Azure Biosystems
Normalization is often done by comparing the signal for the target protein to that of a “housekeeping protein.” A housekeeping protein is thought to be consistently expressed across different sample types. Its expression is believed to be unaffected by whatever intervention was carried out to produce the samples being compared.
Western blotting will tell you if your protein of interest is present in a sample. To determine if the amount of target protein is different between two or more samples, quantitative blotting is required. This involves:
However, experimental conditions may change the expression of some commonly used housekeeping proteins. The expression level of the housekeeping protein must be similar to that of the protein of interest, otherwise one of the two proteins may not be within the linear range of detection. If the signal for the housekeeping protein is saturated under conditions needed to detect the target protein, then the housekeeping signal is not useful for normalization.
Total protein normalization (TPN) avoids the pitfalls associated with housekeeping protein normalization. In TPN, the signal for the protein of interest is normalized to the total amount of protein loaded in the lane. TPN provides a larger useful dynamic range, is not dependent on the expression of a housekeeping protein being unaffected by experimental manipulations, and can provide additional information about the quality of electrophoresis and blotting.
Total protein stains are used for TPN and easily integrated into the Western blotting workflow. After transfer, the blot is stained with either a fluorescent or colorimetric stain before blocking and antibody detection of the target protein. Some stains are compatible with downstream detection. For example, AzureRed stain may be imaged with the 520nm laser, while one to three proteins may be detected using the other fluorescent channels (see Figure 1). TotalStain Q is compatible with downstream chemiluminescent or NIR detection. With other total protein stains, the Western blot may need to be imaged and then destained before blocking and antibody detection.
Azure’s range of imaging systems includes several models that allow target protein detection to be multiplexed with TPN– with no need for dedicated precast gels or laborious stripping and re-probing. Instead, treat your blots with TotalStain Q, between protein transfer and blocking, and process them as you would normally. The new Sapphire FL (using the 532 module), Azure 300Q and Azure 500Q are specifically designed to work with TotalStain Q.
For TPN with NIR Western blot detection, the Azure 500Q and the new Sapphire FL both provide detection of target analytes in the 700nm and 800nm channels, with a third channel used to measure TotalStain Q. Read more >>
The common practice for getting quantitative data from Western blots has been to normalize your band of interest to the signal from a housekeeping protein or to normalize to total protein. Read more about how to normalize your blot to total protein
Total protein normalization uses the entire protein content of each sample for normalization instead of relying on only a single housekeeping protein. Check out this example of total protein staining that shows detection of total protein in six identical samples of HeLa lysate before immunodetecting pSTAT3.
FREE WESTERN BLOT eBOOK
Best solution for sensitive near-infrared and ECL Western blots
Next generation laser-scanning system with unmatched flexibility and performance
Looking for a full list of applications?
Total protein normalization (TPN) is used to quantify the abundance of the protein of interest, without having to rely on housekeeping genes. It is usually
Far from being an “is-it-there-or-not” technique, modern digital detection instruments can make Western blotting reproducible and quantitative. By working within the linear dynamic range of
If you love Western blotting as much as we do, you’ll have noticed a growing trend toward using total protein staining rather than housekeeping proteins to normalize
