Daily Archives: January 12, 2015


01.21.15

CellNet: Network Biology Applied to Stem Cell Engineering

Patrick Cahan, Hu Li, Samantha A. Morris, Edroaldo Lummertz da Rocha, George Q. Daley, James J. Collins5,
doi:10.1016/j.cell.2014.07.020

Refers To
Samantha A. Morris, Patrick Cahan, Hu Li, Anna M. Zhao, Adrianna K. San Roman, Ramesh A. Shivdasani, James J. Collins, George Q. Daley
Dissecting Engineered Cell Types and Enhancing Cell Fate Conversion via CellNet
Cell, Volume 158, Issue 4, 14 August 2014, Pages 889-902
PDF (4068 K) Supplementary content
Referred to by
Kee-Pyo Kim, Hans R. Schöler
CellNet—Where Your Cells Are Standing
Cell, Volume 158, Issue 4, 14 August 2014, Pages 699-701
PDF (596 K)
Samantha A. Morris, Patrick Cahan, Hu Li, Anna M. Zhao, Adrianna K. San Roman, Ramesh A. Shivdasani, James J. Collins, George Q. Daley
Dissecting Engineered Cell Types and Enhancing Cell Fate Conversion via CellNet
Cell, Volume 158, Issue 4, 14 August 2014, Pages 889-902
PDF (4068 K) Supplementary content

Summary
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.

 

Dissecting Engineered Cell Types and Enhancing Cell Fate Conversion via CellNet