Stochasticity of intranuclear biochemical reaction processes controls the final decision of cell fate associated with DNA damage

Design patterns for the construction of computational biological models

Computational biological models have proven to be an invaluable tool for understanding and predicting the behaviour of many biological systems. While it may not be too challenging for experienced researchers to construct such models from scratch, it is not a straightforward task for early stage researchers. Design patterns are well-known techniques widely applied in software engineering as they provide a set of typical solutions to common problems in software design. In this paper, we collect and discuss common patterns that are usually used during the construction and execution of computational biological models. We adopt Petri nets as a modelling language to provide a visual illustration of each pattern; however, the ideas presented in this paper can also be implemented using other modelling formalisms. We provide two case studies for illustration purposes and show how these models can be built up from the presented smaller modules. We hope that the ideas discussed in this paper will help many researchers in building their own future models.

Formal verification confirms the role of p53 protein in cell fate decision mechanism

The bio-cell cycle is controlled by a complex biochemical network of signaling pathways. Modeling such challenging networks accurately is imperative for the understanding of their detailed dynamical behavior. In this paper, we construct, analyze, and verify a hybrid Petri net (HPN) model of a complex biochemical network that captures the role of an important protein (namely p53) in deciding the fate of the cell. We model the behavior of the cell nucleus and cytoplasm as two stochastic and continuous Petri nets, respectively, combined together into a single HPN. We use simulative model checking to verify three different properties that capture the dynamical behavior of p53 protein with respect to the intensity of the ionizing radiation (IR) to which the cell is exposed. For each IR dose, 1000 simulation runs are carried out to verify each property. Our verification results showed that the fluctuations in p53, which relies on IR intensity, are compatible with the findings of the preceding simulation studies that have previously examined the role of p53 in cell fate decision.

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.

Mathematical analysis-based feasibility study of pre-emptive medicine for Staphylococcus aureus infectious disease: Early detection and antibiotic-free maintenance therapy

Global efforts are being made to achieve the clinical implementation of pre-emptive medicine for Staphylococcus aureus (S. aureus) infectious disease, which will realize both early detection at the pre-symptom stage and bacteriostatic therapy by antibiotic-free medicine in a future. Several research groups proposed the intercellular signal transduction factor (auto-inducing peptide: AIP) antibody, the synthesised AIP analogues and a cyclic depsipeptide with high constitutional similarity to AIP as a candidate of the pre-emptive medicine for S. aureus infectious disease. In this paper, to evaluate a validity of them, we mathematically explored both a pre-symptom associated with the pathogenic expression process of S. aureus and several therapeutic targets that delay or suppress the appearance of the pre-symptom. The stochastic mathematical analysis identified a peak of fluctuation in intracellular AgrD concentration as the pre-symptom. Moreover, employing parameter sensitivity analysis, the enhancement of binding inhibition between AgrC receptor and AIP was identified as effective therapeutic target. Based on these findings, we evaluated a feasibility of above-mentioned candidates, and concluded that the continuous application of AgrC receptor antagonists, such as the synthesised AIP analogues and a cyclic depsipeptide with high constitutional similarity to AIP, is useful as pre-emptive medicine for S. aureus infectious disease.

