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PixFRET, an ImageJ plug-in for FRET calculation which can ...

PixFRET, an ImageJ plug-in for FRET calculation which can ...

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controls as, under these experimental conditions, variations between cells are small <strong>an</strong>d allfluorescence <strong>in</strong>tensities are close to the average of the population used to calculate SBT ratios(Fig. 4A). The l<strong>in</strong>N<strong>FRET</strong> values are slightly higher due to the underestimation of the ECFPSBT <strong>for</strong> both low <strong>an</strong>d high ECFP <strong>in</strong>tensities (see Fig. 3A). The most dramatic effect is seenwhen N<strong>FRET</strong> is calculated <strong>for</strong> the <strong>in</strong>teraction between the two nuclear receptors. Indeed, themore accurate l<strong>in</strong>N<strong>FRET</strong> <strong>an</strong>d expN<strong>FRET</strong> <strong>calculation</strong>s signific<strong>an</strong>tly reduce st<strong>an</strong>dard deviation,with a more pronounced effect <strong>for</strong> expN<strong>FRET</strong>. In order to better characterize the reduction ofthe variability of the measurements when model<strong>in</strong>g SBT ratios, we plotted the differencebetween expN<strong>FRET</strong> or l<strong>in</strong>N<strong>FRET</strong> <strong>an</strong>d N<strong>FRET</strong> as a function of fluorophore <strong>in</strong>tensity (Fig.4B). In both cases, the highest variation was observed <strong>for</strong> extreme ECFP values <strong>for</strong> <strong>which</strong>us<strong>in</strong>g <strong>an</strong> average SBT ratio leads to a great under- or over-estimation of the correction factor(Fig. 4B <strong>an</strong>d 4C). The results obta<strong>in</strong>ed with l<strong>in</strong>N<strong>FRET</strong> <strong>an</strong>d expN<strong>FRET</strong> are hence not onlymore precise, but also improve the statistical properties of the data, allow<strong>in</strong>g to compare moreaccurately mild ch<strong>an</strong>ges. We also tried to fit the donor SBT with a 2 nd order polynomial modelrather th<strong>an</strong> <strong>an</strong> exponential growth, but this model greatly overestimates SBT values whendonor <strong>in</strong>tensities are very low or very high (data not shown).Pixel-by-pixel <strong>FRET</strong> <strong>an</strong>alysis <strong>an</strong>d visualizationCells are highly org<strong>an</strong>ized <strong>an</strong>d prote<strong>in</strong> distribution as well as <strong>in</strong>teractions are often limitedto specific compartments. It is hence crucial <strong>for</strong> biologists to be able to map <strong>in</strong>teractions withprecision with<strong>in</strong> a cell or a population of cells to better underst<strong>an</strong>d the spatial org<strong>an</strong>ization ofcellular activities. We there<strong>for</strong>e developed <strong>an</strong> <strong>ImageJ</strong> <strong>plug</strong>-<strong>in</strong> called "<strong>Pix<strong>FRET</strong></strong>" that allows togenerate normalized <strong>FRET</strong> images, by comput<strong>in</strong>g pixel by pixel the images of a sampleacquired <strong>in</strong> a three ch<strong>an</strong>nel sett<strong>in</strong>g. The <strong>plug</strong>-<strong>in</strong> allows either to enter m<strong>an</strong>ually SBTparameters <strong>for</strong> the donor <strong>an</strong>d the acceptor, or to determ<strong>in</strong>e these values onl<strong>in</strong>e us<strong>in</strong>g stacks of11

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