Conservation and Divergence of p53 Oscillation Dynamics across Species

Cell confluency affects p53 dynamics in response to DNA damage

The tumor suppressor protein p53 plays a key role in the cellular response to DNA damage. In response to DNA double-strand breaks (DSB), cultured cells exhibit oscillations of p53 levels, which impact gene expression and cell fate. The dynamics of p53 in vivo have only been studied in fixed tissues or using reporters for p53's transcriptional activity. Here we established breast tumors expressing a fluorescent reporter for p53 levels and employed intravital imaging to quantify its dynamics in response to DSB in vivo. Our findings revealed large heterogeneity among individual cells, with most cells exhibiting a single prolonged pulse. We then tested how p53 dynamics might change under high cell confluency, one factor that differs between cell culture and tissues. We revealed that highly confluent cultured breast cancer cells also show one broad p53 pulse instead of oscillations. Through mathematical modeling, sensitivity analysis, and live-cell imaging, we identified low levels of the phosphatase Wip1, a transcriptional target and negative regulator of p53, as a key contributor to these dynamics. Because high cell confluency better reflects the microenvironment of tissues, the impact of cell confluency on p53 dynamics may have important consequences for cancerous tissues responding to DNA damage-inducing therapies.

Systems Biology of the Cancer Cell

Questions in cancer have engaged systems biologists for decades. During that time, the quantity of molecular data has exploded, but the need for abstractions, formal models, and simplifying insights has remained the same. This review brings together classic breakthroughs and recent findings in the field of cancer systems biology, focusing on cancer cell pathways for tumorigenesis and therapeutic response. Cancer cells mutate and transduce information from their environment to alter gene expression, metabolism, and phenotypic states. Understanding the molecular architectures that make each of these steps possible is a long-term goal of cancer systems biology pursued by iterating between quantitative models and experiments. We argue that such iteration is the best path to deploying targeted therapies intelligently so that each patient receives the maximum benefit for their cancer.

Pulsed stimuli enable p53 phase resetting to synchronize single cells and modulate cell fate

Oscillatory p53 expression occurs in individual cells responding to DNA breaks. While the majority of cells exhibit the same qualitative response, quantitative features of the oscillations (e.g., amplitude or period) can be highly variable between cells, generating heterogeneity in downstream cell fate responses. Since heterogeneity can be detrimental to therapies based on DNA damage, methods to induce synchronization of p53 oscillations across cells in a population have the potential to generate more predictable responses to DNA-damaging treatments. Using mathematical modeling and time-lapse microscopy, we demonstrated that p53 oscillations can be synchronized through the phenomenon of phase resetting. Surprisingly, p53 oscillations were synchronized over a wider range of damage-induction frequencies than predicted computationally. Recapitulating the range of synchronizing frequencies required, non-intuitively, a less robust oscillator. We showed that p53 phase resetting altered the expression of downstream targets responsible for cell fate depending on target mRNA stability. This study demonstrates that p53 oscillations can be phase reset and highlights the potential of driving p53 dynamics to reduce cellular variability and synchronize cell fate responses to DNA damage.

Exploring the Single-Cell Dynamics of FOXM1 Under Cell Cycle Perturbations

The cell cycle is crucial for maintaining normal cellular functions and preventing replication errors. FOXM1, a key transcription factor, plays a pivotal role in regulating cell cycle progression and is implicated in various physiological and pathological processes, including cancers like liver, prostate, breast, lung and colon cancer. Despite previous research, our understanding of FOXM1 dynamics under different cell cycle perturbations and its connection to heterogeneous cell fate decisions remains limited. In this study, we investigated FOXM1 behaviour in individual cells exposed to various perturbagens. We found that different drugs induce diverse responses due to heterogeneous FOXM1 dynamics at the single-cell level. Single-cell analysis identified six distinct cellular phenotypes: on-time cytokinesis, cytokinesis delay, cell cycle delay, G1 arrest, G2 arrest and cell death, observed across different drug types and doses. Specifically, treatments with PLK1, CDK1, CDK1/2 and Aurora kinase inhibitors revealed varied FOXM1 dynamics leading to heterogeneous cellular outcomes. Our findings affirm that the dynamics of FOXM1 are essential in shaping cellular outcomes, influencing the signals that dictate responses to various stimuli. Our results gave insights into how FOXM1 dynamics contribute to cell cycle fate decisions, especially under different cell cycle perturbations.

Entrainment and multi-stability of the p53 oscillator in human cells

The tumor suppressor p53 responds to cellular stress and activates transcription programs critical for regulating cell fate. DNA damage triggers oscillations in p53 levels with a robust period. Guided by the theory of synchronization and entrainment, we developed a mathematical model and experimental system to test the ability of the p53 oscillator to entrain to external drug pulses of various periods and strengths. We found that the p53 oscillator can be locked and entrained to a wide range of entrainment modes. External periods far from p53's natural oscillations increased the heterogeneity between individual cells whereas stronger inputs reduced it. Single-cell measurements allowed deriving the phase response curves (PRCs) and multiple Arnold tongues of p53. In addition, multi-stability and non-linear behaviors were mathematically predicted and experimentally detected, including mode hopping, period doubling, and chaos. Our work revealed critical dynamical properties of the p53 oscillator and provided insights into understanding and controlling it. A record of this paper's transparent peer review process is included in the supplemental information.

