Development of a Flow Injection Biosensor System Enables Glucose and Cortisol Simultaneous Measurement for the Evaluation of Fish Stress

Abstract

The continued growth of the aquaculture industry has led fish farmers to increase production capacity. Increasing production capacity requires high-density aquaculture and excess feeding, which are stressful to the fish and negatively affect fish health and immunity. Further, the accumulation of residual feed and excretions deteriorates the water quality of the aquaculture environment. Although medicine can be administered to the fish for disease prevention, there are concerns about the effects of the medicine that remain in the fish, which may be harmful to the consumer. Thus, a rapid and convenient, non-scheduled fish stress check would be an ideal solution. To evaluate fish stress, people always focus on the change of some plasma indicator, such as cortisol and glucose. Fish respond to stressors by the release of stress hormones such as cortisol. These stress hormones singly and in combination increase glucose production in fish. Because glucose is an important energy substrate for several tissues, the higher glucose production is thought to assist the animal in metabolically coping with the increased energy demand caused by stress. Currently, blood tests are performed to evaluate fish stress states. Conventional methods, such as enzyme-linked immunosorbent assay or colorimetric method, are both very time-consuming and costly, however, making it impractical to perform regular stress evaluations. On the other hand, cortisol, which is secreted rapidly after exposure to a stressor, is not easy to be detected. In addition, though glucose changes are easy to monitor, it may also arise after the feeding. Therefore, rather than measure both cortisol and glucose separately, simultaneous detection of both cortisol and glucose will enhance our understanding of fish stress conditions. In this study, we developed a flow injection biosensor system for measuring fish glucose and cortisol simultaneously. System schematic diagram was shown in the supplement image. For the glucose measurement, it was based on the decrease of the oxygen concentration detected by optical probe due to a glucose oxidation reaction. While, the measurement of cortisol based on competitive immunologic reactions, magnetic separation, and an electrochemical measurement. An anti-cortisol antibody was immobilised on magnetic beads and injected into the system. At first, the glucose concentration was detected first from the change on oxygen decrease by optical probe which immobilized glucose oxidase on its surface. After that, a specific quantity of acetylcholinesterase-labelled cortisol (cort-AChE) was injected into the flow system and the sample will go through a reaction coil as a competitive reaction unit. After reacting in the reaction coil, the sample was separated magnetically using a neodymium magnet. The cort-AChE was detached from the magnetic beads and transferred into the enzyme reaction unit with acetylthiocholine (ATCh). ATCh was hydrolysed by the cort-AChE to produce thiocholine. The thiocholine was quantified downstream by electrochemical detection using a Pt-Ir electrode. We also found that the performance of the proposed biosensor system was optimised under the following conditions: pH 7.5, temperature 25°C, flow rate 0.16 ml min− 1. After the understanding the optimal parameters, we performed the measurement on both glucose and cortisol. The fluorescence intensity was well correlated with the concentration of the cortisol standard solution (range: 0–30 mg dL− 1, R= 0.9785). While the output current was well correlated with the concentration of the cortisol standard solution (range: 0.06–40 ng mL− 1, R= 0.9812). The results obtained using the proposed flow method were compared with those obtained using conventional method (correlation coefficient was 0.9869 for glucose and 0.9848 for cortisol). These findings suggest that the proposed system can be used to analyse glucose and cortisol in fish plasma samples simultaneously and help us to understand the relationship between the stress hormone and glucose change. Figure 1