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NF-κB Signaling Dynamics Play a Key Role in Infection Control in Tuberculosis.

Fallahi-Sichani M, Kirschner DE, Linderman JJ - Front Physiol (2012)

Bottom Line: The NF-κB signaling pathway is central to the body's response to many pathogens.We build a multi-scale model of the immune response to the pathogen Mycobacterium tuberculosis (Mtb) to explore the impact of NF-κB dynamics occurring across molecular, cellular, and tissue scales in the lung.We show how the stability of mRNA transcripts corresponding to NF-κB-mediated responses significantly controls bacterial load in a granuloma, inflammation level in tissue, and granuloma size.

View Article: PubMed Central - PubMed

Affiliation: Department of Chemical Engineering, University of Michigan Ann Arbor, MI, USA.

ABSTRACT
The NF-κB signaling pathway is central to the body's response to many pathogens. Mathematical models based on cell culture experiments have identified important molecular mechanisms controlling the dynamics of NF-κB signaling, but the dynamics of this pathway have never been studied in the context of an infection in a host. Here, we incorporate these dynamics into a virtual infection setting. We build a multi-scale model of the immune response to the pathogen Mycobacterium tuberculosis (Mtb) to explore the impact of NF-κB dynamics occurring across molecular, cellular, and tissue scales in the lung. NF-κB signaling is triggered via tumor necrosis factor-α (TNF) binding to receptors on macrophages; TNF has been shown to play a key role in infection dynamics in humans and multiple animal systems. Using our multi-scale model, we predict the impact of TNF-induced NF-κB-mediated responses on the outcome of infection at the level of a granuloma, an aggregate of immune cells and bacteria that forms in response to infection and is key to containment of infection and clinical latency. We show how the stability of mRNA transcripts corresponding to NF-κB-mediated responses significantly controls bacterial load in a granuloma, inflammation level in tissue, and granuloma size. Because we incorporate intracellular signaling pathways explicitly, our analysis also elucidates NF-κB-associated signaling molecules and processes that may be new targets for infection control.

No MeSH data available.


Related in: MedlinePlus

The timing of NF-κB-induced macrophage activation is critical to control of inflammation. (A) Varying the chemokine mRNA half-life [t1/2(CHEM): 12 min, 1 h, and 3 h, respectively] and the chemokine secretion rate (e3chem: 7.65 × 10−5 s−1, 1.39 × 10−5 s−1, 4.52 × 10−6 s−1, respectively) by an individual macrophage simultaneously leads to secretion of the same average number of chemokine molecules, but with distinct temporal patterns of chemokine secretion. Simulated results are produced using the single-cell level NF-κB signaling dynamics model for continuous stimulation of a cell by 1 ng/ml TNF, with parameters and equations as described in Tables A3, A5, and A6 in Appendix. A similar pattern of response can be observed when the effects of mRNA stability on the timing of other NF-κB-mediated responses (i.e., expression of ACT, IAP, and TNF) are studied (data not shown). (B,C) Simulation results for the effect of the timing of NF-κB-mediated responses, including macrophage activation [regulated by t1/2(ACT)], TNF expression [regulated by t1/2(TNF)], chemokine expression [regulated by t1/2(CHEM)], and inhibitor of apoptosis protein expression [regulated by t1/2(IAP)], on bacteria numbers (B), and on the activated fraction of macrophages (C) at 200 days post-infection. Small squares represent different values of t1/2(CHEM) vertically and different values of t1/2(TNF) horizontally. Large boxes represent different values of t1/2(ACT) vertically and different values of t1/2(IAP) horizontally. Four values of mRNA half-life were tested in simulations: 12 min, 30 min, 1 h, and 3 h. Simulation results were averaged over 10 repetitions.
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Figure 6: The timing of NF-κB-induced macrophage activation is critical to control of inflammation. (A) Varying the chemokine mRNA half-life [t1/2(CHEM): 12 min, 1 h, and 3 h, respectively] and the chemokine secretion rate (e3chem: 7.65 × 10−5 s−1, 1.39 × 10−5 s−1, 4.52 × 10−6 s−1, respectively) by an individual macrophage simultaneously leads to secretion of the same average number of chemokine molecules, but with distinct temporal patterns of chemokine secretion. Simulated results are produced using the single-cell level NF-κB signaling dynamics model for continuous stimulation of a cell by 1 ng/ml TNF, with parameters and equations as described in Tables A3, A5, and A6 in Appendix. A similar pattern of response can be observed when the effects of mRNA stability on the timing of other NF-κB-mediated responses (i.e., expression of ACT, IAP, and TNF) are studied (data not shown). (B,C) Simulation results for the effect of the timing of NF-κB-mediated responses, including macrophage activation [regulated by t1/2(ACT)], TNF expression [regulated by t1/2(TNF)], chemokine expression [regulated by t1/2(CHEM)], and inhibitor of apoptosis protein expression [regulated by t1/2(IAP)], on bacteria numbers (B), and on the activated fraction of macrophages (C) at 200 days post-infection. Small squares represent different values of t1/2(CHEM) vertically and different values of t1/2(TNF) horizontally. Large boxes represent different values of t1/2(ACT) vertically and different values of t1/2(IAP) horizontally. Four values of mRNA half-life were tested in simulations: 12 min, 30 min, 1 h, and 3 h. Simulation results were averaged over 10 repetitions.

