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Published 27 May, 2021
Confirming antibody specificity is an essential part of assay development. The ability to accurately detect the analyte of interest, even at low expression levels, is critical to achieving reproducible results at every stage of the drug discovery pipeline. Therefore, assay validation is a continuous process, from initial assay development to applying the assay to a different sample or process further down the pipeline.
Experts have highlighted concerns that antibodies are often not specific enough for their intended use and can show cross-reactivity with off-target proteins1. Antibody specificity can be confirmed through extensive validation, increasing the quality and reproducibility of research findings. Thorough validation of antibodies used in assay development ensures high assay specificity, accelerating the process of getting effective treatments to the patients who need them.
Yet until recently, there was no accepted scientific framework for ensuring antibody specificity. In 2016, scientists from around the globe formed an International Working Group for Antibody Validation and outlined five key techniques, or pillars, to successfully validate research and therapeutic antibodies2.
Here, we discuss the five pillars, the advantages and disadvantages of each method, and how our solutions can increase assay specificity to achieve the high performance you need.
Antibody specificity can be assessed by comparing binding signals in cells expressing the target protein to control cells with the target gene knocked out by CRISPR or RNA interference (RNAi). A highly specific antibody should show no binding activity if the target isn’t there.
While RNAi can be used to suppress protein expression, the transient nature of RNAi combined with its inability to completely knock out critical genes means this approach can be unreliable.
Knock-out (KO) cell lines provide the most direct route to high antibody specificity and are often considered the gold-standard technique. Creating reliable KO cell lines can be a laborious process, but the availability of ready-made KO cell lines accelerates assay development and improves the viability of this strategy.
Orthogonal strategies involve assessing the target protein abundance using an antibody-independent assay, such as transcriptomics or targeted proteomics, and comparing the results with those obtained using antibodies across a range of relevant samples.
While this method can be quick thanks to high throughput analytical techniques, it relies on additional tools and technologies. What’s more, results from these kinds of secondary methods can be hard to interpret. For example, correlating transcriptomic data with antibody specificity can be particularly challenging because the relationship between mRNA and protein abundance is non-linear and often highly variable.
Assessing the antibody binding of two independent antibodies is another strategy to improve assay specificity. This method involves comparing the desired antibody with a second antibody that has a non-overlapping epitope on the same target protein.
While this technique provides easy verification and straightforward results, it relies on a suitable independent, validated antibody for comparison. Recombinant antibodies are particularly good for this strategy because they offer high batch-to-batch consistency, reliable ongoing supply, and high specificity.
Expressing the target protein with a fusion tag enables the determination of antibody specificity by comparing the signal from the antibody to the tag-specific signal. Examples include using an affinity tag such as c-Myc or His for biochemical assays or a fluorescence tag like green fluorescence protein (GFP) for microscopy or flow cytometry.
Similar to genetic strategies, this approach requires additional time and skill to express a tagged protein successfully. It can also be challenging to obtain or create a functional plasmid containing the protein and tag of interest.
The tag itself can also change the characteristics of the target protein, such as solubility or localization, leading to spurious results, and over-expression of proteins can generate false-positive signals due to non-specific binding.
Immunoprecipitation-mass spectrometry (IP-MS) involves isolating and analyzing all proteins bound by an antibody using immunoprecipitation from cell lysate followed by mass spectrometry, revealing the true target protein and also any off-target binding.
Although this is one of the best techniques for demonstrating antibody specificity and is amenable to high-throughput assays, it has several limitations.
Firstly, not all antibodies and targets are suitable for immunoprecipitation, and the protocol can be challenging to optimize. The results can also be skewed depending on the relative abundance and binding strength of target protein isoforms or related family members in the starting lysate.
Finally, it can be difficult to distinguish between signals from off-target binding and proteins that form complexes with the target, making the data difficult to interpret.
Implementing assay validation throughout your discovery pipeline can be an arduous and costly process, but it is essential to ensure reliable and reproducible results. We’re playing our part in tackling the reproducibility crisis and driving science forward by making antibody validation simple, whether you’re looking to buy antibodies off the shelf or validate your own.
To ensure unrivaled specificity and rapidly progress your discovery workflow, we validate our antibodies using the gold-standard approach of knock-out cell lines. If you chose to use an independent antibody approach, our wide range of more than 24,000 recombinant antibodies is likely to have a match for your target.
Additionally, our extensive portfolio of over 2,000 ready-made lines ensures you can rapidly find your specific knock-out for genetic validation strategies. With experience executing over 1,000 projects in 100+ distinct lines, our team can also engineer custom lines for even the most challenging project.
Determining antibody specificity is crucial to driving long-term success, and choosing high-quality, verified reagents will speed up the pipeline to discover new and exciting therapeutics.