Western blotting is an important tool for researchers studying signal transduction and other processes where understanding the phosphorylation state of a protein is important for elucidating protein function. But some researchers are hesitant to use Western blotting to calculate the relative amount of phosphorylated to unphosphorylated protein.
In this article, I’ll cover the steps you can take to get accurate and reliable relative measurements of phosphorylated versus non-phosphorylated forms of the same protein using multiplex fluorescent Western blotting.

Multiplexing enables simultaneous detection of phosphorylated and non-phosphorylated protein. One of the great advantages of fluorescent detection is that it allows for multiplexing. With multiplexing, you can detect signal from multiple antibodies simultaneously, without needing to strip and re-probe the blot. The quantitative information from your Western blot will be more accurate and reliable. You just need to ensure your secondary antibodies are conjugated to different dies with non-overlapping spectra. We can help.
10 Tips to help Western blotting run more smoothly:
AZURE EXPERT TIP #1: Use primary antibodies from different host species to avoid cross-reactivity from the secondary antibodies.
A critical considerations when multiplexing a fluorescent Western blot is ensuring your secondary antibodies are highly specific for the target species. Even low levels of cross-reactivity can hamper the quality of your results.
Quick Tip: One way to ensure the specificity of your secondary antibodies is to add cross-adsorption step against the IgGs of the other species your primary antibodies are generated in.
AZURE EXPERT TIP #2: Use a robust imager with a wide dynamic range or else skip a lane between fluorescent molecular weight markers and samples.
If you are concerned that your molecular weight markers might be overloaded relative to your sample, skipping a lane can reduce bleed-over into the sample lanes. A wide dynamic range is necessary to detect weak bands alongside strong bands. One way to avoid this issue is to use an imager with a wide dynamic range, like Azure Biosystems Imagers. Azure Imagers allow you to use multiple binning options to collect more light.
AZURE EXPERT TIP #3: Choose low-fluorescence PVDF membranes.
Because nitrocellulose autofluorensces, PVDF is a better choice when using fluorescent detection. Azure offers pre-cut PVDF membranes to save you time in the lab. These low-fluorescence PVDF membranes are available in three sizes, and reduce background noise for improved sensitivity.
AZURE EXPERT TIP #4: Work fast!
To avoid artifacts from phosphatase activity after lysing your cells, it’s important to put samples with lots of phosphoproteins in protein loading buffer on ice as quickly as possible.
AZURE EXPERT TIP #5: Add phosphatase inhibitors to the lysis buffer when looking for phosphorylated proteins.
Along with working fast, phosphatase inhibitors help ensure will make sure that your signal is a true representation of the presence of the phosphoprotein of interest at the time you lysed your cells.
AZURE EXPERT TIP #6: Avoid using milk as a blocking buffer.
Milk as a blocking buffer interferes with phosphotyrosine detection. Tyrosine phosphorylation is one of the most common post-translational modifications (PTM). Optimizing your blocking buffer for detection of this PTM is important for obtaining high-quality data. We offer a blocking buffer optimized for fluorescent detection. If you’re studying cell signaling, this is bound to be important. That’s why it’s best to avoid milk altogether.
AZURE EXPERT TIP #7: Run duplicates or triplicates samples on the same gel.
Quantification requires reliable, reproducible data, and duplicating samples can help account for some of the variability inherent in Western Blotting. Running replicates on the same gel/blot ensures you understand the precision of your measurement.
AZURE EXPERT TIP #8: Do multiple runs, doing all samples each run.
Also make sure exposure time is the same. Otherwise statistical analysis will be difficult because data are not comparable.
AZURE EXPERT TIP #9: Ensure linearity for the most accurate quantitation
In order to obtain an accurate measurement from a Western blot, you need to ensure that the signal you detect is proportional to the amount of protein present, which is another way of saying that detection is in the linear range. However, because there are multiple steps in the process that can lead to signal saturation, there are several factors you can vary to optimize both signal saturation and dynamic range.
Azure Imaging Systems provide a broad, linear dynamic range to accurately detect strong and weak bands. The accuracy and linearity of the Azure Imagers and reagents allow you to be confident about differences you see in protein levels.
AZURE EXPERT TIP #10: Start by verifying that the amounts of sample you are using are in the linear range of your system.
To obtain the most robust quantitative Western blot data, we recommend generating a standard curve that covers the full range of sample amounts you will assess, and to test multiple replicates for each sample amount (Figure 4). When you graph signal intensity versus the sample amount, the linear portion of the graph will indicate how much protein you can load and be confident that the signal is proportional to the amount of protein.
Note that the linear range of your system should be determined for each antibody-protein pair.
Figure 2. Determining the linear range of your assay. A titration of HeLa lysate was loaded and probed for GAPDH. The system is linear at values below 5 µg.
How to optimize saturation and dynamic range
There are many different steps you can try if your signal is saturating below the highest amount of sample you need to assess. Check out these recommendations on how you can optimize saturation and dynamic range:
Optimize saturation / dynamic range | |
---|---|
Reduce the amount of sample | While this is an obvious first step, there are many situations where you may not be able to reduce how much sample you add. Never fear, keep reading for other solutions to try. |
Change your transfer conditions | The amount of protein a membrane can hold can saturate. If this step is limiting the performance of your Western blot, reducing transfer times may help. |
Titrate your primary antibody | Testing different antibody dilutions against your sample can give you information on the amount of antibody that delivers the widest dynamic range (Figure 5). |
Shorten your image acquisition time | Reducing the amount of time you expose your blot to the detector/image acquisition system may be all you need to do to get your signal into a linear range. |
Table 1. How to best optimize saturation and dynamic range
Normalize to total protein
In the past, housekeeping proteins were used for normalizing Western blots. Recent studies have highlighted unexpected variability in the amount of certain housekeeping proteins1-3. This is why many journals and Western blotting experts recommend using total protein normalization.
Total protein normalization (TPN) involves the use of a stain to visualize total protein, either before or after immunodetection, although not all protein stains are compatible with fluorescent detection.


Enter AzureRed, a Total Protein Stain designed to streamline and simplify TPN. With AzureRed, there’s no need to strip or destain the membrane—you simply add an extra wash step, and then visualize using the Cy3 channel. We’ll talk about the procedure and calculations involved and provide tips on analyzing phospho-proteins by Western blot in Part 2.
Additional blog posts on total protein:
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SOURCES
Ghosh R, Gilda JE, and Gomes AV. The necessity of and strategies for improving confidence in the accuracy of western blots. Expert Rev Proteomics. 2014 Oct; 11(5):549-60. PMCID: PMC4791038.
Thacker JS, et al. Total protein or high-abundance protein: Which offers the best loading control for Western blotting? Anal Biochem. 2016 Mar 1; 496:76-8. PMID: 26706797.
Fosang AJ and Colbran RJ. Transparency Is the Key to Quality. J Biol Chem. 2015 Dec 11; 290(50): 29692–29694. PMCID: PMC4705984.