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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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Related in: MedlinePlus

Distribution of different sensing classes in coherent and incoherent FFL motif sub-types identified in E. coli. (a) Proportion of different sensing categories among the TFs occupying the first position of the different FFL sub-types. (b) Proportion of different sensing categories among the TFs occupying the second position for all the FFL sub-types. FFL motif sub-types are named according to Mangan and Alon (28). C1-4 correspond to the coherent FFL types while IC1-4 correspond to the incoherent motif types, described earlier. For instance in a FFL if TF X regulates the activity of the genes Y and Z, while TF Y regulates Z, the sign −+ in the figure corresponds to the repression of Y and Z by X while activation of Z by Y thus representing the regulatory links between the gene pairs XY, XZ and YZ, respectively. Numbers below each motif type show the abundance of motifs of that kind identified in the TRN.
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Figure 2: Distribution of different sensing classes in coherent and incoherent FFL motif sub-types identified in E. coli. (a) Proportion of different sensing categories among the TFs occupying the first position of the different FFL sub-types. (b) Proportion of different sensing categories among the TFs occupying the second position for all the FFL sub-types. FFL motif sub-types are named according to Mangan and Alon (28). C1-4 correspond to the coherent FFL types while IC1-4 correspond to the incoherent motif types, described earlier. For instance in a FFL if TF X regulates the activity of the genes Y and Z, while TF Y regulates Z, the sign −+ in the figure corresponds to the repression of Y and Z by X while activation of Z by Y thus representing the regulatory links between the gene pairs XY, XZ and YZ, respectively. Numbers below each motif type show the abundance of motifs of that kind identified in the TRN.

Mentions: To unravel the function of the FFLs, one needs to understand how X and Y are integrated to regulate the promoter upstream of Z. Since each of the three regulatory interactions in the FFL can be either activation or repression, there are eight possible structural types of FFL. These eight types can in turn be divided into coherent or incoherent FFLs, depending on whether the sign of the direct path from TF X to output Z is the same as the overall sign of the indirect path through transcription factor Y or the two paths have opposite signs (28). Previous studies showed that two of these eight motif subtypes, namely coherent type-1 and incoherent type-1, occur much more predominantly in the TRNs of E. coli and yeast (28,32). While the former was shown to possess the property of producing a delay in the initial response when the input function at the Z promoter is AND, the later was demonstrated to function as response accelerator and pulse generator of the Z promoter (32,33). Given these observations and understanding of the motif dynamics we sought to address the composition of the sensing classes for the first and second position of different motif subtypes. Figure 2 shows the distribution of different sensing classes for the first and second position of the eight FFL motif subtypes identified in the TRN of E. coli (see Materials and Methods section). We found that apart from the coherent and incoherent type-1 subtypes of FFLs, coherent type-4 and incoherent type-2 motif subtypes are also dominant in the currently known TRN of E. coli. Although previous theoretical works have shown that increased effective cooperativity of the coherent type-1 FFL could be evolutionarily advantageous and selected for due to its capability to reduce noise propagation associated with the input signal, no strong theoretical rational could be arrived at for the prevalence of incoherent FFLs (28,34,35). Therefore, it is possible that other motif subtypes which are also found to be prevalent in the TRN of E. coli have important functions which are yet to be explored in detail both theoretically and experimentally. It is interesting to note that four motif subtypes, namely coherent and incoherent types 1 and 3 clearly show a preference for IDB TFs in the first position and about 50% of the TFs in their respective second positions are occupied by H and IDB classes put together, consistent with previous observation that IDB TFs frequently coregulate their targets in conjunction with either IDB or H TFs. It is also evident that in only coherent and incoherent types 2 and 4, ETC TFs are mostly found in the first position. Curiously, the same sensing class is also enriched in the second position for these motif subtypes. From the perspective of the second position, it is worth noting that IDB TFs show a preference to occur in coherent and incoherent type-3 FFLs, given their number of instances while ISM TFs appear more commonly in the coherent and incoherent type-2 motif subtypes. ETM TFs, which sense external transported metabolites and were found to be significantly co-occurring with the ISM TFs in FFLs show a strong tendency to occur in the second position of coherent and incoherent type-1 FFLs. Despite the sensing classification of the TFs, which is based on literature evidence about the physiological role of the TFs and the motif structures, which are based on their non-random occurrence in the TRNs, being very different they still show tendencies for similar distributions in the corresponding coherent and incoherent motif subtypes. For instance, in several cases discussed above similar coherent and incoherent subtypes show very similar preferences for sensing classes in both TF positions, suggesting that the mode of action of the TF (activation or repression) in the second position has little influence in their sensing class distribution. This is especially curious to note given that most TFs occupying the second position of the FFL are not dual regulators but rather one of the other two kinds of regulators. A possible explanation for the observed tendencies is that the second TF (Y) of the FFLs in coherent and incoherent types varies from condition to condition, depending on the available metabolites exterior to the cell. For instance, alternative metabolites to the cell like galactose could be degraded rapidly in the absence of core metabolites using an incoherent system while coherent system with the help of its initial response delay can wait for a persistent external signal to degrade the available metabolites, as has been demonstrated in the case of the arabinose system in E. coli, thereby providing a defined order for the degradation of different substrates (32,33). This could also imply that coherent type could be used for uptake of metabolites which are most commonly available in the cell's natural environment as they could have been tuned for low cellular noise due to a persistent signal, while incoherent types could be used for optional metabolites that need to be degraded by the cell under starvation conditions.Figure 2.


