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Review
. 2009 Oct;10(10):672-81.
doi: 10.1038/nrm2766. Epub 2009 Sep 9.

Systems biology of stem cell fate and cellular reprogramming

Ben D Macarthur  1 , Avi Ma'ayan, Ihor R Lemischka
Affiliations
Review

Systems biology of stem cell fate and cellular reprogramming

Ben D Macarthur et al. Nat Rev Mol Cell Biol. 2009 Oct.

Abstract

Stem cell differentiation and the maintenance of self-renewal are intrinsically complex processes requiring the coordinated dynamic expression of hundreds of genes and proteins in precise response to external signalling cues. Numerous recent reports have used both experimental and computational techniques to dissect this complexity. These reports suggest that the control of cell fate has both deterministic and stochastic elements: complex underlying regulatory networks define stable molecular 'attractor' states towards which individual cells are drawn over time, whereas stochastic fluctuations in gene and protein expression levels drive transitions between coexisting attractors, ensuring robustness at the population level.

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Figures

Figure 1
Figure 1. Stem cell regulatory networks
a | Schematic showing high-confidence protein–protein interactions between NANOG and NANOG-associated proteins, as derived from rEFS ,,. b | Schematic showing the stem cell transcriptional regulatory circuit. This network was reconstructed from the data presented in various recent high-throughput chromatin immunoprecipitation (ChIP) experiments–,,,–,–. Both networks are rich in regulatory loops (see also BOX 2), suggesting a complex system with the ability to exhibit a wide range of context-dependent dynamic behaviours. Factors present in both the NANOG interactome and the core transcriptional network are shown in red. Note that there is great overlap between these two networks (with shared factors being the most central elements of both networks), suggesting that the core transcription factors regulate each other’s expression in a coordinated, combinatorial manner, involving both protein–protein and protein–DNA interactions. See Integrated Stem Cell Molecular Interactions database for an interactive version of this network.
Figure 2
Figure 2. Cellular reprogramming as navigation through a complex attractor landscape
In a complex cellular attractor landscape there might be many coexisting stationary attractors (here represented as local minima), each of which might be associated with a unique molecular signature. In this view, cellular reprogramming corresponds to guiding the cell through the landscape from one local minimum to another (shown by the dotted arrows). As there might be many distinct paths between minima (both direct and through intermediary minima), reprogramming from one cell type to another might be achieved though numerous different routes,,.
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