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Research Article

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, and Aseem Z. Ansari
PNAS December 20, 2016 113 (51) E8257-E8266; first published December 5, 2016; https://doi.org/10.1073/pnas.1611142114
Asuka Eguchi
aCellular and Molecular Biology Training Program, University of Wisconsin–Madison, Madison, WI 53706;
bDepartment of Biochemistry, University of Wisconsin–Madison, Madison, WI 53706;
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Matthew J. Wleklinski
bDepartment of Biochemistry, University of Wisconsin–Madison, Madison, WI 53706;
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Mackenzie C. Spurgat
bDepartment of Biochemistry, University of Wisconsin–Madison, Madison, WI 53706;
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Evan A. Heiderscheit
bDepartment of Biochemistry, University of Wisconsin–Madison, Madison, WI 53706;
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Anna S. Kropornicka
bDepartment of Biochemistry, University of Wisconsin–Madison, Madison, WI 53706;
cGenetics Training Program, University of Wisconsin–Madison, Madison, WI 53706;
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Catherine K. Vu
bDepartment of Biochemistry, University of Wisconsin–Madison, Madison, WI 53706;
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Devesh Bhimsaria
bDepartment of Biochemistry, University of Wisconsin–Madison, Madison, WI 53706;
dDepartment of Electrical and Computer Engineering, University of Wisconsin–Madison, Madison, WI 53706;
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Scott A. Swanson
eMorgridge Institute for Research, Madison, WI 53715;
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Ron Stewart
eMorgridge Institute for Research, Madison, WI 53715;
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Parameswaran Ramanathan
dDepartment of Electrical and Computer Engineering, University of Wisconsin–Madison, Madison, WI 53706;
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Timothy J. Kamp
fDepartment of Medicine, University of Wisconsin School of Medicine and Public Health, Madison, WI 53792;
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Igor Slukvin
gWisconsin National Primate Research Center, University of Wisconsin–Madison, Madison, WI 53715;
hDepartment of Pathology and Laboratory Medicine, University of Wisconsin–Madison, Madison, WI 53715;
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James A. Thomson
eMorgridge Institute for Research, Madison, WI 53715;
iDepartment of Cell and Regenerative Biology, University of Wisconsin School of Medicine and Public Health, Madison, WI 53706;
jThe Genome Center of Wisconsin, University of Wisconsin–Madison, Madison, WI 53706;
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James R. Dutton
kStem Cell Institute, University of Minnesota, Minneapolis, MN 55455
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Aseem Z. Ansari
bDepartment of Biochemistry, University of Wisconsin–Madison, Madison, WI 53706;
jThe Genome Center of Wisconsin, University of Wisconsin–Madison, Madison, WI 53706;
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  • For correspondence: azansari@wisc.edu
  1. Edited by Michael R. Green, University of Massachusetts Medical School, Worcester, MA, and approved November 14, 2016 (received for review July 7, 2016)

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Significance

The ability to convert cells into desired cell types enables tissue engineering, disease modeling, and regenerative medicine; however, methods to generate desired cell types remain difficult, uncertain, and laborious. We developed a strategy to screen gene regulatory elements on a genome scale to discover paths that trigger cell fate changes. The proteins used in this study cooperatively bind DNA and activate genes in a synergistic manner. Subsequent identification of transcriptional networks does not depend on prior knowledge of specific regulators important in the biological system being tested. This powerful forward genetic approach enables direct cell state conversions as well as other challenging manipulations of cell fate.

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.

  • artificial transcription factor
  • genome-scale library
  • cell fate
  • reprogramming
  • gene regulatory networks

Footnotes

  • ↵1To whom correspondence should be addressed. Email: azansari{at}wisc.edu.
  • Author contributions: A.E. and A.Z.A. designed research; A.E., M.J.W., M.C.S., E.A.H., and C.K.V. performed research; P.R., T.J.K., I.S., J.A.T., and J.R.D. contributed new reagents/analytic tools; A.E., A.S.K., D.B., S.A.S., and R.S. analyzed data; and A.E., J.R.D., and A.Z.A. wrote the paper.

  • Conflict of interest statement: A.Z.A. is the sole member of VistaMotif, LLC, and founder of the nonprofit WINStep Forward.

  • This article is a PNAS Direct Submission.

  • Data deposition: The RNA-seq and ChIP-seq data reported in this paper have been deposited in the Gene Expression Omnibus (GEO) database, www.ncbi.nlm.nih.gov/geo (accession no. GSE89221).

  • This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10.1073/pnas.1611142114/-/DCSupplemental.

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Artificial transcription factor reprogramming
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
Proceedings of the National Academy of Sciences Dec 2016, 113 (51) E8257-E8266; DOI: 10.1073/pnas.1611142114

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Artificial transcription factor reprogramming
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
Proceedings of the National Academy of Sciences Dec 2016, 113 (51) E8257-E8266; DOI: 10.1073/pnas.1611142114
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