Stimulus-specificity of NFkappaB signaling in macrophages.

Macrophages are ubiquitous tissue-resident cells that are essential for tissue homeostasis and function. Macrophages initiate, coordinate, and resolve the inflammatory response to pathogens, as well as coordinate tissue repair programs. The inflammatory program of macrophages is largely controlled by the inducible transcription factor NFκB. The temporal pattern of NFκB activity (signaling dynamics) regulates the immune response of macrophages to a diverse set of ligands. The extent to which NFκB signaling dynamics are stimulus-specific is not known. Furthermore, the functions of macrophages are regulated by the cytokine milieu. The effect that cytokine milieu may have on the stimulus specificity of NFκB signaling dynamics in primary macrophages has not been reported.In Chapter 2, I examined the specificity of the temporal pattern of NFκB nuclear translocation in response to diverse ligands associated with host, bacteria and viruses. Using macrophages isolated from knockin mice that express a fluorescent NFκB fusion protein at endogenous levels, I measured and tracked nuclear NFκB in individual cells over many hours using an automated image acquisition and analysis workflow. Using supervised machine learning, I quantified the stimulus specificity of NFκB signaling dynamics by measuring the performance of ligand classification using NFκB activity alone. Then, I tested the hypothesis that NFκB signaling dynamics are less stimulus-specific in macrophages from a mouse model of a systemic autoimmune disease (Sj�gren’s syndrome (S.S.)). My results indicated that oscillatory characteristics that define host-associated and virus-associated ligands are greatly diminished. Close examination of results showed that the sensitivity of classifying host-associated ligands is nearly abolished in SS macrophages. Furthermore, dose response studies of NFκB signaling dynamics revealed that the dose specificity of bacterium-associated ligands, but not host- and virus-associated ligands, are diminished in S.S. macrophages.In Chapter 3, I explored the effect of the cytokine milieu on the stimulus specificity of NFκB signaling dynamics. Using time-lapse, live cell microscopy, I examined the effect of IFNγ, IL-4, and TNF conditioning on stimulus specificity of host-, virus-, and bacterium associated ligands. Supervised machine learning revealed that NFκB response to virus-associated ligands and bacterium-associated ligands are less distinguishable in the context of IFNγ conditioning. In contrast, NFκB responses to host-associated and pathogen-associated ligands is more distinguishable in the context of IFNγ conditioning. Examination of NFκB dynamics in IFNγ conditioned macrophages revealed a loss of oscillatory character in response to virus-associated ligands but not to host-associated ligands. Since host-associated and virus-associated ligands induce predominantly oscillatory dynamics in na�ve macrophages, abrogation of oscillatory character in response to virus-associated but not to host-associated ligands in IFNγ conditioning makes the NFκB oscillations a distinguishing hallmark of host-associated ligands, at the expense of distinguishing virus-associated ligands from bacterium-associated ligands.The results showed that NFκB dynamics are more stimulus-specific in the context of IL-4 conditioning. Close examination of the NFκB dynamics showed IL-4 conditioning diminishes responsiveness of NFκB translocation to virus-associated ligands, while it preserves the responsiveness to bacterium-associated and host-associated ligands and differentially enhances peak prominence of NFκB to bacterium-associated ligands but not to host-associated ligands.Finally, interrogating the effects of TNF conditioning on stimulus specificity of NFκB dynamics revealed that bacterium-associated ligands are nearly indistinguishable in the absence of constitutive tonic TNF. Further, NFκB response to host-associated and bacterium-associated ligands are less distinguishable. In the absence of constitutive, tonic TNF, oscillatory characteristics of NFκB signaling are abolished, which means that host- and bacterium-associated ligands both induce non-oscillatory NFκB signaling, whereas NFκB responsiveness to virus-associated ligands is nearly abolished. Furthermore, the absence of constitutive, tonic TNF and feedforward, paracrine TNF abrogate the dose specificity of NFκB signaling in response to bacteria-associated and host-associated ligands, respectively. In conclusion, the work presented in this dissertation shows that the stimulus-specificity of NFκB signaling in macrophages is greatly diminished in a murine model of Sj�gren’s Syndrome, an autoimmune disorder and that cytokine milieu control the specificity of NFκB signaling in macrophages. These findings suggest that modulation of NFκB signaling in macrophages by IFNγ, IL-4, and TNF signaling pathways may yield fruitful pharmaceutical targets for treating autoimmune and infectious diseases

