The E. coli transcriptional regulatory network and its spatial embedding

Abstract.Usually complex networks are studied as graphs consisting of nodes whose spatial arrangement is of no significance. Several real biological networks are, however, embedded in space. In this paper we study the transcription regulatory network (TRN) of E. coli as a spatially embedded network. The embedding space of this network is the circular E. coli chromosome, i.e. it is practically one dimensional. However, the TRN itself is a high-dimensional network due to the existence of an adequate number of long-range connections. We find that nodes in short topological distance l = 1, 2 tend, on average, to be in shorter spatial distances r indicating an abundance of short-range connections as well. Community analysis of the TRN reveals the interesting fact that highly interconnected subnets consist of nodes that tend to be in spatial proximity on the circular chromosome. We also find indications that for certain transcriptional aspects of the E. coli it is advantageous to treat the circular genome as two line segments starting from the OriC and ending to Ter.Graphical abstract

[1]  P. R. ten Wolde,et al.  Statistical analysis of the spatial distribution of operons in the transcriptional regulation network of Escherichia coli. , 2003, Journal of molecular biology.

[2]  Adam M. Feist,et al.  Basic and applied uses of genome-scale metabolic network reconstructions of Escherichia coli , 2013, Molecular systems biology.

[3]  Réka Albert,et al.  A comparative study of qualitative and quantitative dynamic models of biological regulatory networks , 2016 .

[4]  Adrian H. Elcock,et al.  Features of genomic organization in a nucleotide-resolution molecular model of the Escherichia coli chromosome , 2017, Nucleic acids research.

[5]  Changsong Zhou,et al.  Trade-off between Multiple Constraints Enables Simultaneous Formation of Modules and Hubs in Neural Systems , 2013, PLoS Comput. Biol..

[6]  B Marshall,et al.  Gene Ontology Consortium: The Gene Ontology (GO) database and informatics resource , 2004, Nucleic Acids Res..

[7]  Marc Barthelemy Crossover from scale-free to spatial networks , 2002 .

[8]  Marc-Thorsten Hütt,et al.  Understanding genetic variation - the value of systems biology. , 2014, British journal of clinical pharmacology.

[9]  A. Travers,et al.  DNA thermodynamic stability and supercoil dynamics determine the gene expression program during the bacterial growth cycle. , 2013, Molecular bioSystems.

[10]  Daqing Li,et al.  Download details: IP Address: 129.74.250.206 , 2011 .

[11]  S. Shen-Orr,et al.  Network motifs in the transcriptional regulation network of Escherichia coli , 2002, Nature Genetics.

[12]  Uri Alon,et al.  An Introduction to Systems Biology , 2006 .

[13]  Michael T. Gastner,et al.  Shape and efficiency in spatial distribution networks , 2006 .

[14]  U. Alon Network motifs: theory and experimental approaches , 2007, Nature Reviews Genetics.

[15]  C. Christensen,et al.  Large-scale inference and graph-theoretical analysis of gene-regulatory networks in B. Subtilis , 2006, q-bio/0607024.

[16]  Marc Barthelemy,et al.  Spatial Networks , 2010, Encyclopedia of Social Network Analysis and Mining.

[17]  Renaud Lambiotte,et al.  Uncovering space-independent communities in spatial networks , 2010, Proceedings of the National Academy of Sciences.

[18]  S. Havlin,et al.  Dimension of spatially embedded networks , 2011 .

[19]  Claudio Castellano,et al.  Defining and identifying communities in networks. , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[20]  Mark E. J. Newman,et al.  An efficient and principled method for detecting communities in networks , 2011, Physical review. E, Statistical, nonlinear, and soft matter physics.

[21]  Jean-Loup Guillaume,et al.  Fast unfolding of communities in large networks , 2008, 0803.0476.

[22]  P. Swain,et al.  Gene Regulation at the Single-Cell Level , 2005, Science.

[23]  Rutger Hermsen,et al.  Chance and necessity in chromosomal gene distributions. , 2008, Trends in genetics : TIG.

[24]  Frederick Mosteller,et al.  Data Analysis and Regression , 1978 .

[25]  Julio Collado-Vides,et al.  RegulonDB v8.0: omics data sets, evolutionary conservation, regulatory phrases, cross-validated gold standards and more , 2012, Nucleic Acids Res..

[26]  Marc-Thorsten Hütt,et al.  Dissecting the logical types of network control in gene expression profiles , 2008, BMC Systems Biology.

[27]  Marc-Thorsten Hütt,et al.  Analog regulation of metabolic demand , 2011, BMC Systems Biology.

[28]  S. Mangan,et al.  Structure and function of the feed-forward loop network motif , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[29]  J. Thompson,et al.  DNA information: from digital code to analogue structure , 2012, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[30]  Dieter W. Heermann,et al.  A model for Escherichia coli chromosome packaging supports transcription factor-induced DNA domain formation , 2011, Nucleic acids research.

[31]  Andrew Travers,et al.  Gene order and chromosome dynamics coordinate spatiotemporal gene expression during the bacterial growth cycle , 2011, Proceedings of the National Academy of Sciences.

[32]  S. Havlin,et al.  Structural properties of spatially embedded networks , 2008, 0804.2575.

[33]  F. Jacob,et al.  Délétions fusionnant ľopéron lactose et un opéron purine chez Escherichia coli , 1965 .

[34]  S. Shen-Orr,et al.  Network motifs: simple building blocks of complex networks. , 2002, Science.