Quantitative Westerns: What is the Best Way to Normalize your Western blot?

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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 your detection method and normalizing the data to control for variations in protein load and membrane transfer, you can get truly quantitative results.

But what is the best way to normalize protein levels for a Western blot? In the past, the gold standard normalization method was to use a housekeeping protein based on the assumption that the levels of these proteins are fairly consistent across experimental conditions and cell lines. However more recent studies have shown that this assumption is not always true1,2 leading to inaccurate measurements of relative protein abundance. Instead, quantitative Western blotting experts1,2 and the journals they publish in4 are recommending a new gold standard for normalization—normalizing to total protein detected in each lane, preferably by staining on the membrane.

Housekeeping protein vs. total protein

Challenges to using Housekeeping Proteins for Normalization

Inconsistent levels

The most significant drawback of using housekeeping proteins is that their levels may not be consistent across samples and conditions.1,2 It is possible to use a housekeeping protein for normalization, but you must first spend the time and effort to validate your choice, and may need to examine multiple potential standards before you find one that is truly expressed at the same level across all of your samples and does not change across your experimental conditions.

High abundance

A second significant challenge associated with housekeeping proteins is their high abundance.1,3 If the housekeeping protein is present at a very high level in your sample, this limits the amount of sample you can load on the gel because you will need to keep the housekeeping protein within the linear range of detection and not saturate the signal for the housekeeping protein. This is particularly problematic if the protein of interest is not similarly highly expressed because the two proteins will not be within the same linear range of detection.2,3

Generating primary and secondary antibodies from non-overlapping species is difficult

A third challenge to consider if you’re doing multiplex Western blots—such as comparing phosphorylated and non-phosphorylated forms of the same protein—is the complexity of generating primary and secondary antibodies from non-overlapping species.

It is always possible that detecting the housekeeping protein could interfere with detection of the protein of interest.1 Ideally, the housekeeping protein should be a different size than the protein of interest so the two proteins are spatially resolved on the blot. This becomes increasingly difficult when an experiment examines multiple proteins of interest on the same blot.

Using Total Protein Staining for Normalization

With total protein normalization, instead of trying to find a protein that can represent the total amount of sample that transferred to the membrane, total protein is measured on the membrane directly and this value is used as the denominator when normalizing.1-4 Many total protein stains are available that can be used to stain gels and membranes.1 Total protein stains provide a larger dynamic range and demonstrate lower variability and cleaner data than housekeeping proteins.1,2

 

Total protein normalization can be much faster than using a housekeeping protein, especially for chemiluminescent blots because the staining step takes less time that stripping and reprobing the blot. Ideally, total protein staining is conducted on the membrane, either before or after immunodetection.2 With some stains such as AzureRed Fluorescent Total Protein Stain, it is possible to stain the blot before immunodetection and then to image total protein simultaneously with the protein(s) of interest.  With this simplest of workflows, images for the protein(s) of interest and total protein are automatically aligned, avoiding the need resize and align images captured at different times.

The analysis workflow after image capture is essentially unchanged compared to using a housekeeping protein; the signal density for the entire lane or a large portion of the lane is used for normalization instead of the density for a single band.

Staining the membrane with a total protein stain provides an added quality control benefit, allowing verification that membrane transfer was complete and free of artifacts.

Frequently Asked Questions

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 done by incubating the membrane with a total protein stain. Read more

TPN uses the entire protein content of each sample for normalization instead of relying on only a single housekeeping protein. You can see an example of total protein staining here.

AzureRed is a perfect choice for staining applications, including post-transfer staining to confirm uniform protein transfer from gel to membrane, and
staining quantitative Western blots as part of a TPN protocol. Read more

Azure offers a 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, you simply treat your blots with TotalStain Q between protein transfer and blocking, and process them as you would normally. Read more

 

SOURCES

  1. Moritz CP. Tubulin or not tubulin: heading toward total protein staining as loading control in Western blots. Proteomics. 2017;17:1600189.
  2. Thacker JS et al. Total protein or high-abundance protein: which offers the best loading control for Western blotting? Anal Biochem. 2016;496:76-78.
  3. McDonough AA et al. Considerations when quantitating protein abundance by immunoblot. Am J Cell Physiol. 2015;308(6):C426-C433.
  4. Fosang AJ, Colbran RJ. Transparency is the key to quality. J Biol Chem. 2015;209(50):29692-29694.

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