Single stranded-DNA detection: the role of Wip1 in ATR-dependent pathway

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Monika Kurpas^∗ (Gliwice) Katarzyna Jonak (Gliwice) Krzysztof Puszynski^∗ (Gliwice)

Single stranded-DNA detection: the role of Wip1 in ATR-dependent pathway

Abstract Single-stranded DNA (ssDNA) areas arise in cells as a result of exposure to stress agents like UVC or during repair of DNA double-strand breaks. ATR (ataxia telangiectasia mutated and Rad3-related) is responsible for detecting ssDNA.

Recently, it has been shown that one of the most important components of cellular response to the damage is Wip1 phosphatase, which inactivates main elements of DNA damage response (DDR) pathways. We developed a mathematical model of ATR detector system, connected to p53 tumor suppressor responsible for activation of genes involved in the cellular response to the damage (DNA repair/apoptosis).

Moreover, we added Wip1 phosphatase, as the main agent responsible for turning o DDR. Our results show, that with an accurate dose of UVC and silenced or blocked Wip1, it may be possible to drive cancer cells to apoptotic pathway.

2010 Mathematics Subject Classification: Primary: 92B05; Secondary: 34C11, 34D20, 34K60, 92C60.

Key words and phrases: ATR, Wip1, mathematical model, UV, p53.

1. Introduction. Studying signaling pathways is essential in the field of investigation of the cellular response to the damaging agents, in order to predict, prevent and prepare an appropriate treatment for disorders appearing as a result of DNA breakages and incorrect mechanisms of DNA repair.

Here, we focus on ATR (ataxia telangiectasia mutated and Rad3-related) signaling pathway, a detector module of single-stranded DNA (ssDNA) in cells. Mutations in ATR module are associated with cancer development through the direct interaction with tumor suppressors BRCA1/2 (breast cancer type 1 and 2 susceptibility proteins) and p53 (cellular tumor antigen), as well as cell cycle checkpoint kinases Chk1 and Chk2.

1.1. The biological overview of ATR signaling pathway. ATR module can be activated by chemical agents, exposure to ultraviolet (UV) radiation, or endogenously by replication errors resulting in stalled replication

∗This work was partially financed by the Polish BKM fund supporting young resear- chers (MK)

∗ This work was partially supported by the grant number 2016/23/B/ST6/03455 fo- unded by National Science Centre, Poland (KP)

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forks, causing the appearance of ssDNA. ATR-ATRIP attaches to ssDNA coated with RPA molecules, what results in activatory autophosphorylation of ATR and signal amplification. Activated ATR phosphorylates the components of Rad9-Rad1-Hus1 (9-1-1) complex, what leads to its activation. In turn, activated Rad9 subunit of 9-1-1 complex takes part in the full activation of ATR, what initiates its downstream signaling cascade [7].

In the next step, ATR activates through phosphorylation Chk1, Chk2 and p53 – transcription factor, which regulates expression of large number of genes that encode proteins involved in DNA repair, apoptosis or control of the cell cycle. P53, called also "the guardian of the genome", prevents cancer formation by directing the cell to the apoptosis pathway. P53 is most frequently mutated gene in human cancer. This protein negatively regulates expression of Chk1 and Chk2, and induces transcription of its main inhibitor Mdm2 (E3 ubiquitin-protein ligase, double minute 2 homolog), forming the negative loop.

Mdm2 is inactivated by ATR kinase through additional phosphorylation on Ser-407 site and by the action of Chk1 and Chk2. This chemical modification prevents Mdm2 from inhibiting p53. Additionally, checkpoint kinases take part also in phosphorylation of the cancer suppressor. Both actions increase the stability of the p53 protein, what results in the increase of its level [13].

