Speedy and detailed protein ID of SDS gel bands

Jun 9. 2020


Can I identify hundreds of gel bands in a few days?

The biopharmaceutical company I work for consistently uses SDS PAGE and Western Blotting to check protein expression. But this means we spend a great deal of money on antibodies, which I feel may be unnecessary. In addition, we would like to identify several unknown proteins in the gels, possibly degradation products.

Is there a fast and reproducible method to identify hundreds of gel bands within a few days?


If you develop or manufacture any protein-based biologic, you know it is essential to evaluate protein expression. Both to verify that the biopharmaceutical protein was produced in a sufficient amount and to investigate impurities co-produced by the host cell.

Fast protein ID of gel bands

The typical approach is to rely on one of these standard methods:

  • SDS-PAGE and Western Blotting (WB)


  • SDS-PAGE and In-gel digestion/mass spectrometry

The WB method is fast and easy to run if you have the antibody needed to recognize the drug product. However, since this approach depends on antibodies and their specificity toward the target protein, there is a degree of uncertainty [1].

Also, you should be aware that you rely on a constant antibody supply, making it costly when you have many samples. And it is vulnerable since you cannot analyze if you run out of antibodies. Furthermore, the antibodies (probably) will not cover the degradation products or other unknown proteins, making the approach incapable of identifying proteins in the sample beside the drug product [1, 2].

protein id from gel

Therefore, it makes sense to apply a method that runs without antibodies – and can take a high number of samples within a short time (hours and days). Some companies thus benefit from protein ID /confirmation by in-gel digestion and mass spectrometry (LC-MS). However, this requires more time than SDS-PAGE and WB – at least for traditional ways of setting up the method [1-3].

Improved speed and lower cost of running protein ID of gel-bands

Luckily, there is a way to reduce the time it takes to identify proteins in large numbers of gel bands using NanoLC-MS/MS: Adding an EVOSEP® one instrument in front of the mass spec instrument reduces the run time to 25% of traditional protein ID LC-MS. The gradient is 4x shorter without compromising protein detection and identification.

The setup combines robotic automation of the in-gel protein digestion and sample preparation for LC-MS. This results in higher speed, which is one of the most significant advantages compared to standard methods.

Furthermore, the approach overcomes problems with carryover, which is sometimes an issue with traditional LC-MS analysis [1-3]. We can thus increase reproducibility and sample throughput.

Identify impurities and degradation products

You will also obtain an overview of all proteins in your samples – not only confirming the drug product presence. You can even identify process-related impurities, such as residual protein added as part of the process development or host cell protein originating from the expression system (CHO, yeast, E. coli, etc.) used to produce the active pharmaceutical ingredient (API).

Finally, 20-80 percent sequence coverage is easily obtained and may be enough to distinguish isoforms and protein/peptide variants from each other. And the approach even identifies degradation products. This is because it does not rely on antibodies but determines all proteins in the sample independently of the process or the expression system.

Increase protein concentration on PVDF membrane


[1]          Luque-Garcia et al.: “Analysis of electroblotted proteins by mass spectrometry: protein identification after Western blotting,” Mol Cell Proteomics, 2008

[2]          Lahm HW, Langen H.: “Mass spectrometry: a tool for the identification of proteins separated by gels,” Electrophoresis, 2000

[3]          Ranjan AK, Gulati A: “Two-Dimensional Electrophoresis and Mass Spectrometry for Protein Identification,” Methods Mol Biol, 2019

Thomas Kofoed, Alphalyse
Thomas Kofoed, PhD

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