Model of colonic inflammation: Immune modulatory mechanisms in inflammatory bowel disease

Abstract

Inflammatory Bowel Disease (IBD) is an immunoinflammatory illness of the gut initiated by an immune response to bacteria in the microflora. The resulting immunopathogenesis leads to lesions in epithelial lining of the colon through which bacteria may infiltrate the tissue causing recurring bouts of diarrhea, rectal bleeding, and mal-nutrition. In healthy individuals such immunopathogenesis is avoided by the presence of regulatory cells that inhibit the inflammatory pathway. Highly relevant to the search for treatment strategies is the identification of components of the inflammatory pathway that allow regulatory mechanisms to be overridden and immunopathogenesis to proceed. In vitro techniques have identified cellular interactions involved in inflammation-regulation crosstalk. However, tracing immunological mechanisms discovered at the cellular level confidently back to an in vivo context of multiple, simultaneous interactions has met limited success. To explore the impact of specific interactions, we have constructed a system of 29 ordinary differential equations representing different phenotypes of T-cells, macrophages, dendritic cells, and epithelial cells as they move and interact with bacteria in the lumen, lamina propria, and lymphoid tissue of the colon. Simulations revealed the positive inflammatory feedback loop formed by inflammatory M1 macrophage activation of T-cells as a driving force underlying the immunopathology of IBD. Furthermore, strategies that remove M1 from the site of infection, by either i) increasing its potential to switch to a regulatory M2 phenotype or ii) increasing the rate of reversion (for M1 and M2 alike) to a resting state, cease immunopathogenesis even as bacteria are eliminated by other inflammatory cells. Based on these results, we identify macrophages and their mechanisms of plasticity as key targets for mucosal inflammation intervention strategies. In addition, we propose that the primary mechanism behind the association of PPARγ mutation with IBD is its ability to mediate the M1 to M2 switch.

Inflammatory Macrophages Induce Nrf2 Transcription Factor-dependent Proteasome Activity in Colonic NCM460 Cells and Thereby Confer Anti-apoptotic Protection

“…Among these, pro-inflammatory (M1 polarized) macrophages play an important role. These cells are found in high number in the diseased tissue, such as the colonic mucosa, and attract other immune cells such as monocytes, neutrophils, and T-cells to the site of inflammation and activate them (46). In addition to cytokines and chemokines eliciting endogenous ROS production by the epithelial cells, these inflammatory macrophages themselves produce high level of ROS (35,47,48) normally contributing to the defense against pathogens.…”

The Protective Effect of the Recombinant 53-kDa Protein of Trichinella spiralis on Experimental Colitis in Mice

“…A Ts-specific 53-kDa glycoprotein (TsP53) has been identified as a major component of its ESA and is present in much greater amounts from Ts larva [15], so it is used as an immunodiagnostic antigen [16], however, its immunomodulatory function has not yet been investigated. In our preliminary study, mice immunized with recombinant TsP53 (rTsP53) produced high levels of specific IgG1, but not of IgG2a, either with complete Freund's adjuvant (CFA) or without any adjuvant, suggesting it is a potent antigen to stimulate Th2-prone response (data shown in the result 5).…”

Integration of Reaction Kinetics Theory and Gene Expression Programming to Infer Reaction Mechanism

“…The technology also permits verification against experimental results. Ideally, the resulting model may be used to predict progression of the disease (Bogojeska et al 2010, Burg et al 2009, Castiglione and Paci 2010, Degon et al 2008, de Sousa et al 2010, Guedj et al 2010, Hoffmann et al 2002, Itakura 2010, Perelson et al 1996, Smith and Ribeiro 2010, Srivastava et al 2002, von Kleist et al 2010, Wendelsdorf et al 2010, Yang et al 2007. It is also possible to identify, develop, and optimize treatment strategies in a mathematically rigorous fashion.…”