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Construction of a computable network model for DNA damage, autophagy, cell death, and senescence.

ABSTRACT: Towards the development of a systems biology-based risk assessment approach for environmental toxicants, including tobacco products in a systems toxicology setting such as the "21st Century Toxicology", we are building a series of computable biological network models specific to non-diseased pulmonary and cardiovascular cells/tissues which capture the molecular events that can be activated following exposure to environmental toxicants. Here we extend on previous work and report on the construction and evaluation of a mechanistic network model focused on DNA damage response and the four main cellular fates induced by stress: autophagy, apoptosis, necroptosis, and senescence. In total, the network consists of 34 sub-models containing 1052 unique nodes and 1538 unique edges which are supported by 1231 PubMed-referenced literature citations. Causal node-edge relationships are described using the Biological Expression Language (BEL), which allows for the semantic representation of life science relationships in a computable format. The Network is provided in .XGMML format and can be viewed using freely available network visualization software, such as Cytoscape.

SUBMITTER: Gebel S

PROVIDER: S-EPMC3596057 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

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Construction of a computable network model for DNA damage, autophagy, cell death, and senescence.

Gebel Stephan S Lichtner Rosemarie B RB Frushour Brian B Schlage Walter K WK Hoang Vy V Talikka Marja M Hengstermann Arnd A Mathis Carole C Veljkovic Emilija E Peck Michael M Peitsch Manuel C MC Deehan Renee R Hoeng Julia J Westra Jurjen W JW

Bioinformatics and biology insights 20130307

Towards the development of a systems biology-based risk assessment approach for environmental toxicants, including tobacco products in a systems toxicology setting such as the "21st Century Toxicology", we are building a series of computable biological network models specific to non-diseased pulmonary and cardiovascular cells/tissues which capture the molecular events that can be activated following exposure to environmental toxicants. Here we extend on previous work and report on the constructi ...[more]

PMID: 23515068

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Project description:BackgroundCritical to advancing the systems-level evaluation of complex biological processes is the development of comprehensive networks and computational methods to apply to the analysis of systems biology data (transcriptomics, proteomics/phosphoproteomics, metabolomics, etc.). Ideally, these networks will be specifically designed to capture the normal, non-diseased biology of the tissue or cell types under investigation, and can be used with experimentally generated systems biology data to assess the biological impact of perturbations like xenobiotics and other cellular stresses. Lung cell proliferation is a key biological process to capture in such a network model, given the pivotal role that proliferation plays in lung diseases including cancer, chronic obstructive pulmonary disease (COPD), and fibrosis. Unfortunately, no such network has been available prior to this work.ResultsTo further a systems-level assessment of the biological impact of perturbations on non-diseased mammalian lung cells, we constructed a lung-focused network for cell proliferation. The network encompasses diverse biological areas that lead to the regulation of normal lung cell proliferation (Cell Cycle, Growth Factors, Cell Interaction, Intra- and Extracellular Signaling, and Epigenetics), and contains a total of 848 nodes (biological entities) and 1597 edges (relationships between biological entities). The network was verified using four published gene expression profiling data sets associated with measured cell proliferation endpoints in lung and lung-related cell types. Predicted changes in the activity of core machinery involved in cell cycle regulation (RB1, CDKN1A, and MYC/MYCN) are statistically supported across multiple data sets, underscoring the general applicability of this approach for a network-wide biological impact assessment using systems biology data.ConclusionsTo the best of our knowledge, this lung-focused Cell Proliferation Network provides the most comprehensive connectivity map in existence of the molecular mechanisms regulating cell proliferation in the lung. The network is based on fully referenced causal relationships obtained from extensive evaluation of the literature. The computable structure of the network enables its application to the qualitative and quantitative evaluation of cell proliferation using systems biology data sets. The network is available for public use.

Project description:Macroautophagy (hereafter autophagy) is a multistep intracellular catabolic process with pleiotropic implications in cell fate. Attending to its activation, autophagy can be classified into inducible or constitutive. Constitutive, or basal autophagy, unfolds under nutrient-replete conditions to maintain the cellular homeostasis. Autophagy inhibitory drugs are powerful tools to interrogate the role of autophagy and its consequences on cell fate. However, 3-methyladenine and various of these compounds present an intrinsic capacity to trigger cell death, for instance the broadly-employed 3-methyladenine. To elucidate whether the inhibition of basal autophagy is causative of cell demise, we have employed several representative compounds acting at different phases of the autophagic process: initiation (SBI0206965 and MHY1485), nucleation (3-methyladenine, SAR405, Spautin-1 and Cpd18), and completion (Bafilomycin A1 and Chloroquine). These compounds inhibited the basal autophagy of MEF cultures in growing conditions. Among them, 3-methyladenine, SBI-0206965, Chloroquine, and Bafilomycin A1 triggered BAX- and/or BAK-dependent cytotoxicity and caspase activation. 3-methyladenine was the only compound to induce a consistent and abrupt decrease in cell viability across a series of ontologically unrelated human cell lines. 3-methyladenine-induced cytotoxicity was not driven by the inhibition of the AKT/mTOR axis. Autophagy-deficient Fip200-/- MEFs displayed an increased sensitivity to activate caspases and to undergo cell death in response to 3-methyladenine. The cytotoxicity induced by 3-methyladenine correlated with a massive DNA damage, as shown by γ-H2A.X. This genotoxicity was observed at 10 mM 3-methyladenine, the usual concentration to inhibit autophagy and was maximized in Fip200-/- MEFs. In sum, our results suggest that, in growing conditions, autophagy acts as a protective mechanism to diminish the intrinsic cytotoxicity of 3-methyladenine. However, when the cellular stress exerted by 3-methyladenine surpasses the protective effect of basal autophagy, caspase activation and DNA damage compromise the cell viability.

Dataset Information

Construction of a computable network model for DNA damage, autophagy, cell death, and senescence.

Publications

Construction of a computable network model for DNA damage, autophagy, cell death, and senescence.

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