Feedbacks, Bifurcations, and Cell Fate Decision-Making in the p53 System

Abstract

The p53 transcription factor is a regulator of key cellular processes including DNA repair, cell cycle arrest, and apoptosis. In this theoretical study, we investigate how the complex circuitry of the p53 network allows for stochastic yet unambiguous cell fate decision-making. The proposed Markov chain model consists of the regulatory core and two subordinated bistable modules responsible for cell cycle arrest and apoptosis. The regulatory core is controlled by two negative feedback loops (regulated by Mdm2 and Wip1) responsible for oscillations, and two antagonistic positive feedback loops (regulated by phosphatases Wip1 and PTEN) responsible for bistability. By means of bifurcation analysis of the deterministic approximation we capture the recurrent solutions (i.e., steady states and limit cycles) that delineate temporal responses of the stochastic system. Direct switching from the limit-cycle oscillations to the “apoptotic” steady state is enabled by the existence of a subcritical Neimark—Sacker bifurcation in which the limit cycle loses its stability by merging with an unstable invariant torus. Our analysis provides an explanation why cancer cell lines known to have vastly diverse expression levels of Wip1 and PTEN exhibit a broad spectrum of responses to DNA damage: from a fast transition to a high level of p53 killer (a p53 phosphoform which promotes commitment to apoptosis) in cells characterized by high PTEN and low Wip1 levels to long-lasting p53 level oscillations in cells having PTEN promoter methylated (as in, e.g., MCF-7 cell line).

A Primer on Modeling and Measurement of Signaling Outcomes Affecting Decision Making in Cells: Methods for Determining Optimal and Incorrect Outcomes in Noisy Biochemical Dynamics

“…Consider the p53 system model [9] shown in Fig 1. The p53 system is activated due to a DNA damage induced by IR. Initially the protein kinase ataxia-telangiectasia mutated (ATM) is activated by the DNA Fig 1: A p53 system model [9].…”

“…Consider the p53 system model [9] shown in Fig 1. The p53 system is activated due to a DNA damage induced by IR. Initially the protein kinase ataxia-telangiectasia mutated (ATM) is activated by the DNA Fig 1: A p53 system model [9]. Arrow-headed dashed lines represent positive transcriptional regulations, arrow-headed solid lines stand for protein transformations, circle-headed solid lines are activatory regulations, and hammer-headed solid lines represent inhibitory regulations.…”

“…We accomplish this by introducing metrics and methods to evaluate success and failure rates of the signaling outcomes and actions, in response to the DNA damage caused by different IR doses and under various conditions. In order to do this, we collected data using the simulator of Hat et al [9], to obtain single cell data of healthy cells, when different IR doses are applied. Moreover, we collected single cell data of abnormal cells exposed to different IR doses, to measure how the decision making is affected when there is an anomaly in the system, in addition to the DNA damage.…”

Modeling cytokine regulatory network dynamics driving neuroinflammation in central nervous system disorders

“…For instance, the initial levels of system components have been shown to regulate cytokine network dynamics and apoptotic responses to cytokine treatment (Aldridge et al, 2006; Anderson et al, 2015; Fig 2D, top). Similarly, related approaches involving phase space analysis (Fig 2D, middle) and bifurcation analysis (Fig 2D, bottom) can be pursued to understand the conditions underlying critical transitions to pathological states (Liu et al, 2015; Hat et al, 2016). Such analyses further aid in identifying biomarkers that distinguish disease trajectories (as opposed to instantaneously observed states), for identifying early-warning signals of critical transitions driven by stochasticity, and for predicting effective targets that can prevent transitions to disease or reverse course towards a healthy state.…”

Regulation of Tip60‐dependent p53 acetylation in cell fate decision

“…Furthermore, cell fates are tightly controlled by p53 dynamics, and perturbing the dynamic mode of p53 may be a potential approach for cancer therapy [14,15]. A series of models have been developed to explore the mechanism for cell fate decision by p53 in the DDR [16][17][18][19][20]. However, most of them focused on the role of p53 phosphorylation in regulating its activity, and the role of p53 acetylation was seldom considered.…”