Detecting cellular reprogramming determinants by differential stability analysis of gene regulatory networks

BMC Systems Biology

Antonio del Sol¹  Wiktor Jurkowski¹  Thanneer M Perumal¹  Isaac Crespo¹ 

[1] Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, L-4362, Esch-Belval, Luxembourg

关键词: Reprogramming determinants;    Positive circuit;    Attractor;    Stability;    Dedifferentiation;    Transdifferentiation;    Cellular reprogramming;   

Others  :  1141703
DOI  :  10.1186/1752-0509-7-140

 received in 2013-05-31, accepted in 2013-12-11,  发布年份 2013

【 摘 要 】

Background

Cellular differentiation and reprogramming are processes that are carefully orchestrated by the activation and repression of specific sets of genes. An increasing amount of experimental results show that despite the large number of genes participating in transcriptional programs of cellular phenotypes, only few key genes, which are coined here as reprogramming determinants, are required to be directly perturbed in order to induce cellular reprogramming. However, identification of reprogramming determinants still remains a combinatorial problem, and the state-of-art methods addressing this issue rests on exhaustive experimentation or prior knowledge to narrow down the list of candidates.

Results

Here we present a computational method, without any preliminary selection of candidate genes, to identify reduced subsets of genes, which when perturbed can induce transitions between cellular phenotypes. The method relies on the expression profiles of two stable cellular phenotypes along with a topological analysis stability elements in the gene regulatory network that are necessary to cause this multi-stability. Since stable cellular phenotypes can be considered as attractors of gene regulatory networks, cell fate and cellular reprogramming involves transition between these attractors, and therefore current method searches for combinations of genes that are able to destabilize a specific initial attractor and stabilize the final one in response to the appropriate perturbations.

Conclusions

The method presented here represents a useful framework to assist researchers in the field of cellular reprogramming to design experimental strategies with potential applications in the regenerative medicine and disease modelling.

【 授权许可】

   
2013 Crespo et al.; licensee BioMed Central Ltd.

【 图 表 】

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