Another turn for p53

Application of Sensitivity Analysis to Discover Potential Molecular Drug Targets

Mathematical modeling of signaling pathways and regulatory networks has been supporting experimental research for some time now. Sensitivity analysis, aimed at finding model parameters whose changes yield significantly altered cellular responses, is an important part of modeling work. However, sensitivity methods are often directly transplanted from analysis of technical systems, and thus, they may not serve the purposes of analysis of biological systems. This paper presents a novel sensitivity analysis method that is particularly suited to the task of searching for potential molecular drug targets in signaling pathways. Using two sample models of pathways, p53/Mdm2 regulatory module and IFN-β-induced JAK/STAT signaling pathway, we show that the method leads to biologically relevant conclusions, identifying processes suitable for targeted pharmacological inhibition, represented by the reduction of kinetic parameter values. That, in turn, facilitates subsequent search for active drug components.

System-based strategies for p53 recovery

The authors have proposed a systems theory-based novel drug design approach for the p53 pathway. The pathway is taken as a dynamic system represented by ordinary differential equations-based mathematical model. Using control engineering practices, the system analysis and subsequent controller design is performed for the re-activation of wild-type p53. p53 revival is discussed for both modes of operation, i.e. the sustained and oscillatory. To define the problem in control system paradigm, modification in the existing mathematical model is performed to incorporate the effect of Nutlin. Attractor point analysis is carried out to select the suitable domain of attraction. A two-loop negative feedback control strategy is devised to drag the system trajectories to the attractor point and to regulate cellular concentration of Nutlin, respectively. An integrated framework is constituted to incorporate the pharmacokinetic effects of Nutlin in the cancerous cells. Bifurcation analysis is also performed on the p53 model to see the conditions for p53 oscillation.

The Future of Computational Chemogenomics

Following the elucidation of the human genome, chemogenomics emerged in the beginning of the twenty-first century as an interdisciplinary research field with the aim to accelerate target and drug discovery by making best usage of the genomic data and the data linkable to it. What started as a systematization approach within protein target families now encompasses all types of chemical compounds and gene products. A key objective of chemogenomics is the establishment, extension, analysis, and prediction of a comprehensive SAR matrix which by application will enable further systematization in drug discovery. Herein we outline future perspectives of chemogenomics including the extension to new molecular modalities, or the potential extension beyond the pharma to the agro and nutrition sectors, and the importance for environmental protection. The focus is on computational sciences with potential applications for compound library design, virtual screening, hit assessment, analysis of phenotypic screens, lead finding and optimization, and systems biology-based prediction of toxicology and translational research.

Excitability in the p53 network mediates robust signaling with tunable activation thresholds in single cells

Cellular signaling systems precisely transmit information in the presence of molecular noise while retaining flexibility to accommodate the needs of individual cells. To understand design principles underlying such versatile signaling, we analyzed the response of the tumor suppressor p53 to varying levels of DNA damage in hundreds of individual cells and observed a switch between distinct signaling modes characterized by isolated pulses and sustained oscillations of p53 accumulation. Guided by dynamic systems theory we show that this requires an excitable network structure comprising positive feedback and provide experimental evidence for its molecular identity. The resulting data-driven model reproduced all features of measured signaling responses and is sufficient to explain their heterogeneity in individual cells. We present evidence that heterogeneity in the levels of the feedback regulator Wip1 sets cell-specific thresholds for p53 activation, providing means to modulate its response through interacting signaling pathways. Our results demonstrate how excitable signaling networks can provide high specificity, sensitivity and robustness while retaining unique possibilities to adjust their function to the physiology of individual cells.