Mentions: In the previous section, we showed that stability of mRNA transcripts associated with NF-κB-mediated inflammatory molecules significantly affects the immune response to Mtb. The stability of mRNA controls both the extent and the timing of NF-κB-mediated responses in individual cells (Tay et al., 2010). However, it is not clear whether it is mostly the extent of response, the timing of response, or both that influence granuloma outcomes. In other words, how important is the speed of each individual macrophage’s response to TNF signals in determining the overall function of a granuloma? To address this question, we analyzed the effect on granuloma outcomes of varying the stability of ACT, CHEM, TNF, and IAP mRNA transcripts while maintaining the average extent of these responses at their containment baseline levels (determined in the previous section). To maintain the average extent of each response as its corresponding mRNA stability is varied, we simultaneously vary another parameter associated with a process downstream of mRNA translation. Parameters varied to adjust the extent of the four NF-κB-mediated responses are: TNF secretion rate (e3TNF), chemokine secretion rate (e3chem), ACT concentration threshold for macrophage activation (τACT), macrophage activation rate constant (kACT), and apoptosis inhibition constant (kIAP). For example, we increase the chemokine mRNA half-life [t1/2(CHEM)] and decrease the chemokine secretion rate (e3chem) simultaneously to achieve the same average number of chemokine molecules secreted in tissue by an individual macrophage (Figure 6A).


NF-κB Signaling Dynamics Play a Key Role in Infection Control in Tuberculosis.

Fallahi-Sichani M, Kirschner DE, Linderman JJ - Front Physiol (2012)

The timing of NF-κB-induced macrophage activation is critical to control of inflammation. (A) Varying the chemokine mRNA half-life [t1/2(CHEM): 12 min, 1 h, and 3 h, respectively] and the chemokine secretion rate (e3chem: 7.65 × 10−5 s−1, 1.39 × 10−5 s−1, 4.52 × 10−6 s−1, respectively) by an individual macrophage simultaneously leads to secretion of the same average number of chemokine molecules, but with distinct temporal patterns of chemokine secretion. Simulated results are produced using the single-cell level NF-κB signaling dynamics model for continuous stimulation of a cell by 1 ng/ml TNF, with parameters and equations as described in Tables A3, A5, and A6 in Appendix. A similar pattern of response can be observed when the effects of mRNA stability on the timing of other NF-κB-mediated responses (i.e., expression of ACT, IAP, and TNF) are studied (data not shown). (B,C) Simulation results for the effect of the timing of NF-κB-mediated responses, including macrophage activation [regulated by t1/2(ACT)], TNF expression [regulated by t1/2(TNF)], chemokine expression [regulated by t1/2(CHEM)], and inhibitor of apoptosis protein expression [regulated by t1/2(IAP)], on bacteria numbers (B), and on the activated fraction of macrophages (C) at 200 days post-infection. Small squares represent different values of t1/2(CHEM) vertically and different values of t1/2(TNF) horizontally. Large boxes represent different values of t1/2(ACT) vertically and different values of t1/2(IAP) horizontally. Four values of mRNA half-life were tested in simulations: 12 min, 30 min, 1 h, and 3 h. Simulation results were averaged over 10 repetitions.
© Copyright Policy - open-access
Related In: Results  -  Collection