p53motifDB: integration of genomic information and tumor suppressor p53 binding motifs

The tumor suppressor gene TP53 encodes the DNA binding transcription factor p53 and is one of the most commonly mutated genes in human cancer. Tumor suppressor activity requires binding of p53 to its DNA response elements and subsequent transcriptional activation of a diverse set of target genes. Despite decades of close study, the logic underlying p53 interactions with its numerous potential genomic binding sites and target genes is not yet fully understood. Here, we present a database of DNA and chromatin-based information focused on putative p53 binding sites in the human genome to allow users to generate and test new hypotheses related to p53 activity in the genome. Users can query genomic locations based on experimentally observed p53 binding, regulatory element activity, genetic variation, evolutionary conservation, chromatin modification state, and chromatin structure. We present multiple use cases demonstrating the utility of this database for generating novel biological hypotheses, such as chromatin-based determinants of p53 binding and potential cell type-specific p53 activity. All database information is also available as a precompiled sqlite database for use in local analysis or as a Shiny web application.

Repetitive CREB-DNA interactions at gene loci predetermined by CBP induce activity-dependent gene expression in human cortical neurons

Neuronal activity-dependent transcription plays a key role in plasticity and pathology in the brain. An intriguing question is how neuronal activity controls gene expression via interactions of transcription factors with DNA and chromatin modifiers in the nucleus. By utilizing single-molecule imaging in human embryonic stem cell (ESC)-derived cortical neurons, we demonstrate that neuronal activity increases repetitive emergence of cAMP response element-binding protein (CREB) at histone acetylation sites in the nucleus, where RNA polymerase II (RNAPII) accumulation and FOS expression occur rapidly. Neuronal activity also enhances co-localization of CREB and CREB-binding protein (CBP). Increased binding of a constitutively active CREB to CBP efficiently induces CREB repetitive emergence. On the other hand, the formation of histone acetylation sites is dependent on CBP histone modification via acetyltransferase (HAT) activity but is not affected by neuronal activity. Taken together, our results suggest that neuronal activity promotes repetitive CREB-CRE and CREB-CBP interactions at predetermined histone acetylation sites, leading to rapid gene expression.

The multiple activations in budding yeast S-phase checkpoint are Poisson processes

Eukaryotic cells activate the S-phase checkpoint signal transduction pathway in response to DNA replication stress. Affected by the noise in biochemical reactions, such activation process demonstrates cell-to-cell variability. Here, through the analysis of microfluidics-integrated time-lapse imaging, we found multiple S-phase checkpoint activations in a certain budding yeast cell cycle. Yeast cells not only varied in their activation moments but also differed in the number of activations within the cell cycle, resulting in a stochastic multiple activation process. By investigating dynamics at the single-cell level, we showed that stochastic waiting times between consecutive activations are exponentially distributed and independent from each other. Finite DNA replication time provides a robust upper time limit to the duration of multiple activations. The mathematical model, together with further experimental evidence from the mutant strain, revealed that the number of activations under different levels of replication stress agreed well with Poisson distribution. Therefore, the activation events of S-phase checkpoint meet the criterion of Poisson process during DNA replication. In sum, the observed Poisson activation process may provide new insights into the complex stochastic dynamics of signal transduction pathways.

Species-specific metabolic reprogramming in human and mouse microglia during inflammatory pathway induction

Metabolic reprogramming is a hallmark of the immune cells in response to inflammatory stimuli. This metabolic process involves a switch from oxidative phosphorylation (OXPHOS) to glycolysis or alterations in other metabolic pathways. However, most of the experimental findings have been acquired in murine immune cells, and little is known about the metabolic reprogramming of human microglia. In this study, we investigate the transcriptomic, proteomic, and metabolic profiles of mouse and iPSC-derived human microglia challenged with the TLR4 agonist LPS. We demonstrate that both species display a metabolic shift and an overall increased glycolytic gene signature in response to LPS treatment. The metabolic reprogramming is characterized by the upregulation of hexokinases in mouse microglia and phosphofructokinases in human microglia. This study provides a direct comparison of metabolism between mouse and human microglia, highlighting the species-specific pathways involved in immunometabolism and the importance of considering these differences in translational research.

Insights into radiation carcinogenesis based on dose-rate effects in tissue stem cells

PURPOSE

Increasing epidemiological and biological evidence suggests that radiation exposure enhances cancer risk in a dose-dependent manner. This can be attributed to the 'dose-rate effect,' where the biological effect of low dose-rate radiation is lower than that of the same dose at a high dose-rate. This effect has been reported in epidemiological studies and experimental biology, although the underlying biological mechanisms are not completely understood. In this review, we aim to propose a suitable model for radiation carcinogenesis based on the dose-rate effect in tissue stem cells.

METHODS

We surveyed and summarized the latest studies on the mechanisms of carcinogenesis. Next, we summarized the radiosensitivity of intestinal stem cells and the role of dose-rate in the modulation of stem-cell dynamics after irradiation.

