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

https://doi.org/10.1016/j.jtbi.2010.03.027Get rights and content

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 malnutrition. 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.

Introduction

Inflammatory bowel disease (IBD) is a chronic illness of the gut characterized by a recurring inflammatory response to bacteria in the lumen microflora resulting in lesions of the epithelial lining and lamina propria (Swidsinski et al., 2002). The lamina propria is the tissue site where immune cells initially recognize bacterial antigen prior to migrating to the distal lymphoid tissue to mount the inflammatory response. IBD results in two clinical manifestations, Crohn's disease and ulcerative colitis, in which the patient experiences relapses of diarrhea, rectal bleeding, and malnutrition as bacteria from the lumen leak into the lamina propria through the lesions in the epithelial barrier (Cho, 2008). Over 1 million people are afflicted by IBD in North America and 4 million worldwide resulting in a severe decrease in quality of life as well as significant health care-related costs (Stenson, 1995). Total expenses exceed $15 billion annually in the U.S. not including indirect expenses of treating complications such as recurrent pancreatitis, abscesses, intestinal obstruction, anemia, thromboses, perianal lesions, arthritis, uveitis, iritis, or cutaneous lesions (Braverman, 2003, Barba et al., 2002).

In a healthy individual, immune cells of the gut mucosa remain largely inactive towards the 1014 bacteria that compose the microflora. This tolerance to most bacterial strains is attributed to the prominent presence of regulatory immune cells that may be triggered by the commensal microflora and whose functions are antagonistic to inflammatory pathways triggered by small, transient populations of pathogenic bacteria.

For an illustration of immune response pathways in the gut mucosa, please look to Fig. 1. The inflammatory pathway portrayed is currently believed to occur as follows: Inflammation is initiated when resting antigen presenting cells, dendritic cells and macrophages, endocytose bacterial antigen at the initial site of infection, the lumen. In the lamina propria (LP), these cells then differentiate to inflammatory or effector phenotypes, termed M1 macrophages (M1) and effector dendritic cells (De) secreting inflammatory mediators including factors that aid infiltration of additional resting macrophage and dendritic cell precursors (monocytes) as well as T-cells into the LP. De and M1 present antigen to resting T-cells while secreting cytokines IL-12, IFN-γ, TNF-α, and IL-23 inducing their differentiation to pro-inflammatory T-helper cells (Th), specifically Th1 or Th17 phenotypes, that also secrete inflammatory mediators (Iwasaki, 2007, Gordon and Taylor, 2005). Antigen presenting cells may also migrate away from the infection site to the lymphoid tissue where they contact and stimulate a larger concentration of T-cells that will, in turn, relocate to the infection site in the lamina propria. There, Th1 and Th17 act synergistically with M1 and De to recruit more monocytes and promote their differentiation to the pro-inflammatory M1 and De phenotypes closing a positive feedback loop.

Immunopathogenesis results from secretion of toxic peroxide anions, proteases, and oxygen/nitrogen radicals by M1 and Th1-activated cells that kill the invading bacteria, but also cause indiscriminate tissue damage. In sterile organ systems, the inflammatory process generally ceases once the antigen population is eliminated and immune cells are no longer stimulated directly. However, in the gut, inflammation induced by bacterial microflora presents a scenario where the antigen population cannot be eliminated allowing the collateral cost of immunopathogenesis to mount and become more harmful to the host than the invading bacteria itself. Compounding the problem, inflammation-induced damage to the epithelial barrier between the lumen and lamina propria allows increased permeability and infiltration of bacteria into the lamina propria, thereby allowing heightened macrophage and dendritic cell stimulation completing another positive feedback loop that magnifies the inflammatory responses during IBD (Fig. 1).

In healthy individuals, to avoid this occurrence, the gut mucosa contains various regulatory factors such as M2 macrophages (M2), tolerogenic dendritic cells (Dt), and T-regulatory cells that are analogous to, and act antagonistically with, their inflammatory counter parts M1, De, and Th1/Th17. In the regulatory pathway, binding of ligands recognized as self, including commensal bacteria, to specific surface receptors of resting macrophages and dendritic cells induce their differentiation to M2 and Dt as opposed to M1 and De. One such receptor is the peroxisome proliferator-activated receptor, PPARγ, expressed in T-cells, dendritic cells, macrophages, and epithelial cells (Spiegelman, 1998, Mansen et al., 1996). This process is aided by the presence of anti-inflammatory cytokines IL-10 and TGF-β that inhibit pro-inflammatory cytokine secretion and down-regulation of co-stimulatory molecule expression (Asseman et al., 1999). The net result is that, upon antigen presentation by M2 and Dt, resting T-cells differentiated to a T-regulatory phenotypes. These are called induced T-regulatory cells (Ti) because their resting precursors have the ability to become Th1 upon stimulation by IFNγ+IL12 secreting M1 and De. In contrast, natural T-regulatory cells (Tr) are T-cells that are pre-destined to be regulatory cells independent of the cytokine environment. Both Ti and Tr secrete IL-10 and TGF-β promoting further M2 and Dt creation. In addition, Tr has been shown to bind effector dendritic cells with high affinity and inhibit their stimulation of resting T-cells to inflammatory phenotypes (Onishi et al., 2008).