Signaling Crosstalk Mechanisms That May Fine-Tune Pathogen-Responsive NFκB

Precise control of inflammatory gene expression is critical for effective host defense without excessive tissue damage. The principal regulator of inflammatory gene expression is nuclear factor kappa B (NFκB), a transcription factor. Nuclear NFκB activity is controlled by IκB proteins, whose stimulus-responsive degradation and re-synthesis provide for transient or dynamic regulation. The IκB-NFκB signaling module receives input signals from a variety of pathogen sensors, such as toll-like receptors (TLRs). The molecular components and mechanisms of NFκB signaling are well-understood and have been reviewed elsewhere in detail. Here we review the molecular mechanisms that mediate cross-regulation of TLR-IκB-NFκB signal transduction by signaling pathways that do not activate NFκB themselves, such as interferon signaling pathways. We distinguish between potential regulatory crosstalk mechanisms that (i) occur proximal to TLRs and thus may have stimulus-specific effects, (ii) affect the core IκB-NFκB signaling module to modulate NFκB activation in response to several stimuli. We review some well-documented examples of molecular crosstalk mechanisms and indicate other potential mechanisms whose physiological roles require further study

An NFkB activity calculator to delineate signaling crosstalk: type I and II interferons enhance NFkB via distinct mechanisms

Nuclear factor kappa B (NFκB) is a transcription factor that controls inflammation and cell survival. In clinical histology, elevated NFκB activity is a hallmark of poor prognosis in inflammatory disease and cancer, and may be the result of a combination of diverse micro-environmental constituents. While previous quantitative studies of NFκB focused on its signaling dynamics in single cells, we address here how multiple stimuli may combine to control tissue level NFκB activity. We present a novel, simplified model of NFκB (SiMoN) that functions as an NFκB activity calculator. We demonstrate its utility by exploring how type I and type II interferons modulate NFκB activity in macrophages. Whereas, type I IFNs potentiate NFκB activity by inhibiting translation of IκBα and by elevating viral RNA sensor (RIG-I) expression, type II IFN amplifies NFκB activity by increasing the degradation of free IκB through transcriptional induction of proteasomal cap components (PA28). Both cross-regulatory mechanisms amplify NFκB activation in response to weaker (viral) inducers, while responses to stronger (bacterial or cytokine) inducers remain largely unaffected. Our work demonstrates how the NFκB calculator can reveal distinct mechanisms of crosstalk on NFκB activity in interferon-containing microenvironments

Stimulus-specificity of NFkappaB signaling in macrophages.

