Anti-inflammatory effects of reactive oxygen species – a multi-valued logical model validated by formal concept analysis

BMC Systems Biology

Olaf Wolkenhauer²  Katja Rateitschak³  Sarah Müller¹  Robert Jaster¹  Johannes Wollbold³ 

[1] Department of Medicine II, Division of Gastroenterology and Endocrinology, University Medicine Rostock, E.-Heydemann-Str. 6, Rostock, D-18057, Germany;Stellenbosch Institute for Advanced Study (STIAS), Wallenberg Research Centre, 10 Marais Street, Stellenbosch 7600, South Africa;Department of Systems Biology and Bioinformatics, University of Rostock, Ulmenstr 69, Rostock, D-18057, Germany

关键词: Necrosis;    Apoptosis;    Formal concept analysis;    Multi-valued logic;    Calcium;    Reactive oxygen species;    Mitochondria;    Acute pancreatitis;   

Others  :  1126943
DOI  :  10.1186/s12918-014-0101-7

 received in 2014-03-13, accepted in 2014-08-14,  发布年份 2014

【 摘 要 】

Background

Recent findings suggest that in pancreatic acinar cells stimulated with bile acid, a pro-apoptotic effect of reactive oxygen species (ROS) dominates their effect on necrosis and spreading of inflammation. The first effect presumably occurs via cytochrome C release from the inner mitochondrial membrane. A pro-necrotic effect – similar to the one of Ca²⁺ – can be strong opening of mitochondrial pores leading to breakdown of the membrane potential, ATP depletion, sustained Ca²⁺ increase and premature activation of digestive enzymes. To explain published data and to understand ROS effects during the onset of acute pancreatitis, a model using multi-valued logic is constructed. Formal concept analysis (FCA) is used to validate the model against data as well as to analyze and visualize rules that capture the dynamics.

Results

Simulations for two different levels of bile stimulation and for inhibition or addition of antioxidants reproduce the qualitative behaviour shown in the experiments. Based on reported differences of ROS production and of ROS induced pore opening, the model predicts a more uniform apoptosis/necrosis ratio for higher and lower bile stimulation in liver cells than in pancreatic acinar cells. FCA confirms that essential dynamical features of the data are captured by the model. For instance, high necrosis always occurs together with at least a medium level of apoptosis. At the same time, FCA helps to reveal subtle differences between data and simulations. The FCA visualization underlines the protective role of ROS against necrosis.

Conclusions

The analysis of the model demonstrates how ROS and decreased antioxidant levels contribute to apoptosis. Studying the induction of necrosis via a sustained Ca²⁺ increase, we implemented the commonly accepted hypothesis of ATP depletion after strong bile stimulation. Using an alternative model, we demonstrate that this process is not necessary to generate the dynamics of the measured variables. Opening of plasma membrane channels could also lead to a prolonged increase of Ca²⁺ and to necrosis. Finally, the analysis of the model suggests a direct experimental testing for the model-based hypothesis of a self-enhancing cycle of cytochrome C release and ROS production by interruption of the mitochondrial electron transport chain.

【 授权许可】

   
2014 Wollbold et al.; licensee BioMed Central Ltd.

【 图 表 】

Figure 1.

Figure 2.

Figure 3.

Figure 4.

Figure 5.

Figure 6.

Figure 7.

Figure 8.

