A systems biology pipeline identifies regulatory networks for stem cell engineering

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 proteom...

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Main Authors: Kinney, Melissa A. (Author), Vo, Linda T. (Author), Frame, Jenna M. (Author), Barragan, Jessica (Author), Conway, Ashlee J. (Author), Li, Shuai (Author), Wong, Kwok-Kin (Author), Collins, James J. (Author), Cahan, Patrick (Author), North, Trista E. (Author), Lauffenburger, Douglas A (Author), Daley, George Q. (Author)
Other Authors: Massachusetts Institute of Technology. Department of Biological Engineering (Contributor), Massachusetts Institute of Technology. Institute for Medical Engineering & Science (Contributor), Broad Institute of MIT and Harvard (Contributor), Harvard University- (Contributor)
Format: Article
Language:English
Published: Springer Science and Business Media LLC, 2020-06-22T19:47:30Z.
Subjects:
Online Access:Get fulltext
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100 1 0 |a Kinney, Melissa A.  |e author 
100 1 0 |a Massachusetts Institute of Technology. Department of Biological Engineering  |e contributor 
100 1 0 |a Massachusetts Institute of Technology. Institute for Medical Engineering & Science  |e contributor 
100 1 0 |a Broad Institute of MIT and Harvard  |e contributor 
100 1 0 |a Harvard University-  |e contributor 
700 1 0 |a Vo, Linda T.  |e author 
700 1 0 |a Frame, Jenna M.  |e author 
700 1 0 |a Barragan, Jessica  |e author 
700 1 0 |a Conway, Ashlee J.  |e author 
700 1 0 |a Li, Shuai  |e author 
700 1 0 |a Wong, Kwok-Kin  |e author 
700 1 0 |a Collins, James J.  |e author 
700 1 0 |a Cahan, Patrick  |e author 
700 1 0 |a North, Trista E.  |e author 
700 1 0 |a Lauffenburger, Douglas A  |e author 
700 1 0 |a Daley, George Q.  |e author 
245 0 0 |a A systems biology pipeline identifies regulatory networks for stem cell engineering 
260 |b Springer Science and Business Media LLC,   |c 2020-06-22T19:47:30Z. 
856 |z Get fulltext  |u https://hdl.handle.net/1721.1/125922 
520 |a 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. 
520 |a National Institute of General Medical Sciences (NIGMS) (Grant R01-GM081336) 
520 |a National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) (Grant R24-DK092760) 
520 |a National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) (R24-DK49216) 
546 |a en 
655 7 |a Article 
773 |t Nature Biotechnology