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Nat Biotechnol. 2019 Jul;37(7):810-818. doi: 10.1038/s41587-019-0159-2. Epub 2019 Jul 1.

A systems biology pipeline identifies regulatory networks for stem cell engineering.

Kinney MA1,2,3, Vo LT1,2,4, Frame JM1,2,5, Barragan J1,2, Conway AJ1,2, Li S6,7, Wong KK6,7, Collins JJ8,9,10,11, Cahan P12, North TE1,2,5, Lauffenburger DA13, Daley GQ14,15,16,17.

Author information

1
Stem Cell Program, Boston Children's Hospital, Boston, MA, USA.
2
Division of Hematology/Oncology, Boston Children's Hospital and Dana Farber Cancer Institute, Boston, MA, USA.
3
Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA.
4
Harvard Medical School, Boston, MA, USA.
5
Department of Pathology, Beth Israel-Deaconess Medical Center, Boston, MA, USA.
6
Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA.
7
Laura & Isaac Perlmutter Cancer Center, NYU Langone Medical Center, New York, NY, USA.
8
Institute for Medical Engineering & Science, Department of Biological Engineering, Synthetic Biology Center, Massachusetts Institute of Technology, Cambridge, MA, USA.
9
Harvard-MIT Program in Health Sciences and Technology, Cambridge, MA, USA.
10
Broad Institute of MIT and Harvard, Cambridge, MA, USA.
11
Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, MA, USA.
12
Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA.
13
Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA. lauffen@mit.edu.
14
Stem Cell Program, Boston Children's Hospital, Boston, MA, USA. George.Daley@childrens.harvard.edu.
15
Division of Hematology/Oncology, Boston Children's Hospital and Dana Farber Cancer Institute, Boston, MA, USA. George.Daley@childrens.harvard.edu.
16
Harvard Medical School, Boston, MA, USA. George.Daley@childrens.harvard.edu.
17
Harvard Stem Cell Institute, Boston, MA, USA. George.Daley@childrens.harvard.edu.

Abstract

A major challenge for stem cell engineering is achieving a holistic understanding of the molecular networks and biological processes governing cell differentiation. To address this challenge, we describe a computational approach that combines gene expression analysis, previous knowledge from proteomic pathway informatics and cell signaling models to delineate key transitional states of differentiating cells at high resolution. Our network models connect sparse gene signatures with corresponding, yet disparate, biological processes to uncover molecular mechanisms governing cell fate transitions. This approach builds on our earlier CellNet and recent trajectory-defining algorithms, as illustrated by our analysis of hematopoietic specification along the erythroid lineage, which reveals a role for the EGF receptor family member, ErbB4, as an important mediator of blood development. We experimentally validate this prediction and perturb the pathway to improve erythroid maturation from human pluripotent stem cells. These results exploit an integrative systems perspective to identify new regulatory processes and nodes useful in cell engineering.

PMID:
31267104
DOI:
10.1038/s41587-019-0159-2

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