Published today in Bioinformatics and Biology Insights is a new original research article by Jurjen W. Westra, Walter K. Schlage, Arnd Hengstermann, Stephan Gebel, Carole Mathis, Ty Thomson, Ben Wong, Vy Hoang, Emilija Veljkovic, Michael Peck, Rosemarie B. Lichtner, Dirk Weisensee, Marja Talikka, Renee Deehan, Julia Hoeng and Manuel C. Peitsch.  Read more about this paper below:

Title

A Modular Cell-Type Focused Inflammatory Process Network Model for Non-Diseased Pulmonary Tissue

Abstract

Exposure to environmental stressors such as cigarette smoke (CS) elicits a variety of biological responses in humans, including the induction of inflammatory responses. These responses are especially pronounced in the lung, where pulmonary cells sit at the interface between the body’s internal and external environments. We combined a literature survey with a computational analysis of multiple transcriptomic data sets to construct a computable causal network model (the Inflammatory Process Network (IPN)) of the main pulmonary inflammatory processes. The IPN model predicted decreased epithelial cell barrier defenses and increased mucus hypersecretion in human bronchial epithelial cells, and an attenuated pro-inflammatory (M1) profile in alveolar macrophages following exposure to CS, consistent with prior results. The IPN provides a comprehensive framework of experimentally supported pathways related to CS-induced pulmonary inflammation. The IPN is freely available to the scientific community as a resource with broad applicability to study the pathogenesis of pulmonary disease.

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