RESULTS

Consistently, driver mutations can be detected in most cancers from past to present, supporting the hypothesis that cancer progression is initiated by the accumulation of driver mutations. Recent reports demonstrated that driver mutations can be observed even in normal tissues, which suggests that the accumulation of mutations is a necessary condition for cancer progression. In addition, driver mutations in tissue stem cells can cause tumors, whereas they are not sufficient when they occur in non-stem cells. For non-stem cells, tissue remodeling induced by marked inflammation after the loss of tissue cells is important in addition to the accumulation of mutations. Therefore, the mechanism of carcinogenesis differs according to the cell type and magnitude of stress. In addition, our results indicated that non-irradiated stem cells tend to be eliminated from three-dimensional cultures of intestinal stem cells (organoids) composed of irradiated and non-irradiated stem cells, supporting the stem-cell competition.

CONCLUSIONS

We propose a unique scheme in which the dose-rate dependent response of intestinal stem cells incorporates the concept of the threshold of stem-cell competition and context-dependent target shift from stem cells to whole tissue. The concept highlights four key issues that should be considered in radiation carcinogenesis: i.e. accumulation of mutations; tissue reconstitution; stem-cell competition; and environmental factors like epigenetic modifications.

Elucidating the Implications of Diverse Dynamical Responses in p53 Protein

p53 is a well-known tumor suppressor gene that acts as a transcription factor to exhibit a variety of dynamical responses by sensing different types and extent of stress conditions causing DNA damage in Mammalian cells. Mathematical modeling has played a crucial role to correlate cell fate decision-making with some of these dynamic p53 regulations. However, it is extremely challenging to explain the various cell-type and stimulus-specific p53 protein dynamics under different stress conditions by using a single mathematical model. In this article, we propose a simple mathematical model of p53 regulation based on a generic p53 regulatory network that elucidates a range of p53 dynamical responses. By employing bifurcation analysis along with deterministic and stochastic simulations, we explain an array of p53 dynamics by correlating it with the corresponding cell fate regulations in a cell type-specific and stimulus-dependent manner. Moreover, our model makes experimentally testable predictions to fine-tune p53 dynamics under various DNA damage conditions and can be systematically used and improved to analyze complex p53 dynamics in the future.

Encoding and Decoding of p53 Dynamics in Cellular Response to Stresses

In the cellular response to stresses, the tumor suppressor p53 is activated to maintain genomic integrity and fidelity. As a transcription factor, p53 exhibits rich dynamics to allow for discrimination of the type and intensity of stresses and to direct the selective activation of target genes involved in different processes including cell cycle arrest and apoptosis. In this review, we focused on how stresses are encoded into p53 dynamics and how the dynamics are decoded into cellular outcomes. Theoretical modeling may provide a global view of signaling in the p53 network by coupling the encoding and decoding processes. We discussed the significance of modeling in revealing the mechanisms of the transition between p53 dynamic modes. Moreover, we shed light on the crosstalk between the p53 network and other signaling networks. This review may advance the understanding of operating principles of the p53 signaling network comprehensively and provide insights into p53 dynamics-based cancer therapy.

Patterns of interdivision time correlations reveal hidden cell cycle factors

The time taken for cells to complete a round of cell division is a stochastic process controlled, in part, by intracellular factors. These factors can be inherited across cellular generations which gives rise to, often non-intuitive, correlation patterns in cell cycle timing between cells of different family relationships on lineage trees. Here, we formulate a framework of hidden inherited factors affecting the cell cycle that unifies known cell cycle control models and reveals three distinct interdivision time correlation patterns: aperiodic, alternator, and oscillator. We use Bayesian inference with single-cell datasets of cell division in bacteria, mammalian and cancer cells, to identify the inheritance motifs that underlie these datasets. From our inference, we find that interdivision time correlation patterns do not identify a single cell cycle model but generally admit a broad posterior distribution of possible mechanisms. Despite this unidentifiability, we observe that the inferred patterns reveal interpretable inheritance dynamics and hidden rhythmicity of cell cycle factors. This reveals that cell cycle factors are commonly driven by circadian rhythms, but their period may differ in cancer. Our quantitative analysis thus reveals that correlation patterns are an emergent phenomenon that impact cell proliferation and these patterns may be altered in disease.

Network inference from perturbation time course data

Networks underlie much of biology from subcellular to ecological scales. Yet, understanding what experimental data are needed and how to use them for unambiguously identifying the structure of even small networks remains a broad challenge. Here, we integrate a dynamic least squares framework into established modular response analysis (DL-MRA), that specifies sufficient experimental perturbation time course data to robustly infer arbitrary two and three node networks. DL-MRA considers important network properties that current methods often struggle to capture: (i) edge sign and directionality; (ii) cycles with feedback or feedforward loops including self-regulation; (iii) dynamic network behavior; (iv) edges external to the network; and (v) robust performance with experimental noise. We evaluate the performance of and the extent to which the approach applies to cell state transition networks, intracellular signaling networks, and gene regulatory networks. Although signaling networks are often an application of network reconstruction methods, the results suggest that only under quite restricted conditions can they be robustly inferred. For gene regulatory networks, the results suggest that incomplete knockdown is often more informative than full knockout perturbation, which may change experimental strategies for gene regulatory network reconstruction. Overall, the results give a rational basis to experimental data requirements for network reconstruction and can be applied to any such problem where perturbation time course experiments are possible.

