Self-referencing optrodes for measuring spatially resolved, real-time metabolic oxygen flux in plant systems
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The ability to non-invasively measure metabolic oxygen flux is a very important tool for physiologists interested in a variety of questions ranging from basic metabolism, growth/development, and stress adaptation. Technologies for measuring oxygen concentration near the surface of cells/tissues include electrochemical and optical techniques. A wealth of knowledge was gained using these tools for quantifying real-time physiology. Fiber-optic microprobes (optrodes) have recently been developed for measuring oxygen in a variety of biomedical and environmental applications. We have adopted the use of these optical microsensors for plant physiology applications, and used the microsensors in an advanced sensing modality known as self-referencing. Self-referencing is a non-invasive microsensor technique used for measuring real-time flux of analytes. This paper demonstrates the use of optical microsensors for non-invasively measuring rhizosphere oxygen flux associated with respiration in plant roots, as well as boundary layer oxygen flux in phytoplankton mats. Highly sensitive/selective optrodes had little to no hysteresis/calibration drift during experimentation, and an extremely high signal-to-noise ratio. We have used this new tool to compare various aspects of rhizosphere oxygen flux for roots of Glycine max, Zea mays, and Phaseolus vulgaris, and also mapped developmentally relevant profiles and distinct temporal patterns. We also characterized real-time respiratory patterns during inhibition of cytochrome and alternative oxidase pathways via pharmacology. Boundary layer oxygen flux was also measured for a phytoplankton mat during dark:light cycling and exposure to pharamacological inhibitors. This highly sensitive technology enables non-invasive study of oxygen transport in plant systems under physiologically relevant conditions.
KeywordsOptrode Self-referencing Rhizosphere Phytoplankton
The authors would like to thank the National Science Foundation for funding this research.
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