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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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Statistical significance of combination of sensing classes in bifan motifs observed in the transcriptional network of E. coli. (a) In a bifan motif, two TFs A and B, both regulate the expression of two different target genes C and D. Thus making the positions of the TFs to be symmetric, unlike in FFLs. (b) Matrix shows statistical significance for occurrence of different sensing category combinations in bifans using the z-scores calculated by comparing against 1000 sets of randomly generated bifans as described in Materials and Methods section. Notice that since the positions of the TFs are not relevant only a lower-triangular matrix is shown. Positive z-scores correspond to favored combinations of sensing classes in bifan motifs and vice versa. /z-scores/ >3.3 were considered significant as they corresponded to P-values <0.001, unless otherwise stated.
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Figure 3: Statistical significance of combination of sensing classes in bifan motifs observed in the transcriptional network of E. coli. (a) In a bifan motif, two TFs A and B, both regulate the expression of two different target genes C and D. Thus making the positions of the TFs to be symmetric, unlike in FFLs. (b) Matrix shows statistical significance for occurrence of different sensing category combinations in bifans using the z-scores calculated by comparing against 1000 sets of randomly generated bifans as described in Materials and Methods section. Notice that since the positions of the TFs are not relevant only a lower-triangular matrix is shown. Positive z-scores correspond to favored combinations of sensing classes in bifan motifs and vice versa. /z-scores/ >3.3 were considered significant as they corresponded to P-values <0.001, unless otherwise stated.

Mentions: A Bifan motif is composed of two TFs, A and B, which both control the expression of two different target genes C and D (see Figure 3a). Thus, unlike a FFL motif, the Bifan motif is not hierarchical but rather forms a horizontal layer of interactions. In fact, bifan motifs are a particular subset of complex regulons. A simple regulon being a group of genes regulated by one regulator, and complex regulons, groups of genes regulated by the same set of two or more TFs. The structure of the bifan motif makes the two positions of the TFs symmetric in contrast to the organization of FFLs. Bifan motifs are essential to maintain the network backbone and link it in a horizontal way by connecting across transcriptional regulatory modules (9,36). Figure 3b shows the z-score matrix for co-occurrence of TFs from different sensing classes to appear in bifan motifs identified in the TRN of E. coli (see Materials and Methods section). A clear and strong tendency of coregulation was found between the following pairs of sensing classes: ISM-ISM, ISM-IDB, IDB-H and ETC-ETC (P < 0.001 in each case) suggesting that unlike in FFLs, there is a preference for internal sensing classes to coregulate their targets with other internal TFs and external sensing ETC TFs to control their targets with other TFs of their own class. The enrichment seen in two-component systems to frequently occur together in bifans, i.e regulating the same set of targets, might be a means of feeding multiple external signals, each corresponding to different environmental conditions, as inputs to the interior of the cell. This observation implies that bifans are more homogenous in their sensing class composition compared to FFLs and do not link the external signals using the two component systems with internal TFs, but rather could link to internal machinery with signal transduction cascades. However, bifans do link the ETM with ISM TFs (P < 0.005). On the other hand, the following sensing class combinations showed no preference to coregulate their targets: ISM-H, ISM-ETC, IDB-IDB, IDB-ETM, IDB-ETC, H-H and H-ETC (P < 0.001). IDB and H TFs, which showed strong preference to occur together with other of their kind in FFLs were found to show avoidance to appear together in bifans. This observation implies that bifans are used by IDB and H TFs to connect to each other, while FFLs are used by these TF classes to link among themselves in a hierarchical fashion. It is possible to speculate from these observations that DNA-bending TFs (IDB class) and Hybrid (H) class of TFs combinatorially regulate their targets with the help of TFs of their own class in FFLs, but at the same time also coordinate and integrate their signal responses in a horizontal way with the help of bifan motifs. Taken together, our results suggest that FFLs and bifans distribute the sensing classes of TFs in very distinct ways. While FFLs link internal and external sensing machinery in a hierarchical fashion, bifans show a tendency to connect internal or external sensing classes among themselves in a horizontal manner.Figure 3.


