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. 2010 May 6;6(5):e1000778.
doi: 10.1371/journal.pcbi.1000778.

Identification of key processes that control tumor necrosis factor availability in a tuberculosis granuloma

Affiliations

Identification of key processes that control tumor necrosis factor availability in a tuberculosis granuloma

Mohammad Fallahi-Sichani et al. PLoS Comput Biol. .

Abstract

Tuberculosis (TB) granulomas are organized collections of immune cells comprised of macrophages, lymphocytes and other cells that form in the lung as a result of immune response to Mycobacterium tuberculosis (Mtb) infection. Formation and maintenance of granulomas are essential for control of Mtb infection and are regulated in part by a pro-inflammatory cytokine, tumor necrosis factor-alpha (TNF). To characterize mechanisms that control TNF availability within a TB granuloma, we developed a multi-scale two compartment partial differential equation model that describes a granuloma as a collection of immune cells forming concentric layers and includes TNF/TNF receptor binding and trafficking processes. We used the results of sensitivity analysis as a tool to identify experiments to measure critical model parameters in an artificial experimental model of a TB granuloma induced in the lungs of mice following injection of mycobacterial antigen-coated beads. Using our model, we then demonstrated that the organization of immune cells within a TB granuloma as well as TNF/TNF receptor binding and intracellular trafficking are two important factors that control TNF availability and may spatially coordinate TNF-induced immunological functions within a granuloma. Further, we showed that the neutralization power of TNF-neutralizing drugs depends on their TNF binding characteristics, including TNF binding kinetics, ability to bind to membrane-bound TNF and TNF binding stoichiometry. To further elucidate the role of TNF in the process of granuloma development, our modeling and experimental findings on TNF-associated molecular scale aspects of the granuloma can be incorporated into larger scale models describing the immune response to TB infection. Ultimately, these modeling and experimental results can help identify new strategies for TB disease control/therapy.

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Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Figure 1
Figure 1. PPD antigen-bead pulmonary granuloma model.
(A) Schematic representation (rbead: radius of bead, rg: radius of granuloma) and (B) histological appearance of an artificial pulmonary granuloma induced in mouse 4 days after injection of PPD-coated beads , , (H&E staining; magnification: ×800).
Figure 2
Figure 2. Schematic representation of the multi-scale two-compartment model of PPD bead granuloma and TNF-associated reactions.
(A) Binding interactions and reactions controlling TNF/TNFR dynamics at the single-cell level, including synthesis of TNFR1, TNFR2 and mTNF, sTNF release to the extracellular space under the effect of TACE activity, reversible binding of sTNF to TNFR1 and TNFR2, sTNF degradation, internalization of free and sTNF-bound TNFR1 and TNFR2, degradation of internalized TNFR1 and TNFR2, recycling of internalized TNFR1 and TNFR2, shedding of sTNF-bound TNFR2 and release of sTNF from the shed sTNF/TNFR2 complex. (B) TNF neutralization-associated reactions, including reversible binding of drug to mTNF and sTNF, release of drug-bound TNF from the membrane to the extracellular space and drug degradation. (C) Two-compartment model of granuloma that includes a bead of radius rbead surrounded by the inner compartment populated by macrophages and DCs and the outer compartment composed of lymphocytes. Numbers in (A) and (B) represent model reactions as listed in Table 2.
Figure 3
Figure 3. Simulation results for the steady-state profile of sTNF-bound fraction of cell surface TNFR1 in a granuloma using seven different sample sets of parameter values within ranges specified in Table 3.
Arrow indicates radius of the bead (rbead). Parameter values for the particular curves shown are listed in Supplementary Table S2.
Figure 4
Figure 4. Cellular fractions in PPD bead granulomas at 2 and 4 days of granuloma formation in thirty CBA/J mice quantified by multi-color flow cytometry.
Results are expressed as the percentage of each cell type in the total population of granuloma cells. Error bars represent standard deviation from the mean.
Figure 5
Figure 5. Quantification of the rate of mTNF synthesis by each cell type.
Experimental data on the number of mTNF molecules on the surface of each cell type after addition of TAPI-1 were fitted to Equation 10 to estimate ksynth for that cell type. Displayed data represent TNF synthesis by day 4 granuloma cells for three hours in the presence of TAPI-1. Error bars indicate standard deviations. Values of R2 for curve fitting for mDCs, macrophages and pDCs are 0.97, 0.99 and 0.98, respectively.
Figure 6
Figure 6. Predictions of the two-compartment model for a PPD bead granuloma.
(A) The effects of receptor binding, intracellular trafficking of TNF and cellular organization within granuloma (represented by separation) on the steady state spatial distribution of free sTNF in a granuloma. (B) The effect of separation between different cell types in a granuloma on the spatial concentration of sTNF-bound cell surface TNFR1. Parameter values for the rate of mTNF synthesis (and similarly for TNFR densities) in each compartment were computed via Equations 6 and 7, using experimental data for day 4 granulomas presented in Figure 4 and Tables 7 and 8. Other parameter values are as listed in Table 3. The qualitative aspects of these plots are similar for day 2 granulomas.
Figure 7
Figure 7. Model predictions for the effect of TNF-neutralizing drugs with various properties on the availability of TNF within a granuloma.
(A) Class 1: the drug can only bind to sTNF with a binding ratio of 1∶1. (B) Class 2: the drug can bind to both mTNF and sTNF with a binding ratio of 1∶1. The star shows the location of a drug with TNF binding kinetics similar to etanercept. (C) Class 3: the drug can bind to both mTNF and sTNF with a binding ratio of 3∶1. The star shows the location of a drug with TNF binding kinetics similar to infliximab. (D) Model predictions for the effect of TNF/drug association rate constant on neutralization efficiency of drugs of different classes but identical affinities (Kd_Drug = koff_TNF/Drug/kon_TNF/Drug = 10−9 M). Model parameter values are the same as Figure 6. TNF neutralization-associated parameter values are as listed in Table 4.
Figure 8
Figure 8. Spatial coordination of the TNF-induced immunological functions in a classical granuloma composed of a core of macrophages and DCs surrounded by a ring of lymphocytes.
Great availability of TNF in the core of granuloma (together with TNF-induced TNFR2 activation) can turn on the TNFR1-dependent caspase-mediated apoptotic pathway that favors antigen cross-presentation as well as elimination of the pathogen inside the granuloma. Low level of TNF availability in the mantle of granuloma is sufficient to turn on the NF-κB signaling which favors cell survival and expression of pro-inflammatory genes but not the apoptotic pathway.

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