Limits...
Genomic analysis reveals a tight link between transcription factor dynamics and regulatory network architecture.

Jothi R, Balaji S, Wuster A, Grochow JA, Gsponer J, Przytycka TM, Aravind L, Babu MM - Mol. Syst. Biol. (2009)

Bottom Line: At the protein level, the top-layer TFs are relatively abundant, long-lived, and noisy compared with the core- and bottom-layer TFs.Although variability in expression of top-layer TFs might confer a selective advantage, as this permits at least some members in a clonal cell population to initiate a response to changing conditions, tight regulation of the core- and bottom-layer TFs may minimize noise propagation and ensure fidelity in regulation.We propose that the interplay between network organization and TF dynamics could permit differential utilization of the same underlying network by distinct members of a clonal cell population.

View Article: PubMed Central - PubMed

Affiliation: Biostatistics Branch, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC 27709, USA. jothi@mail.nih.gov

ABSTRACT
Although several studies have provided important insights into the general principles of biological networks, the link between network organization and the genome-scale dynamics of the underlying entities (genes, mRNAs, and proteins) and its role in systems behavior remain unclear. Here we show that transcription factor (TF) dynamics and regulatory network organization are tightly linked. By classifying TFs in the yeast regulatory network into three hierarchical layers (top, core, and bottom) and integrating diverse genome-scale datasets, we find that the TFs have static and dynamic properties that are similar within a layer and different across layers. At the protein level, the top-layer TFs are relatively abundant, long-lived, and noisy compared with the core- and bottom-layer TFs. Although variability in expression of top-layer TFs might confer a selective advantage, as this permits at least some members in a clonal cell population to initiate a response to changing conditions, tight regulation of the core- and bottom-layer TFs may minimize noise propagation and ensure fidelity in regulation. We propose that the interplay between network organization and TF dynamics could permit differential utilization of the same underlying network by distinct members of a clonal cell population.

Show MeSH
A schematic model describing the conceptual framework of differential utilization of the same underlying regulatory network by distinct members of a genetically identical cell population. (A) A toy regulatory network showing two regulatory pathways, which will be used to respond to two specific extracellular stimuli. The red, green, and blue nodes in the network represent transcription factors (TFs), symbolically representing the inferred top-, core-, and bottom-layer TFs in the hierarchical network, respectively. (B) Members of a clonal cell population responding to stimulus 1 (top panel). The variability in expression of top-layer TFs (shown as nodes in varying shades of red; middle panel) permits differential sampling of the same underlying network by distinct members of a genetically identical population of cells. TFs colored in gray are not expressed at necessary levels, and are shown as inactive nodes. Edges originating from inactive TFs are inactive (shown in gray). A noisy master-regulator TF at the top of the hierarchy would mean that only a subset of a population, in which this TF is expressed at necessary levels, will have this TF in active form. An inactive TF at the top of a hierarchical regulatory cascade will result in the non-expression per inactivation of all downstream TFs and TGs dependent on this TF. Members of a clonal population whose regulatory pathway for a specific extracellular stimulus is active will initiate an effective response when that stimulus is encountered. And, those members in whom this regulatory pathway is inactive will be unable to mount an effective response. Though all members in the population are sampling the part of the network necessary to respond to stimulus 1, only a few members (shown as purple and orange cells; bottom panel) are sampling (or poised to sample) the part of the network necessary to respond to stimulus 2. (C) A change in stimulus (from stimulus 1 to 2) causes only those cells that have an active regulatory response pathway for stimulus 2 to effectively respond and survive, whereas the others may mount a late response or will not survive. Alternatively, low expression of top-layer TFs might facilitate cell survival if the pathway regulated by such TFs leads to cell death (e.g., apoptosis). Thus, the presence of noisy TFs at the top of the hierarchical regulatory cascade might confer a selective advantage as this permits at least some members in a clonal population to respond to changing conditions.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC2736650&req=5

f6: A schematic model describing the conceptual framework of differential utilization of the same underlying regulatory network by distinct members of a genetically identical cell population. (A) A toy regulatory network showing two regulatory pathways, which will be used to respond to two specific extracellular stimuli. The red, green, and blue nodes in the network represent transcription factors (TFs), symbolically representing the inferred top-, core-, and bottom-layer TFs in the hierarchical network, respectively. (B) Members of a clonal cell population responding to stimulus 1 (top panel). The variability in expression of top-layer TFs (shown as nodes in varying shades of red; middle panel) permits differential sampling of the same underlying network by distinct members of a genetically identical population of cells. TFs colored in gray are not expressed at necessary levels, and are shown as inactive nodes. Edges originating from inactive TFs are inactive (shown in gray). A noisy master-regulator TF at the top of the hierarchy would mean that only a subset of a population, in which this TF is expressed at necessary levels, will have this TF in active form. An inactive TF at the top of a hierarchical regulatory cascade will result in the non-expression per inactivation of all downstream TFs and TGs dependent on this TF. Members of a clonal population whose regulatory pathway for a specific extracellular stimulus is active will initiate an effective response when that stimulus is encountered. And, those members in whom this regulatory pathway is inactive will be unable to mount an effective response. Though all members in the population are sampling the part of the network necessary to respond to stimulus 1, only a few members (shown as purple and orange cells; bottom panel) are sampling (or poised to sample) the part of the network necessary to respond to stimulus 2. (C) A change in stimulus (from stimulus 1 to 2) causes only those cells that have an active regulatory response pathway for stimulus 2 to effectively respond and survive, whereas the others may mount a late response or will not survive. Alternatively, low expression of top-layer TFs might facilitate cell survival if the pathway regulated by such TFs leads to cell death (e.g., apoptosis). Thus, the presence of noisy TFs at the top of the hierarchical regulatory cascade might confer a selective advantage as this permits at least some members in a clonal population to respond to changing conditions.