Quantifying information of intracellular signaling: progress with machine learning

Cells convey information about their extracellular environment to their core functional machineries. Studying the capacity of intracellular signaling pathways to transmit information addresses fundamental questions about living systems. Here, we review how information-theoretic approaches have been used to quantify information transmission by signaling pathways that are functionally pleiotropic and subject to molecular stochasticity. We describe how recent advances in machine learning have been leveraged to address the challenges of complex temporal trajectory datasets and how these have contributed to our understanding of how cells employ temporal coding to appropriately adapt to environmental perturbations.

Model-based translation of DNA damage signaling dynamics across cell types

Interindividual variability in DNA damage response (DDR) dynamics may evoke differences in susceptibility to cancer. However, pathway dynamics are often studied in cell lines as alternative to primary cells, disregarding variability. To compare DDR dynamics in the cell line HepG2 with primary human hepatocytes (PHHs), we developed a HepG2-based computational model that describes the dynamics of DDR regulator p53 and targets MDM2, p21 and BTG2. We used this model to generate simulations of virtual PHHs and compared the results to those for PHH donor samples. Correlations between baseline p53 and p21 or BTG2 mRNA expression in the absence and presence of DNA damage for HepG2-derived virtual samples matched the moderately positive correlations observed for 50 PHH donor samples, but not the negative correlations between p53 and its inhibitor MDM2. Model parameter manipulation that affected p53 or MDM2 dynamics was not sufficient to accurately explain the negative correlation between these genes. Thus, extrapolation from HepG2 to PHH can be done for some DDR elements, yet our analysis also reveals a knowledge gap within p53 pathway regulation, which makes such extrapolation inaccurate for the regulator MDM2. This illustrates the relevance of studying pathway dynamics in addition to gene expression comparisons to allow reliable translation of cellular responses from cell lines to primary cells. Overall, with our approach we show that dynamical modeling can be used to improve our understanding of the sources of interindividual variability of pathway dynamics.

Susceptibility to develop cancer varies among people, partially due to differences in genetic background. Ideally, healthy human-derived cells are used to investigate intracellular signaling pathways and their interindividual variability contributing to cancer susceptibility. Because cells from healthy human tissue are difficult to obtain and culture for periods longer than a few days, cell lines are often used as substitute. However, it is unclear to what extent signaling dynamics in cell lines represent dynamics in healthy human tissue. We asked whether we could reproduce interindividual variability in DNA damage response gene expression in a set of 50 human liver cell donors. Therefore, we built a mathematical model that simulates temporal expression dynamics of the DNA damage response in the HepG2 liver cell line upon chemical activation and used the simulations to create virtual donors. Our virtual donors displayed similar relations between genes as the samples from human donors, provided that we adjusted the strength of specific molecular interactions. Thus, our approach can be used to examine the applicability of widely used cell systems to healthy human tissue in terms of their dynamic responses.

A long and stressful day: Photoperiod shapes aluminium tolerance in plants

Aluminium (Al), a limiting factor for crop productivity in acidic soils (pH ≤ 5.5), imposes drastic constraints for food safety in developing countries. The major mechanisms that allow plants to cope with Al involve manipulations of organic acids metabolism and DNA-checkpoints. When assumed individually both approaches have been insufficient to overcome Al toxicity. On analysing the centre of origin of most cultivated plants, we hypothesised that day-length seems to be a pivotal agent modulating Al tolerance across distinct plant species. We observed that with increasing distance from the Equator, Al tolerance decreases, suggesting a relationship with the photoperiod. We verified that long-day (LD) species are generally more Al-sensitive than short-day (SD) species, whereas genetic conversion of tomato for SD growth habit boosts Al tolerance. Reduced Al tolerance correlates with DNA-checkpoint activation under LD. Furthermore, DNA-checkpoint-related genes are under positive selection in Arabidopsis accessions from regions with shorter days, suggesting that photoperiod act as a selective barrier for Al tolerance. A diel regulation and genetic diversity affect Al tolerance, suggesting that day-length orchestrates Al tolerance. Altogether, photoperiodic control of Al tolerance might contribute to solving the historical obstacle that imposes barriers for developing countries to reach a sustainable agriculture.

Low and high doses of ionizing radiation evoke discrete global (phospho)proteome responses

BACKGROUND

Although cancer risk is assumed to be linear with ionizing radiation (IR) dose, it is unclear to what extent low doses (LD) of IR from medical and occupational exposures pose a cancer risk for humans. Improved mechanistic understanding of the signaling responses to LD may help to clarify this uncertainty. Here, we performed quantitative mass spectrometry-based proteomics and phosphoproteomics experiments, using mouse embryonic stem cells, at 0.5 h and 4 h after exposure to LD (0.1 Gy) and high doses (HD; 1 Gy) of IR.