In the current biological model of gut homeostasis commensal bacteria-mediated stimulation is largely responsible for upholding the basal population of regulatory factors that inhibit the inflammatory responses of their neighboring cells (Fig. 1). This normally allows the presence of a small population of inflammatory immune cells in response to the occasional invasion of pathogenic bacteria while the system remains inactive towards non-pathogenic strains in the microflora that maintain gut function. In abnormal cases, such as IBD, this low-level inflammatory response is able to mount, from an initially small population, to a much larger population able to override the suppressive activity of its regulatory antagonists. An area of key interest to IBD intervention is identification of the specific interactions of the inflammatory pathway that allow this cascade effect to take hold and subsequent immunopathogenesis to proceed.

Many of the mentioned interactions involved in inflammatory-regulatory crosstalk have been identified in vitro. It is yet to be identified which of these in vitro observed mechanisms lie behind the immunopathogenic cell dynamics observed in vivo during inflammation. For example, IBD recovery is associated with increased levels of T-regulatory cells in animal models (Powrie et al., 1993, Hontecillas and Bassaganya-Riera, 2007). Is this due to Tr-specific activity, such as the direct disruption of De-mediated T-cell stimulation, or its role as one of many IL-10 secreting cells, which could have numerous downstream effects?

There is still no cure for IBD and the only available treatments include those that universally weaken mucosal immunity leaving the patient vulnerable to opportunistic pathogens (Bassaganya-Riera et al., 2004). Identifying the specific regulatory functions that mediate the chronic inflammatory response would provide new strategies for more sophisticated treatment options.

Towards this goal we have developed a system of 29 ordinary differential equations describing the movement, interaction, and activation of inflammatory regulatory macrophages, T-cells, and dendritic cells in the presence of bacteria and cytokines in the lumen, lamina propria, and lymphoid tissue regions of gut mucosa. In silico, we induced chronic inflammation by allowing resting macrophages and dendritic cells to differentiate to inflammatory phenotypes upon contact with bacteria of the microflora. We then traced dynamics of inflammation markers back to specific interactions identifying those that override regulatory factors and sustain an immunopathogenic inflammatory response.

Section snippets

Mathematical model

Our model describes population dynamics of immune cells and epithelial cells as they interact, flow, and differentiate over time in response to dynamic populations of cytokines and bacteria (Fig. 2). The populations are further compartmentalized by three locations between which the cells may migrate: (i) the lumen, where bacteria reside, which is denoted by the superscript ‘L’, (ii) the lamina propria, more generally termed the effector site of the immune response, denoted by the superscript

Impairment of antigen presenting cell tolerance pathways causes IBD

Commensal bacteria should not induce inflammatory phenotypes in dendritic cells or macrophages, De or M1, in a healthy individual (Strober et al., 2002). For this reason, in the healthy model we set the rate of this occurrence, νBc, to 0 causing all immature dendritic cells and resting macrophages to enter the tolerogenic dendritic cell and M2 macrophage pools upon stimulation by bacteria of the microflora, assumed to be commensal. To represent a dysfunctional regulatory pathway or a

Conclusions

Our objective is to understand the critical interactions between the two competing pathways, inflammation and tolerance, that uphold gut homeostasis in healthy individuals. We focus on those mechanisms of inflammatory and regulatory pathway crosstalk that mediate IBD-like chronic inflammation. Though the underlying cell interactions have been characterized in vitro, their net effects in the context of complex immunological networks of dynamic populations is still unknown. In this study we took

Acknowledgments

We thank our external collaborators and members of the Network Dynamics and Simulation Science Laboratory (NDSSL) for their suggestions and comments. This work has been supported by NIH-NIGMS MIDAS Project 5 U01 GM070694-05 and NIH MIDAS Project 2U01GM070694-7.

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