Samantha A. Morris, Ph.D.

Associate Professor
Developmental Biology

Developmental, Regenerative and Stem Cell Biology Program
Molecular Genetics and Genomics Program
Computational and Systems Biology Program
Biomedical Informatics and Data Science Program

  • 314 747-8618

  • MRB - McKinley Research Building, Room 3316



  • Developing new single-cell technologies to create high-resolution maps of lineage and identity; Manipulating gene regulatory networks, via direct lineage reprogramming, to generate clinically valuable cell types

Research Abstract:

The generation of clinically valuable cells, such as neurons, cardiomyocytes, and hepatocytes, in vitro, offers promise for new regenerative therapies and permits disease modeling, toxicology testing, and drug discovery. Cell differentiation had long been thought a unidirectional process toward restricted potential and increased specialization. In the past half-century, this has been challenged: Mature somatic cells can be returned to a pluripotent state, and subsequently differentiated to desired cell types. Alternatively, mature cells can be ‘directly converted’ from one mature state to another via transcription factor overexpression, bypassing pluripotency. Many approaches are employed to generate defined fate in vitro, however, the resultant cells often appear developmentally immature or incompletely specified, limiting their utility.

The evaluation of cell identity has been confounded by the lack of any systematic means by which to assess the fidelity of engineered cells. We developed ‘CellNet’, a network biology-based computational platform that accurately evaluates cell fate through gene regulatory network reconstruction and generates hypotheses for improving cell differentiation protocols. Using this platform we surveyed a range of engineered cells and found that cells derived via directed differentiation more faithfully recapitulated target cell identity than cells generated by direct conversion. These directly converted cells commonly failed to silence expression programs of the original cell type, and illicit gene expression programs were frequently induced. Employing induced hepatocytes generated from fibroblasts as a prototypical conversion, our computational and functional analyses showed that iHeps behave as embryonic progenitors with the potential to functionally engraft both the liver and colon. We found that these engineered cells resembled mature colonic epithelium after transplantation into the colon niche, leading us to rename this cell type, ‘induced endoderm progenitors’ (iEPs).

Recently, we have revealed further mechanisms of reprogramming to iEPs. Successful reprogramming is a rare event, thus it had remained a challenge to isolate and analyze the few iEPs emerging from fibroblasts. High-throughput single-cell RNA-sequencing has enabled this heterogeneity to be deconstructed, although lineage relationships between cells were lost, making interpretation of the data a challenge. To overcome this, we have developed a straightforward, high-throughput cell tracking method, ‘CellTagging’. Sequential lentiviral delivery of heritable random unique molecular indexes, CellTags, permits the construction of multi-level lineage trees. Application of CellTagging to direct lineage reprogramming to iEPs has allowed us to better define successful reprogramming trajectories and enhance the yield of iEPs.

Overall, we apply our technologies to study gene regulatory networks, to dissect and engineer cell fate of clinically relevant tissues. This focus integrates three major themes: First, we aim to understand how transcription factor overexpression drives changes in the transcriptional program to remodel cell identity, and how we can exploit this to derive desired cell types. Second, we transplant engineered cells into the in vivo niche, tracking their maturation in order to understand the steps required to fully differentiate cells in vitro. Finally, we employ single-cell transcriptomics to understand how cell fate is reprogrammed and matured, formulating a blueprint of cell identity to help engineer fate in vitro. Ultimately, we wish to translate new insights in cell fate specification into better human models of disease and eventually into the development of novel therapeutic strategies.

Selected Publications:

Li Y, Kong W, Yang W, Okeyo-Owuor T, Patel RM, Casey EB, Morris SA*, Magee JA*. Single cell analysis of neonatal HSC ontogeny reveals gradual and uncoordinated transcriptional reprogramming that begins prior to birth. Cell Stem Cell. 2020. Aug 20. *co-corresponding authors.

Moudgil A, Wilkinson MN, Chen X, He J, Cammack AJ, Vasek MJ, Lagunas T, Qi Z, Morris SA, Dougherty, JD, and Mitra RM. Self-reporting transposons enable simultaneous readout of gene expression and transcription factor binding in single cells. Cell. 2020

Kong W, Biddy BA, Kamimoto K, Amrute JA, Butka EG, Morris SA. CellTagging: combinatorial indexing to simultaneously map lineage and identity at single-cell resolution. Nature Protocols. 2020
Guo C, Kong W, Kamimoto K, Rivera-Gonzalez CG, Yang X, Kirita Y, Morris SA. CellTag Indexing: genetic barcode-based sample multiplexing for single-cell genomics. Genome Biology. 2019 May;9;20(1):90.

Biddy BA, Kong W, Kamimoto K, Guo C, Waye SE, Sun T, Morris SA. Single-cell mapping of lineage and identity in direct reprogramming. Nature. 2018 Dec 13; 564(7735):219-224.

Morris SA. Direct lineage reprogramming via pioneer factors; a detour through developmental gene regulatory networks. Development. 2016 143: 2696-2705

Morris SA*, Cahan PC*, Li H*, Zhao A, San Roman AK, Shivdasani RA, Collins JJ, Daley GQ. Dissecting Engineered Cell Types and Enhancing Cell Fate Conversion via CellNet. Cell. 2014 Aug 14;158(4):889-902.* Equal contribution.

Cahan PC*, Li H*, Morris SA*, Lummertz da Rocha E, Daley GQ, Collins JJ. CellNet: Network Biology Applied to Stem Cell Engineering. Cell. 2014 Aug 14;158(4):903-15. * Equal contribution.

Last Updated: 5/25/2021 2:20:27 PM

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