Systems Approaches Evaluating the Perturbation of Xenobiotic Metabolism in Response to Cigarette Smoke Exposure in Nasal and Bronchial Tissues

Abstract

Capturing the effects of exposure in a specific target organ is a major challenge in risk assessment. Exposure to cigarette smoke (CS) implicates the field of tissue injury in the lung as well as nasal and airway epithelia. Xenobiotic metabolism in particular becomes an attractive tool for chemical risk assessment because of its responsiveness against toxic compounds, including those present in CS. This study describes an efficient integration from transcriptomic data to quantitative measures, which reflect the responses against xenobiotics that are captured in a biological network model. We show here that our novel systems approach can quantify the perturbation in the network model of xenobiotic metabolism. We further show that this approach efficiently compares the perturbation upon CS exposure in bronchial and nasal epithelial cells in vivo samples obtained from smokers. Our observation suggests the xenobiotic responses in the bronchial and nasal epithelial cells of smokers were similar to those observed in their respective organotypic models exposed to CS. Furthermore, the results suggest that nasal tissue is a reliable surrogate to measure xenobiotic responses in bronchial tissue.

Impact Assessment of Repeated Exposure of Organotypic 3D Bronchial and Nasal Tissue Culture Models to Whole Cigarette Smoke

“…Interestingly, the observed alteration in xenobiotic metabolism in the organotypic bronchial and nasal in vitro models exposed to CS resemble that of the in vivo situation in smokers as discussed in greater detail in a previous publication 15 . For gene expression analyses, using the robotic instrument makes a high-throughput analysis possible.…”

“…The activity of the phase I xenobiotic metabolism enzymes, CYP1A1 and CYP1B1, of the tissue models can be measured. Additionally, as previously reported, global gene expression can be measured in the organotypic bronchial tissue models 6,14,15 . A transcriptomic data and network-based systems biology approach is leveraged to assess the impact of CS on xenobiotic metabolism 15 .…”

“…In results described below, the organotypic tissues were primary human epithelial cells isolated from healthy, non-smoking, Caucasian donors and were reconstituted using fibroblasts 15 .…”

“…Subsequently, microarray analysis was conducted to generate gene expression profiles of the CS-and air-exposed tissues. Impact of the CS exposure on xenobiotic metabolism was investigated using a network-based systems biology approach leveraged from the gene-expression profiles and as reported earlier 15 . Using a network-based systems biology approach shows that CS exposure impacts at the level of backbone nodes in the Xenobiotic Metabolism network model were nicely correlated between the in vitro and in vivo datasets (Figure 5).…”

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

“…In similar examples, we have used the CBN models to identify changes in the cell cycle following exposure of NHBEs to a cell cycle inhibitor (26), and to identify changes in cell proliferation, inflammation and necrosis in the rat nasal epithelium following exposure to formaldehyde (27). Of interest, specific subsets of biological networks may be applied to different experimental settings ranging from cigarette smoke exposure of rats (28), to environmental toxicants analyses in vitro (29), or to translational biology of xenobiotic metabolism (30). These examples illustrate how the network models contained in the CBN database (or similar network databases) can identify and even quantitate biological changes induced by diverse stimuli.…”