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

Abstract

BackgroundReactive 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. ObjectivesOur 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. MethodsTo 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. ResultsWe 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. DiscussionOur 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.