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 different sensing classes in coherent and incoherent FFL motif sub-types identified in E. coli. (a) Proportion of different sensing categories among the TFs occupying the first position of the different FFL sub-types. (b) Proportion of different sensing categories among the TFs occupying the second position for all the FFL sub-types. FFL motif sub-types are named according to Mangan and Alon (28). C1-4 correspond to the coherent FFL types while IC1-4 correspond to the incoherent motif types, described earlier. For instance in a FFL if TF X regulates the activity of the genes Y and Z, while TF Y regulates Z, the sign −+ in the figure corresponds to the repression of Y and Z by X while activation of Z by Y thus representing the regulatory links between the gene pairs XY, XZ and YZ, respectively. Numbers below each motif type show the abundance of motifs of that kind identified in the TRN.
© Copyright Policy - creative-commons
Related In: Results  -  Collection

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

Figure 2: Distribution of different sensing classes in coherent and incoherent FFL motif sub-types identified in E. coli. (a) Proportion of different sensing categories among the TFs occupying the first position of the different FFL sub-types. (b) Proportion of different sensing categories among the TFs occupying the second position for all the FFL sub-types. FFL motif sub-types are named according to Mangan and Alon (28). C1-4 correspond to the coherent FFL types while IC1-4 correspond to the incoherent motif types, described earlier. For instance in a FFL if TF X regulates the activity of the genes Y and Z, while TF Y regulates Z, the sign −+ in the figure corresponds to the repression of Y and Z by X while activation of Z by Y thus representing the regulatory links between the gene pairs XY, XZ and YZ, respectively. Numbers below each motif type show the abundance of motifs of that kind identified in the TRN.
Mentions: To unravel the function of the FFLs, one needs to understand how X and Y are integrated to regulate the promoter upstream of Z. Since each of the three regulatory interactions in the FFL can be either activation or repression, there are eight possible structural types of FFL. These eight types can in turn be divided into coherent or incoherent FFLs, depending on whether the sign of the direct path from TF X to output Z is the same as the overall sign of the indirect path through transcription factor Y or the two paths have opposite signs (28). Previous studies showed that two of these eight motif subtypes, namely coherent type-1 and incoherent type-1, occur much more predominantly in the TRNs of E. coli and yeast (28,32). While the former was shown to possess the property of producing a delay in the initial response when the input function at the Z promoter is AND, the later was demonstrated to function as response accelerator and pulse generator of the Z promoter (32,33). Given these observations and understanding of the motif dynamics we sought to address the composition of the sensing classes for the first and second position of different motif subtypes. Figure 2 shows the distribution of different sensing classes for the first and second position of the eight FFL motif subtypes identified in the TRN of E. coli (see Materials and Methods section). We found that apart from the coherent and incoherent type-1 subtypes of FFLs, coherent type-4 and incoherent type-2 motif subtypes are also dominant in the currently known TRN of E. coli. Although previous theoretical works have shown that increased effective cooperativity of the coherent type-1 FFL could be evolutionarily advantageous and selected for due to its capability to reduce noise propagation associated with the input signal, no strong theoretical rational could be arrived at for the prevalence of incoherent FFLs (28,34,35). Therefore, it is possible that other motif subtypes which are also found to be prevalent in the TRN of E. coli have important functions which are yet to be explored in detail both theoretically and experimentally. It is interesting to note that four motif subtypes, namely coherent and incoherent types 1 and 3 clearly show a preference for IDB TFs in the first position and about 50% of the TFs in their respective second positions are occupied by H and IDB classes put together, consistent with previous observation that IDB TFs frequently coregulate their targets in conjunction with either IDB or H TFs. It is also evident that in only coherent and incoherent types 2 and 4, ETC TFs are mostly found in the first position. Curiously, the same sensing class is also enriched in the second position for these motif subtypes. From the perspective of the second position, it is worth noting that IDB TFs show a preference to occur in coherent and incoherent type-3 FFLs, given their number of instances while ISM TFs appear more commonly in the coherent and incoherent type-2 motif subtypes. ETM TFs, which sense external transported metabolites and were found to be significantly co-occurring with the ISM TFs in FFLs show a strong tendency to occur in the second position of coherent and incoherent type-1 FFLs. Despite the sensing classification of the TFs, which is based on literature evidence about the physiological role of the TFs and the motif structures, which are based on their non-random occurrence in the TRNs, being very different they still show tendencies for similar distributions in the corresponding coherent and incoherent motif subtypes. For instance, in several cases discussed above similar coherent and incoherent subtypes show very similar preferences for sensing classes in both TF positions, suggesting that the mode of action of the TF (activation or repression) in the second position has little influence in their sensing class distribution. This is especially curious to note given that most TFs occupying the second position of the FFL are not dual regulators but rather one of the other two kinds of regulators. A possible explanation for the observed tendencies is that the second TF (Y) of the FFLs in coherent and incoherent types varies from condition to condition, depending on the available metabolites exterior to the cell. For instance, alternative metabolites to the cell like galactose could be degraded rapidly in the absence of core metabolites using an incoherent system while coherent system with the help of its initial response delay can wait for a persistent external signal to degrade the available metabolites, as has been demonstrated in the case of the arabinose system in E. coli, thereby providing a defined order for the degradation of different substrates (32,33). This could also imply that coherent type could be used for uptake of metabolites which are most commonly available in the cell's natural environment as they could have been tuned for low cellular noise due to a persistent signal, while incoherent types could be used for optional metabolites that need to be degraded by the cell under starvation conditions.Figure 2.

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