RESULTS

The proteome remained relatively stable (29; 0.5% proteins responded), whereas the phosphoproteome changed dynamically (819; 7% phosphosites changed) upon irradiation. Dose-dependent alterations of 25 IR-responsive proteins were identified, with only four in common between LD and HD. Mitochondrial metabolic proteins and pathways responded to LD, whereas transporter proteins and mitochondrial uncoupling pathways responded to HD. Congruently, mitochondrial respiration increased after LD exposure but decreased after HD exposure. While the bulk of the phosphoproteome response to LD (76%) occurred already at 0.5 h, an equivalent proportion of the phosphosites responded to HD at both time points. Motif, kinome/phosphatome, kinase-substrate, and pathway analyses revealed a robust DNA damage response (DDR) activation after HD exposure but not after LD exposure. Instead, LD-irradiation induced (de)phosphorylation of kinases, kinase-substrates and phosphatases that predominantly respond to reactive oxygen species (ROS) production.

CONCLUSION

Our analyses identify discrete global proteome and phosphoproteome responses after LD and HD, uncovering novel proteins and protein (de)phosphorylation events involved in the dose-dependent ionizing radiation responses.

It’s Getting Complicated—A Fresh Look at p53-MDM2-ARF Triangle in Tumorigenesis and Cancer Therapy

Anti-tumorigenic mechanisms mediated by the tumor suppressor p53, upon oncogenic stresses, are our bodies’ greatest weapons to battle against cancer onset and development. Consequently, factors that possess significant p53-regulating activities have been subjects of serious interest from the cancer research community. Among them, MDM2 and ARF are considered the most influential p53 regulators due to their abilities to inhibit and activate p53 functions, respectively. MDM2 inhibits p53 by promoting ubiquitination and proteasome-mediated degradation of p53, while ARF activates p53 by physically interacting with MDM2 to block its access to p53. This conventional understanding of p53-MDM2-ARF functional triangle have guided the direction of p53 research, as well as the development of p53-based therapeutic strategies for the last 30 years. Our increasing knowledge of this triangle during this time, especially through identification of p53-independent functions of MDM2 and ARF, have uncovered many under-appreciated molecular mechanisms connecting these three proteins. Through recognizing both antagonizing and synergizing relationships among them, our consideration for harnessing these relationships to develop effective cancer therapies needs an update accordingly. In this review, we will re-visit the conventional wisdom regarding p53-MDM2-ARF tumor-regulating mechanisms, highlight impactful studies contributing to the modern look of their relationships, and summarize ongoing efforts to target this pathway for effective cancer treatments. A refreshed appreciation of p53-MDM2-ARF network can bring innovative approaches to develop new generations of genetically-informed and clinically-effective cancer therapies.

DNA Damage Response (DDR) proteins in canine cancer as potential research targets in comparative oncology

The DNA damage response (DDR) is a complex signal transduction network that is activated when endogenous or exogenous genotoxins damage or interfere with the replication of genomic DNA. Under such conditions, the DDR promotes DNA repair and ensures accurate replication and division of the genome. High levels of genomic instability are frequently observed in cancers and can stem from germline loss‐of‐function mutations in certain DDR genes, such as BRCA1, BRCA2, and p53, that form the basis of human cancer predisposition syndromes. In addition, mutation and/or aberrant expression of multiple DDR genes are frequently observed in sporadic human cancers. As a result, the DDR is considered to represent a viable target for cancer therapy in humans and a variety of strategies are under investigation. Cancer is also a significant cause of mortality in dogs, a species that offers certain advantages for experimental oncology. Domestic dogs present numerous inbred lines, many of which display predisposition to specific forms of cancer and the study of which may provide insight into the biological basis of this susceptibility. In addition, clinical trials are possible in dogs and may lead to therapeutic insights that could ultimately be extended to humans. Here we review what is known specifically about the DDR in dogs and discuss how this knowledge could be extended and exploited to advance experimental oncology in this species.

Crosstalk between Plk1, p53, cell cycle, and G2/M DNA damage checkpoint regulation in cancer: computational modeling and analysis

Different cancer cell lines can have varying responses to the same perturbations or stressful conditions. Cancer cells that have DNA damage checkpoint-related mutations are often more sensitive to gene perturbations including altered Plk1 and p53 activities than cancer cells without these mutations. The perturbations often induce a cell cycle arrest in the former cancer, whereas they only delay the cell cycle progression in the latter cancer. To study crosstalk between Plk1, p53, and G2/M DNA damage checkpoint leading to differential cell cycle regulations, we developed a computational model by extending our recently developed model of mitotic cell cycle and including these key interactions. We have used the model to analyze the cancer cell cycle progression under various gene perturbations including Plk1-depletion conditions. We also analyzed mutations and perturbations in approximately 1800 different cell lines available in the Cancer Dependency Map and grouped lines by genes that are represented in our model. Our model successfully explained phenotypes of various cancer cell lines under different gene perturbations. Several sensitivity analysis approaches were used to identify the range of key parameter values that lead to the cell cycle arrest in cancer cells. Our resulting model can be used to predict the effect of potential treatments targeting key mitotic and DNA damage checkpoint regulators on cell cycle progression of different types of cancer cells.