ATR is responsible for positive regulation of Akt (protein kinase B), which is one of the main components of the p53-Mdm2 pathway involving PTEN (phosphatase and tensin homolog), which is transcriptionally regulated by p53 (described in details in [11]). PTEN forms a positive feedback loop with p53 what introduces a delay to the system and acts like a molecular clock, which gives time to repair DNA damage (if it is possible), or allows to maintain high level of p53 when lesions are unrepairable, what may lead to the death of the cell.

Recent works [6], [8] have shown that the essential role in the DDR regulatory pathways is played by phosphatase Wip1 (PPM1D, protein phosphatase 1D), which functions as a main dephosphorylating agent. This phosphatase accumulates after DNA damage in order to "turn off" DDR after success- ful repair of the lesions. The phosphatase is transcriptionally regulated by p53, forming the negative feedback loop by inactivation of p53. Moreover, it is involved in inactivation of Chk1 and Chk2 and reactivation of Mdm2 by dephosphorylation of the ATR binding site. When there is no continuous stimulation by DNA damage present in the cell, Wip1 is able to decrease levels of active p53 and checkpoint proteins. Negative loops between Wip1 and other components of the ATR-p53 pathway may limit the p53-dependent DNA damage response.

1.2. Existing mathematical models. The existing mathematical models of the ATR-p53 pathway ([14], [1], and [16]) do not consider various cell compartments or proteins and their forms, that we found essential for activation of damage response and simulation analysis of cells behavior.

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Figure 1: Schematic representation of the ATR-p53-Wip1 model. DNA damage induces activation of 9-1-1 complex and ATR, which transduces the signal on Chk1 and Chk2 proteins (involved in cell cycle regulation), and p53 module consisting of the negative feedback loop with the participation of Mdm2 and the positive feedback loop containing PTEN. P53 is an effector element, which can induce cell cycle arrest, DNA repair or apoptosis. The activity of cell cycle checkpoint proteins and the p53 module is inhibited by Wip1 phosphatase. Novel parts of the model (Wip1 module and the interaction between ATR and Akt) are depicted by dark grey ellipses and bolded solid or dashed lines. ATR module with checkpoint kinases is shown in light grey and the p53-Mdm2 module is in black (uncolored fill). Dotted lines with arrow-heads are positive regulation, solid lines are transitions between states of the components, crossed circle is degradation, and P is phosphorylated form of the protein, while a in ATR case means fully active form. Stochastic gene states are depicted together as "DNA" ellipse. The arrows coming out of it correspond to the transcription process, which can be regulated by other proteins (transcription factors).

In many cases, it is important to distinguish nuclear and cytoplasmic local- ization of proteins, which modulate their activity. In the existing models, the stochastic approach is not used. Deterministic simulations are not able to properly describe the complexity of biological systems, where a lot of processes have stochastic character. Moreover performing stochastic simulations provides an opportunity to study the responses of the cell population and to examine how apoptotic fraction size changes depending on the simulation

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conditions.

2. The model. Macromolecules, stochasticity, cytoplasmatic and nuclear compartments, omitted in the existing mathematical models are in our opinion, necessary to reflect the proper, close to the reality, dynamics of the pathway. Moreover, there is still lack of ATR-p53 pathway models. There- fore, we became interested in creating a novel mathematical model describing the ATR detector module. We combined the new approach with the updated version of our previously constructed p53 model [11].

The model of ATR-p53-Wip1 (Figure1), distinguishes two compartments:

nucleus and cytoplasm. There are four main states of the model components:

state of the gene, mRNA, protein active and inactive state. For ATR there is additional state indicating the full activation.

The input of the model is a dose of UV radiation, which is then trans- formed to the corresponding level of ssDNA. The level of p53 protein decides about cell fate. Mdm2 and Wip1 cause a decrease of the p53 level and intro- duce the oscillations to the system. We assumed that the cell survives with an ability to proliferate when the level of p53 is below the apoptotic threshold (see the results section). If the repair does not occur, p53 level increases and cell undergoes apoptosis [11]. Detailed DNA lesions repair mechanism was not subject of this work, so we assumed simplified repair mechanism.

