*This will change the Lookup Table in this channel to a "heatmap" where "black" indicates no signal and "white" indicates that a pixel has a signal intensity of 100%. * On the menu bar select: “Image” -> “Lookup Tables” -> “Fire” *This will allow you to look at and manipulate just the "Red" or "ER-RFP" Channel in your image* * In the Channels Tool select "Color" from the dropdown menu and check "Channel 1" * Composite: combine colors (turn on and off individual colors) * Color: turn on and off individual colors ![]() * On the menu bar select: Image-> Color-> Channels Tool * On the menu bar select: Image-> Adjust-> Brightness/Contrast Adjust/optimize the brightness/contrast of each of your color channels** *Your cropped image should look like something like this:* * On the menu bar select: Image->Crop (The program will crop the image to the selected region) * click on your image and drag to select your rectangular region of interest (yellow box) * select the “square” tool (selected in the screenshot below) *To crop the image to the region you are interested in:* *Your Composite image should look like this:* * Make sure that “Create Composite” is checked as well as “Keep Source Images” * Select Emerald-ELP1 i from the dropdown for C2 (green). * Select ER-RFP i from the dropdown for C1 (red). * On the menu bar select: Image-> Color-> Merge Channels * On the menu bar select: “Image” -> “Lookup Tables” -> “Red” *To pseudocolor your image you will need to select a new Lookup Table:* ***(For practice, you can open the test images used in class last week: ER-RFP i and Emerals-ELP1 i found on the course Google Drive.)*** In FIJI: Start by opening your image files the pixel intensity correlations for an image. The COLOC2 pluggin also performs automatic thresholding of images, generates scatterplots and conducts statistical significance testing. This software package includes a pluggin called () which is able to calculate the pixel intensity correlation for an image using multiple methods including: Pearson, Manders, Costes and Li. This is most commonlu done using image analysis software, such as the FIJI/ImageJ software you will be using today. Today, the determining whether two molecules are "colocalized" in an image is most often determined through computational analysis of the overlapping (non-overlapping) signal distribution and intensity within an image. Images shown in (A) and (B) were superimposed using FIJI/ImageJ to highlight regions of signal overlap ( C). # Figure 2: Fluorescence images of transgenic HEK293T cells expressing (A) Emerald:ELP1-25 (golgi) and (B) ER-RFP (endoplasmic reticulum). The problem is that an intermediate color, indicating colocalization, is obtained only if the intensities of the two probes are similar. However, numerous results can be ambiguous. To accomplish this fluorescence images were digitally superimposed on top of one another and either visually inspected for regions of signal overlap or, in cases where tools for displaying multiple-channel fluorescence images were used, inspected for regions of "merge" color (when Red and Green images are overlaid, "merge" color is conventionally displayed as "yellow") suggestive of colocalization. # Figure 1: Schematic depiction of the spatial overlap of two probes (molecules) that display (A) no colocalization, (B) partial colocalization or (C) complete colocalization.įor decades the prevailing method for determining whether two molecules "colocalized" in an image relied on the visual evaluation of the distribution of fluorescently labeled molecules in images of cells. ![]() Fluorescence colocalization analysis-quantitative analysis of the overlap in the spatial distribution (also referred to as "co-occurrence") of two molecules/probes-is a powerful tool for determining whether two molecules localize to the same structure(s) in cells. ![]() In modern biological research, fluorescent microscopy is frequently used to examine the spatial distributions of molecules in cells. The spatial distribution of molecules in cells has significant impact on their function. **You will also need to download the test files from the BI227 google drive, ER-RFP i and Emerald-ELP1 i found on the course Google Drive.** **Please download the FIJI software (and not ImageJ) as it comes preloaded with plugins necessary for opening your images).* **In order to open your images and analyze colocalization you will need to download the following program: ImageJ/FIJI. The goal this week is to introduce you to one method for quantifying the kind of visual data you might collect during the course of lab this semester:ġ) Use image analysis software, ImageJ/FIJI, to quantify the distribution of colocalization of proteins in transgenic mammalian NIH3T3 cellsĢ) Identify the potential strengths and weaknesses of using this type of analysis in this system
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