Abstract

Lipopolysaccharide (LPS), an endotoxin molecule, has been used to induce inflammatory responses. In this study, LPS was used to establish an in vivo inflammation model in zebrafish for drug screening. We present an experimental method that conveniently and rapidly assesses the anti-inflammatory properties of drugs. The yolks of 3-day post-fertilization (dpf) larvae were injected with 0.5 mg/mL LPS to induce fatal inflammation. After LPS stimulation, macrophages were tracked by NR and SB staining and neutrophil migration was observed using the MPO:GFP line. Larval mortality was used as the primary end-point. Expression levels of key cytokines involved in the inflammatory response including IL-1β, IL-6, and TNF-α, were measured using quantitative reverse transcription polymerase chain reaction (RT-PCR). Macrophages and neutrophils were both recruited to the LPS-injected site during the inflammatory response. Mortality was increased by LPS in a dose-dependent manner within 48 h. Analyses of IL-1β, IL-6, and TNF-α expression levels revealed the upregulation of the inflammatory response in the LPS-injected larvae. Further, the anti-inflammatory activity of chlorogenic acid (CA) was evaluated in this zebrafish model to screen for anti-inflammatory drugs. A preliminary result showed that CA revealed a similar effect as the corticosteroid dexamethasone (DEX), which was used as a positive control, by inhibiting macrophage and neutrophil recruitment to the LPS site and improving survival. Our results suggest that this zebrafish screening model could be applied to study inflammation-mediated diseases. Moreover, the Traditional Chinese Medicine CA displays potential anti-inflammatory activity.

Highlights

  • Lipopolysaccharide (LPS) is an endotoxin molecule and the major constituent of the outer membrane of all Gram-negative bacteria [1]

  • We showed that the injection of LPS could induce the inflammatory responses via increasing the expression levels of the inflammatory cytokines including IL-1β, TNF-α, and IL-6

  • (B) Necrotic yolk; (C) yolk crenulation and cyrtosis; (D) swollen pericardium sac; (E) hemorrhagic pericardium; (F) death. (A) phosphate-buffered saline (PBS) injection was used for negative control while (G) un-treated zebrafish larvaes served as normal control

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Summary

Introduction

Lipopolysaccharide (LPS) is an endotoxin molecule and the major constituent of the outer membrane of all Gram-negative bacteria [1]. LPS elicits directly or indirectly multiple pathophysiological processes in vivo, such as metabolic changes, fever, multiple organ dysfunction syndrome (MODS), endotoxic shock, and death in extreme cases [2,3] These effects are associated with the stimulation of LPS to receptors which mediate the signaling cascades and lead to the activation of neutrophils and macrophages and the release of inflammatory cytokines such as IL-6, IL-8, and TNF-α [4]. Many experimental methods and animal models have been established for the determination of the numerous LPS-mediated biological effects on a host [9,10,11] These models fulfill many of the accepted requirements for developing anti- inflammatory strategies through genetics, immunology, and pharmacology. This study provided a novel model for the screening of anti-inflammatory agents

Results and Discussion
LPS Causes Abnormalities in Zebrafish Larvae
Comparision of Immersion and Injection for Inflammatory Responses
Tracking the Neutrophil Inflammatory Response using the MPO
Survival Rates
Stage for LPS Injection
Effect of LPS Injection Dose on Inflammation
Effect of Injection time for the Genes Expressions of Inflammation Cytokines
Effectiveness of CA on Reducing LPS-Induced Acute Inflammation in Zebrafish
Macrophage Recruitment is Reduced by CA Treatment
The Reduction of CA Treatment on Neutrophil Recruitment
Survival Analysis of CA-Treated Larvae
Discussion
Chemicals and Reagents
Zebrafish Embryo and Larvae Maintenance
Routes of Delivery
Neutral Red Staining
Sudan Black Staining
Timing of LPS Injection
LPS Injection Doses
Quantitative Real-Time PCR
Statistical Analysis
Conclusions

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