Reprogramming cell fate with a genome-scale library of artificial transcription factors

Asuka Eguchi, Matthew J. Wleklinski, Mackenzie C. Spurgat, Evan A. Heiderscheit, Anna S. Kropornicka, Catherine K. Vu, Devesh Bhimsaria, Scott A. Swanson, Ron Stewart, Parameswaran Ramanathan, Timothy J. Kamp, Igor Slukvin, James A. Thomson, James R. Dutton, Aseem Z. Ansari

Research output: Contribution to journalArticlepeer-review

16 Scopus citations

Abstract

Artificial transcription factors (ATFs) are precision-tailored molecules designed to bind DNA and regulate transcription in a preprogrammed manner. Libraries of ATFs enable the high-throughput screening of gene networks that trigger cell fate decisions or phenotypic changes. We developed a genome-scale library of ATFs that display an engineered interaction domain (ID) to enable cooperative assembly and synergistic gene expression at targeted sites. We used this ATF library to screen for key regulators of the pluripotency network and discovered three combinations of ATFs capable of inducing pluripotency without exogenous expression of Oct4 (POU domain, class 5, TF 1). Cognate site identification, global transcriptional profiling, and identification of ATF binding sites reveal that the ATFs do not directly target Oct4; instead, they target distinct nodes that converge to stimulate the endogenous pluripotency network. This forward genetic approach enables cell type conversions without a priori knowledge of potential key regulators and reveals unanticipated gene network dynamics that drive cell fate choices.

Original languageEnglish (US)
Pages (from-to)E8257-E8266
JournalProceedings of the National Academy of Sciences of the United States of America
Volume113
Issue number51
DOIs
StatePublished - Dec 20 2016

Bibliographical note

Funding Information:
We thank Sandra Tseng and Graham Erwin for help with ChIP-seq analysis. We thank Jos? Rodr?guez-Mart?nez for CSI analysis and Christina Shafer with RNA-seq analysis. We also acknowledge Mitchell Probasco with help with flow cytometry, Jennifer Bolin for help with Illumina sequencing, and Bret Duffin for the teratoma assay. We thank Laura Vanderploeg for help with figure graphics. We are also grateful to Judith Kimble, Sushmita Roy, Garrett Lee, and Fang Wan for helpful discussions. This work was supported by the NIH Grant HL099773, W. M. Keck Medical Research Award, and Progenitor Cell Biology Consortium Jump-Start Award 5U01HL099997-05 (Subaward 101330A). A.E. was supported by the Morgridge Biotechnology Wisconsin Distinguished Fellowship Award and the Stem Cell and Regenerative Medicine Training Award. A.S.K. was supported by Genomic Sciences Training Program Grant 5T32HG002760. D.B. was supported by a National Science Foundation-Nanoscale Science and Engineering Center grant.

Publisher Copyright:
© 2016, National Academy of Sciences. All rights reserved.

Keywords

  • Artificial transcription factor
  • Cell fate
  • Gene regulatory networks
  • Genome-scale library
  • Reprogramming

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