Science Forum: Antibody characterization is critical to enhance reproducibility in biomedical research

Department of Biochemistry, Emory University School of Medicine, United States
Department of Respiratory Sciences, University of Leicester, United Kingdom
Department of Neurology and Neurosurgery, Structural Genomics Consortium, The Montreal Neurological Institute, McGill University, Canada
The Development Studies Hybridoma Databank, University of Iowa, United States
The Michael J Fox Foundation for Parkinson’s Research, United States
Institute for Protein Innovation, United States
Department of Neurology, Emory University School of Medicine, United States
Department of Neurology and Program in Neuroscience, Harvard Medical School and Beth Israel Deaconess Medical Center, United States
Center for Open Science, United States
Department of Microbiology and Immunology, Stanford University School of Medicine, United States
Department of Neuroscience, University of California, San Diego, United States
Department of Physiology and Membrane Biology, University of California, Davis School of Medicine, United States
Addgene, United States
Frederick National Laboratory for Cancer Research, United States
Specifica, a Q2 company, United States
Department of Research and Development, Abcam, United Kingdom
CiteAb, United Kingdom

Aug 14, 2024

https://doi.org/10.7554/eLife.100211

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1 figure and 1 table

Figures

Figure 1

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Key projects related to antibody characterization.

Timeline showing when the projects discussed in this article were started: the Protein Capture Reagents Program and the Affinomics project were funded for five years (as indicated by dashed lines). CPTAC: Clinical Proteomic Tumor Analysis Consortium; FASEB: Federation of American Societies of Experimental Biology; HUPO: Human Proteome Organization; OGA: Only Good Antibodies; RRID: Research Resource Identifier; YCharOS: Antibody Characterization through Open Science.

Tables

Table 1

The ‘five pillars’ of antibody characterization.

In 2016 an ad hoc International Working Group for Antibody Validation introduced the five pillars of antibody validation/characterization: (i) genetic strategies; (ii) orthogonal strategies; (iii) (multiple) independent antibody strategies; (iv) recombinant strategies (originally called “expression of tagged proteins”); (v) capture MS strategies (Uhlen et al., 2016). In this table each pillar/strategy (left column) is followed by a brief description of the pillar/strategy, an indication of specificity, example applications for use, and pitfalls. Adapted from Waldron, 2022 and used with permission.

	Pillar/strategy	Description	Specificity	Example applications	Pitfalls
i	Genetic strategies	Knock-out/ knock-down target gene	High	WB, IHC, IF, ELISA, IP	Requires a genetically tractable system and awareness of potential confounders (such as alternative isoforms)
ii	Orthogonal strategies	Compare results from Ab-dependent and Ab-independent experiments	Varies	WB, IHC, IF, ELISA	Requires variable expression of the target and cannot entirely rule out non-specific binding to similar proteins
iii	Independent antibody strategies	Compare results from experiments using unique Abs to the same target	Medium	WB, IHC, IF, ELISA, IP	Requires the purchase of multiple Abs and knowledge of their epitopes
iv	Recombinant strategies	Experimentally increase target protein expression	Medium	WB, IHC, IF	Overexpression of exogenous protein can lead to overconfidence in the specificity of the Ab
v	Capture MS strategies	Use MS to identify protein captured by Ab	Low	IP	Requires access to MS and it can be challenging to distinguish between Ab binding target vs protein bound to target

Ab: antibody; ELISA: enzyme-linked immunosorbent assay; IF: immunofluorescence; IHC: immunohistochemistry; IP: immunoprecipitation; MS: mass spectrometry; WB: Western blotting.