A computable cellular stress network model for non-diseased pulmonary and cardiovascular tissue

Abstract

BackgroundHumans and other organisms are equipped with a set of responses that can prevent damage from exposure to a multitude of endogenous and environmental stressors. If these stress responses are overwhelmed, this can result in pathogenesis of diseases, which is reflected by an increased development of, e.g., pulmonary and cardiac diseases in humans exposed to chronic levels of environmental stress, including inhaled cigarette smoke (CS). Systems biology data sets (e.g., transcriptomics, phosphoproteomics, metabolomics) could enable comprehensive investigation of the biological impact of these stressors. However, detailed mechanistic networks are needed to determine which specific pathways are activated in response to different stressors and to drive the qualitative and eventually quantitative assessment of these data. A current limiting step in this process is the availability of detailed mechanistic networks that can be used as an analytical substrate.ResultsWe have built a detailed network model that captures the biology underlying the physiological cellular response to endogenous and exogenous stressors in non-diseased mammalian pulmonary and cardiovascular cells. The contents of the network model reflect several diverse areas of signaling, including oxidative stress, hypoxia, shear stress, endoplasmic reticulum stress, and xenobiotic stress, that are elicited in response to common pulmonary and cardiovascular stressors. We then tested the ability of the network model to identify the mechanisms that are activated in response to CS, a broad inducer of cellular stress. Using transcriptomic data from the lungs of mice exposed to CS, the network model identified a robust increase in the oxidative stress response, largely mediated by the anti-oxidant NRF2 pathways, consistent with previous reports on the impact of CS exposure in the mammalian lung.ConclusionsThe results presented here describe the construction of a cellular stress network model and its application towards the analysis of environmental stress using transcriptomic data. The proof-of-principle analysis described here, coupled with the future development of additional network models covering distinct areas of biology, will help to further clarify the integrated biological responses elicited by complex environmental stressors such as CS, in pulmonary and cardiovascular cells.

Causal Biological Network Database: A Comprehensive Platform of Causal Biological Network Models Focused on the Pulmonary and Vascular Systems

“…The first versions of 98 network models (Version 1.0) were constructed and evaluated following the strategy reported previously (7)(8)(9)(10)(11)(12). This strategy ( Figure 3A and B) is summarized briefly here:…”

“…Structurally, the CBN collection is organized into the following biological areas (Figure 1): cell response to stress, cell proliferation, cell fate (including DNA damage response, autophagy, senescence, apoptosis and necroptosis), tissue repair and angiogenesis, pulmonary inflammatory processes, vascular inflammatory processes and chronic obstructive pulmonary disease (COPD)-specific networks. Details of these network models have been published previously (7)(8)(9)(10)(11)(12).…”

Enhancement of COPD biological networks using a web-based collaboration interface

“…These networks cover mechanisms of cell proliferation 5 , cell stress 4 , DNA damage, autophagy, cell death and senescence 3 , pulmonary inflammation 6 , and tissue repair and angiogenesis 7 in the non-diseased pulmonary context. To create COPD-relevant networks, these non-diseased networks were enhanced by incorporating COPD mechanisms sourced using a literature and data set approach ( Figure 1) in an iterative approach, as described in detail for the non-diseased network model construction, by a team of subject matter experts in computational biology, molecular biology, inhalation toxicology, and COPD.…”

“…The 90 previously published non-diseased network models used for the initial substrate included networks involved in cell proliferation 5 , cell stress 4 , DNA damage, apoptosis, senescence, autophagy, necroptosis (DACS) 3 , pulmonary inflammation (IPN) 6 , and tissue repair and angiogenesis (TRAG) 7 . The Endothelial Shear Stress network from the cell stress model was excluded because the focus of the COPD Network was to describe lung biology.…”

Developing Network-Based Systems Toxicology by Combining Transcriptomics Data with Literature Mining and Multiscale Quantitative Modeling

“…The initial mechanistic interest focused on the lung biology, and version 1.0 of the collection consisted of 108 assembled causal networks regrouped into five high-level functional families (cell proliferation 15 [53], cellular stress 7 [54], cell fate 34 [55], pulmonary inflammation 24 [56], and tissue repair/angiogenesis 9 [57]). The design and assembly processes were the same for all the networks, each of them having been defined by biological boundaries chosen to globally cover all of the essential biological processes and responses of healthy lung tissues (Figure 3).…”