Mapping regulators of cell fate determination: Approaches and challenges
Author(s) -
Aditya Kumar,
Prashant Mali
Publication year - 2020
Publication title -
apl bioengineering
Language(s) - English
Resource type - Journals
ISSN - 2473-2877
DOI - 10.1063/5.0004611
Subject(s) - reprogramming , transdifferentiation , biology , regenerative medicine , computational biology , stromal cell , lineage (genetic) , cellular differentiation , cell fate determination , cell type , cell , microbiology and biotechnology , stem cell , genetics , transcription factor , cancer research , gene
Given the limited regenerative capacities of most organs, strategies are needed to efficiently generate large numbers of parenchymal cells capable of integration into the diseased organ. Although it was initially thought that terminally differentiated cells lacked the ability to transdifferentiate, it has since been shown that cellular reprogramming of stromal cells to parenchymal cells through direct lineage conversion holds great potential for the replacement of post-mitotic parenchymal cells lost to disease. To this end, an assortment of genetic, chemical, and mechanical cues have been identified to reprogram cells to different lineages both in vitro and in vivo . However, some key challenges persist that limit broader applications of reprogramming technologies. These include: (1) low reprogramming efficiencies; (2) incomplete functional maturation of derived cells; and (3) difficulty in determining the typically multi-factor combinatorial recipes required for successful transdifferentiation. To improve efficiency by comprehensively identifying factors that regulate cell fate, large scale genetic and chemical screening methods have thus been utilized. Here, we provide an overview of the underlying concept of cell reprogramming as well as the rationale, considerations, and limitations of high throughput screening methods. We next follow with a summary of unique hits that have been identified by high throughput screens to induce reprogramming to various parenchymal lineages. Finally, we discuss future directions of applying this technology toward human disease biology via disease modeling, drug screening, and regenerative medicine.
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