A ChIP-exo screen of 887 Protein Capture Reagents Program transcription factor antibodies in human cells

William K.M. Lai, Luca Mariani, Gerson Rothschild, Edwin R. Smith, Bryan J. Venters, Thomas R. Blanda, Prashant K. Kuntala, Kylie Bocklund, Joshua Mairose, Sarah N. Dweikat, Katelyn Mistretta, Matthew J. Rossi, Daniela James, James T. Anderson, Sabrina K. Phanor, Wanwei Zhang, Zibo Zhao, Avani P. Shah, Katherine Novitzky, Eileen McAnarneyMichael C. Keogh, Ali Shilatifard, Uttiya Basu, Martha L. Bulyk*, B. Franklin Pugh*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

9 Scopus citations

Abstract

Antibodies offer a powerful means to interrogate specific proteins in a complex milieu. However, antibody availability and reliability can be problematic, whereas epitope tagging can be impractical in many cases. To address these limitations, the Protein Capture Reagents Program (PCRP) generated over a thousand renewable monoclonal antibodies (mAbs) against human presumptive chromatin proteins. However, these reagents have not been widely field-tested. We therefore performed a screen to test their ability to enrich genomic regions via chromatin immunoprecipitation (ChIP) and a variety of orthogonal assays. Eight hundred eighty-seven unique antibodies against 681 unique human transcription factors (TFs) were assayed by ultra-high-resolution ChIP-exo/seq, generating approximately 1200 ChIP-exo data sets, primarily in a single pass in one cell type (K562). Subsets of PCRP mAbs were further tested in ChIP-seq, CUT&RUN, STORM super-resolution microscopy, immunoblots, and protein binding microarray (PBM) experiments. About 5% of the tested antibodies displayed high-confidence target (i.e., cognate antigen) enrichment across at least one assay and are strong candidates for additional validation. An additional 34% produced ChIP-exo data that were distinct from background and thus warrant further testing. The remaining 61% were not substantially different from background, and likely require consideration of a much broader survey of cell types and/or assay optimizations. We show and discuss the metrics and challenges to antibody validation in chromatin-based assays.

Original languageEnglish (US)
Pages (from-to)1663-1679
Number of pages17
JournalGenome research
Volume31
Issue number9
DOIs
StatePublished - Sep 2021

Funding

The Basu laboratory thanks Drs. Teresa Swayne and Emilia Laura Munteanu of the Herbert Irving Comprehensive Cancer Center Core Microscopy facility at Columbia University. The Pugh laboratory thanks Kyle Nilson for donating the peroxide-stressed cells. The Shilatifard laboratory thanks Anna Whelan and Jordan Harris for technical assistance and Marc Morgan for helpful discussions. The Bulyk laboratory thanks Steve S. Gisselbrecht for assistance with preparation of figures. ChIP-exo data were made available through the Cornell Institute of Biotechnology's Epigenomic Core Facility using the Platform for Epigenome and Genomic Research (PEGR), with National Institutes of Health (NIH) 5R01-ES013768-12 funding for the development and dissemination of PEGR. We acknowledge the support of the Institute for Computational and Data Sciences at the Pennsylvania State University through an ICDS Seed Grant. This work was supported by an administrative supplement to National Institute of Allergy and Infectious Diseases (NIAID) grant 1R01AI099195 to U.B., an administrative supplement to NIH grant R21 HG009268 to M.L.B., NIH grant R01-GM125722 and an administrative supplement to NIH grant R01-ES013768 to B.F.P., an administrative supplement to NIH grant R01CA214035 to A.S., NIH grant R50CA211428 to E.R.S., and NIH grant R44 DE029633 to EpiCypher. The Basu laboratory thanks Drs. Teresa Swayne and Emilia Laura Munteanu of the Herbert Irving Comprehensive Cancer Center Core Microscopy facility at Columbia University. The Pugh laboratory thanks Kyle Nilson for donating the peroxide-stressed cells. The Shilatifard laboratory thanks Anna Whelan and Jordan Harris for technical assistance and Marc Morgan for helpful discussions. The Bulyk laboratory thanks Steve S. Gisselbrecht for assistance with preparation of figures. ChIP-exo data were made available through the Cornell Institute of Biotechnology’s Epigenomic Core Facility using the Platform for Epigenome and Genomic Research (PEGR), with National Institutes of Health (NIH) 5R01-ES013768-12 funding for the development and dissemination of PEGR. We acknowledge the support of the Institute for Computational and Data Sciences at the Pennsylvania State University through an ICDS Seed Grant. This work was supported by an administrative supplement to National Institute of Allergy and Infectious Diseases (NIAID) grant 1R01AI099195 to U.B., an administrative supplement to NIH grant R21 HG009268 to M.L.B., NIH grant R01-GM125722 and an administrative supplement to NIH grant R01-ES013768 to B.F.P., an administrative supplement to NIH grant R01CA214035 to A.S., NIH grant R50CA211428 to E.R.S., and NIH grant R44 DE029633 to EpiCypher.

ASJC Scopus subject areas

  • Genetics(clinical)
  • Genetics

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