Abstract
Despite an impressive growth in the business of research antibodies a general lack of trust in commercial antibodies remains in place. A variety of issues, each one potentially causing an antibody to fail, underpin the frustrations that scientists endure. Lots of money goes to waste in buying and trying one failing antibody after the other without realizing all the pitfalls that come with the product: Antibodies can get inactivated, both the biological material and the assay itself can potentially be flawed, a single antibody featuring in many different catalogues can be deemed as a set of different products, and a bad choice of antibody type, wrong dilutions, and lack of proper validation can all jeopardize the intended experiments. Antibodies endorsed by scientific research papers do not always meet the scientist's requirements either due to flawed specifications, or due to batch-to-batch variations. Antibodies can be found with Quality Control data obtained from previous batches that no longer represent the batch on sale. In addition, one cannot assume that every antibody is fit for every application. The best chance of success is to try an antibody that already was confirmed to perform correctly in the required platform.
Highlights
Based on feedback from about 10 years ago, scepticism and mistrust towards commercial antibodies was already commonplace
In contrast to 10 years ago when Western Blot (WB), ELISA and ImmunoHistoChemistry (IHC) were the most used assay types, at present antibodies are increasingly used in more sophisticated platforms such as flow cytometry, multiplex assays, immune-mass spectrometry and other capture-based assays as modern technologies have made them widely accessible
When an antibody is raised to an entire protein, it is easy to see how multiple parts of the protein will generate a collection of different specificities and affinities
Summary
Everest Biotech Ltd, Upper Heyford, OX25 5HD, UK v2 First published: 02 Oct 2014, 3:232 ( https://doi.org/10.12688/f1000research.4966.1) Latest published: 15 Oct 2014, 3:232 ( https://doi.org/10.12688/f1000research.4966.2)
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