Dual roles of SIRT1 in the BAX switch through the P53 module: A mathematical modeling study

SIRT1 is a multifunctional deacetylase that participates in a variety of cellular physiological processes to cope with stress. The anticancer protein P53 is an important target of SIRT1. It has been found that SIRT1 is involved in apoptosis by regulating the activity and intracellular location of P53. Moreover, P53-dependent apoptosis is inseparable from the BCL-2 protein family. Among the members of this family, BAX’s switching dynamics may play a key role in apoptosis. Therefore, a challenging question arises: what effect does SIRT1 have on the BAX switch? To answer this question, we built a small-scale protein network model. Through computer simulation, the properties of SIRT1 that on the one hand promote and on the other inhibit apoptosis are revealed. We found that the opening time of the BAX switch will be delayed in the case of either SIRT1 excess or deficiency. Similarly, the stimulus threshold required for apoptosis will also increase in the above two scenarios. Thereby, we proposed that SIRT1 has an optimal content at which the probability of apoptosis is greatest. In addition, P53 oscillation requires the concentration of SIRT1 to be higher than the optimal value. This work may be helpful both experimentally and clinically.

Autonomous clocks that regulate organelle biogenesis, cytoskeletal organization, and intracellular dynamics

How do cells perceive time? Do cells use temporal information to regulate the production/degradation of their enzymes, membranes, and organelles? Does controlling biological time influence cytoskeletal organization and cellular architecture in ways that confer evolutionary and physiological advantages? Potential answers to these fundamental questions of cell biology have historically revolved around the discussion of 'master' temporal programs, such as the principal cyclin-dependent kinase/cyclin cell division oscillator and the circadian clock. In this review, we provide an overview of the recent evidence supporting an emerging concept of 'autonomous clocks,' which under normal conditions can be entrained by the cell cycle and/or the circadian clock to run at their pace, but can also run independently to serve their functions if/when these major temporal programs are halted/abrupted. We begin the discussion by introducing recent developments in the study of such clocks and their roles at different scales and complexities. We then use current advances to elucidate the logic and molecular architecture of temporal networks that comprise autonomous clocks, providing important clues as to how these clocks may have evolved to run independently and, sometimes at the cost of redundancy, have strongly coupled to run under the full command of the cell cycle and/or the circadian clock. Next, we review a list of important recent findings that have shed new light onto potential hallmarks of autonomous clocks, suggestive of prospective theoretical and experimental approaches to further accelerate their discovery. Finally, we discuss their roles in health and disease, as well as possible therapeutic opportunities that targeting the autonomous clocks may offer.

A functionally divergent intrinsically disordered region underlying the conservation of stochastic signaling

Stochastic signaling dynamics expand living cells' information processing capabilities. An increasing number of studies report that regulators encode information in their pulsatile dynamics. The evolutionary mechanisms that lead to complex signaling dynamics remain uncharacterized, perhaps because key interactions of signaling proteins are encoded in intrinsically disordered regions (IDRs), whose evolution is difficult to analyze. Here we focused on the IDR that controls the stochastic pulsing dynamics of Crz1, a transcription factor in fungi downstream of the widely conserved calcium signaling pathway. We find that Crz1 IDRs from anciently diverged fungi can all respond transiently to calcium stress; however, only Crz1 IDRs from the Saccharomyces clade support pulsatility, encode extra information, and rescue fitness in competition assays, while the Crz1 IDRs from distantly related fungi do none of the three. On the other hand, we find that Crz1 pulsing is conserved in the distantly related fungi, consistent with the evolutionary model of stabilizing selection on the signaling phenotype. Further, we show that a calcineurin docking site in a specific part of the IDRs appears to be sufficient for pulsing and show evidence for a beneficial increase in the relative calcineurin affinity of this docking site. We propose that evolutionary flexibility of functionally divergent IDRs underlies the conservation of stochastic signaling by stabilizing selection.

Landscape and flux quantify the stochastic transition dynamics for p53 cell fate decision

The p53 transcription factor is a key mediator in cellular responses to various stress signals including DNA repair, cell cycle arrest, and apoptosis. In this work, we employ landscape and flux theory to investigate underlying mechanisms of p53-regulated cell fate decisions. Based on a p53 regulatory network, we quantified the potential landscape and probabilistic flux for the p53 system. The landscape topography unifies and quantifies three cell fate states, including the limit cycle oscillations (representing cell cycle arrest), high p53 state (characterizing apoptosis), and low p53 state (characterizing the normal proliferative state). Landscape and flux results provide a quantitative explanation for the biphasic dynamics of the p53 system. In the oscillatory phase (first phase), the landscape attracts the system into the ring valley and flux drives the system cyclically moving, leading to cell cycle arrest. In the fate decision-making phase (second phase), the ring valley shape of the landscape provides an efficient way for cells to return to the normal proliferative state once DNA damage is repaired. If the damage is unrepairable with larger flux, the system may cross the barrier between two states and switch to the apoptotic state with a high p53 level. By landscape-flux decomposition, we revealed a trade-off between stability (guaranteed by landscape) and function (driven by flux) in cellular systems. Cells need to keep a balance between appropriate speed to repair DNA damage and appropriate stability to survive. This is further supported by flux landscape analysis showing that flux may provide the dynamical origin of phase transition in a non-equilibrium system by changing landscape topography.