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)

Statistical significance of combination of sensing classes in bifan motifs observed in the transcriptional network of E. coli. (a) In a bifan motif, two TFs A and B, both regulate the expression of two different target genes C and D. Thus making the positions of the TFs to be symmetric, unlike in FFLs. (b) Matrix shows statistical significance for occurrence of different sensing category combinations in bifans using the z-scores calculated by comparing against 1000 sets of randomly generated bifans as described in Materials and Methods section. Notice that since the positions of the TFs are not relevant only a lower-triangular matrix is shown. Positive z-scores correspond to favored combinations of sensing classes in bifan motifs and vice versa. /z-scores/ >3.3 were considered significant as they corresponded to P-values <0.001, unless otherwise stated.
© Copyright Policy - creative-commons
Related In: Results  -  Collection

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

Figure 3: Statistical significance of combination of sensing classes in bifan motifs observed in the transcriptional network of E. coli. (a) In a bifan motif, two TFs A and B, both regulate the expression of two different target genes C and D. Thus making the positions of the TFs to be symmetric, unlike in FFLs. (b) Matrix shows statistical significance for occurrence of different sensing category combinations in bifans using the z-scores calculated by comparing against 1000 sets of randomly generated bifans as described in Materials and Methods section. Notice that since the positions of the TFs are not relevant only a lower-triangular matrix is shown. Positive z-scores correspond to favored combinations of sensing classes in bifan motifs and vice versa. /z-scores/ >3.3 were considered significant as they corresponded to P-values <0.001, unless otherwise stated.
Mentions: A Bifan motif is composed of two TFs, A and B, which both control the expression of two different target genes C and D (see Figure 3a). Thus, unlike a FFL motif, the Bifan motif is not hierarchical but rather forms a horizontal layer of interactions. In fact, bifan motifs are a particular subset of complex regulons. A simple regulon being a group of genes regulated by one regulator, and complex regulons, groups of genes regulated by the same set of two or more TFs. The structure of the bifan motif makes the two positions of the TFs symmetric in contrast to the organization of FFLs. Bifan motifs are essential to maintain the network backbone and link it in a horizontal way by connecting across transcriptional regulatory modules (9,36). Figure 3b shows the z-score matrix for co-occurrence of TFs from different sensing classes to appear in bifan motifs identified in the TRN of E. coli (see Materials and Methods section). A clear and strong tendency of coregulation was found between the following pairs of sensing classes: ISM-ISM, ISM-IDB, IDB-H and ETC-ETC (P < 0.001 in each case) suggesting that unlike in FFLs, there is a preference for internal sensing classes to coregulate their targets with other internal TFs and external sensing ETC TFs to control their targets with other TFs of their own class. The enrichment seen in two-component systems to frequently occur together in bifans, i.e regulating the same set of targets, might be a means of feeding multiple external signals, each corresponding to different environmental conditions, as inputs to the interior of the cell. This observation implies that bifans are more homogenous in their sensing class composition compared to FFLs and do not link the external signals using the two component systems with internal TFs, but rather could link to internal machinery with signal transduction cascades. However, bifans do link the ETM with ISM TFs (P < 0.005). On the other hand, the following sensing class combinations showed no preference to coregulate their targets: ISM-H, ISM-ETC, IDB-IDB, IDB-ETM, IDB-ETC, H-H and H-ETC (P < 0.001). IDB and H TFs, which showed strong preference to occur together with other of their kind in FFLs were found to show avoidance to appear together in bifans. This observation implies that bifans are used by IDB and H TFs to connect to each other, while FFLs are used by these TF classes to link among themselves in a hierarchical fashion. It is possible to speculate from these observations that DNA-bending TFs (IDB class) and Hybrid (H) class of TFs combinatorially regulate their targets with the help of TFs of their own class in FFLs, but at the same time also coordinate and integrate their signal responses in a horizontal way with the help of bifan motifs. Taken together, our results suggest that FFLs and bifans distribute the sensing classes of TFs in very distinct ways. While FFLs link internal and external sensing machinery in a hierarchical fashion, bifans show a tendency to connect internal or external sensing classes among themselves in a horizontal manner.Figure 3.

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