On the increase in network robustness and decrease in network response ability during the aging process: a systems biology approach via microarray data

Aging, an extremely complex and system-level process, has attracted much attention in medical research, especially since chronic diseases are quite prevalent in the elderly population. These may be the result of both gene mutations that lead to intrinsic perturbations and environmental changes that may stimulate signaling in the body. Therefore, analysis of network robustness to tolerate intrinsic perturbations and network response ability of gene networks to respond to external stimuli during the aging process may provide insight into the systematic changes caused by aging. We first propose novel methods to estimate network robustness and measure network response ability of gene regulatory networks by using their corresponding microarray data in the aging process. Then, we find that an aging-related gene network is more robust to intrinsic perturbations in the elderly than the young, and therefore is less responsive to external stimuli. Finally, we find that the response abilities of individual genes, especially FOXOs, NF-κB, and p53, are significantly different in the young versus the aged subjects. These observations are consistent with experimental findings in the aged population, e.g., elevated incidence of tumorigenesis and diminished resistance to oxidative stress. The proposed method can also be used for exploring and analyzing the dynamic properties of other biological processes via corresponding microarray data to provide useful information on clinical strategy and drug target selection.

Rigor of cell fate decision by variable p53 pulses and roles of cooperative gene expression by p53

Upon DNA damage, the cell fate decision between survival and apoptosis is largely regulated by p53-related networks. Recent experiments found a series of discrete p53 pulses in individual cells, which led to the hypothesis that the cell fate decision upon DNA damage is controlled by counting the number of p53 pulses. Under this hypothesis, Sun et al. (2009) modeled the Bax activation switch in the apoptosis signal transduction pathway that can rigorously "count" the number of uniform p53 pulses. Based on experimental evidence, here we use variable p53 pulses with Sun et al.'s model to investigate how the variability in p53 pulses affects the rigor of the cell fate decision by the pulse number. Our calculations showed that the experimentally anticipated variability in the pulse sizes reduces the rigor of the cell fate decision. In addition, we tested the roles of the cooperativity in PUMA expression by p53, finding that lower cooperativity is plausible for more rigorous cell fate decision. This is because the variability in the p53 pulse height is more amplified in PUMA expressions with more cooperative cases.

Noise amplification in human tumor suppression following gamma irradiation

The influence of noise on oscillatory motion is a subject of permanent interest, both for fundamental and practical reasons. Cells respond properly to external stimuli by using noisy systems. We have clarified the effect of intrinsic noise on the dynamics in the human cancer cells following gamma irradiation. It is shown that the large amplification and increasing mutual information with delay are due to coherence resonance. Furthermore, frequency domain analysis is used to study the mechanisms.

Dynamic modeling and analysis of cancer cellular network motifs

With the advent of high-throughput biology, we now routinely scan cells and organisms at practically all levels, from genome to protein, metabolism, signaling and other cellular functions. This methodology allowed biological studies to move from a reductionist approach, such as isolation of specific pathways and mechanisms, to a more integrative approach, where biological systems are seen as a network of interconnected components that provide specific outputs and functions in response to stimuli. Recent literature on biological networks demonstrates two important concepts that we will consider in this review: (i) cellular pathways are highly interconnected and should not be studied separately, but as a network; (ii) simple, recurrent feedback motifs within the network can produce very specific functions that favor their modular use. The first theme differs from the traditional approach in biology because it provides a framework (i.e., the network view) in which large datasets are analyzed with an unbiased view. The second theme (feedback motifs) shows the importance of locally analyzing the dynamic properties of biological networks in order to better understand their functionality. We will review these themes with examples from cell signaling networks, gene regulatory networks and metabolic pathways. The deregulation of cellular networks (metabolism, signaling etc.) is involved in cancer, but the size of the networks and resulting non-linear behavior do not allow for intuitive reasoning. In that context, we argue that the qualitative classification of the 'building blocs' of biological networks (i.e. the motifs) in terms of dynamics and functionality will be critical to improve our understanding of cancer biology and rationalize the wealth of information from high-throughput experiments. From the examples highlighted in this review, it is clear that dynamic feedback motifs can be used to provide a unified view of various cellular processes involved in cancer and this will be critical for future research on personalized and predictive cancer therapies.

Decision making of the p53 network: death by integration

The tumor suppressor protein p53 plays a central role in the multiple response pathways activated by DNA damage. In particular, p53 is involved in both the pro-survival response of cell cycle arrest and DNA repair, and the pro-death response of apoptosis. How does the p53 network coordinate the different pathways that lead to the opposite cell fates and what is its strategy in making the life-death decisions? To address these questions, we develop an integrated mathematical model that embraces three key modules of the p53 network: p53 core regulation, p53-induced cell cycle arrest and p53-dependent apoptosis initiation. Our analyses reveal that different aspects of the nuclear p53 dynamic profile are being used to differentially regulate the pro-survival and the pro-death modules. While the activation of the pro-survival module is dependent on the current or recent status of the DNA damage, the activation of the pro-death module relies on the accumulation or integration of the damage level over time. Thus, the cell will take the death fate if it cannot recover from the damage within a time period that is inversely proportional to the damage level. This "adaptive timer" strategy is likely to be adopted in other stress response systems.

