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Dose response relationship in anti-stress gene regulatory networks.

Zhang Q, Andersen ME - PLoS Comput. Biol. (2006)

Bottom Line: Multimerization of anti-stress enzymes and transcription factors into homodimers, homotrimers, or even higher-order multimers, play a significant role in maintaining robust homeostasis.Each phase relies on specific gain-changing events that come into play as stressor level increases.The general dose response transition proposed here was further examined in a complex anti-electrophilic stress pathway, which involves multiple genes, enzymes, and metabolic reactions.

View Article: PubMed Central - PubMed

Affiliation: Division of Computational Biology, CIIT Centers for Health Research, Research Triangle Park, North Carolina, United States of America. qzhang@ciit.org

ABSTRACT
To maintain a stable intracellular environment, cells utilize complex and specialized defense systems against a variety of external perturbations, such as electrophilic stress, heat shock, and hypoxia, etc. Irrespective of the type of stress, many adaptive mechanisms contributing to cellular homeostasis appear to operate through gene regulatory networks that are organized into negative feedback loops. In general, the degree of deviation of the controlled variables, such as electrophiles, misfolded proteins, and O2, is first detected by specialized sensor molecules, then the signal is transduced to specific transcription factors. Transcription factors can regulate the expression of a suite of anti-stress genes, many of which encode enzymes functioning to counteract the perturbed variables. The objective of this study was to explore, using control theory and computational approaches, the theoretical basis that underlies the steady-state dose response relationship between cellular stressors and intracellular biochemical species (controlled variables, transcription factors, and gene products) in these gene regulatory networks. Our work indicated that the shape of dose response curves (linear, superlinear, or sublinear) depends on changes in the specific values of local response coefficients (gains) distributed in the feedback loop. Multimerization of anti-stress enzymes and transcription factors into homodimers, homotrimers, or even higher-order multimers, play a significant role in maintaining robust homeostasis. Moreover, our simulation noted that dose response curves for the controlled variables can transition sequentially through four distinct phases as stressor level increases: initial superlinear with lesser control, superlinear more highly controlled, linear uncontrolled, and sublinear catastrophic. Each phase relies on specific gain-changing events that come into play as stressor level increases. The low-dose region is intrinsically nonlinear, and depending on the level of local gains, presence of gain-changing events, and degree of feedforward gene activation, this region can appear as superlinear, sublinear, or even J-shaped. The general dose response transition proposed here was further examined in a complex anti-electrophilic stress pathway, which involves multiple genes, enzymes, and metabolic reactions. This work would help biologists and especially toxicologists to better assess and predict the cellular impact brought about by biological stressors.

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Multi-Phasic Dose Response Relationships and Systems-Level Gains in the Presence of Constitutive Activation, Saturation of Gene Activation, and Saturation of Enzyme G by YPhase 1: superlinear with lesser control; phase 2: superlinear more highly controlled; phase 3: linear uncontrolled; phase 4: sublinear catastrophic.
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pcbi-0030024-g007: Multi-Phasic Dose Response Relationships and Systems-Level Gains in the Presence of Constitutive Activation, Saturation of Gene Activation, and Saturation of Enzyme G by YPhase 1: superlinear with lesser control; phase 2: superlinear more highly controlled; phase 3: linear uncontrolled; phase 4: sublinear catastrophic.

Mentions: Above, we have discussed how individual gain-changing events associated with constitutive activation, saturation of gene activation, and saturation of G-catalyzed reaction, generate different types of curvature changes in dose response relationships. In a homeostatic gene regulatory network, it is unlikely that these events take place exclusively of one another. Rather, these processes could come into play in combinations and in orders as the stressor level increases, steering the dose response curve through distinct phases. A very possible scenario which can fully manifest all the effects of these events is as follows (Figure 7). In the beginning when S is very small, the gain-repressing effect of constitutive activation keeps the loop gain Rloop very small, hence is close to unity. As S increases, the influence of constitutive activation lessens, bringing closer to the lowest possible value. In this initial -decreasing phase, the Y versus S dose response becomes increasingly superlinear, but compared with situations where no constitutive activation exists, Y is less controlled. The second phase, which is also superlinear in appearance, is characterized by remaining at the lowest value, and is a stage where Y is least sensitive to changes in S compared with other phases. As S increases further, signaling events leading to gene activation move closer to saturation; thus starts to rise and approaches unity as saturation of activation fully sets in. In this process, the superlinear second phase first bends upward through a transitional sublinear segment, then extends into the third phase, which is largely linear. As discussed in the next section, the sublinear transition from phase 2 to 3 could play a significant part in the shape of the curve in the low-dose region. At the end of the third phase, saturation of G by Y becomes increasingly significant, the dose response curve extends into the catastrophic fourth phase, which is sublinear in appearance and grows with increasing . The corresponding G versus S dose response initially experiences a transient unresponsive phase, followed by a superlinear or nearly linear phase, which eventually levels off into a plateau phase (Figure 7C).


Dose response relationship in anti-stress gene regulatory networks.

