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Coordination logic of the sensing machinery in the transcriptional regulatory network of Escherichia coli.

Janga SC, Salgado H, Martínez-Antonio A, Collado-Vides J - Nucleic Acids Res. (2007)

Bottom Line: The active and inactive state of transcription factors in growing cells is usually directed by allosteric physicochemical signals or metabolites, which are in turn either produced in the cell or obtained from the environment by the activity of the products of effector genes.Finally we show that evolutionary families of TFs do not show a tendency to preserve their sensing abilities.Our results provide a detailed panorama of the topological structures of E. coli TRN and the way TFs they compose off, sense their surroundings by coordinating responses.

View Article: PubMed Central - PubMed

Affiliation: Programa de Genómica Computacional, Centro de Ciencias Genómicas, Universidad Nacional Autónoma de México, Cuernavaca, Morelos, 62100, México. sarath@ccg.unam.mx

ABSTRACT
The active and inactive state of transcription factors in growing cells is usually directed by allosteric physicochemical signals or metabolites, which are in turn either produced in the cell or obtained from the environment by the activity of the products of effector genes. To understand the regulatory dynamics and to improve our knowledge about how transcription factors (TFs) respond to endogenous and exogenous signals in the bacterial model, Escherichia coli, we previously proposed to classify TFs into external, internal and hybrid sensing classes depending on the source of their allosteric or equivalent metabolite. Here we analyze how a cell uses its topological structures in the context of sensing machinery and show that, while feed forward loops (FFLs) tightly integrate internal and external sensing TFs connecting TFs from different layers of the hierarchical transcriptional regulatory network (TRN), bifan motifs frequently connect TFs belonging to the same sensing class and could act as a bridge between TFs originating from the same level in the hierarchy. We observe that modules identified in the regulatory network of E. coli are heterogeneous in sensing context with a clear combination of internal and external sensing categories depending on the physiological role played by the module. We also note that propensity of two-component response regulators increases at promoters, as the number of TFs regulating a target operon increases. Finally we show that evolutionary families of TFs do not show a tendency to preserve their sensing abilities. Our results provide a detailed panorama of the topological structures of E. coli TRN and the way TFs they compose off, sense their surroundings by coordinating responses.

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Distribution of sensing classes of TFs regulating the promoter regions upstream of experimentally known operons in E. coli. (a) Number of promoters regulated by a given number of transcription factors. (b) Proportion of different sensing classes transcriptionally controlling the expression of operons in E. coli at various thresholds of the number of TFs controlling an operon. To represent, for each bin, first a vector showing the proportion of sensing classes for each operon was calculated and then an average was obtained over the total number of operons present in a given bin, thus obtaining the occurrence of a sensing class. As the number of TFs regulating an operon increased proportion of ISM and hybrid (H) TFs showed a tendency to decrease, while the external TFs from two-component systems increased slightly. Interestingly, IDB TFs were also found to increase their propensity as the number of TFs increased.
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Figure 5: Distribution of sensing classes of TFs regulating the promoter regions upstream of experimentally known operons in E. coli. (a) Number of promoters regulated by a given number of transcription factors. (b) Proportion of different sensing classes transcriptionally controlling the expression of operons in E. coli at various thresholds of the number of TFs controlling an operon. To represent, for each bin, first a vector showing the proportion of sensing classes for each operon was calculated and then an average was obtained over the total number of operons present in a given bin, thus obtaining the occurrence of a sensing class. As the number of TFs regulating an operon increased proportion of ISM and hybrid (H) TFs showed a tendency to decrease, while the external TFs from two-component systems increased slightly. Interestingly, IDB TFs were also found to increase their propensity as the number of TFs increased.

Mentions: Understanding network motifs, which are topological structures controlling the local expression dynamics in the cell, although is of great interest, studies on them is often limited to combinatorial regulation of a promoter by no more than two TFs. However, to appreciate the effect of the action of multiple TFs on a single promoter in the context of sensing classes, one has to study the frequency distribution of TFs from different sensing classes when promoters are regulated by one or more TFs. Indeed control of transcription by multiple TFs at a promoter has been an area of immense interest in itself due to a variety of possible mechanisms by which TFs can combinatorially control the expression of a gene (3,19). As seen in Figure 5a, very few promoters are regulated by four or more TFs suggesting limitations on the number of different binding sites possible in the already short intergenic regions in prokaryotic organisms. A possible explanation for this limitation could be the structural and functional constraints imposed in the intergenic regions of bacterial genomes due to restrictions on the sizes of the protein complexes formed during transcription. Figure 5b shows the distribution of sensing classes when the promoters are regulated by only one, two, three and four or more TFs. It is evident from this figure that as the number of TFs regulating a promoter increases the proportion of TFs of internal origin remain constant (ISM and IDB taken together form about 50% of the TFs regulating a promoter) while the ETC TFs show an inclination to increase suggesting that promoters with several TFs regulating them could show a propensity for external TFs after a saturation threshold of the number of internal TFs controlling them. This observation implies that certain transcription units with multiple inputs can be used under a variety of exogenous conditions depending on the external TFs which modulate their activity particular to a condition.Figure 5.


Coordination logic of the sensing machinery in the transcriptional regulatory network of Escherichia coli.

