell line C166 identified 22 compounds that both disrupted zebrafish vascular development and murine endothelial in vitro tubulogenesis. Putative molecular targets for the VDCs were predicted using EPA’s Toxicological Prioritization Index tool and a VDC signature based on a proposed adverse outcome pathway for developmental vascular toxicity. In conclusion, our screening approach identified 22 novel VDCs, some of which were active at nanomolar concentrations

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An important factor facilitating the application of zebrafish in biomedical research is high throughput screening of vertebrate animal models. For example, being able to model the growth of blood vessel in the vasculature system is interesting for understanding both the circulatory system in humans, and for facilitating large scale screening of the influence of various chemicals on vascular development. Compared to other models, the zebrafish embryo is an attractive alternative for environmental risk assessment of chemicals since it offers the possibility to perform high-throughput analyses in vivo. However the lack of an automated image analysis framework restricts high throughput screening. In this paper, we provide a method for quantitative measurements of zebrafish blood vessel morphology since it is difficult to assess changes in vessel structure by visual inspection. The method presented is generalized, i.e. it is not restricted to any specific chemically treated zebrafish, and can be used with wide variety of chemicals.

In this paper, we propose an approach to detect abnormalities in the vascular development of zebrafish embryos due to exposure to toxins. Morphological changes due to toxin exposure is modeled based on the proposed gradient weighted co-occurrence histogram of oriented gradients (gCo-HOG). These features are compared to more commonly used histogram of oriented gradients (HOG) features and Co-HOG features that utilizes spatial distribution of neighboring pixels to capture spatial structure. The features are used to train a linear SVM classifier to identify morphological changes in a dataset of zebrafish embryo images. Results show that proposed gCo-HOG based technique clearly outperforms HOG and Co-HOG features. The importance of descriptor lies in the fact that features are discriminative enough to capture subtle morphological changes between normal anatomy and toxin induced changes.