ProteoCool Pills#13: Densitometric Protein quantification from SDS-page using the Image J free software package

 Several different methods are currently available to perform quantification of purified recombinant proteins and antibodies

There is not a best, universal method, the provide a reliable result for all the proteins;  

Each methods have it some prons and cons and its applicability depend from the intrinsic properties of the target protein.

For example:

UV quantification that exploits the properties of aromatic amino acids (tryptophan and tyrosines) to absorb energy around 280 nm is fast and require limited amount of sample but cannot be performed with proteins that do not contain aromatic amino acids or with buffers with an intrinsic absorbance in the UV regions.

Colorimetric-fluorimetric assays as Bradford, BCA, Nanoorange are susceptible to buffer compositions (eg BCA is not compatible with reducing agents) and to extrapolate quantitative results, the comparison with a  calibration line is required Results may change a lot on the basis of the protein that is used to build the calibration line (generally BSA) because different proteins may show different response in function of their aminoacidic composition or stability of their conformation in presence of the dye.

gg: Bradford assay is less sensitive to full length antibodies (igG) than BSA (see fig 2 page 6 ) and therefore in case you would like to use Bradford assay to quantify a monoclonal antibody (mab) a calibration with a commercial mab is required.

In some unlucky cases, for those proteins that do not contain hydrophobic amino acid and shows low response to colorimetric assay (due to strong conformational stability of presence of post translational modifications, eg hyper glycosylation) all the previous methods may not be reliable and densitometric analysis from SDS-page may represent a simple and cheap alternative.

Quantitative densitometry of proteins from SDS-page stained with colorimetric reagents (eg  coomassie blue) require a software to perform image processing,  extrapolate peak area and correlate it with the sample concentration.

To date most of the commercial gel documentation systems are supplied with their Image analysis Software able to perform band intensity determination.

However, if those Gel acquisition systems are still essential for acquisition of agarose gel images, high quality images of SDS-page gels stained with Coomassie can be obtained using modern smartphone those carrying high resolution camera.

ImageJ (NIH), a public domain program from the National Institutes of Health downloadable at https://imagej.nih.gov/ij/download.html can be used to analyse the SDS-page images.

1. Open the gel image

On the gel selected for this example, we load several dilutions of a purified protein sample with unknown concentration (to be determined) and several know amount of BSA required to build a reference calibration curve

2. Select rectangle in the AREA SELECTION TOOL

3. Choose the 1^st  line, select the rectangle tool, and draw a box around the lane, 

making sure to include some of the empty gel between lanes and white space outside of the band. 

When creating the selection, drag with the shift key down to constrain it to a square.

4. Define the 1^st  line: Go to Analyze→Gels→Select first lane

      5. Select the 2^nd line

        Make sure your cursor shows as an arrow, grab the rectangle you just made, and drag it to the next lan

DO NOT DRAW NEW RECTANGLES! You must drag the same rectangle you just made because to compare the band you have to use the exact same size originally defined area in Lane 1.

6. Define the 2^nd line: Go to Analyze→Gels→Select next lane

 

7.  Repeat the step 5 and 6 since all the line (sample and standard dilutions) are selected and numbered

 8. Go to Analyze→Gels→Plot lanes 

 

A new windows containing an histograms for each line will appear

9. Drag two fingers on the mousepad to scroll up and down and navigate the grids

The peaks in each grid correspond to the intensity of the bands in the lane

 10.   On the ImageJ interface, select the "line" button (red arrow) to define the peak baseline

     11. Draw a line at the bottom of the peak that represents the baseline of your peak and it allow to define the area of the curve.

12. Drag two fingers on the mousepad to scroll down and keep drawing all the single lines to define the curves in your standard and protein of interest lanes.

 

  13. Once you draw a baseline for each peak, on the ImageJ interface, select the "magic wand" button (red arrow)

 

 14. Click on the line defining the area of the curve of the first peak

 A "Results" window containing the measured area will appear

  15. Drag two fingers on the mousepad to scroll down and define the area of all peaks with the defined baseline

16. In the Result window Go to File→Save as

ans Save your Results in .csv format so that you can transfer the measurements to excel to generate the standard curve (linear regression analysis) and determine the concentration of your protein sample.

A Possible mistakes:

When you draw the peak baselines (point 10-12), the line has to interpolate both “feet” of each peak 

to correctly define and measure the peak area. 

The same analysis could be used to determine band intensity and extrapolate dna or rna quantification from agarose gel. 

However in my opinion the limited linear range of densitometric analysis and low reproducibility in gel load and coloration make this quantification approach not very precise and have to be applied only when better alternatives (as 280nm quantification for DNA) are not available.