Intrinsic noise and Hill dynamics in the p53 system

The p53 feedback loop can induce cellular senescence, cell cycle arrest and apoptosis in response to various stresses, including DNA damage, hypoxia and nutrient deprivation. Using a stochastic model of the negative feedback circuit involving p53 and its inhibitor Mdm2, we present the different oscillatory dynamics at the single-cell and population-cell levels as described in the experiments, and the resonant nature of the oscillations is captured. The stationary distributions of protein populations are characterized by non-Gaussian nature which is due to the interplay between time delay and nonlinearity of reactions.

Stress-specific response of the p53-Mdm2 feedback loop

Background

The p53 signalling pathway has hundreds of inputs and outputs. It can trigger cellular senescence, cell-cycle arrest and apoptosis in response to diverse stress conditions, including DNA damage, hypoxia and nutrient deprivation. Signals from all these inputs are channeled through a single node, the transcription factor p53. Yet, the pathway is flexible enough to produce different downstream gene expression patterns in response to different stresses.

Results

We construct a mathematical model of the negative feedback loop involving p53 and its inhibitor, Mdm2, at the core of this pathway, and use it to examine the effect of different stresses that trigger p53. In response to DNA damage, hypoxia, etc., the model exhibits a wide variety of specific output behaviour - steady states with low or high levels of p53 and Mdm2, as well as spiky oscillations with low or high average p53 levels.

Conclusions

We show that even a simple negative feedback loop is capable of exhibiting the kind of flexible stress-specific response observed in the p53 system. Further, our model provides a framework for predicting the differences in p53 response to different stresses and single nucleotide polymorphisms.

Harmonic oscillations in homeostatic controllers: Dynamics of the p53 regulatory system

Homeostatic mechanisms are essential for the protection and adaptation of organisms in a changing and challenging environment. Previously, we have described molecular mechanisms that lead to robust homeostasis/adaptation under inflow or outflow perturbations. Here we report that harmonic oscillations occur in models of such homeostatic controllers and that a close relationship exists between the control of the p53/Mdm2 system and that of a homeostatic inflow controller. This homeostatic control model of the p53 system provides an explanation why large fluctuations in the amplitude of p53/Mdm2 oscillations may arise as part of the homeostatic regulation of p53 by Mdm2 under DNA-damaging conditions. In the presence of DNA damage p53 is upregulated, but is subject to a tight control by Mdm2 and other factors to avoid a premature apoptotic response of the cell at low DNA damage levels. One of the regulatory steps is the Mdm2-mediated degradation of p53 by the proteasome. Oscillations in the p53/Mdm2 system are considered to be part of a mechanism by which a cell decides between cell cycle arrest/DNA repair and apoptosis. In the homeostatic inflow control model, harmonic oscillations in p53/Mdm2 levels arise when the binding strength of p53 to degradation complexes increases. Due to the harmonic character of the oscillations rapid fluctuating noise can lead, as experimentally observed, to large variations in the amplitude of the oscillation but not in their period, a behavior which has been difficult to simulate by deterministic limit-cycle models. In conclusion, the oscillatory response of homeostatic controllers may provide new insights into the origin and role of oscillations observed in homeostatically controlled molecular networks.

