Discovering what works: Protein Capture Reagents Program (PCRP) sunsets with large-scale antibody validation
A substantial barrier for biomedical researchers is the lack of renewable reagents that can both strongly and specifically target a single protein type out of the tens of thousands found in human cells. Using reagents that do not meet these criteria can lead to rigor and reproducibility issues in biomedical research. The Common Fund’s Protein Capture Reagents Program (PCRP) aimed to develop and validate reagents that specifically targeted and held tightly onto the entire span of human proteins – also called the proteome. With validated reagents, researchers would have increased confidence when picking a reagent to use in their own studies and in reproducing the results of others. PCRP began by piloting a pipeline to generate reagents targeting a subset of proteins, transcription factors, before scaling to the entire human proteome. Transcription factors are proteins that recognize specific sequences of DNA and aid in the process of converting DNA into RNA. The program produced and validated a collection of approximately 1400 antibodies capable of targeting around 700 human transcription factors. However, the biomedical community expressed a need for additional validation of these antibodies under specific experimental conditions to encourage broader use of the reagents.
In response, researchers validated nearly all the program’s transcription factor antibodies in a high throughput version of the widely used chromatin immunoprecipitation (ChIP) sequencing lab procedure. They also validated a subset of the antibodies in several other popular experimental approaches for detecting interactions between transcription factors and DNA, in both cell-free and cell-based assays. Large-scale validation of antibodies as performed in this study is rare and therefore had not been performed in ChIP before. This work demonstrated the importance of experimental approach-specific validation to aid researchers in their antibody selection. It also showed how validation criteria for reagents like antibodies that recognize other molecular structures can be applied to a particular experimental technique, including consideration of how experimental variations may affect outcomes. The researchers have made their data publicly available to inspire broader use of the PCRP antibodies and encourage further research on antibody validation.
While PCRP ultimately did not produce reagents to target the entire human proteome, the program did identify important lessons learned while providing validated protein-targeting reagents in an area that previously lacked a substantiative number of them. An important finding is that large-scale generation of reagents to target proteins is possible, but high-throughput and systematic validation of these reagents may not be feasible nor necessary. Validation of reagents performed by individual labs for their own specific uses may be a better way to enhance rigor and reproducibility in biomedical research.
A ChIP-exo screen of 887 Protein Capture Reagents Program transcription factor antibodies in human cells. Lai WKM, Mariani L, Rothschild G, Smith ER, Venters BJ, Blanda TR, Kuntala PK, Bocklund K, Mairose J, Dweikat SN, Mistretta K, Rossi MJ, James D, Anderson JT, Phanor SK, Zhang W, Zhao Z, Shah AP, Novitzky K, McAnarney E, Keogh M-C, Shilatifard A, Basu U, Bulyk ML, Pugh BF. Genome Research. 2021 Sep;31(9):1663-1679. doi:10.1101/gr.275472.121. Epub 2021 Aug 23.
Validation of antibodies: Lessons learned from the Common Fund Protein Capture Reagents Program. Roy AL, Wilder EL, Anderson JM. Science Advances. 2021 Nov 12; 7(46). doi:10.1126/sciadv.abl7148. Epub 2021 Nov 10.
A Toolbox to Study Proteins
New Resource for Researchers
Antibodies are a type of natural proteins that can bind to proteins and other pathogens known as antigens. Antibodies can also be created in the laboratory for biomedical research, allowing researchers to identify and isolate proteins within cells. However, many of the antibodies developed for research lack the ability to specifically bind to only the protein of interest, limiting their utility. Hence, there is a great need for the development of high affinity, high specificity, renewable antibodies for research. As part of the NIH Common Fund Protein Capture Reagents program, a team of researchers used an integrated production and validation pipeline to generate a collection of 1406 high specificity and high affinity mouse monoclonal antibodies (mAbs) to 737 human transcription factors (proteins that bind DNA to regulate gene expression), which have been distributed to multiple suppliers. The optimized pipeline involves production of full length antigens to immunize mice, use of human protein microarrays to identify mAbs with high specificity for the target protein, and further testing of mAbs by immunoblotting and immunoprecipitation. Over-expressed protein was used for validation, and so the next step will be for researchers to validate the ability of each mAb to selectively recognize specific proteins in cells and/or tissues. This study produced a large collection of antibodies that can potentially be used to determine the role of transcription factors in human development, health, and disease.