A Stochastic Model of DNA Double-Strand Breaks Repair Throughout the Cell Cycle

Cell cycle phase is a decisive factor in determining the repair pathway of DNA double-strand breaks (DSBs) by non-homologous end joining (NHEJ) or homologous recombination (HR). Recent experimental studies revealed that 53BP1 and BRCA1 are the key mediators of the DNA damage response (DDR) with antagonizing roles in choosing the appropriate DSB repair pathway in G1, S, and G2 phases. Here, we present a stochastic model of biochemical kinetics involved in detecting and repairing DNA DSBs induced by ionizing radiation during the cell cycle progression. A three-dimensional stochastic process is defined to monitor the cell cycle phase and DSBs repair at times after irradiation. To estimate the model parameters, a Metropolis Monte Carlo method is applied to perform maximum likelihood estimation utilizing the kinetics of γ-H2AX and RAD51 foci formation in G1, S, and G2 phases. The recruitment of DSB repair proteins is verified by comparing our model predictions with the corresponding experimental data on human cells after exposure to X and γ-radiation. Furthermore, the interaction between 53BP1 and BRCA1 is simulated for G1 and S/G2 phases determining the competition between NHEJ and HR pathways in repairing induced DSBs throughout the cell cycle. In accordance with recent biological data, the numerical results demonstrate that the maximum proportion of HR occurs in S phase cells and the high level of NHEJ takes place in G1 and G2 phases. Moreover, the stochastic realizations of the total yield of simple and complex DSBs ligation are compared for G1 and S/G2 damaged cells. Finally, the proposed stochastic model is validated when DSBs induced by different particle radiation such as iron, silicon, oxygen, proton, and carbon.

Metformin as a Radiation Modifier; Implications to Normal Tissue Protection and Tumor Sensitization

BACKGROUND

Nowadays, ionizing radiation is used for several applications in medicine, industry, agriculture, and nuclear power generation. Besides the beneficial roles of ionizing radiation, there are some concerns about accidental exposure to radioactive sources. The threat posed by its use in terrorism is of global concern. Furthermore, there are several side effects to normal organs for patients who had undergone radiation treatment for cancer. Hence, the modulation of radiation response in normal tissues was one of the most important aims of radiobiology. Although, so far, several agents have been investigated for protection and mitigation of radiation injury. Agents such as amifostine may lead to severe toxicity, while others may interfere with radiation therapy outcomes as a result of tumor protection. Metformin is a natural agent that is well known as an antidiabetic drug. It has shown some antioxidant effects and enhances DNA repair capacity, thereby ameliorating cell death following exposure to radiation. Moreover, through targeting endogenous ROS production within cells, it can mitigate radiation injury. This could potentially make it an effective radiation countermeasure. In contrast to other radioprotectors, metformin has shown modulatory effects through induction of several genes such as AMPK, which suppresses reduction/ oxidation (redox) reactions, protects cells from accumulation of unrepaired DNA, and attenuates initiation of inflammation as well as fibrotic pathways. Interestingly, these properties of metformin can sensitize cancer cells to radiotherapy.

CONCLUSION

In this article, we aimed to review the interesting properties of metformin such as radioprotection, radiomitigation and radiosensitization, which could make it an interesting adjuvant for clinical radiotherapy, as well as an interesting candidate for mitigation of radiation injury after a radiation disaster.

The effect of stochasticity on repair of DNA double strand breaks throughout non-homologous end joining pathway

DNA double strand breaks (DSBs) are the most lethal lesions of DNA induced by ionizing radiation, industrial chemicals and a wide variety of drugs used in chemotherapy. In the context of DNA damage response system modelling, uncertainty may arise in several ways such as number of induced DSBs, kinetic rates and measurement error in observable quantities. Therefore, using the stochastic approaches is imperative to gain further insight into the dynamic behaviour of DSBs repair process. In this article, a continuous-time Markov chain (CTMC) model of the non-homologous end joining (NHEJ) mechanism is formulated according to the DSB complexity. Additionally, a Metropolis Monte Carlo method is used to perform maximum likelihood estimation of the kinetic rate constants. Here, the effects of fluctuating kinetic rates and DSBs induction rate of the NHEJ mechanism are investigated. The stochastic realizations of the total yield of simple and complex DSBs ligation are simulated to compare their asymptotic dynamics. Furthermore, it has been proved that the total yield of DSBs has a normal distribution for sufficiently large number of DSBs. In order to estimate the expected duration of repairing DSBs, the probability distribution of DSBs lifetime is calculated based on the CTMC NHEJ model. Moreover, the variability of total yield of DSBs during constant low-dose radiation is evaluated in the presented model. The findings indicate that in stochastic NHEJ model, when there is no new DSBs induction through the repair process, all DSBs are eventually repaired. However, when DSBs are induced by constant low-dose radiation, a number of DSBs remains un-repaired.