We assumed that each gene has two copies (allele): both can be active, only one or none. In the stochastic model, the number of active genes is equal to 2, 1 or 0, respectively, while in the deterministic approach the values are within the range <0,2>, what represents the mean state of cells population.

3. Methods. Numerical implementation of the model is based on Haseltine- Rawlings postulate, which combines stochastic and deterministic approach [3]. The first one (Gillespie method) is used for reactions, which involve small number of molecules (PTEN, Mdm2, p53, Wip1, Chk2 and Chk1 gene switch- ing, ssDNA formation and repair process). The second one (ordinary differ- ential equations, Runge-Kutta 4th order method) is used for reactions, in which large number of molecules take part – like phosphorylation and other protein-protein interactions.

To build our model we used the basic biochemistry laws: the law of mass action and Michaelis-Menten kinetics. The parameters for the model equations were estimated by fitting the model to the known data. In most cases, we used data from transcript half-life database [12] and results of western- blot experiments [5,9,10,15]. We compared the intensity of tracks in several time points to the control (untreated) track and calculated fold change using program developed by Jonak et al. [4]. Time courses of simulated transcripts and proteins were then manually fitted to the available data.

We did not construct our model for any specific cell line. Also, parameters obtained from the literature are not restricted to be taken from a particular

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cell line. We focused mainly on obtaining responses, which are qualitatively proper. Very accurate fit to the parameters of one, chosen line may be the reason why the model turns out incorrect in case of the others.

4. Results. In [2], it was demonstrated that 4000 single strand breaks occur in response to UV dose of 20 J/m² per minute. While simulating our model, we assumed a linear relationship between UV dose and the number of DNA lesions.

Figure 2: DNA damage detection and repair after irradiation with 10, 15, 20 and 50 J/m². AB: Comparison between results of stochastic simulation for 200 cells:

level of ssDNA after 15 J/m² (A) and 20 J/m² (B). CD: Median, first and third quartile of the level of active p53 (P53p), nuclear active Mdm2 (MDMn) and Wip1 (WIP1) in response to 10 J/m²(C) and 50 J/m²(D).

4.1. Apoptotic threshold. We determined the threshold value of UV dose, which causes apoptosis in the majority of cells. We performed stochastic simulations on 200 cells for different doses of UV and analyzed cells behavior (Figure 2A, B).

We assumed that the threshold apoptotic value is equal to 2.0x10⁴ (number of p53 molecules), and the cell is treated as apoptotic when the high level of p53 is stabilized for more than 6 hours.

We identified the dose of 20 J/m² as the threshold value above which we observe the apoptotic death of more than half population of simulated cells (Figure 2B). However, the critical dose depends strongly on cell line and its specific parameters.

4.2. Cell behavior after exposure to various doses of UV. In order to compare the response of the cells to the low and high dose of UV, we performed 200 stochastic simulations with 10 J/m² and 50 J/m². The

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damage caused by 10 J/m² is repaired fast, due to strong, but short lasting activation of p53 protein (Figure 2C). The levels of active p53 and Mdm2 start to oscillate, but these oscillations damped together with the end of DNA repair process. Interestingly, the level of Wip1 protein remains elevated longer than levels of the other proteins, what may be related with the role of the phosphatase: limitation of p53 response.

In case of irradiation with high UV dose, level of active p53 remains elevated for more than 96 hours after irradiation (Figure 2D). Such behavior is characteristic to the apoptotic response to stimuli.

4.3. Blockade of the pathway components. A frequently observed feature of cancer cell lines is a presence of mutations in modules which are crucial for proper functioning of DNA repair and apoptosis processes.

We performed stochastic simulations on 200 cells treated with UV dose of 12 J/m². Two main components of the ATR-p53-Wip1 pathway – Wip1 phosphatase and ATR kinase – were silenced to 25% of nominal value.

