CellNet: Network biology applied to stem cell engineering

Patrick Cahan, Hu Li, Samantha A. Morris, Edroaldo Lummertz Da Rocha, George Q. Daley, James J. Collins

Research output: Contribution to journalArticle

269 Scopus citations

Abstract

Somatic cell reprogramming, directed differentiation of pluripotent stem cells, and direct conversions between differentiated cell lineages represent powerful approaches to engineer cells for research and regenerative medicine. We have developed CellNet, a network biology platform that more accurately assesses the fidelity of cellular engineering than existing methodologies and generates hypotheses for improving cell derivations. Analyzing expression data from 56 published reports, we found that cells derived via directed differentiation more closely resemble their in vivo counterparts than products of direct conversion, as reflected by the establishment of target cell-type gene regulatory networks (GRNs). Furthermore, we discovered that directly converted cells fail to adequately silence expression programs of the starting population and that the establishment of unintended GRNs is common to virtually every cellular engineering paradigm. CellNet provides a platform for quantifying how closely engineered cell populations resemble their target cell type and a rational strategy to guide enhanced cellular engineering.

Original languageEnglish (US)
Pages (from-to)903-915
Number of pages13
JournalCell
Volume158
Issue number4
DOIs
StatePublished - Aug 14 2014

ASJC Scopus subject areas

  • Biochemistry, Genetics and Molecular Biology(all)

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    Cahan, P., Li, H., Morris, S. A., Lummertz Da Rocha, E., Daley, G. Q., & Collins, J. J. (2014). CellNet: Network biology applied to stem cell engineering. Cell, 158(4), 903-915. https://doi.org/10.1016/j.cell.2014.07.020