Logical Modeling and Analysis of Cellular Regulatory Networks With GINsim 3.0

The logical formalism is well adapted to model large cellular networks, in particular when detailed kinetic data are scarce. This tutorial focuses on this well-established qualitative framework. Relying on GINsim (release 3.0), a software implementing this formalism, we guide the reader step by step toward the definition, the analysis and the simulation of a four-node model of the mammalian p53-Mdm2 network.

Understanding non-linear effects from Hill-type dynamics with application to decoding of p53 signaling

Analytical equations are derived depicting four possible scenarios resulting from pulsed signaling of a system subject to Hill-type dynamics. Pulsed Hill-type dynamics involves the binding of multiple signal molecules to a receptor and occurs e.g., when transcription factor p53 orchestrates cancer prevention, during calcium signaling, and during circadian rhythms. The scenarios involve: (i) enhancement of high-affinity binders compared to low-affinity ones, (ii) slowing reactions involving high-affinity binders, (iii) transfer of the clocking of low-affinity binders from the signal molecule to the products, and (iv) a unique clocking process that produces incremental increases in the activity of high-affinity binders with each signal pulse. In principle, these mostly non-linear effects could control cellular outcomes. An applications to p53 signaling is developed, with binding to most gene promoters identified as category (iii) responses. However, currently unexplained enhancement of high-affinity promoters such as CDKN1a (p21) by pulsed signaling could be an example of (i). In general, provision for all possible scenarios is required in the design of mathematical models incorporating pulsed Hill-type signaling as some aspect.

Effect of the adenovirus‑mediated Wip1 gene on lumbar intervertebral disc degeneration in a rabbit model

The present study aimed to investigate the effect of the adenovirus-mediated wild-type p53-induced protein phosphatase 1 (Wip1) gene on lumbar disc degeneration (LDD) in a rabbit model. Adult New Zealand white rabbits were used as experimental subjects. The rabbits were divided into LDD groups (groups A-C of rabbit models of LDD) and control groups (groups D-F of normal rabbits). The animals in groups A and D were injected with the Wip1 gene vector, those in groups B and E were injected with an empty vector, and those in groups C and F were injected with phosphate-buffered saline. Type II collagen was detected using a streptavidin-biotin complex immunohistochemistry method. Postoperative X-ray imaging showed a significant increase in the recovery of rabbits from group A, compared with those from groups B and C. The nucleus pulposus proteoglycan content of the intervertebral discs (L2-3, L3-4 and L4-5) of group A remained higher, compared with the content in groups B and C, and the values in groups B and C differed from those of groups E and F. At 3, 6 and 9 weeks post-injection, the content of type II collagen of intervertebral discs (L2-3, L3-4 and L4-5) in group A differed from groups B and C, and the values in groups A-C remained lower, compared with those in groups D-F. The Wip1 gene exhibited a therapeutic effect in the treatment of LDD.

Bifurcation in Cell Cycle Dynamics Regulated by p53

We study the regulating mechanism of p53 on the properties of cell cycle dynamics in the light of the proposed model of interacting p53 and cell cycle networks via p53. Irradiation (IR) introduce to p53 compel p53 dynamics to suffer different phases, namely oscillating and oscillation death (stabilized) phases. The IR induced p53 dynamics undergo collapse of oscillation with collapse time Δt which depends on IR strength. The stress p53 via IR drive cell cycle molecular species MPF and cyclin dynamics to different states, namely, oscillation death, oscillations of periods, chaotic and sustain oscillation in their bifurcation diagram. We predict that there could be a critical Δtc induced by p53 via IRc, where, if Δt〈Δtc the cell cycle may come back to normal state, otherwise it will go to cell cycle arrest (apoptosis).