It’s not you, it’s the antibody

One of the problems pervading life science research is that of antibody quality. Researchers know that ‘good’ antibodies which can boost a research project (in the way we all hope for) do exist- providing strong signals with low or no background. However it is openly acknowledged that not all antibodies are made equal. Some antibodies fail to detect their target protein, some fail in specific applications, some provide little above background noise. Sadly this isn’t all that uncommon and despite all the finger-crossing in the world, if you’re unlucky enough to be the road-tester for the ‘bad’ antibody it can set your research back weeks.

Over the past decade the issue of research use antibody quality has come increasingly to the fore, to the extent that a number of manuscripts detailing novel biomarkers were withdrawn from the Journal of Comparative Neurology as a result of mistaken results based on assumed antibody specificity with inadequate controls1. The artifactual binding of a monoclonal antibody in a type I diabetes study led to a shift in the research focus of this disease worldwide, before the results were discovered to be based on yet another example of a ‘bad’ antibody2.
This has led to calls from the research community for the publication of detailed information regarding antibody use and documentation of antibody specificity in scientific manuscripts, including controls and characterisation techniques used, along with the publication of antigen information and antibody lot numbers1, 3. This recognises that antibodies are not simple research reagents that always recognise the same thing; variability does occur from batch-to-batch in these animal-derived reagents.
Yale University professor David Rimm and colleagues published an algorithm for antibody validation by researchers prior to their use, suggesting the use of western blotting, immunoprecipitation, cytochemistry and histochemistry staining techniques and transfection and knockdown experiments in the validation of antibodies for research4. Yet, this is a hefty undertaking which understandably many researchers don’t have the time or money to put fully into place, particularly considering the already high costs research reagents. Shouldn’t manufacturer’s share some of this responsibility for validation? Meanwhile more and more ‘bad’ antibodies continue to pour onto the market5-7.
At Avacta Life Sciences all Affimer reagents are validated in-house by our expert validation team, testing multiple experimental controls in both protein-specific and whole cell samples across multiple applications. Affimer moledules are engineered affinity proteins which can be used as an antibody alternative to target proteins of interest in many applications, and as they are generated in recombinant systems there is no batch-to-batch variability. While every researcher must verify the use of the Affimer within their own experimental system, our rigorous testing and on-hand technical support are here to ensure the days of the ‘bad’ antibody experience are finally over.
1Saper CB (2005) An open letter to our readers on the use of antibodies. J. Comp. Neurol. 493(4), 477–8.
2Hansson SF, Korsgren S, Pontén F, Korsgren O (2013) Enteroviruses and the pathogenesis of type 1 diabetes revisited: cross-reactivity of enterovirus capsid protein (VP1) antibodies with human mitochondrial proteins. J. Pathol. 229(5), 719–28.
3Marx V (2013) Calling the next generation of affinity reagents. Nature Methods 10, 829-833.
4Bordeaux J, Welsh A, Agarwal S, Killiam E, Baquero M, Hanna J, Anagnostou V, Rimm D (2010) Antibody validation. BioTechniques 48(3), 197–209.
5Welsh AW, Lannin DR, Young GS, Sherman ME, Figueroa JD, Henry NL, Ryden L, Kim C, Love RR, Schiff R, Rimm DL (2012) Cytoplasmic estrogen receptor in breast cancer. Clin. Cancer Res. 18(1), 118–26.
6Lukinavi?ius G, Lavogina D, Gönczy P, Johnsson K (2013) Commercial Cdk1 antibodies recognize the centrosomal protein Cep152. BioTechniques 55(3), 111–4.
7Blow, N (2013) Antibody Validation: Whose Job is it?, Oct 23