Mentions: The observation that top-layer TFs show a relatively higher variability in protein abundance between individuals in a clonal population of cells (Figure 5F) suggests that such a behavior may confer a selective advantage to individuals, as this permits at least some members in a population to respond effectively to changing conditions by triggering relevant transcriptional cascades (Spudich and Koshland, 1976; McAdams and Arkin, 1999; Rao et al, 2002; Kaern et al, 2005; Raser and O'Shea, 2005; Blake et al, 2006; Ramsey et al, 2006; Samoilov et al, 2006; Acar et al, 2008; Heath et al, 2008; Lopez-Maury et al, 2008; Raj and van Oudenaarden, 2008; Shahrezaei and Swain, 2008b). For instance, ABF1, which is a multifunctional TF present in the top layer, is an abundant protein whose levels are noisy in a clonal population of cells. However, the activity of ABF1 depends on the availability of its co-activators (e.g., CDC6) and on its phosphorylation state, which is known to be regulated by several kinases (e.g., casein kinase 2) or phosphatases (Silve et al, 1992; Upton et al, 1995). The relatively higher noise in the abundance of ABF1 might ensure that, at least, some members in a population would respond rapidly to changing environments (i.e., when co-activators or kinases are activated in response to the altered external stimulus). We propose that high variability in the expression of key TFs, whose TGs might contribute to phenotypic variation, might be a general strategy to facilitate adaptation to diverse environments (see Figure 6 for a model). This does not exclude the possibility that variation in the protein expression levels of specific target genes (independent of the variation in the levels of their regulating TFs) might dictate cell-fate outcomes in a post-transcriptional or post-translational manner. Hence, a detailed investigation that integrates multiple types of networks with data on cell-to-cell variation in the levels of transcripts and proteins might elucidate the contribution from TF-dependent and TF-independent modes for adaptability of cells to changing environments.


Genomic analysis reveals a tight link between transcription factor dynamics and regulatory network architecture.

Jothi R, Balaji S, Wuster A, Grochow JA, Gsponer J, Przytycka TM, Aravind L, Babu MM - Mol. Syst. Biol. (2009)

A schematic model describing the conceptual framework of differential utilization of the same underlying regulatory network by distinct members of a genetically identical cell population. (A) A toy regulatory network showing two regulatory pathways, which will be used to respond to two specific extracellular stimuli. The red, green, and blue nodes in the network represent transcription factors (TFs), symbolically representing the inferred top-, core-, and bottom-layer TFs in the hierarchical network, respectively. (B) Members of a clonal cell population responding to stimulus 1 (top panel). The variability in expression of top-layer TFs (shown as nodes in varying shades of red; middle panel) permits differential sampling of the same underlying network by distinct members of a genetically identical population of cells. TFs colored in gray are not expressed at necessary levels, and are shown as inactive nodes. Edges originating from inactive TFs are inactive (shown in gray). A noisy master-regulator TF at the top of the hierarchy would mean that only a subset of a population, in which this TF is expressed at necessary levels, will have this TF in active form. An inactive TF at the top of a hierarchical regulatory cascade will result in the non-expression per inactivation of all downstream TFs and TGs dependent on this TF. Members of a clonal population whose regulatory pathway for a specific extracellular stimulus is active will initiate an effective response when that stimulus is encountered. And, those members in whom this regulatory pathway is inactive will be unable to mount an effective response. Though all members in the population are sampling the part of the network necessary to respond to stimulus 1, only a few members (shown as purple and orange cells; bottom panel) are sampling (or poised to sample) the part of the network necessary to respond to stimulus 2. (C) A change in stimulus (from stimulus 1 to 2) causes only those cells that have an active regulatory response pathway for stimulus 2 to effectively respond and survive, whereas the others may mount a late response or will not survive. Alternatively, low expression of top-layer TFs might facilitate cell survival if the pathway regulated by such TFs leads to cell death (e.g., apoptosis). Thus, the presence of noisy TFs at the top of the hierarchical regulatory cascade might confer a selective advantage as this permits at least some members in a clonal population to respond to changing conditions.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2736650&req=5