Janga SC, Salgado H, Martínez-Antonio A, Collado-Vides J - Nucleic Acids Res. (2007)

Distribution of sensing classes of TFs regulating the promoter regions upstream of experimentally known operons in E. coli. (a) Number of promoters regulated by a given number of transcription factors. (b) Proportion of different sensing classes transcriptionally controlling the expression of operons in E. coli at various thresholds of the number of TFs controlling an operon. To represent, for each bin, first a vector showing the proportion of sensing classes for each operon was calculated and then an average was obtained over the total number of operons present in a given bin, thus obtaining the occurrence of a sensing class. As the number of TFs regulating an operon increased proportion of ISM and hybrid (H) TFs showed a tendency to decrease, while the external TFs from two-component systems increased slightly. Interestingly, IDB TFs were also found to increase their propensity as the number of TFs increased.
© Copyright Policy - creative-commons
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2175315&req=5

Figure 5: Distribution of sensing classes of TFs regulating the promoter regions upstream of experimentally known operons in E. coli. (a) Number of promoters regulated by a given number of transcription factors. (b) Proportion of different sensing classes transcriptionally controlling the expression of operons in E. coli at various thresholds of the number of TFs controlling an operon. To represent, for each bin, first a vector showing the proportion of sensing classes for each operon was calculated and then an average was obtained over the total number of operons present in a given bin, thus obtaining the occurrence of a sensing class. As the number of TFs regulating an operon increased proportion of ISM and hybrid (H) TFs showed a tendency to decrease, while the external TFs from two-component systems increased slightly. Interestingly, IDB TFs were also found to increase their propensity as the number of TFs increased.
Mentions: Understanding network motifs, which are topological structures controlling the local expression dynamics in the cell, although is of great interest, studies on them is often limited to combinatorial regulation of a promoter by no more than two TFs. However, to appreciate the effect of the action of multiple TFs on a single promoter in the context of sensing classes, one has to study the frequency distribution of TFs from different sensing classes when promoters are regulated by one or more TFs. Indeed control of transcription by multiple TFs at a promoter has been an area of immense interest in itself due to a variety of possible mechanisms by which TFs can combinatorially control the expression of a gene (3,19). As seen in Figure 5a, very few promoters are regulated by four or more TFs suggesting limitations on the number of different binding sites possible in the already short intergenic regions in prokaryotic organisms. A possible explanation for this limitation could be the structural and functional constraints imposed in the intergenic regions of bacterial genomes due to restrictions on the sizes of the protein complexes formed during transcription. Figure 5b shows the distribution of sensing classes when the promoters are regulated by only one, two, three and four or more TFs. It is evident from this figure that as the number of TFs regulating a promoter increases the proportion of TFs of internal origin remain constant (ISM and IDB taken together form about 50% of the TFs regulating a promoter) while the ETC TFs show an inclination to increase suggesting that promoters with several TFs regulating them could show a propensity for external TFs after a saturation threshold of the number of internal TFs controlling them. This observation implies that certain transcription units with multiple inputs can be used under a variety of exogenous conditions depending on the external TFs which modulate their activity particular to a condition.Figure 5.

Bottom Line: The active and inactive state of transcription factors in growing cells is usually directed by allosteric physicochemical signals or metabolites, which are in turn either produced in the cell or obtained from the environment by the activity of the products of effector genes.Finally we show that evolutionary families of TFs do not show a tendency to preserve their sensing abilities.Our results provide a detailed panorama of the topological structures of E. coli TRN and the way TFs they compose off, sense their surroundings by coordinating responses.

View Article: PubMed Central - PubMed

Affiliation: Programa de Genómica Computacional, Centro de Ciencias Genómicas, Universidad Nacional Autónoma de México, Cuernavaca, Morelos, 62100, México. sarath@ccg.unam.mx

ABSTRACT
The active and inactive state of transcription factors in growing cells is usually directed by allosteric physicochemical signals or metabolites, which are in turn either produced in the cell or obtained from the environment by the activity of the products of effector genes. To understand the regulatory dynamics and to improve our knowledge about how transcription factors (TFs) respond to endogenous and exogenous signals in the bacterial model, Escherichia coli, we previously proposed to classify TFs into external, internal and hybrid sensing classes depending on the source of their allosteric or equivalent metabolite. Here we analyze how a cell uses its topological structures in the context of sensing machinery and show that, while feed forward loops (FFLs) tightly integrate internal and external sensing TFs connecting TFs from different layers of the hierarchical transcriptional regulatory network (TRN), bifan motifs frequently connect TFs belonging to the same sensing class and could act as a bridge between TFs originating from the same level in the hierarchy. We observe that modules identified in the regulatory network of E. coli are heterogeneous in sensing context with a clear combination of internal and external sensing categories depending on the physiological role played by the module. We also note that propensity of two-component response regulators increases at promoters, as the number of TFs regulating a target operon increases. Finally we show that evolutionary families of TFs do not show a tendency to preserve their sensing abilities. Our results provide a detailed panorama of the topological structures of E. coli TRN and the way TFs they compose off, sense their surroundings by coordinating responses.

Show MeSH
Related in: MedlinePlus