Zhang Q, Andersen ME - PLoS Comput. Biol. (2006)

Multi-Phasic Dose Response Relationships and Systems-Level Gains in the Presence of Constitutive Activation, Saturation of Gene Activation, and Saturation of Enzyme G by YPhase 1: superlinear with lesser control; phase 2: superlinear more highly controlled; phase 3: linear uncontrolled; phase 4: sublinear catastrophic.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC1808489&req=5

pcbi-0030024-g007: Multi-Phasic Dose Response Relationships and Systems-Level Gains in the Presence of Constitutive Activation, Saturation of Gene Activation, and Saturation of Enzyme G by YPhase 1: superlinear with lesser control; phase 2: superlinear more highly controlled; phase 3: linear uncontrolled; phase 4: sublinear catastrophic.
Mentions: Above, we have discussed how individual gain-changing events associated with constitutive activation, saturation of gene activation, and saturation of G-catalyzed reaction, generate different types of curvature changes in dose response relationships. In a homeostatic gene regulatory network, it is unlikely that these events take place exclusively of one another. Rather, these processes could come into play in combinations and in orders as the stressor level increases, steering the dose response curve through distinct phases. A very possible scenario which can fully manifest all the effects of these events is as follows (Figure 7). In the beginning when S is very small, the gain-repressing effect of constitutive activation keeps the loop gain Rloop very small, hence is close to unity. As S increases, the influence of constitutive activation lessens, bringing closer to the lowest possible value. In this initial -decreasing phase, the Y versus S dose response becomes increasingly superlinear, but compared with situations where no constitutive activation exists, Y is less controlled. The second phase, which is also superlinear in appearance, is characterized by remaining at the lowest value, and is a stage where Y is least sensitive to changes in S compared with other phases. As S increases further, signaling events leading to gene activation move closer to saturation; thus starts to rise and approaches unity as saturation of activation fully sets in. In this process, the superlinear second phase first bends upward through a transitional sublinear segment, then extends into the third phase, which is largely linear. As discussed in the next section, the sublinear transition from phase 2 to 3 could play a significant part in the shape of the curve in the low-dose region. At the end of the third phase, saturation of G by Y becomes increasingly significant, the dose response curve extends into the catastrophic fourth phase, which is sublinear in appearance and grows with increasing . The corresponding G versus S dose response initially experiences a transient unresponsive phase, followed by a superlinear or nearly linear phase, which eventually levels off into a plateau phase (Figure 7C).

Bottom Line: Multimerization of anti-stress enzymes and transcription factors into homodimers, homotrimers, or even higher-order multimers, play a significant role in maintaining robust homeostasis.Each phase relies on specific gain-changing events that come into play as stressor level increases.The general dose response transition proposed here was further examined in a complex anti-electrophilic stress pathway, which involves multiple genes, enzymes, and metabolic reactions.

View Article: PubMed Central - PubMed

Affiliation: Division of Computational Biology, CIIT Centers for Health Research, Research Triangle Park, North Carolina, United States of America. qzhang@ciit.org

ABSTRACT
To maintain a stable intracellular environment, cells utilize complex and specialized defense systems against a variety of external perturbations, such as electrophilic stress, heat shock, and hypoxia, etc. Irrespective of the type of stress, many adaptive mechanisms contributing to cellular homeostasis appear to operate through gene regulatory networks that are organized into negative feedback loops. In general, the degree of deviation of the controlled variables, such as electrophiles, misfolded proteins, and O2, is first detected by specialized sensor molecules, then the signal is transduced to specific transcription factors. Transcription factors can regulate the expression of a suite of anti-stress genes, many of which encode enzymes functioning to counteract the perturbed variables. The objective of this study was to explore, using control theory and computational approaches, the theoretical basis that underlies the steady-state dose response relationship between cellular stressors and intracellular biochemical species (controlled variables, transcription factors, and gene products) in these gene regulatory networks. Our work indicated that the shape of dose response curves (linear, superlinear, or sublinear) depends on changes in the specific values of local response coefficients (gains) distributed in the feedback loop. Multimerization of anti-stress enzymes and transcription factors into homodimers, homotrimers, or even higher-order multimers, play a significant role in maintaining robust homeostasis. Moreover, our simulation noted that dose response curves for the controlled variables can transition sequentially through four distinct phases as stressor level increases: initial superlinear with lesser control, superlinear more highly controlled, linear uncontrolled, and sublinear catastrophic. Each phase relies on specific gain-changing events that come into play as stressor level increases. The low-dose region is intrinsically nonlinear, and depending on the level of local gains, presence of gain-changing events, and degree of feedforward gene activation, this region can appear as superlinear, sublinear, or even J-shaped. The general dose response transition proposed here was further examined in a complex anti-electrophilic stress pathway, which involves multiple genes, enzymes, and metabolic reactions. This work would help biologists and especially toxicologists to better assess and predict the cellular impact brought about by biological stressors.

Show MeSH
Related in: MedlinePlus