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Chemical screening to uncover small molecules that modulate neural stem cell self-renewal and differentiation

In vitro expanded neural stem cells provide an important cellular model to explore mechanisms of neural development, for modelling of disease, and in the longer term may have applications in new types of stem cell-based therapies. However, our ability to steer neural stem (NS) cell lines into specific desired lineages in vitro remains limited. PDGFRα is one of the earliest markers of the transition of neural stem cells to oligodendrocyte progenitors. I established and characterised a novel set of mouse NS cell lines that report the activation of PDGFRα via expression of an H2B:GFP ‘knock-in’. Three clonal ‘PG1’ cell lines were fully characterised. Under self-renewing conditions I found <1% of NS cell express the H2B:GFP reporter but this increases to ~15-20% following induction of differentiation. Using this cellular model system I carried out a high-content chemical screen of a diverse collection of 463 pharmacologically active small molecule modulators of ‘stem cell pathways’ and kinase inhibitors, to identify those capable of modulating NS cell self-renewal and differentiation. I did not uncover any small molecules capable of promoting OPC lineage specification. However, I found multiple HDAC inhibitors that were highly effective in blocking the activation of PDGFRα, a finding that mirrors published studies implicating HDAC inhibition in the later differentiation of OPCs to oligodendrocytes. Three further compounds, Nigericin (an ionophore), Withaferin (a steroidal lactone) and NFkB inhibitor also completely blocked OPC commitment. I focused on the specific cellular responses and downstream molecular events triggered by these molecules and tested their differentiation potential on human NS cells and malignant glioblastoma-derived NS cells.

Identiferoai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:666794
Date January 2015
CreatorsBaranowski, B.
PublisherUniversity College London (University of London)
Source SetsEthos UK
Detected LanguageEnglish
TypeElectronic Thesis or Dissertation
Sourcehttp://discovery.ucl.ac.uk/1468463/

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