The guardian's choice: how p53 enables context-specific decision-making in individual cells

p53 plays a central role in defending the genomic integrity of our cells. In response to genotoxic stress, this tumour suppressor orchestrates the expression of hundreds of target genes, which induce a variety of cellular outcomes ranging from damage repair to induction of apoptosis. In this review, we examine how the p53 response is regulated on several levels in individual cells to allow precise and context-specific fate decisions. We discuss that the p53 response is not only controlled by its canonical regulators but also controlled by interconnected signalling pathways that influence the dynamics of p53 accumulation upon damage and modulate its transcriptional activity at target gene promoters. Additionally, we consider how the p53 response is diversified through a variety of mechanisms at the promoter level and beyond to induce context-specific outcomes in individual cells. These layers of regulation allow p53 to react in a stimulus-specific manner and fine-tune its signalling according to the individual needs of a given cell, enabling it to take the right decision on survival or death.

Health and Fitness at the Single-Cell Level

Genetically identical cells in a tissue can respond differently to perturbations in their environment or "stress." Such stresses can be physicochemical, mechanical, or infectious or may come from competition with other cells in the tissue. Here, I discuss how the varying responses to stress influence the decision of a cell to repair or die, and how one cell's response can have effects on surrounding cells. Such responses control the health and fitness of single cells and how they compete with other genetically identical cells.See related article on p. 129.

Trajectory-based energy landscapes of gene regulatory networks

Multistability and natural biological variability can result in significant heterogeneity within a cell population, leading to challenges in understanding and modulating cell behavior. Energy landscapes can offer qualitatively intuitive visualizations of cell phenotype and facilitate a more quantitative understanding of cellular dynamics, but current methods for landscape generation are mathematically involved and often require specific system properties (e.g., ergodicity or independent gene/protein probability distributions) that do not always hold. Here, we present a simple kinetic Monte Carlo-based method for landscape generation from a system of ordinary differential equations using only simulation trajectories initialized throughout the phase space of interest. The resulting landscape produces three quantitative features relevant to understanding cell behavior: stability (reflected by the depth or potential of landscape valleys), velocity (representing average directional movement on the landscape), and variance in velocity (indicative of landscape positions with heterogeneous movements). We applied this method to a genetic toggle switch, a core decision-making network in binary cellular responses, to elucidate effects of biologically relevant intrinsic and extrinsic cues. Intrinsic noise, such as stochasticity in transcription-translation and differences in cell cycle position, manifests through changes in valley width and position, reflecting increased population heterogeneity and more probabilistic cell fate transitions. The landscapes also capture the effect of an external inducer, revealing a quantitative correlation between the rate of cell fate transition and the energy barrier above a threshold inducer concentration determined by the permissivity of the valley. Further, in tracking dynamically changing landscapes under time-varying external cues, we unexpectedly found that an oscillatory inducer input can modulate cell fate heterogeneity and lead to periodic cell fate transitions entrained to the input frequency, depending on the intrinsic degradation rate of the switch. The landscape generation approach outlined herein is generalizable to other network topologies and may provide new quantitative insights into their dynamics.

Species-specific segmentation clock periods are due to differential biochemical reaction speeds

Although mechanisms of embryonic development are similar between mice and humans, the time scale is generally slower in humans. To investigate these interspecies differences in development, we recapitulate murine and human segmentation clocks that display 2- to 3-hour and 5- to 6-hour oscillation periods, respectively. Our interspecies genome-swapping analyses indicate that the period difference is not due to sequence differences in the HES7 locus, the core gene of the segmentation clock. Instead, we demonstrate that multiple biochemical reactions of HES7, including the degradation and expression delays, are slower in human cells than they are in mouse cells. With the measured biochemical parameters, our mathematical model accounts for the two- to threefold period difference between the species. We propose that cell-autonomous differences in biochemical reaction speeds underlie temporal differences in development between species.

Tumor suppressor p53: from engaging DNA to target gene regulation

The p53 transcription factor confers its potent tumor suppressor functions primarily through the regulation of a large network of target genes. The recent explosion of next generation sequencing protocols has enabled the study of the p53 gene regulatory network (GRN) and underlying mechanisms at an unprecedented depth and scale, helping us to understand precisely how p53 controls gene regulation. Here, we discuss our current understanding of where and how p53 binds to DNA and chromatin, its pioneer-like role, and how this affects gene regulation. We provide an overview of the p53 GRN and the direct and indirect mechanisms through which p53 affects gene regulation. In particular, we focus on delineating the ubiquitous and cell type-specific network of regulatory elements that p53 engages; reviewing our understanding of how, where, and when p53 binds to DNA and the mechanisms through which these events regulate transcription. Finally, we discuss the evolution of the p53 GRN and how recent work has revealed remarkable differences between vertebrates, which are of particular importance to cancer researchers using mouse models.

Does frequency-dependent cell proliferation exhibit a Fano-type resonance?

We examined PC12 cell proliferation in environments with temporally varying epidermal growth factor concentrations by means of a microfluidic system. Our measurements revealed frequency-dependent cell behaviour over an observation period of three days. The cell population either increased, decreased or remained constant depending on the frequency of epidermal growth factor applied. A plot of the apparent proliferation rate as a function of growth-factor frequency was mathematically described by the Fano line-shape formula. In the context of linear response theory, these results imply that the PC12 cells compute zero, first and second-order time derivatives of the ligand concentration and utilise this information to decide to proliferate or die. We discuss a physical model based on periodic forcing of coupled oscillators that accounts for these observations. Our results and analysis suggest the possibility to influence cell fate by controlling the dynamics of the extracellular environment.

