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

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-sc...

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Bibliographic Details
Published in:Proceedings of the National Academy of Sciences - PNAS 2016-12, Vol.113 (51), p.E8257-E8266
Main Authors: Eguchi, Asuka, Wleklinski, Matthew J., Spurgat, Mackenzie C., Heiderscheit, Evan A., Kropornicka, Anna S., Vu, Catherine K., Bhimsaria, Devesh, Swanson, Scott A., Stewart, Ron, Ramanathan, Parameswaran, Kamp, Timothy J., Slukvin, Igor, Thomson, James A., Dutton, James R., Ansari, Aseem Z.
Format: Article
Language:English
Subjects:
Binding sites
Biological Sciences
Deoxyribonucleic acid
DNA
Genomes
Genotype & phenotype
Molecules
PNAS Plus
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Summary: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.
ISSN:0027-8424
1091-6490
DOI:10.1073/pnas.1611142114