Macrophages are ubiquitous tissue-resident cells that are essential for tissue homeostasis and function. Macrophages initiate, coordinate, and resolve the inflammatory response to pathogens, as well as coordinate tissue repair programs. The inflammatory program of macrophages is largely controlled by the inducible transcription factor NFκB. The temporal pattern of NFκB activity (signaling dynamics) regulates the immune response of macrophages to a diverse set of ligands. The extent to which NFκB signaling dynamics are stimulus-specific is not known. Furthermore, the functions of macrophages are regulated by the cytokine milieu. The effect that cytokine milieu may have on the stimulus specificity of NFκB signaling dynamics in primary macrophages has not been reported.In Chapter 2, I examined the specificity of the temporal pattern of NFκB nuclear translocation in response to diverse ligands associated with host, bacteria and viruses. Using macrophages isolated from knockin mice that express a fluorescent NFκB fusion protein at endogenous levels, I measured and tracked nuclear NFκB in individual cells over many hours using an automated image acquisition and analysis workflow. Using supervised machine learning, I quantified the stimulus specificity of NFκB signaling dynamics by measuring the performance of ligand classification using NFκB activity alone. Then, I tested the hypothesis that NFκB signaling dynamics are less stimulus-specific in macrophages from a mouse model of a systemic autoimmune disease (Sj�gren’s syndrome (S.S.)). My results indicated that oscillatory characteristics that define host-associated and virus-associated ligands are greatly diminished. Close examination of results showed that the sensitivity of classifying host-associated ligands is nearly abolished in SS macrophages. Furthermore, dose response studies of NFκB signaling dynamics revealed that the dose specificity of bacterium-associated ligands, but not host- and virus-associated ligands, are diminished in S.S. macrophages.In Chapter 3, I explored the effect of the cytokine milieu on the stimulus specificity of NFκB signaling dynamics. Using time-lapse, live cell microscopy, I examined the effect of IFNγ, IL-4, and TNF conditioning on stimulus specificity of host-, virus-, and bacterium associated ligands. Supervised machine learning revealed that NFκB response to virus-associated ligands and bacterium-associated ligands are less distinguishable in the context of IFNγ conditioning. In contrast, NFκB responses to host-associated and pathogen-associated ligands is more distinguishable in the context of IFNγ conditioning. Examination of NFκB dynamics in IFNγ conditioned macrophages revealed a loss of oscillatory character in response to virus-associated ligands but not to host-associated ligands. Since host-associated and virus-associated ligands induce predominantly oscillatory dynamics in na�ve macrophages, abrogation of oscillatory character in response to virus-associated but not to host-associated ligands in IFNγ conditioning makes the NFκB oscillations a distinguishing hallmark of host-associated ligands, at the expense of distinguishing virus-associated ligands from bacterium-associated ligands.The results showed that NFκB dynamics are more stimulus-specific in the context of IL-4 conditioning. Close examination of the NFκB dynamics showed IL-4 conditioning diminishes responsiveness of NFκB translocation to virus-associated ligands, while it preserves the responsiveness to bacterium-associated and host-associated ligands and differentially enhances peak prominence of NFκB to bacterium-associated ligands but not to host-associated ligands.Finally, interrogating the effects of TNF conditioning on stimulus specificity of NFκB dynamics revealed that bacterium-associated ligands are nearly indistinguishable in the absence of constitutive tonic TNF. Further, NFκB response to host-associated and bacterium-associated ligands are less distinguishable. In the absence of constitutive, tonic TNF, oscillatory characteristics of NFκB signaling are abolished, which means that host- and bacterium-associated ligands both induce non-oscillatory NFκB signaling, whereas NFκB responsiveness to virus-associated ligands is nearly abolished. Furthermore, the absence of constitutive, tonic TNF and feedforward, paracrine TNF abrogate the dose specificity of NFκB signaling in response to bacteria-associated and host-associated ligands, respectively. In conclusion, the work presented in this dissertation shows that the stimulus-specificity of NFκB signaling in macrophages is greatly diminished in a murine model of Sj�gren’s Syndrome, an autoimmune disorder and that cytokine milieu control the specificity of NFκB signaling in macrophages. These findings suggest that modulation of NFκB signaling in macrophages by IFNγ, IL-4, and TNF signaling pathways may yield fruitful pharmaceutical targets for treating autoimmune and infectious diseases

Signaling Crosstalk Mechanisms That May Fine-Tune Pathogen-Responsive NFκB.

Precise control of inflammatory gene expression is critical for effective host defense without excessive tissue damage. The principal regulator of inflammatory gene expression is nuclear factor kappa B (NFκB), a transcription factor. Nuclear NFκB activity is controlled by IκB proteins, whose stimulus-responsive degradation and re-synthesis provide for transient or dynamic regulation. The IκB-NFκB signaling module receives input signals from a variety of pathogen sensors, such as toll-like receptors (TLRs). The molecular components and mechanisms of NFκB signaling are well-understood and have been reviewed elsewhere in detail. Here we review the molecular mechanisms that mediate cross-regulation of TLR-IκB-NFκB signal transduction by signaling pathways that do not activate NFκB themselves, such as interferon signaling pathways. We distinguish between potential regulatory crosstalk mechanisms that (i) occur proximal to TLRs and thus may have stimulus-specific effects, (ii) affect the core IκB-NFκB signaling module to modulate NFκB activation in response to several stimuli. We review some well-documented examples of molecular crosstalk mechanisms and indicate other potential mechanisms whose physiological roles require further study

Stimulus-response signaling dynamics characterize macrophage polarization states.

The functional state of cells is dependent on their microenvironmental context. Prior studies described how polarizing cytokines alter macrophage transcriptomes and epigenomes. Here, we characterized the functional responses of 6 differentially polarized macrophage populations by measuring the dynamics of transcription factor nuclear factor κB (NF-κB) in response to 8 stimuli. The resulting dataset of single-cell NF-κB trajectories was analyzed by three approaches: (1) machine learning on time-series data revealed losses of stimulus distinguishability with polarization, reflecting canalized effector functions. (2) Informative trajectory features driving stimulus distinguishability (signaling codons) were identified and used for mapping a cell state landscape that could then locate macrophages conditioned by an unrelated condition. (3) Kinetic parameters, inferred using a mechanistic NF-κB network model, provided an alternative mapping of cell states and correctly predicted biochemical findings. Together, this work demonstrates that a single analytes dynamic trajectories may distinguish the functional states of single cells and molecular network states underlying them. A record of this papers transparent peer review process is included in the supplemental information