Firstly, we focused on the cellular response after increasing the degradation of Wip1 phosphatase transcript (Figures 3B and 3E) to achieve an effect of Wip1 silencing to 25% (biologically possible). We observed the high peak of p53 after irradiation and higher median level of p53 during the whole simulation. Apoptotic response is very strong in this case and DNA becomes rapidly degraded (Figure 3E). For the UV dose equal 12 J/m² in cells with normally functioning pathway the apoptotic event is rare (1%, Figure 3G) and DNA damage is effectively repaired (Figures 3A and 3D). In cells with silenced Wip1, the size of the apoptotic fraction is equal to 93.5% (Figure3G).

Secondly, we focused on decreasing the amount of the ATR molecules to 25%. We also reduced the rate of its activation by ssDNA (Figures 3C and 3F). In cells irradiated with 12 J/m² we did not observe apoptosis. However, decreased p53 level and elongated DNA damage repair are noticeable.

In order to verify if this pattern of response of cells mutated in such way will be still present with higher UV doses, we performed similar experiments for cells irradiated with 15, 20 and 60 J/m²UVC (Figure3G). The size of the apoptotic fraction in cells with silenced Wip1 becomes higher with increasing UV dose and reach 100% after irradiation with 15 J/m². In contrast, the size of the apoptotic fraction in cells with silenced ATR is still equal 0% regardless of UV dose (but with increasing DNA repair time, data not shown), except the case of extremely high UV dose (60 J/m²). In such conditions, 100%

of cells become apoptotic due to strongly elongated DNA damage repair. In other cases, level of the active p53 is too low to initiate apoptosis. In such conditions the genetic material, which remain unrepaired until the next cell division, possibly may cause mitotic catastrophe.

5. Conclusions. Our novel model of the ATR-p53-Wip1 regulatory pathway is able to predict the behavior of cells after treatment with UV

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Figure 3: Modifications of ATR pathway. Stochastic simulations on 200 cells treated with UV dose of 12 J/m². ABC: Median, first and third quartile of the level of active p53 (P53p), nuclear active Mdm2 (MDMn) and Wip1 (WIP1) with fully active components of the pathway (A), with Wip1 silenced to 25 percent (B) and with ATR silenced to 25 percent (C). DEF: Stochastic simulations on 200 cells, ssDNA level after treatment with UV dose of 12 J/m², with fully active components of the pathway (D), with Wip1 silenced to 25 percent (E) and with ATR silenced to 25 percent (F). G: Comparison of the number of apoptotic cells between normal cells and cells with reduced expression of Wip1 and ATR proteins.

radiation causing the formation of ssDNA. We investigated the effects of different doses of UV on a single cell and population of cells. We examined also the effect of increased transcript degradation or reduction of the protein level and activation rate for two of the pathway components: Wip1, the main gatekeeper of p53-Mdm2 feedback loop, and ATR, the detection signal trans- ducer. Here we have shown that the reduction in activity of these proteins is very noticeable. Our predictions also indicate that Wip1 may be a promising

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future drug target used against cancer and other diseases being a result of incorrect mechanisms occurring inside p53 pathway.

References

[1] E. Batchelor, A. Loewer, C. Mock, and G. Lahav. Stimulus-dependent dynamics of p53 in single cells. Mol Syst Biol, 7:1–8, 2011. doi:

10.1038/msb.2011.20. Cited on p.118.

[2] K. Erixon and G. Ahnstrom. Single-strand breaks in DNA during repair of UV-induced damage in normal human and xeroderma pigmen- tosum cells as determined by alkaline DNA unwinding and hydroxylap- atite chromatography: Effects of hydroxyurea, 5-fluorodeoxyuridine and 1-beta-D-arabinofuranosylcytosine on the kinetics of repair. Mutat Res - Fund Mol M, 59:257–271, 1979. doi: 10.1016/0027-5107(79)90164-7.

Cited on p. 121.