Cell fate decision mediated by p53 pulses

The tumor suppressor p53 plays a crucial role in cellular response to various stresses. Recent experiments have shown that p53 level exhibits a series of pulses after DNA damage caused by ionizing radiation (IR). However, how the p53 pulses govern cell survival and death remains unclear. Here, we develop an integrated model with four modules for the p53 network and explore the mechanism for cell fate decision based on the dynamics of the network. By numerical simulations, the following processes are characterized. First, DNA repair proteins bind to IR-induced double-strand breaks, forming complexes, which are then detected by ataxia telangiectasia mutated (ATM). Activated ATM initiates the p53 oscillator to produce pulses. Consequently, the target genes of p53 are selectively induced to control cell fate. We propose that p53 promotes the repair of minor DNA damage but suppresses the repair of severe damage. We demonstrate that cell fate is determined by the number of p53 pulses relying on the extent of DNA damage. At low damage levels, few p53 pulses evoke cell cycle arrest by inducing p21 and promote cell survival, whereas at high damage levels, sustained p53 pulses trigger apoptosis by inducing p53AIP1. We find that p53 can effectively maintain genomic integrity by regulating the efficiency and fidelity of DNA repair. We also show that stochasticity in the generation and repair of DNA damage leads to variability in cell fate. These findings are consistent with experimental observations and advance our understanding of the dynamics and functions of the p53 network.

Oscillations of the p53-Akt network: implications on cell survival and death

Intracellular protein levels of p53 and MDM2 have been shown to oscillate in response to ionizing radiation (IR), but the physiological significance of these oscillations remains unclear. The p53-MDM2 negative feedback loop – the putative cause of the oscillations – is embedded in a network involving a mutual antagonism (or positive feedback loop) between p53 and AKT. We have shown earlier that this p53-AKT network predicts an all-or-none switching behavior between a pro-survival cellular state (low p53 and high AKT levels) and a pro-apoptotic state (high p53 and low AKT levels). Here, we show that upon exposure to IR, the p53-AKT network can also reproduce the experimentally observed p53 and MDM2 oscillations. The present work is based on the hypothesis that the physiological significance of the experimentally observed oscillations could be found in their role in regulating the switching behavior of the p53-AKT network between pro-survival and pro-apoptotic states. It is shown here that these oscillations are associated with a significant decrease in the threshold level of IR at which switching from a pro-survival to a pro-apoptotic state occurs. Moreover, oscillations in p53 protein levels induce higher levels of expression of p53-target genes compared to non-oscillatory p53, and thus influence cell-fate decisions between cell cycle arrest/DNA damage repair versus apoptosis.

Oscillations by the p53-Mdm2 feedback loop

The p53 network is perhaps the most important pathway involved in preventing the initiation of cancer, p53 levels and activity are upregulated in response to various stresses including DNA damage, hypoxia, and oncogene activation. Active p53 initiates different transcriptional programs that result in cell cycle arrest, cellular senescence or apoptosis. p53 also activates the transcription of Mdm2, which in turns target p53 for degradation, therefore creating a negative feedback loop on p53. Previous studies showed that the level of p53 increased dramatically after exposure to damaging radiation, then declined in a series of damped oscillations. Recent quantitative studies examined p53 responses in individual living cells, using time-lapse fluorescent microscopy and showed that-on an individual cell level-the oscillations are not damped. Instead, one cell may have only one pulse of p53, while its neighbor may show several repeated pulses. As the amount of irradiation increased, the percentage of cells showing a high number of p53 pulses also increased. The mean height and width of the pulses was constant and did not depend on the damage level. These observations opened new questions regarding the mechanism and function of p53 oscillatory dynamics. In this chapter I will review the different models that have been suggested for p53 oscillations, including proposed reasons for variation between cells, and will discuss potential functions for oscillatory dynamics in the p53 signaling pathway and in stress responses in general.

Oscillations and bistability in the stochastic model of p53 regulation

The p53 regulatory pathway controls cell responses, which include cell cycle arrest, DNA repair, apoptosis and cellular senescence. We propose a stochastic model of p53 regulation, which is based on two feedback loops: the negative, coupling p53 with its immediate downregulator Mdm2, and the positive, which involves PTEN, PIP3 and Akt. Existence of the negative feedback assures homeostasis of healthy cells and oscillatory responses of DNA-damaged cells, which are persistent when DNA repair is inefficient and the positive feedback loop is broken. The positive feedback destroys the negative coupling between Mdm2 and p53 by sequestering most of Mdm2 in cytoplasm, so it may no longer prime the nuclear p53 for degradation. It works as a clock, giving the cell some time for DNA repair. However, when DNA repair is inefficient, the active p53 rises to a high level and triggers transcription of proapoptotic genes. As a result, small DNA damage may be repaired and the cell may return to its initial "healthy" state, while the extended damage results in apoptosis. The stochasticity of p53 regulation, introduced at the levels of gene expression, DNA damage and repair, leads to high heterogeneity of cell responses and causes cell population split after irradiation into subpopulations of apoptotic and surviving cells, with fraction of apoptotic cells growing with the irradiation dose.