Reference: A toolbox of immunoprecipitation-grade monoclonal antibodies to human transcription factors. Venkataraman, A, et al. 2018 March. Nature Methods 15(5):330-338.
Standardizing Antibody Quality
Antibodies are a crucial component in multiple cell biology applications, but there are currently no standardized methods to assess antibody quality. Not knowing the quality of an antibody used in an experiment places doubt on the integrity and reproducibility of the data generated with it. Dr. Kossiakoff was a key collaborator in a study aimed at trying to reduce that uncertainty by developing a standard operating procedure (SOP) using mass spectrometry to quantitatively assess antibodies used in immunoprecipitation experiments (IP-MS). Abundance of 1,124 recombinant antibodies was quantified by IP-MS. SOP performance was validated in five independent laboratories. The quality of the antibodies was well-matched between laboratories despite variations in personnel, techniques, protocols, and mass spectrometry machines. In addition to validating the antibody, the method generates data on antibody quality that is quantitative and can be stored in a database for easy access. The new method is a major step toward standardizing antibody quality, improving data generated from antibody experiments, and making antibodies more accessible to all researchers.
Assessment of a Method to Characterize Antibody Selectivity and Specificity for Use in Immunoprecipitation. Marcon E, et al. Nat Methods. 2015 June 29; 12:725-731.
Using DNA for More than Genetic Information
Long chains of DNA make up our chromosomes and collectively contain the genetic information needed for our cells to function. However, we can synthesize DNA molecules in the laboratory and put them to use in other ways. Tiny chains of DNA that fold up into variety of 3-dimensional shapes that recognize and bind to a whole host of biological molecules are called aptamers. Because aptamers can target and bind to specific biological molecules within a complex mixture of molecules they are being developed as so-called “affinity reagents” that allow researchers to isolate and study targeted molecules. Large collections of aptamers are generated randomly and are screened for their interactions with target molecules. The aptamers that bind to the target molecule are selected for multiple rounds of testing until only the aptamers best able to recognize and bind to the target molecule survive the increasingly rigorous screening conditions. Dr. Soh, a Protein Capture Reagents Program grantee, and colleagues have developed a method called Quantitative Parallel Aptamer Selection System (QPASS) that enables them to test thousands of selected aptamers simultaneously. QPASS also reduces the number of rounds of screening necessary to find the aptamers that bind best. The increased efficiency in identifying aptamers that bind tightly to specific molecules could make aptamers a feasible and economical reagent for biomedical researchers who wish to isolate and study specific molecules in the future.
QPASS could also make aptamers a useful tool in creating new medical devices. Dr. Soh and his research team developed a sensor that uses aptamers to recognize specific drug molecules. The sensor continuously measures the amount of drug molecules in the bloodstream by recording an electrical signal when aptamers bind to drug molecules. Monitoring this signal over time informed the researchers how much drug was present at any time during of the course of the experiment.
The hope is that aptamers will be a less expensive and more efficient alternative to antibody molecules in research and medical practice. Antibodies are used every day in many diagnostic assays and as therapeutic agents when a certain target biological molecule needs to be recognized. However, antibodies are very complex molecules that are expensive to produce, and difficult to reproduce exactly from batch to batch. Aptamers are relatively straightforward to produce, and once an optimal aptamer has been found, it can be reproduced indefinitely with little or no variation from batch to batch.
Image information: Green drug molecules in the blood bind purple apatmers attached to the sensor. Image source: Ferguson et al. Sci Transl Med 5, 213ra165 (2013). Reprinted with permission from AAAS.
Science published a brief free-access article and video describing the sensor at:
Cho M, Soo Oh S, Nie J, Stewart R, Eisenstein M, Chambers J, Marth JD, Walker F, Thomson JA, Soh HT. Quantitative selection and parallel characterization of aptamers. PNAS, Nov 12, 2013; 110(46): 18460-5. PMID: 24167271.
Drug Sensor Reference:
Ferguson BS, Hoggarth DA, Maliniak D, Ploense K, White RJ, Woodward N, Hsieh K, Bonham AJ, Eisenstein M, Kippin TE, Plaxco KW, Soh HT. Real-time, aptamer-based tracking of circulating therapeutic agents in living animals. Science Translational Medicine. Nov 27, 2013; 5(213): 213ra165. PMID: 24285484.
This page last reviewed on November 15, 2021