New insights into organ-specific oxidative stress mechanisms using a novel biosensor zebrafish

Background: Reactive oxygen species (ROS) arise as a result from, and are essential in, numerous cellular processes. ROS, however, are highly reactive and if left unneutralised by endogenous antioxidant systems, can result in extensive cellular damage and/or pathogenesis. In addition, exposure to a wide range of environmental stressors can also result in surplus ROS production leading to oxidative stress (OS) and downstream tissue toxicity. Objectives: Our aim was to produce a stable transgenic zebrafish line, unrestricted by tissue-specific gene regulation, which was capable of providing a whole organismal, real-time read-out of tissue-specific OS following exposure to a wide range of OS-inducing environmental contaminants and conditions. This model could, therefore, serve as a sensitive and specific mechanistic in vivo biomarker for all environmental conditions that result in OS. Methods: To achieve this aim, we exploited the pivotal role of the electrophile response element (EpRE) as a globally-acting master regulator of the cellular response to OS. To test tissue specificity and quantitative capacity, we selected a range of chemical contaminants known to induce OS in specific organs or tissues, and assessed dose-responsiveness in each using microscopic measures of mCherry fluorescence intensity. Results: We produced the first stable transgenic zebrafish line Tg (3EpRE:hsp70:mCherry) with high sensitivity for the detection of cellular RedOx imbalances, in vivo in near-real time. We applied this new model to quantify OS after exposure to a range of environmental conditions with high resolution and provided quantification both of compound- and tissue-specific ROS-induced toxicity. Discussion: Our model has an extremely diverse range of potential applications not only for biomonitoring of toxicants in aqueous environments, but also in biomedicine for identifying ROS-mediated mechanisms involved in the progression of a number of important human diseases, including cancer.