Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

0

Dissecting engineered cell types and enhancing cell fate conversion via CellNet


ABSTRACT: Engineering clinically relevant cells in vitro holds promise for regenerative medicine, but most protocols fail to faithfully recapitulate target cell properties. To address this, we developed CellNet, a network biology platform that determines whether engineered cells are equivalent to their target tissues, diagnoses aberrant gene regulatory networks, and prioritizes candidate transcriptional regulators to enhance engineered conversions. Using CellNet, we improved B cell to macrophage conversion, transcriptionally and functionally, by knocking down predicted B cell regulators. Analyzing conversion of fibroblasts to induced hepatocytes (iHeps), CellNet revealed an unexpected intestinal program regulated by the master regulator Cdx2. We observed functional engraftment of mouse colon by iHeps, thereby establishing their broader potential as endoderm progenitors and demonstrating direct conversion of fibroblasts into intestinal epithelium. Our studies illustrate how CellNet can be employed to improve direct conversion and to uncover unappreciated properties of engineered cells. 15 samples

ORGANISM(S): Mus musculus

SUBMITTER: Hu Li 

PROVIDER: E-GEOD-59037 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

altmetric image

Publications

Dissecting engineered cell types and enhancing cell fate conversion via CellNet.

Morris Samantha A SA   Cahan Patrick P   Li Hu H   Zhao Anna M AM   San Roman Adrianna K AK   Shivdasani Ramesh A RA   Collins James J JJ   Daley George Q GQ  

Cell 20140801 4


Engineering clinically relevant cells in vitro holds promise for regenerative medicine, but most protocols fail to faithfully recapitulate target cell properties. To address this, we developed CellNet, a network biology platform that determines whether engineered cells are equivalent to their target tissues, diagnoses aberrant gene regulatory networks, and prioritizes candidate transcriptional regulators to enhance engineered conversions. Using CellNet, we improved B cell to macrophage conversio  ...[more]

Similar Datasets

2013-12-03 | E-GEOD-52566 | biostudies-arrayexpress
2014-05-21 | E-GEOD-47147 | biostudies-arrayexpress
2014-02-03 | E-GEOD-46730 | biostudies-arrayexpress
2015-03-27 | E-GEOD-67362 | biostudies-arrayexpress
2023-02-09 | PXD038048 | Pride
2015-02-01 | E-GEOD-62962 | biostudies-arrayexpress
2015-08-01 | E-GEOD-66962 | biostudies-arrayexpress
2016-05-17 | E-GEOD-81491 | biostudies-arrayexpress
2023-11-29 | E-MTAB-13266 | biostudies-arrayexpress
2022-02-10 | E-MTAB-11244 | biostudies-arrayexpress