Analysis of structures causing instabilities

We present a simple new method to systematically identify all topological structures (e.g., positive feedback loops) potentially leading to locally unstable steady states: ICSA-The instability causing structure analysis. Systems without any instability causing structure (i.e., not fulfilling the necessary topological condition for instabilities) cannot have unstable steady states. It follows that common bistability or multistability and Hopf bifurcations are excluded and sustained oscillations and deterministic chaos are most unlikely. The ICSA leads to new insights into the topological organization of chemical and biochemical systems, such as metabolic, gene regulatory, and signal transduction networks.

Reassessing the role of p53 in cancer and ageing from an evolutionary perspective

The gene p53 has been fashioned as the guardian of the genome and as prototype of the tumour suppressor gene (TSG) whose function must be inactivated in order for tumours to develop. The ubiquitous expression of truncated p53 protein isoforms, results in "premature ageing" of laboratory mouse strains engineered for expressing such isoforms. These facts have been construed in the argument that p53 evolved in order to protect organisms with renewable tissues from developing cancer yet, because p53 is also an inducer of cellular senescence or apoptosis after extensive DNA damage, it becomes a limiting factor for tissue renewal by depleting tissues from stem/precursor cells thus leading to whole-organism ageing. From that point of view p53 displays antagonist pleiotropy contributing to the establishment of degenerative diseases and ageing. Therefore, tumour suppression becomes a balancing act between cancer prevention and ageing. Nevertheless, here we present current evidence showing that the aforementioned argument is rather inconsistent and unwarranted on evolutionary grounds. The evolutionary perspective indicates that p53 evolved so as to play a subtle but very important role during development while its role as a TSG is only important in animals that are protected from most sources of extrinsic mortality, thus suggesting that p53 was primarily selected for its developmental role and not as a TSG. Therefore no real antagonist pleiotropy can be attached to p53 functions and their relationship with whole-organism ageing might be a laboratory artefact.

Growth-induced instability in metabolic networks

Product-feedback inhibition is a ubiquitous regulatory scheme for maintaining homeostasis in living cells. Individual metabolic pathways with product-feedback inhibition are stable as long as one pathway step is rate limiting. However, pathways are often coupled both by the use of a common substrate and by stoichiometric utilization of their products for cell growth. We show that such a coupled network with product-feedback inhibition may exhibit limit-cycle oscillations which arise via a Hopf bifurcation. Our results highlight novel evolutionary constraints on the architecture of metabolism.

YcfR (BhsA) influences Escherichia coli biofilm formation through stress response and surface hydrophobicity

DNA microarrays revealed that expression of ycfR, which encodes a putative outer membrane protein, is significantly induced in Escherichia coli biofilms and is also induced by several stress conditions. We show that deletion of ycfR increased biofilm formation fivefold in the presence of glucose; the glucose effect was corroborated by showing binding of the cyclic AMP receptor protein to the ycfR promoter. It appears that YcfR is a multiple stress resistance protein, since deleting ycfR also rendered the cell more sensitive to acid, heat treatment, hydrogen peroxide, and cadmium. Increased biofilm formation through YcfR due to stress appears to be the result of decreasing indole synthesis, since a mutation in the tnaA gene encoding tryptophanase prevented enhanced biofilm formation upon stress and adding indole prevented enhanced biofilm formation upon stress. Deleting ycfR also affected outer membrane proteins and converted the cell from hydrophilic to hydrophobic, as well as increased cell aggregation fourfold. YcfR seems to be involved in the regulation of E. coli K-12 biofilm formation by decreasing cell aggregation and cell surface adhesion, by influencing the concentration of signal molecules, and by interfering with stress responses. Based on our findings, we propose that this locus be named bhsA, for influencing biofilm through hydrophobicity and stress response.