In the beginning, there are embryonic stem cells, which divide and increasingly differentiate as they do so. The ensuing tissue cells remain in a stable state, a skin cell does not spontaneously change into a nerve cell or heart muscle cell.
The applications for embryonic stem cells
are many: When nerve tissue becomes diseased, for example, then doctors could take healthy cells from the patient's own skin. They could then reprogram these to develop into nerve cells. These healthy nerve cells would then be implanted into the diseased tissue or even replace it entirely. This would treat, and ideally heal, diseases such as Parkinson's disease.
Obviously there are other research efforts that do much the same thing. Stem cell researchers
and John Burdon received the Nobel Prize for showing that ordinary adult skin cells could become pluripotent, like embryonic ones. To do so, biologists add refined cocktails of molecules, i.e. growth factors, to the cell cultures in a certain order. This allows them to control the genetic activity in the conversion process. However, this method so far has been largely guided by trial and error. The techniques for cell programming are still in their infancy.
Computational experts at the University of Luxembourg have developed a model that makes predictions from which differentiated cells, such as skin cells, can be very efficiently changed into completely different cell types, such as nerve cells. Without embryonic stem cells.
Variable jumping between different cell lines is possible
Professor Antonio del Sol, head of the Computational Biology group at Luxembourg Centre for Systems Biomedicine (LCSB) and PhD student Isaac Crespo have replaced trial and error with computer calculations. As Crespo explains, "Our theoretical model first queries databases where vast amounts of information on gene actions and their effects are stored and then identifies the genes that maintain the stability of differentiated cells. Working from the appropriate records, the model suggests which genes in the starting cells need to be switched on and off again, and when, in order to change them into a different cell type."
"Our predictions have proved very accurate in the lab," says del Sol "And it turns out it makes no difference at all how similar the cells are. The models work equally well for cell lines that have only just branched off from one another as for those that are already very far apart."
They say their model allows highly variable jumping between very different cell types without taking a detour via stem cells. Biologists and medical scientists still have their lab work cut out for them: They have to identify all the growth factors that initiate the respective genetic activities in the correct, predicted order.
Citation: Isaac Crespo and Antonio del Sol, 'A General Strategy for Cellular Reprogramming: The Importance of Transcription Factor Cross-Repression', Stem Cells 19 JUL 2013 DOI: 10.1002/stem.1473