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Show All Figures
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Figure 6: The timing of NF-κB-induced macrophage activation is critical to control of inflammation. (A) Varying the chemokine mRNA half-life [t1/2(CHEM): 12 min, 1 h, and 3 h, respectively] and the chemokine secretion rate (e3chem: 7.65 × 10−5 s−1, 1.39 × 10−5 s−1, 4.52 × 10−6 s−1, respectively) by an individual macrophage simultaneously leads to secretion of the same average number of chemokine molecules, but with distinct temporal patterns of chemokine secretion. Simulated results are produced using the single-cell level NF-κB signaling dynamics model for continuous stimulation of a cell by 1 ng/ml TNF, with parameters and equations as described in Tables A3, A5, and A6 in Appendix. A similar pattern of response can be observed when the effects of mRNA stability on the timing of other NF-κB-mediated responses (i.e., expression of ACT, IAP, and TNF) are studied (data not shown). (B,C) Simulation results for the effect of the timing of NF-κB-mediated responses, including macrophage activation [regulated by t1/2(ACT)], TNF expression [regulated by t1/2(TNF)], chemokine expression [regulated by t1/2(CHEM)], and inhibitor of apoptosis protein expression [regulated by t1/2(IAP)], on bacteria numbers (B), and on the activated fraction of macrophages (C) at 200 days post-infection. Small squares represent different values of t1/2(CHEM) vertically and different values of t1/2(TNF) horizontally. Large boxes represent different values of t1/2(ACT) vertically and different values of t1/2(IAP) horizontally. Four values of mRNA half-life were tested in simulations: 12 min, 30 min, 1 h, and 3 h. Simulation results were averaged over 10 repetitions.
Mentions: In the previous section, we showed that stability of mRNA transcripts associated with NF-κB-mediated inflammatory molecules significantly affects the immune response to Mtb. The stability of mRNA controls both the extent and the timing of NF-κB-mediated responses in individual cells (Tay et al., 2010). However, it is not clear whether it is mostly the extent of response, the timing of response, or both that influence granuloma outcomes. In other words, how important is the speed of each individual macrophage’s response to TNF signals in determining the overall function of a granuloma? To address this question, we analyzed the effect on granuloma outcomes of varying the stability of ACT, CHEM, TNF, and IAP mRNA transcripts while maintaining the average extent of these responses at their containment baseline levels (determined in the previous section). To maintain the average extent of each response as its corresponding mRNA stability is varied, we simultaneously vary another parameter associated with a process downstream of mRNA translation. Parameters varied to adjust the extent of the four NF-κB-mediated responses are: TNF secretion rate (e3TNF), chemokine secretion rate (e3chem), ACT concentration threshold for macrophage activation (τACT), macrophage activation rate constant (kACT), and apoptosis inhibition constant (kIAP). For example, we increase the chemokine mRNA half-life [t1/2(CHEM)] and decrease the chemokine secretion rate (e3chem) simultaneously to achieve the same average number of chemokine molecules secreted in tissue by an individual macrophage (Figure 6A).

Bottom Line: The NF-κB signaling pathway is central to the body's response to many pathogens.We build a multi-scale model of the immune response to the pathogen Mycobacterium tuberculosis (Mtb) to explore the impact of NF-κB dynamics occurring across molecular, cellular, and tissue scales in the lung.We show how the stability of mRNA transcripts corresponding to NF-κB-mediated responses significantly controls bacterial load in a granuloma, inflammation level in tissue, and granuloma size.

View Article: PubMed Central - PubMed

Affiliation: Department of Chemical Engineering, University of Michigan Ann Arbor, MI, USA.

ABSTRACT
The NF-κB signaling pathway is central to the body's response to many pathogens. Mathematical models based on cell culture experiments have identified important molecular mechanisms controlling the dynamics of NF-κB signaling, but the dynamics of this pathway have never been studied in the context of an infection in a host. Here, we incorporate these dynamics into a virtual infection setting. We build a multi-scale model of the immune response to the pathogen Mycobacterium tuberculosis (Mtb) to explore the impact of NF-κB dynamics occurring across molecular, cellular, and tissue scales in the lung. NF-κB signaling is triggered via tumor necrosis factor-α (TNF) binding to receptors on macrophages; TNF has been shown to play a key role in infection dynamics in humans and multiple animal systems. Using our multi-scale model, we predict the impact of TNF-induced NF-κB-mediated responses on the outcome of infection at the level of a granuloma, an aggregate of immune cells and bacteria that forms in response to infection and is key to containment of infection and clinical latency. We show how the stability of mRNA transcripts corresponding to NF-κB-mediated responses significantly controls bacterial load in a granuloma, inflammation level in tissue, and granuloma size. Because we incorporate intracellular signaling pathways explicitly, our analysis also elucidates NF-κB-associated signaling molecules and processes that may be new targets for infection control.

No MeSH data available.


Related in: MedlinePlus