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Network motifs: theory and experimental approaches

Nature Reviews Genetics volume 8, pages 450–461 (2007)Cite this article

Key Points

  • Transcription regulation networks seem to be built of a few regulatory patterns called network motifs.

  • Each network motif can carry out defined information-processing functions. These functions have been experimentally studied in selected systems, mostly Escherichia coli.

  • Negative autoregulation can speed up responses and reduce fluctuations, whereas positive autoregulation slows responses and increases variations.

  • Coherent feedforward loops can show persistence detection, whereas incoherent feedforward loops show pulse generation and response acceleration.

  • Single-input modules can generate temporal programmes of expression.

  • Dense overlapping regulons can act as arrays of gates for combinatorial decision making.

  • Developmental networks display these network motifs, and additional motifs, such as two-point positive-feedforward loops for decision making and memory, and cascades for regulating slow multi-step processes.

  • Network motifs in systems that have been studied experimentally so far seem to be wired together in a 'modular' way that allows us to understand the dynamics of each individual motif, even when it is connected to the rest of the network.

  • Evolution seems to have converged on the same motifs in different systems and different organisms, suggesting that they are selected for again and again on the basis of their biological functions.

  • Other biological networks, such as signalling and neuronal networks, also show network motifs, some of which are similar to the motifs that are found in transcription networks.

Abstract

Transcription regulation networks control the expression of genes. The transcription networks of well-studied microorganisms appear to be made up of a small set of recurring regulation patterns, called network motifs. The same network motifs have recently been found in diverse organisms from bacteria to humans, suggesting that they serve as basic building blocks of transcription networks. Here I review network motifs and their functions, with an emphasis on experimental studies. Network motifs in other biological networks are also mentioned, including signalling and neuronal networks.

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Figure 1: Simple regulation and autoregulation.
Figure 2: Feedforward loops (FFLs).
Figure 3: The coherent type-1 feedforward loop (C1-FFL) and its dynamics.
Figure 4: The incoherent type-1 feeforward loop (I1-FFL) and its dynamics.
Figure 5: The single-input module (SIM) network motif and its dynamics.
Figure 6: The dense overlapping regulon (DOR) network motif.
Figure 7: Network motifs in developmental transcription networks.

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Acknowledgements

I thank my laboratory members for stimulating discussions, especially R. Milo, S. Itzkovitz, S. Mangan, S. Shen-Orr and N. Kashtan. I thank M. Elowitz, M. Surette, S. Leibler and H. Westerhoff for discussions, and the Israel Science Foundation, the Human Frontiers Science Foundation, Minerva, National Institutes of Health (USA) and the Kahn Family Foundation for support

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Alon, U. Network motifs: theory and experimental approaches. Nat Rev Genet 8, 450–461 (2007). https://doi.org/10.1038/nrg2102

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