Aggregation of topological motifs in the Escherichia coli transcriptional regulatory network

By Radu Dobrin, Qasim K. Beg, Albert-László Barabási, Zoltn Oltvai, Zoltán N. Oltvai. 2004

248 citations recorded by the source corpus.

BackgroundTranscriptional regulation of cellular functions is carried out through a complex network of interactions among transcription factors and the promoter regions of genes and operons regulated by them.To better understand the system-level function of such networks simplification of their architecture was previously achieved by identifying the motifs present in the network, which are small, overrepresented, topologically distinct regulatory interaction patterns (subgraphs). However, the interaction of such motifs with each other, and their form of integration into the full network has not been previously examined.ResultsBy studying the transcriptional regulatory network of the bacterium, Escherichia coli, we demonstrate that the two previously identified motif types in the network (i.e., feed-forward loops and bi-fan motifs) do not exist in isolation, but rather aggregate into homologous motif clusters that largely overlap with known biological functions. Moreover, these clusters further coalesce into a supercluster, thus establishing distinct topological hierarchies that show global statistical properties similar to the whole network. Targeted removal of motif links disintegrates the network into small, isolated clusters, while random disruptions of equal number of links do not cause such an effect.ConclusionIndividual motifs aggregate into homologous motif clusters and a supercluster forming the backbone of the E. coli transcriptional regulatory network and play a central role in defining its global topological organization.

Subfields: Molecular Biology

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Citations in the corpus

Structure and evolution of transcriptional regulatory networks. (2004, unknown): “[9] showed that many of the multiple input and feed-forward loop motifs in E.”
Network Motif Discovery Using Subgraph Enumeration and Symmetry-Breaking (2007, background): “Although motif clustering has previously been observed [3] and demonstrated analytically [24], previous motifs studied do not have enough nodes to exhibit the extreme combinatorial clustering we observed for large subgraphs (at least 15 nodes).”
Nonlinear dynamics of networks: the groupoid formalism (2006, background): “The phenomenon of 'motifs'—unusually common small subnetworks, Milo et al. [59], Wolf and Arkin [85], Dobrin et al. [22]—is also worth mentioning in this context.”
Graph theory and networks in Biology. (2006, background): “The authors of [165] studied how the FFL and bi-fan motifs in the E.”
The FunCat, a functional annotation scheme for systematic classification of proteins from whole genomes. (2004, methodology): “The capabilities of the FunCat as a controlled (structured) vocabulary and classification scheme are not only limited to the functional annotation of genomes but also provide a powerful tool to analyse genome- and proteome-wide data which have been generated by large-scale transcriptome/ proteome ex”
Network motifs: theory and experimental approaches (2007, background): “The FFLs in transcription networks tend to combine to form multi-output FFL”
Analysis of Biological Networks (2008, methodology): “Thanks to the editors of Wiley’s Bioinformatics series, Yi Pan and Albert Y. Zomaya, for giving us the opportunity to present our research interests as a book in their series.”