There’s no getting around it: Selecting the right antibody can make or break your experiment. If the reagent you’ve selected binds indiscriminately to multiple targets or has low affinity for your protein of interest, it won’t matter if your experimental methodology is bulletproof and you executed the protocol flawlessly—you’ll still get inaccurate results.
Among antibodies to neuroscience-related proteins… as many as two-thirds of reagents do not work as recommended by manufacturers.
~ The antibodies don’t work! , Nature 2024
When you use an antibody reagent from a reputable vendor, it’s easy to assume it will perform as you expect and that your results will accurately characterize the presence of your target in your sample. Unfortunately, it’s not that straightforward.
The Antibodies Aren’t All Right
Time and again, independent groups have found that poor antibody quality is (largely) to blame for the reproducibility crisis. The Antibody Characterization through Open Science (YCharOS, pronounced ‘Icarus’) group, an initiative based in the laboratory of Distinguished James McGill Professor Peter McPherson at the Montreal Neurological Institute (The Neuro, McGill University), found in their initial analysis of over 600 antibodies to neuroscience-related proteins that over half of reagents do not work as recommended by manufacturers.1 With around 7.7 million research antibody products on the market, manufactured by nearly 350 global suppliers, this means there are potentially over five million research antibodies being sold today that won’t work as expected when used in experimentation.
That number alone is a scary prospect. But the most challenging part—and what keeps many researchers up at night—is that it’s often difficult or even impossible to tell if an antibody is working correctly using data from a single set of experiments. False positives or negatives can appear to reflect accurate results, and may even be published as such.
The truth is that no application is immune to bad antibody reagents. For example, YCharOS has found that over half of the antibodies recommended by manufacturers for western blot (WB) don’t work—they either don’t detect the intended target or detect unwanted proteins in addition to the target.
“There are thousands of journal articles out there—even those in highly reputable publications—that are, unfortunately, based on results from antibodies that don’t work,” says Carl Laflamme, PhD, YCharOS co-founder. “Of course, the authors don’t know their results are inaccurate, and many times, the papers have been cited in additional studies, further perpetuating the scientific reproducibility crisis.”
|
|
Laflamme experienced this first-hand in his postdoctoral research on amyotrophic lateral sclerosis (ALS), which is what ultimately inspired him to found YCharOS. While conducting research for his postdoctoral fellowship, he was surprised to find that all existing research on a gene suspected to contribute to the disease leveraged antibodies that didn’t actually bind to the protein target, based on testing conducted by him and his colleagues.
“When researchers use antibodies that don’t work, it’s not only a waste of time, it can cause confusion that will ultimately take even longer to untangle than if the research wasn’t published at all,” says Dr Riham Ayoubi, YCharOS Director of Operations. “This has been a problem for decades, and it can lead to delays in the development of potentially life-saving therapeutics. We’re hopeful that researchers are starting to recognize the issues, and that YCharOS can help them select reagents that work.”
How to Select the Right Antibody for Your Experiment
Recently, YCharOS published a paper in Nature Protocols describing an antibody characterization strategy to validate antibody performance in three of the most common applications—WB, immunoprecipitation, and immunofluorescence.2
As part of the initiative established in the paper, YCharOS is partnering with academic institutions and antibody manufacturers, including Cell Signaling Technology, to re-test commercially available antibodies.
“As part of our standard process to continually re-validate our antibodies, we worked with the YCharOS team and were pleased—but unsurprised—when every single CST reagent performed as we expected by WB when tested using their characterization platform,” said Srikanth Subramanian, PhD, Senior Scientist at CST.
With so much confusion in the industry, understanding antibody validation and selecting the right reagent for your experiment can be a daunting prospect. Approaching the task using a few straightforward principles can help ensure the antibody you choose will work in your experimental model.
Below are tips on how to choose an antibody you can trust:
1. Review the Vendor’s Application-Specific Validation Data
|
When starting a new research project, it may be tempting to breeze through antibody selection based on previous experience with a particular antibody. However, just because an antibody worked in one application doesn’t necessarily mean it will work in another. ~ Katherine (Katie) Crosby, Sr Director of Antibody Applications & Validation, CST |
What to look for in application-specific manufacturer data
| ⇒ |
Chromatin immunoprecipitation (ChIP): Immuno-enrichment of at least two known positive and one known negative target loci, showing a minimum-fold enrichment for known positive loci compared to known negative target loci with optimal signal-to-noise ratio (target loci immuno-enrichment in antibody:isotype control comparisons). |
| ⇒ | Immunohistochemistry (IHC): Clear, specific-staining localized to correct tissues, with minimal background, and appropriate positive and negative controls. |
| ⇒ | Immunofluorescence (IF): Correctly localized signal in cells, potentially in the context of a tissue, with minimial background noise, and appropriate positive and negative controls. |
| ⇒ | Flow Cytometry: Precise identification of cell populations based on protein expression levels, an optimal signal-to-noise ratio (S/N), and appropriate positive and negative controls. |
| ⇒ | Immunoprecipitation: Strong, specific signal for the target protein with minimal background noise, including proper positive and negative controls. |
| ⇒ | Western Blot (WB): Clear, specific band(s) at the correct target molecular weight, with minimal background, and proper positive, negative, and loading controls. |
2. Leverage Reliable Third-Party Data
|
"In addition to YCharOS, there are a number of reliable organizations out there that provide third-party validation data. Check with these organizations to see if the antibody you're considering using has been verified in the application and animal model you’re using by any of these third-party vendors.” ~ Carl Laflamme, PhD, YCharOS co-founder |
The following organizations are known for their reliability
3. Validate Your Experimental Model & Know Your Target
|
“Understanding your protein target(s) of interest and using proper controls are vital for experimental accuracy. This process confirms your results reflect the intended biological process and is critical for success. This means thoroughly reviewing existing research and databases to understand your target’s known functions, interactions, and expression levels that reflect the disease state of interest so you can design an experiment where any observed changes are directly related to the manipulation of your target protein and not due to extraneous variables or off-target effects." ~ Srikanth Subramanian, PhD, Senior Scientist, CST |
Questions to research when selecting and validating your experimental model
CST Antibodies Rise Above the Noise
At CST, we’ve always put antibody quality over quantity, and we’re incredibly proud to have more citations per antibody than any other vendor.
“Meticulous antibody validation is at the core of what we do, and it’s why CST antibodies have set the standard for reliable performance for over 25 years,” says Subramanian. “Based on our own validation experiments and through the testing of third-party organizations like YCharOS, we’re proud to guarantee that, when used as described on the datasheet using the recommended protocol, our antibodies work—the first time and every time.”
We’ve heard from researchers time and again that when they see the “CST blue” cap on their antibody vial, they know that it’s an antibody they can really trust. For over 25 years, our reagents have set the industry standard for reliable performance. We’re incredibly proud of this legacy, and it’s one that we plan to keep up for the next 25 years to come.
Select References
- Ayoubi R, Ryan J, Biddle MS, et al. Scaling of an antibody validation procedure enables quantification of antibody performance in major research applications. Elife. 2023;12:RP91645. Published 2023 Nov 23. doi:10.7554/eLife.91645
- Biddle MS, Virk HS. YCharOS open antibody characterisation data: Lessons learned and progress made. F1000Res. 2023 Oct 16;12:1344. doi: 10.12688/f1000research.141719.1. PMID: 37854875; PMCID: PMC10579855.
