Enhanced DNA repair through droplet formation and p53 oscillations.

Living organisms are constantly exposed to DNA damage, and optimal repair is therefore crucial. A characteristic hallmark of the response is the formation of sub-compartments around the site of damage, known as foci. Following multiple DNA breaks, the transcription factor p53 exhibits oscillations in its nuclear concentration, but how this dynamics can affect the repair remains unknown. Here, we formulate a theory for foci formation through droplet condensation and discover how oscillations in p53, with its specific periodicity and amplitude, optimize the repair process by preventing Ostwald ripening and distributing protein material in space and time. Based on the theory predictions, we reveal experimentally that the oscillatory dynamics of p53 does enhance the repair efficiency. These results connect the dynamical signaling of p53 with the microscopic repair process and create a new paradigm for the interplay of complex dynamics and phase transitions in biology.

Time-series transcriptomics and proteomics reveal alternative modes to decode p53 oscillations.

The cell stress-responsive transcription factor p53 influences the expression of its target genes and subsequent cellular responses based in part on its dynamics (changes in level over time). The mechanisms decoding p53 dynamics into subsequent target mRNA and protein dynamics remain unclear. We systematically quantified p53 target mRNA and protein expression over time under two p53 dynamical regimes, oscillatory and rising, using RNA-sequencing and TMT mass spectrometry. Oscillatory dynamics allowed for a greater variety of dynamical patterns for both mRNAs and proteins. Mathematical modeling of empirical data revealed three distinct mechanisms that decode p53 dynamics. Specific combinations of these mechanisms at the transcriptional and post-transcriptional levels enabled exclusive induction of proteins under particular dynamics. In addition, rising induction of p53 led to higher induction of proteins regardless of their functional class, including proteins promoting arrest of proliferation, the primary cellular outcome under rising p53. Our results highlight the diverse mechanisms cells employ to distinguish complex transcription factor dynamics to regulate gene expression.

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.

Mathematical Modeling of p53 Pathways.

Cells have evolved balanced systems that ensure an appropriate response to stress. The systems elicit repair responses in temporary or moderate stress but eliminate irreparable cells via apoptosis in detrimental conditions of prolonged or severe stress. The tumor suppressor p53 is a central player in these stress response systems. When activated under DNA damage stress, p53 regulates hundreds of genes that are involved in DNA repair, cell cycle, and apoptosis. Recently, increasing studies have demonstrated additional regulatory roles of p53 in metabolism and mitochondrial physiology. Due to the inherent complexity of feedback loops between p53 and its target genes, the application of mathematical modeling has emerged as a novel approach to better understand the multifaceted functions and dynamics of p53. In this review, we discuss several mathematical modeling approaches in exploring the p53 pathways.

Constant rate of p53 tetramerization in response to DNA damage controls the p53 response.

The dynamics of the tumor suppressor protein p53 have been previously investigated in single cells using fluorescently tagged p53. Such approach reports on the total abundance of p53 but does not provide a measure for functional p53. We used fluorescent protein-fragment complementation assay (PCA) to quantify in single cells the dynamics of p53 tetramers, the functional units of p53. We found that while total p53 increases proportionally to the input strength, p53 tetramers are formed in cells at a constant rate. This breaks the linear input-output relation and dampens the p53 response. Disruption of the p53-binding protein ARC led to a dose-dependent rate of tetramers formation, resulting in enhanced tetramerization and induction of p53 target genes. Our work suggests that constraining the p53 response in face of variable inputs may protect cells from committing to terminal outcomes and highlights the importance of quantifying the active form of signaling molecules in single cells.

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.

Two-dimensional polynomial type canonical relaxation oscillator model for p53 dynamics.

p53 network, which is responsible for DNA damage response of cells, exhibits three distinct qualitative behaviours; low state, oscillation and high state, which are associated with normal cell cycle progression, cell cycle arrest and apoptosis, respectively. The experimental studies demonstrate that these dynamics of p53 are due to the ATM and Wip1 interaction. This paper proposes a simple two-dimensional canonical relaxation oscillator model based on the identified topological structure of ATM and Wip1 interaction underlying these qualitative behaviours of p53 network. The model includes only polynomial terms that have the interpretability of known ATM and Wip1 interaction. The introduced model is useful for understanding relaxation oscillations in gene regulatory networks. Through mathematical analysis, we investigate the roles of ATM and Wip1 in forming of these three essential behaviours, and show that ATM and Wip1 constitute the core mechanism of p53 dynamics. In agreement with biological findings, we show that Wip1 degradation term is a highly sensitive parameter, possibly related to mutations. By perturbing the corresponding parameters, our model characterizes some mutations such as ATM deficiency and Wip1 overexpression. Finally, we provide intervention strategies considering our observation that Wip1 seems to be an important target to conduct therapies for these mutations.

Dynamics of p53: A Master Decider of Cell Fate.

Cellular stress-induced temporal alterations-i.e., dynamics-are typically exemplified  by the dynamics of p53 that serve as a master to determine cell fate. p53 dynamics were initially  identified as the variations of p53 protein levels. However, a growing number of studies have  shown that p53 dynamics are also manifested in variations in the activity, spatial location, and  posttranslational modifications of p53 proteins, as well as the interplay among all p53 dynamical  features. These are essential in determining a specific outcome of cell fate. In this review, we  discuss the importance of the multifaceted features of p53 dynamics and their roles in the cell fate  decision process, as well as their potential applications in p53-based cancer therapy. The review  provides new insights into p53 signaling pathways and their potentials in the development of new  strategies in p53-based cancer therapy.