f6: A schematic model describing the conceptual framework of differential utilization of the same underlying regulatory network by distinct members of a genetically identical cell population. (A) A toy regulatory network showing two regulatory pathways, which will be used to respond to two specific extracellular stimuli. The red, green, and blue nodes in the network represent transcription factors (TFs), symbolically representing the inferred top-, core-, and bottom-layer TFs in the hierarchical network, respectively. (B) Members of a clonal cell population responding to stimulus 1 (top panel). The variability in expression of top-layer TFs (shown as nodes in varying shades of red; middle panel) permits differential sampling of the same underlying network by distinct members of a genetically identical population of cells. TFs colored in gray are not expressed at necessary levels, and are shown as inactive nodes. Edges originating from inactive TFs are inactive (shown in gray). A noisy master-regulator TF at the top of the hierarchy would mean that only a subset of a population, in which this TF is expressed at necessary levels, will have this TF in active form. An inactive TF at the top of a hierarchical regulatory cascade will result in the non-expression per inactivation of all downstream TFs and TGs dependent on this TF. Members of a clonal population whose regulatory pathway for a specific extracellular stimulus is active will initiate an effective response when that stimulus is encountered. And, those members in whom this regulatory pathway is inactive will be unable to mount an effective response. Though all members in the population are sampling the part of the network necessary to respond to stimulus 1, only a few members (shown as purple and orange cells; bottom panel) are sampling (or poised to sample) the part of the network necessary to respond to stimulus 2. (C) A change in stimulus (from stimulus 1 to 2) causes only those cells that have an active regulatory response pathway for stimulus 2 to effectively respond and survive, whereas the others may mount a late response or will not survive. Alternatively, low expression of top-layer TFs might facilitate cell survival if the pathway regulated by such TFs leads to cell death (e.g., apoptosis). Thus, the presence of noisy TFs at the top of the hierarchical regulatory cascade might confer a selective advantage as this permits at least some members in a clonal population to respond to changing conditions.
Mentions: The observation that top-layer TFs show a relatively higher variability in protein abundance between individuals in a clonal population of cells (Figure 5F) suggests that such a behavior may confer a selective advantage to individuals, as this permits at least some members in a population to respond effectively to changing conditions by triggering relevant transcriptional cascades (Spudich and Koshland, 1976; McAdams and Arkin, 1999; Rao et al, 2002; Kaern et al, 2005; Raser and O'Shea, 2005; Blake et al, 2006; Ramsey et al, 2006; Samoilov et al, 2006; Acar et al, 2008; Heath et al, 2008; Lopez-Maury et al, 2008; Raj and van Oudenaarden, 2008; Shahrezaei and Swain, 2008b). For instance, ABF1, which is a multifunctional TF present in the top layer, is an abundant protein whose levels are noisy in a clonal population of cells. However, the activity of ABF1 depends on the availability of its co-activators (e.g., CDC6) and on its phosphorylation state, which is known to be regulated by several kinases (e.g., casein kinase 2) or phosphatases (Silve et al, 1992; Upton et al, 1995). The relatively higher noise in the abundance of ABF1 might ensure that, at least, some members in a population would respond rapidly to changing environments (i.e., when co-activators or kinases are activated in response to the altered external stimulus). We propose that high variability in the expression of key TFs, whose TGs might contribute to phenotypic variation, might be a general strategy to facilitate adaptation to diverse environments (see Figure 6 for a model). This does not exclude the possibility that variation in the protein expression levels of specific target genes (independent of the variation in the levels of their regulating TFs) might dictate cell-fate outcomes in a post-transcriptional or post-translational manner. Hence, a detailed investigation that integrates multiple types of networks with data on cell-to-cell variation in the levels of transcripts and proteins might elucidate the contribution from TF-dependent and TF-independent modes for adaptability of cells to changing environments.

Bottom Line: At the protein level, the top-layer TFs are relatively abundant, long-lived, and noisy compared with the core- and bottom-layer TFs.Although variability in expression of top-layer TFs might confer a selective advantage, as this permits at least some members in a clonal cell population to initiate a response to changing conditions, tight regulation of the core- and bottom-layer TFs may minimize noise propagation and ensure fidelity in regulation.We propose that the interplay between network organization and TF dynamics could permit differential utilization of the same underlying network by distinct members of a clonal cell population.

View Article: PubMed Central - PubMed

Affiliation: Biostatistics Branch, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC 27709, USA. jothi@mail.nih.gov

ABSTRACT
Although several studies have provided important insights into the general principles of biological networks, the link between network organization and the genome-scale dynamics of the underlying entities (genes, mRNAs, and proteins) and its role in systems behavior remain unclear. Here we show that transcription factor (TF) dynamics and regulatory network organization are tightly linked. By classifying TFs in the yeast regulatory network into three hierarchical layers (top, core, and bottom) and integrating diverse genome-scale datasets, we find that the TFs have static and dynamic properties that are similar within a layer and different across layers. At the protein level, the top-layer TFs are relatively abundant, long-lived, and noisy compared with the core- and bottom-layer TFs. Although variability in expression of top-layer TFs might confer a selective advantage, as this permits at least some members in a clonal cell population to initiate a response to changing conditions, tight regulation of the core- and bottom-layer TFs may minimize noise propagation and ensure fidelity in regulation. We propose that the interplay between network organization and TF dynamics could permit differential utilization of the same underlying network by distinct members of a clonal cell population.

Show MeSH