[3] E. L. Haseltine and J. B. Rawlings. Approximate simulation of coupled fast and slow reactions for stochastic chemical kinetics. Journal of Chem- ical Physic, 117(15):6959–6969, 2002. doi: 10.1063/1.1505860. Cited on p.120.

[4] K. Jonak, K. Jedrasiak, A. Polanski, and K. Puszynski. Aplication of Image Processing in Proteomics: Automatic Analysis of 2-D Gel Elec- trophoresis Images from Western Blot Assay. Lecture Notes in Computer Science, 7594:433–440, 2012. doi: 10.1007/978-3-642-33564-8_52. Cited on p. 120.

[5] L. Latonen, Y. Taya, and M. Laiho. Uv-radiation induces dose-dependent regulation of p53 response and modulates p53-hdm2 interaction in human fibroblasts. Oncogene, 20(46):6784, 2001. doi: 10.1038/sj.onc.1204883.

Cited on p. 120.

[6] X. Le Guezennec and D. V. Bulavin. WIP1 phosphatase at the cross- roads of cancer and aging. Trends Biochem Sci, 35:109–114, 2010. doi:

10.1016/j.tibs.2009.09.005. Cited on p.118.

[7] S. Liu, B. Shiotani, M. Lahiri, A. Marechal, A. Tse, C.C. Leung, J.N. Glover, X.H. Yang, and L. Zou. ATR Autophosphorylation as a Molecular Switch for Checkpoint Activation. Mol Cell, 43:192–202, 2011. doi: 10.1016/j.molcel.2011.06.019. Cited on p.118.

[8] J. Lowe, H. Cha, M. O. Lee, S. J. Mazur, E. Appella, and A. J. J. Fornace.

Regulation of the Wip1 phosphatase and its effects on the stress response.

Frontiers in bioscience: a journal and virtual library, 17:1480–1498, 2012.

Cited on p. 118.

[9] X. Lu, B. Nannenga, and L. A. Donehower. Reversal of the ATM/ATR- Mediated DNA Damage Response by the Oncogenic Phosphatase PPM1D. Cell Cycle, 4:1060–1064, 2005. doi: 10.4161/cc.4.8.1876. Cited on p. 120.

(9)

[10] X. Lu, O. Ma, T.A. Nguyen, S.N. Jones, M. Oren, and L.A. Donehower.

The Wip1 Phosphatase acts as a gatekeeper in the p53-Mdm2 autoregu- latory loop. Cancer cell, 12:342–354, 2007.doi: 10.1016/j.ccr.2007.08.033.

Cited on p. 120.

[11] K. Puszynski, B. Hat, and T. Lipniacki. Oscillations and bistability in the stochastic model of p53 regulation. J Theor Biol, 254:452–465, 2008.

doi: 10.1016/j.jtbi.2008.05.039. Cited on pp.118 and120.

[12] L.V. Sharova , A.A. Sharov, T. Nedorezov, Y. Piao, N. Shaik, and M.S. Ko. Database for mRNA Half-Life of 19 977 Genes Ob- tained by DNA Microarray Analysis of Pluripotent and Differentiat- ing Mouse Embryonic Stem Cells. DNA Res, 16:45–58, 2009. doi:

10.1093/dnares/dsn030. Cited on p.120.

[13] S.-Y. Shieh, J. Ahn, K. Tamai, Y. Taya, and C. Prives. The human homologs of checkpoint kinases Chk1 and Cds1 (Chk2) phosphorylate p53 at multiple DNA damage-inducible sites. Genes and Development, 14:289–300, 2000. doi: 10.1101/gad.14.3.289. Cited on p.118.

