Quantitative Redox Imaging Software

被引:53
|
作者
Fricker, Mark D. [1 ]
机构
[1] Univ Oxford, Dept Plant Sci, S Parks Rd, Oxford OX1 3RB, England
关键词
FLUORESCENT PROTEIN INDICATORS; FUNGUS MAGNAPORTHE-ORYZAE; RESONANCE ENERGY-TRANSFER; CYTOPLASMIC PH; MITOCHONDRIA; SUPEROXIDE; DISEASE; FLASHES; CPYFP; PROBE;
D O I
10.1089/ars.2015.6390
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
Significance: A wealth of fluorescent reporters and imaging systems are now available to characterize dynamic physiological processes in living cells with high spatiotemporal resolution. The most reliable probes for quantitative measurements show shifts in their excitation or emission spectrum, rather than just a change in intensity, as spectral shifts are independent of optical path length, illumination intensity, probe concentration, and photobleaching, and they can be easily determined by ratiometric measurements at two wavelengths. Recent Advances: A number of ratiometric fluorescent reporters, such as reduction-oxidation-sensitive green fluorescent protein (roGFP), have been developed that respond to the glutathione redox potential and allow redox imaging in vivo. roGFP and its derivatives can be expressed in the cytoplasm or targeted to different organelles, giving fine control of measurements from sub-cellular compartments. Furthermore, roGFP can be imaged with probes for other physiological parameters, such as reactive oxygen species or mitochondrial membrane potential, to give multi-channel, multi-dimensional 4D (x, y, z, t) images. Critical Issues: Live cell imaging approaches are needed to capture transient or highly spatially localized physiological behavior from intact, living specimens, which are often not accessible by other biochemical or genetic means. Future Directions: The next challenge is to be able to extract useful data rapidly from such large (GByte) images with due care given to the assumptions used during image processing. This article describes a suite of software programs, available for download, that provide intuitive user interfaces to conduct multi-channel ratio imaging, or alternative analysis methods such as pixel-population statistics or image segmentation and object-based ratio analysis.
引用
收藏
页码:752 / 762
页数:11
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