Mecanismo: la contratación laboral temporal

Colocalisation immunofluorescence describes the spatial overlap of signals at a pixel location from two or more different fluorophores. These fluorophores are attached to antibodies which bind to specific proteins of interest, and provides information as to whether two targets are located in the same cellular space (157). Colocalisation doesn’t directly prove that two proteins are interacting, but it does provide valuable information about their characteristics. This technique is most often used to determine whether proteins are associated with cellular structures e.g. those located to endosomes, mitochondria etc., or those located to specific nuclear structures such as the nucleolus or in nuclear speckles, or to suggest interaction between two proteins. Colocalisation describes co-occurrence of signal in the same pixel location and their correlation. It is common in the literature, for colocalisation studies to investigate the overlap of two entities labelled with red and green fluorophores and identify yellow colocalised areas without any further analysis. Although appropriate for some incidences for example when the colocalisation is obvious to the eye, when colocalisation is more subtle or when one entity is stained more intensely and masks the other, the use of an automated method with the

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ability to quantify colocalisation may be appropriate. This has the added advantage of not being subjective or misleading, and results in consistency in analysis

between images. Provided images are uniform in their acquisition or the

colocalisation calculation used eliminates any potential human variation, accurate quantification of colocalisation can be obtained. Special attention must be paid to ensure:

 Z-stacks are acquired and analysis is performed on a slice of the image  pixels are not saturated (by lowering the gain)

 background is greatly reduced

 chromatic aberration (when the lens distorts and fails to focus the colours on the same point) is avoided or corrected.

3.1.5 Colocalisation coefficients

There are two metrics typically used in quantifying protein colocalisation; the Pearson’s correlation coefficient and the Mander’s overlap coefficient. These are used to quantify the degree of colocalisation between fluorophores by correlation, and the two calculations possess subtle differences in how they are measured. The Pearson’s correlation coefficient (158) is robust and well characterised method widely used to measure correlations, but its use in fluorescence is a relatively recent occurrence (159). It measures the linear correlation between two variables and generates a value of between +1 and -1, where +1 signifies total correlation, 0; no correlation and -1; total negative correlation. In the context of immunofluorescent colocalisation, it measures the level of colocalisation between two colour channels based on the intensity distribution between them. It is

determined using the following calculation (157), which assumes the two channels are red and green:

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Ri refers to the intensity of the red channel in each pixel and likewise Gi represents intensity of the green channel in each pixel. R and G (with a horizontal line above) refer to the mean intensities of the red and green channels respectively across the whole defined region of interest (ROI). As this coefficient subtracts the mean intensity from pixel intensity, it is not influenced by signal levels and background (offset) (160). This makes it a preferable method for colocalisation when

comparisons between images are being made, as it is not affected by differences in image acquisition or processing (changes in gain and offset) and free from user bias. Its disadvantage however is that the data must follow a linear relationship in order to gain meaningful information from this coefficient. For example if red pixel intensity is increased, so is green pixel intensity. Generation of a simple scatterplot of red vs. green pixel intensity in the region of interest (ROI) on an image will determine linearity and the appropriateness of this calculation (157). The Mander’s coefficient is similar to the Pearson’s correlation coefficient and is calculated using the equation below (161):

Again Ri and Gi represent red and green pixel intensity respectively. It was

developed specifically for use in immunofluorescence to address the deficiencies of using the Pearson’s correlation, and eliminates the process of subtracting the average intensity values for the ROI from each pixel intensity value (160). This removed potential for negative values to arise, which are often confusing to

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is a measure of absolute intensity. It is a more complex interpretation of

colocalisation but is useful for data that does not follow a linear distribution. It is insensitive to variations such as efficiency of antibody binding, sample photo- bleaching or microscope differences. It also excludes areas where both probes are absent, so defining regions of interest would not be necessary, provided

background is eliminated. However alteration of the offset (background) does heavily influence the values. An accurate Mander’s coefficient would depend upon the user reliably and consistently eliminating all background. Manually interpreting what is or isn’t background could prove erratic especially when dealing with multiple images.

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3.2 Aims

To investigate ER protein expression in a range of breast cancer cell lines representing five major molecular groups by:

 establishing the expression patterns and cellular location of ERα, ERβ1 and ERβ2 protein using confocal immunofluorescence

 ascertaining whether cytoplasmic ERβ2 colocalises with mitochondria and quantifying levels of colocalisation in this organelle

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3.3 Methods

The following describes the analysis performed to determine ERβ2 and mitochondrial colocalisation. All other methods are described in chapter 2.

3.3.1 Colocalisation analysis

Colocalisation levels in each cell line were analysed as follows. An image slice from around the centre of the z-stack was selected. The cytoplasm of each cell was specified by manually drawing around the cytoplasmic region of each cell as depicted in Figure 3.1a. A scatter plot was created for each image to ensure the intensity distribution was linear, an example of this is illustrated in Figure 3.1b .A Pearson's correlation coefficient (PCC) was generated for each cell in the image and values were exported to an excel spreadsheet. Values from individual cells were plotted on a frequency distribution histogram, one for each cell line, using GraphPad Prism 6 software. This experiment was repeated at least three times and until a minimum of 30 cells from each cell line were analysed. This number proved sufficient as cumulative data analysis of colocalisation values for MDA-MB-231 was performed, whereby 30 cells was sufficient to result in stabilisation of histogram shape (appendix 7.4).

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Figure 3.1. Quantification analysis of ERβ2 and mitochondria colocalisation a) The cytoplasmic region was selected in each cell (MDA-MB-231 cells shown) by manually drawing around the cytoplasm, illustrated by the white arrow, using the region of interest (ROI) drawing tool in the Nikon A1R confocal elements software v3.2. Scale bar = 50µm

b) A red/green pixel intensity scatterplot was generated for each cell and a Pearson’s colocalisation coefficient value calculated by the software. Each dot on the plot represents a pixel with red and green staining. The yellow dotted line shows the linear relationship of pixel intensities.

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3.4 Results

3.4.1 Immunofluorescent analysis of ERα ERβ1 and ERβ2 expression in