[14] Y. Tashima, Y. Kisaka, T. Hanai, H. Hamada, Y. Eguchi, and M. Okamoto. Mathematical modeling of G2/M phase in the cell cycle with involving the p53/Mdm2 oscillation system. In World Congress on Medical Physics and Biomedical Engineering 2006, volume 14, pages 197–

200. Springer Berlin, Heidelberg, 2007. doi: 10.1007/978-3-540-36841- 0_58. Cited on p.118.

[15] H. Yajima, K.-J. Lee, S. Zhang, J. Kobayashi, and B. P. Chen. Dna double-strand break formation upon uv-induced replication stress activates atm and dna-pkcs kinases. Journal of molecular biology, 385(3):

800–810, 2009. doi: 10.1016/j.jmb.2008.11.036. Cited on p.120.

[16] L. W. Zhang, Y. M. Cheng, and K. M. Liew. A mathematical analysis of DNA damage induced G2 phase transition. Appl Math Comput, 225:

765–774, 2013. doi: 10.1016/j.amc.2013.10.025. Cited on p.118.

Wykrywanie pojedynczoniciowych fragmentów DNA: rola Wip1 w szlaku sygnałowym ATR

Monika Kurpas, Katarzyna Jonak, Krzysztof Puszynski

Streszczenie Obszary pojedynczonciowego DNA (ssDNA) powstają w komórkach w wyniku ekspozycji na stres na przykład– promieniowanie UVC–lub podczas na- prawy podwójnoniciowych pęknięć DNA. ATR (ataxia telangiectasia mutated and Rad3-related) jest odpowiedzialne za wykrywanie ssDNA. Niedawno wykazano klu- czową rolę fosfatazy Wip1, która inaktywuje główne elementy szlaków odpowiedzi na uszkodzenia DNA. Opracowaliśmy matematyczny model ścieżki ATR i połączyliśmy go z modelem szlaku supresora nowotworowego p53, odpowiadającego za aktywację genów zaangażowanych w reakcję komórki na uszkodzenie materiału genetycznego (naprawę DNA/apoptozę). Co więcej, dodaliśmy fosfatazę Wip1, jako główny czyn- nik odpowiedzialny za wyłączenie ścieżek sygnałowych uruchamianych w ramach

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reakcji na uszkodzenie. Uzyskane wyniki pokazują, że dzięki prawidłowo dobranej dawce UVC i wyciszeniu lub zablokowaniu aktywności Wip1, możliwe jest skierowa- nie komórek nowotworowych na szlak apoptotyczny

Klasyfikacja tematyczna AMS (2010): 92B05; 34C11, 34D20, 34K60, 92C60.

Słowa kluczowe: ATR, Wip1, model matematyczny, UV, p53.

Monika Kurpas holds master degree in biotechnology, currently is doing PhD studies in Biocybernetics and Biomedical Engi- neering. Her interests lie in mathematical modeling of signaling pathways and developing stochastic models of cancer growth and spread.

Katarzyna Jonak holds master degrees in Bioinformatics and in Molecular Medicine. Currently, as a graduate student at the Max Planck Institute of Biochemistry, she is studying regulation of meiotic divisions and chromosome segregation using combination of biological experiments and mathematical modeling.

Krzysztof Puszynski PhD in Biocybernetics and Biomedical En- gineering. Interested in mathematical modeling and analysis of intracellular processes, especially tumor related and mathematical modeling in epidemiology. Interested in both deterministic and stochastic approach to the mentioned problems. His research papers are listed in the European Math. Soci., FIZ Karlsruhe, and the Heidelberg Academy of Sciences bibliography database known as zbMath under ai:puszynski.krzysztof, in MathSciNet underID: 784648andORCID ID:0000-0003-3525-1996.

Monika Kurpas

Silesian University of Technology

Faculty of Automatic Control, Electronics and Computer Science Akademicka 16, Gliwice 44-100, Poland

E-mail: monika.kurpas@polsl.pl Katarzyna Jonak

E-mail: katarzyna.jonak@polsl.pl Krzysztof Puszynski

E-mail: krzysztof.puszynski@polsl.pl

Communicated by: Urszula Foryś

(Received: 15th of May 2018; revised: 2nd of July 2018)