![]() ![]() Therefore, both low-abundance target protein levels, measured using sensitive immunodetection techniques, and high-abundance housekeeping protein levels, measured using less sensitive total protein staining techniques, can each be measured in their respective linear dynamic ranges. As a result, they exhibit good linearity in the common loading range of 10–50 μg of cell lysate. Total protein levels can be determined by staining the membrane with total protein stains, e.g., Coomassie, SYPRO Ruby, Flamingo, amido black, or Ponceau S.īecause total protein stains are less sensitive than antibody-based immunodetection, they are far less likely to result in an oversaturated signal. The use of total protein measurement for western blot loading controls (total protein normalization TPN) is a method devised to resolve the inherent difficulties with linearity in the immunodetection of both target and control proteins. Total Protein Normalization: The Better Alternative Common housekeeping proteins are upregulated in colorectal adenocarcinoma and hepatocellular carcinoma, making the total protein a better "housekeeper". Total protein normalization of HKPs yields consistent band intensities. Immunodetection measurements of housekeeping protein levels show poor linearity and do not accurately indicate cell lysate loading levels. The expression level of housekeeping proteins can change due to:ĭifferences in five candidate housekeeping proteins and total protein staining between tumor and non-cancerous tissues in the validation sample set. Variation in Housekeeping Protein (HKP) Expression Levels Furthermore, HKP expression levels may not be constant but instead vary with different experimental treatments and other factors. Thus, to detect the target protein of interest, large amounts of cell lysate may need to be loaded, resulting in overloading of HKPs, yielding oversaturated reference bands, out of their linear range. Unfortunately, housekeeping proteins are usually highly expressed, whereas target proteins are often expressed only in low abundance. Reliable assessment of the changes in target protein expression levels requires the measurement of both the target protein and the loading control protein in their linear dynamic ranges for immunodetection. ![]() Typically, a "housekeeping protein" (HKP) such as β-actin, β-tubulin, or GAPDH is used as a loading control, with the assumption that the expression levels of these proteins remains constant. Proper western blot normalization is required to show that the changes in band intensities correlate to the biological changes in your samples.Ĭonventional loading controls rely on consistent levels of a reference protein in each sample. Western blot normalization allows you to faithfully compare changes in protein expression by establishing the baseline needed to correct against common errors such as inconsistent sample preparation, pipetting error, and uneven protein transfer. Common blot-to-blot variations are accurately assessed by an internal loading control.All quantified targets' signal intensities fall within the linear range of the imaging system.The amount of protein loaded is proportional to the signal intensity.ipynb notebooks for details/example usage.A quantitative western blot accurately measures changes in protein expression by making relative comparisons between different treatments.Ī properly designed quantitative western blotting experiment ensures that: The pipeline is functional and accurate but slow old code is preserved to reflect analysis in. Note: updates needed for SDS-PAGE gel analysis (spotting assay approach is much faster/better implemented). This data is plotted and can be quantified for band intensities. Data for each slice is baselined given a user-specified baselining region. Then splits image into user-specified lanes/boxes, and the average intensity of every pixel per lane/band/blot/spot is calculated.įor gels, intensities have the option to be gaussian-weighted so that the middle of the gel band contributes more to the average than the outer edges, as other lanes in gels sometimes bleed into the lane of interest. Takes an input image which gets cropped by the user and converts to a grayscale numpy array using the Python Image Library (PIL). Currently implemented for protein and DNA gels/blots and yeast spotting assays. Simple python-based quantification software for simple biological images. ![]()
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