【 参考文献 】

• [1]Gukovskaya AS, Gukovsky I: Which way to die: the regulation of acinar cell death in pancreatitis by mitochondria, calcium, and reactive oxygen species. Gastroenterology 2011, 140:1876-1880.
• [2]Booth DM, Murphy JA, Mukherjee R, Awais M, Neoptolemos JP, Gerasimenko OV, Tepikin AV, Petersen OH, Sutton R, Criddle DN: Reactive oxygen species induced by bile Acid induce apoptosis and protect against necrosis in pancreatic acinar cells. Gastroenterology 2011, 140:2116-2125.
• [3]Kirkwood TBL, Kowald A: The free-radical theory of ageing - older, wiser and still alive: Modelling positional effects of the primary targets of ROS reveals new support. Bioessays 2012, 34:692-700.
• [4]Lapointe J, Hekimi S: When a theory of aging ages badly. Cell Mol Life Sci 2010, 67:1-8.
• [5]Yang W, Hekimi S: A mitochondrial superoxide signal triggers increased longevity in Caenorhabditis elegans. PLoS Biol 2010, 8:e1000556.
• [6]Raraty M, Ward J, Erdemli G, Vaillant C, Neoptolemos JP, Sutton R, Petersen OH: Calcium-dependent enzyme activation and vacuole formation in the apical granular region of pancreatic acinar cells. Proc Natl Acad Sci USA 2000, 97:13126-13131.
• [7]Criddle D, Gerasimenko J: Calcium signalling and pancreatic cell death: apoptosis or necrosis? Cell Death 2007, 14:1285-1294.
• [8]Camello-Almaraz C, Gomez-Pinilla PJ, Pozo MJ, Camello PJ: Mitochondrial reactive oxygen species and Ca2+ signaling. Am J Physiol Cell Physiol 2006, 291:C1082-C1088.
• [9]Kowaltowski AJ, Netto LES, Vercesi AE: The Thiol-specific Antioxidant Enzyme Prevents Mitochondrial Permeability Transition. J Biol Chem 1998, 273:12766-12769.
• [10]Odinokova I, Sung K, Mareninova O, Hermann K, Evtodienko Y, Andreyev A, Gukovsky I, Gukovskaya A: Mechanisms regulating cytochrome c release in pancreatic mitochondria. Gut 2008, 58:431-442.
• [11]Heuett WJ, Periwal V: Autoregulation of Free Radicals via Uncoupling Protein Control in Pancreatic beta-Cell Mitochondria. Biophys J 2010, 98:207-217.
• [12]Magnus G, Keizer J: Minimal model of beta-cell mitochondrial Ca2+ handling. Am J Physiol 1997, 273:C717-C733.
• [13]Yang L, Korge P, Weiss JN, Qu Z: Mitochondrial oscillations and waves in cardiac myocytes: insights from computational models. Biophys J 2010, 98:1428-1438.
• [14]Kauffman SA: Metabolic stability and epigenesis in randomly constructed genetic nets. J Theor Biol 1969, 22:437-467.
• [15]Thomas R: Regulatory Networks Seen as Asynchronous Automata: A Logical Description. J Theor Biol 1991, 153:1-23.
• [16]Chaouiya C, Remy E: Logical Modelling of Regulatory Networks, Methods and Applications. Bull Math Biol 2013, 75:891-895.
• [17]Ganter B, Stumme G, Wille R: Formal Concept Analysis. Foundations and Applications. Springer, Berlin, Heidelberg; 2005.
• [18]Wollbold J: Attribute Exploration of Gene Regulatory Processes. PhD thesis. Friedrich Schiller University Jena; 2011:110.
• [19]Bertram R, Pedersen MG, Luciani DS, Sherman A: A simplified model for mitochondrial ATP production. J Theor Biol 2006, 243:575-586.
• [20]Andreyev AY, Kushnareva YE, Starkov AA: Mitochondrial metabolism of reactive oxygen species. Biochemistry (Mosc) 2005, 70:200-214.
• [21]Klamt S, Saez-Rodriguez J, Lindquist JA, Simeoni L, Gilles ED: A methodology for the structural and functional analysis of signaling and regulatory networks. BMC Bioinformatics 2006, 7:56. BioMed Central Full Text
• [22]Schlatter R, Schmich K, Avalos Vizcarra I, Scheurich P, Sauter T, Borner C, Ederer M, Merfort I, Sawodny O: ON/OFF and Beyond – a Boolean Model of Apoptosis. PLoS Comput Biol 2009, 5:e1000595.
• [23]Calzone L, Tournier L, Fourquet S, Thieffry D, Zhivotovsky B, Barillot E, Zinovyev A: Mathematical modelling of cell-fate decision in response to death receptor engagement. PLoS Comput Biol 2010, 6:e1000702.
• [24]Dupont G, Combettes L, Bird GS, Putney JW: Calcium oscillations. Cold Spring Harb Perspect Biol 2011, 3:1-18.
• [25]Ganter B, Wille R: Formal Concept Analysis – Mathematical Foundations. Heidelberg: Springer; 1999:284.
• [26]Ventura AC, Sneyd J: Calcium oscillations and waves generated by multiple release mechanisms in pancreatic acinar cells. Bull Math Biol 2006, 68:2205-2231.
• [27]Petersen OH, Gerasimenko OV, Gerasimenko JV: Pathobiology of acute pancreatitis: focus on intracellular calcium and calmodulin. F1000 Med Rep 2011, 3:15.
• [28]Kushnareva Y, Murphy A, Andreyev A: Complex I-mediated reactive oxygen species generation: modulation by cytochrome c and NAD(P)+ oxidation-reduction state. Biochem J 2002, 553:545-553.
• [29]Kim J, Wang J, Lemasters J: Mitochondrial permeability transition in rat hepatocytes after anoxia/reoxygenation: role of Ca2+−dependent mitochondrial formation of reactive oxygen species. Am J Physiol Gastrointest Liver Physiol 2012, 302:G723-G731.
• [30]Nawaz M, Manzl C, Lacher VKG: Copper-induced stimulation of extracellular signal-regulated kinase in trout hepatocytes: the role of reactive oxygen species, Ca2+, and cell energetics and the impact of extracellular signal-regulated kinase signaling on apoptosis and necrosis. Toxicol Sci 2006, 92:464-475.
• [31]Halangk W, Matthias R, Schild L, Meyer F, Schulz HU, Lippert H: Effect of supramaximal cerulein stimulation on mitochondrial energy metabolism in rat pancreas. Pancreas 1998, 16:88-95.
• [32]Wollbold J, Huber R, Pohlers D, Koczan D, Guthke R, Kinne RW, Gausmann U: Adapted Boolean network models for extracellular matrix formation. BMC Syst Biol 2009, 3:19. BioMed Central Full Text
• [33]Naldi A, Berenguier D, Fauré A, Lopez F, Thieffry D, Chaouiya C: Logical modelling of regulatory networks with GINsim 2.3. BioSystems 2009, 97:134-139.
• [34]Li C, Donizelli M, Rodriguez N, Dharuri H, Endler L, Chelliah V, Li L, He E, Henry A, Stefan MI, Snoep JL, Hucka M, Le Novère N, Laibe C: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. BMC Syst Biol 2010, 4:92. BioMed Central Full Text
• [35]Chaouiya C, Bérenguier D, Keating SM, Naldi A, van Iersel MP, Rodriguez N, Dräger A, Büchel F, Cokelaer T, Kowal B, Wicks B, Gonçalves E, Dorier J, Page M, Monteiro PT, von Kamp A, Xenarios I, de Jong H, Hucka M, Klamt S, Thieffry D, Le Novère N, Saez-Rodriguez J, Helikar T: SBML qualitative models: a model representation format and infrastructure to foster interactions between qualitative modelling formalisms and tools. BMC Syst Biol 2013, 7:135. BioMed Central Full Text