Discordant gene responses to radiation in humans and mice and the role of hematopoietically humanized mice in the search for radiation biomarkers

The mouse (Mus musculus) is an extensively used model of human disease and responses to stresses such as ionizing radiation. As part of our work developing gene expression biomarkers of radiation exposure, dose, and injury, we have found many genes are either up-regulated (e.g. CDKN1A, MDM2, BBC3, and CCNG1) or down-regulated (e.g. TCF4 and MYC) in both species after irradiation at ~4 and 8 Gy. However, we have also found genes that are consistently up-regulated in humans and down-regulated in mice (e.g. DDB2, PCNA, GADD45A, SESN1, RRM2B, KCNN4, IFI30, and PTPRO). Here we test a hematopoietically humanized mouse as a potential in vivo model for biodosimetry studies, measuring the response of these 14 genes one day after irradiation at 2 and 4 Gy, and comparing it with that of human blood irradiated ex vivo, and blood from whole body irradiated mice. We found that human blood cells in the hematopoietically humanized mouse in vivo environment recapitulated the gene expression pattern expected from human cells, not the pattern seen from in vivo irradiated normal mice. The results of this study support the use of hematopoietically humanized mice as an in vivo model for screening of radiation response genes relevant to humans.

p53 pulse modulation differentially regulates target gene promoters to regulate cell fate decisions

The p53 tumor suppressor regulates distinct responses to cellular stresses. Although different stresses generate different p53 dynamics, the mechanisms by which cells decode p53 dynamics to differentially regulate target genes are not well understood. Here, we determined in individual cells how canonical p53 target gene promoters vary in responsiveness to features of p53 dynamics. Employing a chemical perturbation approach, we independently modulated p53 pulse amplitude, duration, or frequency, and we then monitored p53 levels and target promoter activation in individual cells. We identified distinct signal processing features-thresholding in response to amplitude modulation, a refractory period in response to duration modulation, and dynamic filtering in response to frequency modulation. We then showed that the signal processing features not only affect p53 target promoter activation, they also affect p53 regulation and downstream cellular functions. Our study shows how different promoters can differentially decode features of p53 dynamics to generate distinct responses, providing insight into how perturbing p53 dynamics can be used to generate distinct cell fates.

NF-κB signaling dynamics is controlled by a dose-sensing autoregulatory loop

Over the last decade, multiple studies have shown that signaling proteins activated in different temporal patterns, such as oscillatory, transient, and sustained, can result in distinct gene expression patterns or cell fates. However, the molecular events that ensure appropriate stimulus- and dose-dependent dynamics are not often understood and are difficult to investigate. Here, we used single-cell analysis to dissect the mechanisms underlying the stimulus- and dose-encoding patterns in the innate immune signaling network. We found that Toll-like receptor (TLR) and interleukin-1 receptor (IL-1R) signaling dynamics relied on a dose-dependent, autoinhibitory loop that rendered cells refractory to further stimulation. Using inducible gene expression and optogenetics to perturb the network at different levels, we identified IL-1R-associated kinase 1 (IRAK1) as the dose-sensing node responsible for limiting signal flow during the innate immune response. Although the kinase activity of IRAK1 was not required for signal propagation, it played a critical role in inhibiting the nucleocytoplasmic oscillations of the transcription factor NF-κB. Thus, protein activities that may be "dispensable" from a topological perspective can nevertheless be essential in shaping the dynamic response to the external environment.

Conservation and divergence of the p53 gene regulatory network between mice and humans

Understanding the p53 tumor suppressor pathway remains crucial for the design of anticancer strategies. Studies in human tumors and mouse models help to unravel the molecular mechanisms that underlie the p53 signaling pathway. Yet, the p53 gene regulatory network (GRN) is not the same in mice and humans. The comparison of the regulatory networks of p53 in mice and humans reveals that gene up- and down-regulation by p53 are distinctly affected during evolution. Importantly, gene up-regulation by p53 underwent more rapid evolution and gene down-regulation has been evolutionarily constrained. This difference stems from the two major mechanisms employed by p53 to regulate gene expression: up-regulation through direct p53 target gene binding and indirect down-regulation through the p53-p21-DREAM pathway. More than 1000 genes have been identified to differ in their p53-dependent expression between mice and humans. Analysis of p53 gene expression profiles and p53 binding data reveal that turnover of p53 binding sites is the major mechanism underlying extensive variation in p53-dependent gene up-regulation. Only a core set of high-confidence genes appears to be directly regulated by p53 in both species. In contrast to up-regulation, p53-induced down-regulation is well conserved between mice and humans and controls cell cycle genes. Here a curated data set is provided that extends the previously established web-atlas at www.targetgenereg.org to assess the p53 response of any human gene of interest and its mouse ortholog. Taken together, the analysis reveals a limited translation potential from mouse models to humans for the p53 GRN.