Facilitating Drug Discovery: An Automated High-content Inflammation Assay in Zebrafish

Zebrafish larvae are particularly amenable to whole animal small molecule screens(1,2) due to their small size and relative ease of manipulation and observation, as well as the fact that compounds can simply be added to the bathing water and are readily absorbed when administered in a <1% DMSO solution. Due to the optical clarity of zebrafish larvae and the availability of transgenic lines expressing fluorescent proteins in leukocytes, zebrafish offer the unique advantage of monitoring an acute inflammatory response in vivo. Consequently, utilizing the zebrafish for high-content small molecule screens aiming at the identification of immune-modulatory compounds with high throughput has been proposed(3-6), suggesting inflammation induction scenarios e.g. localized nicks in fin tissue, laser damage directed to the yolk surface of embryos(7) or tailfin amputation(3,5,6). The major drawback of these methods however was the requirement of manual larva manipulation to induce wounding, thus preventing high-throughput screening. Introduction of the chemically induced inflammation (ChIn) assay(8) eliminated these obstacles. Since wounding is inflicted chemically the number of embryos that can be treated simultaneously is virtually unlimited. Temporary treatment of zebrafish larvae with copper sulfate selectively induces cell death in hair cells of the lateral line system and results in rapid granulocyte recruitment to injured neuromasts. The inflammatory response can be followed in real-time by using compound transgenic cldnB::GFP/lysC::DsRED2(6,9) zebrafish larvae that express a green fluorescent protein in neuromast cells, as well as a red fluorescent protein labeling granulocytes. In order to devise a screening strategy that would allow both high-content and high-throughput analyses we introduced robotic liquid handling and combined automated microscopy with a custom developed software script. This script enables automated quantification of the inflammatory response by scoring the percent area occupied by red fluorescent leukocytes within an empirically defined area surrounding injured green fluorescent neuromasts. Furthermore, we automated data processing, handling, visualization, and storage all based on custom developed MATLAB and Python scripts. In brief, we introduce an automated HC/HT screen that allows testing of chemical compounds for their effect on initiation, progression or resolution of a granulocytic inflammatory response. This protocol serves a good starting point for more in-depth analyses of drug mechanisms and pathways involved in the orchestration of an innate immune response. In the future, it may help identifying intolerable toxic or off-target effects at earlier phases of drug discovery and thereby reduce procedural risks and costs for drug development.