About the Project

GlioStem is the first product of its kind to be verified for basic research purposes and available from Celluminova. The basic idea is to develop new tools for detection and isolation of different stem cell and progenitor types in the developing organism and in tumors to facilitate studies on single cell basis 0f the character of the individual progenitors and stem cells.

The Nobel prize in physics 2014 was awarded three scientists for the invention of blue light emitting diodes, LEDs. Notably, certain polymers, polythiophenes or oligothiophenes (LCOs), can function as single molecule LEDs. LCOs are able to cross physiological cell membranes without additional reagents and to illuminate when interacting with certain biological structures, such as amyloid. LCOs can therefore also be used to specifically detect certain cell types. We have screened numerous LCOs of different length, structure, and general characteristics, to investigate whether these could be used for detection of various stem cell types. We have generated and characterized a novel LCO called GlioStem, that specifically detects embryonic mammalian neural as well as stem cell-like cells derived from rat glioma (C6) and human glioblastoma multiforme, and we propose that GlioStem is more sensitive and specific than current methods, e.g., CD133 or CD44 antibodies. GlioStem passes the cell membrane without any additional reagent or modification, and within a maximum of 10 minutes specifically detects embryonic neural stem cells from rats and iPS-derived neural progenitors from humans, as well as stem cell-like cells from rat C6 glioma and from human glioblasome multiforme – but no other tested cell types – in vitro by omitting fluorescence at a wavelength similar to GFP (green fluorescent protein) without any modulation of the cells, just by simple administration of the molecule by a pipette or spray to the cell culture in the existing media. We can further very efficiently specifically sort out these cell types from mixed cell populations by cell sorting techniques (FACS).

References to figures: 
Karaca et al, Exp Cell Res, 2015
Lewicka et al, Biomaterials, 2012
Teixeira et al, Biomaterials, 2009