Here we describe a novel high-content chemically induced inflammation assay aiming at the identification of immune-modulatory bioactives. We have successfully combined automated microscopy with custom developed software scripts enabling automated quantification of the inflammatory response as well as further data processing, analysis, mining, and storage.
Zebrafish larvae are particularly amenable to whole animal small molecule screens1,2 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 proposed3-6, suggesting inflammation induction scenarios e.g. localized nicks in fin tissue, laser damage directed to the yolk surface of embryos7 or tailfin amputation3,5,6. 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) assay8 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::DsRED26,9 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.
Here we present a fully automated high-throughput screening strategy enabling identification of immune-modulatory compounds in a whole animal context. Thus allowing monitoring of an acute inflammatory response in vivo and in real time.
We provide a protocol to apply zebrafish as a valuable model organism for drug discovery or drug repurposing efforts, since drug effects on leukocyte recruitment to wounds can be studied with relative ease in the context of a fully functional innate immune system. The unique advantage of our approach is the fact that chemical wounding renders manual larvae manipulation obsolete, thus permitting automation and screening in a high-throughput format.
Additionally, adverse or toxic drug effects as well as strong off-target effects can be easily assessed with the proposed set-up. The FDA approved library however did not contain any toxic compounds at the given screening concentrations. Nevertheless, we propose for apparent toxic compounds to compare the available dataset (e.g. immune modulatory phenotype, drug concentration) between members of the same pharmacological substance class present in the tested library. Toxic members of a substance family, that otherwise exerts a promising immune modulatory phenotype, could be retested at lower concentrations, if need be.
We have demonstrated the possibility of categorizing drugs automatically according to their exerted immune-modulatory effect. Drugs belonging to the category of anti-inflammatory compounds could be validated in independent experiments, most of the compounds exerting their effect in a dose-dependent manner. Four compounds identified as potential pro-resolution drugs could thus far not be confirmed as such. It also indicates that this particular immune modulatory category is difficult to describe, since no drugs solely affecting resolution have so far been described in literature. However, 3 of the 4 retested drugs showed an anti-inflammatory trend at higher molar concentrations. Optimizing the empirically defined threshold criteria should help to reduce the number of false-positives.
Furthermore, the presented technique offers the possibility to be utilized for the identification of mutations in genes affecting leukocyte migratory behavior8.
Concluding, the proposed method can facilitate and accelerate drug discovery or drug repurposing efforts by yielding potential new lead structures with readily available information on drug tolerance, toxicity, dosage as well as potential off-target effects. Therefore, serving as a simple, cost- and time-saving strategy at early stages of drug development.
The authors have nothing to disclose.
We thank Nadeshda Wolf, Nadine Eschen and Susanne Delong for excellent animal husbandry. CW was supported by a PhD fellowship from the Helmholtz program ‘BioInterfaces international graduate school’ (BIFIGS). Further support was provided by a KIT-RISC grant and by a Marie Curie International Reintegration Grant within the 7th European Community Framework Program (PIRG07-GA-2010-267552) to CG. AHS was supported by BOLD (Biology of Liver and Pancreatic Development and Disease) – Marie Curie Initial Training Network (238821). UL was supported by Dopaminet FP7 (Seventh Framework Program) (223744).
Name of the reagent | Company | Catalogue number | Comments |
Dimethyl sulphoxide | Carl Roth GmbH & Co KG | A994.2 | |
Copper(II) sulphate anhydrous | Carl Roth GmbH & Co KG | PO23.1 | |
FDA approved drug library | Enzo Life Sciences | BML-2841-0100 | |
384 microwell plate Non-binding, μClear | Greiner | 781906 | black |
Olympus scan^R | Olympus | ||
Zephyr Compact Liquid Handling Workstation | Caliper |