Computational model explains gene interactions governing stem cells in mice

Stem cell biologists in Cambridge, UK, have teamed up with scientists from Microsoft Research to create a new computational model that explains for the first time how genes interact to keep embryonic stem cells in an unspecialised, pluripotent state.

Whether an embryonic stem cell remains pluripotent or begins to differentiate into specialised cells, is thought to be controlled by around 20 genes. But how these genes are linked together into a control circuit was unknown.

In this study, the team from the Wellcome Trust-MRC Cambridge Stem Cell Institute and Microsoft’s Computational Science laboratory analysed correlations between these genes and used this information to construct a ‘meta model’ of the network. To distil out only those connections that result in observed stem cell behaviours, they adapted techniques traditionally used to identify bugs and guarantee the correctness of software and hardware, especially in safety-critical systems. They found that the decision of a stem cell to self-renew or differentiate can be explained by a program consisting of three input signals, 12 genes, and, in its simplest version, just 16 connections. Furthermore, their modelling approach accurately predicted stem cell behaviour in new conditions, the first time a computational approach has been able to predict this complex decision-making.

The team hope that with further development, they will be able to use their model to explain how stem cells become different types of specialised cell, and how mouse and human stem cells differ. The modelling approach could also be used to improve procedures in the laboratory, for example reprogramming to induce pluripotency which currently has an efficiency of only one percent.

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