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WIREs Syst Biol Med
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Topology, dynamics, and heterogeneity in immune signaling

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Development and function of the immune system depends on cells exchanging information between themselves and with their environment. This information is processed and integrated by complex signal transduction and gene regulatory networks with rich temporal dynamics. A growing body of evidence points to a combination of network topology and temporal dynamics as a fundamental link between stimulus and function. Recent findings also bring cellular variability and stochastic events to the forefront as additional determinants of cell population responses to immune cues. In this article, we review examples of how the trinity of network topology, temporal dynamics, and cellular variability together determine the immune function. In particular we focus on Nuclear Factor kappa‐B and T‐cell receptor signaling networks as they have proven fertile ground for studying how function arises from the combination of topology, dynamics, and variability in a context of great clinical importance. WIREs Syst Biol Med 2015, 7:285–300. doi: 10.1002/wsbm.1306 This article is categorized under: Biological Mechanisms > Cell Signaling Models of Systems Properties and Processes > Mechanistic Models Biological Mechanisms > Regulatory Biology
Dynamical pharmacology. (a) Drugs targeting different reactions within a negative feedback loop selectively affect the out‐of‐equilibrium (Orange) or steady state (Purple) phases of the signal. (b) Drugs that suppress (or enhance) different parts of a signal induce specific alterations in downstream activity (targets T1 and T2, responsive to the node depicted in blue) that may result in different genetic profiles and cellular responses. (c) Drugs with selectivity for specific ‘dynamical features’ can induce stimulus‐specific effects in the presence of stimuli that generate upstream signals with different dynamics. In the hypothetical scenario depicted, stimuli SA, SB, and SC, at the head of three pathways converging into a signaling hub (e.g., IKK‐NFκB), trigger signals with transient, sustained, and graded temporal profiles that elicit specific temporal dynamics at the level of the hub. Distinct hub dynamics activate specific subsets of downstream targets T1 (requires early signals), T2 (requiring early and low levels of sustained signals), and T3 (requiring high levels of sustained signals) for productive activation. (d) For the system in (c), perturbation P1 suppresses early signaling, eliminating the response to SA and SB, but not SC. Perturbation P2 attenuates late signaling thus selectively eliminating the response to SC. Perturbation P3 suppresses late signaling eliminating the response to SC and part (T2) of the response to SB.
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Positive and negative selection of T cells. ERK activation occurs on the cell membrane or on the Golgi for stimuli promoting negative (cell death) or positive selection (cell survival), respectively, resulting in ERK signals with different dynamics. Intense transient signals results in negative selection whereas more sustained ERK activity results in positive selection.
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T‐cell differentiation depends on the duration of the TCR signal. (a) Simplified network controlling T‐cell differentiation into regulatory (Treg) or helper (TH) cells. The IL2/SD25 branch promotes Foxp3 activation leading to differentiation into Treg whereas the mTOR branch inhibits it, leading to TH fate. (b) Brief TCR signals fail to sufficiently induce the inhibitory branch producing a Treg (IL2 Foxp3+) phenotype. (c) The inhibitory mTOR branch is potently activated by sustained TCR signals producing a TH (IL2+ Foxp3) phenotype.
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Kinetic proofreading depends on activation occurring through a series of reversible steps. Ligands with sufficiently long dwell times generate a signal that elicits a cellular functional response (top). Ligands with too short dwell times do not remain bound long enough to generate a response (middle). In T‐cell signaling, the kinetic proofreading process is likely linked with intracellular regulatory processes that include feedback loops (bottom).
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Temporal control of genetic programs. (a) Patterns of gene expression identified by Hao et al. Genes in type I can be induced by transient NFκB signals. Elevated levels of mRNA for genes of types II and III are reached in response to sustained NFκB signals. (b) NFκB signals with a strong early component (typical of TNF responses) cause physiological activation of a subset of genes. Sustained signaling is required to activate different subsets. Changes in the chromatin environment or insufficient early signal strength may prevent meaningful expression of early genes in response to a LPS‐like signal. (c) Temporal control of gene expression induces stimulus‐specific genetic responses because of stimulus‐specific signal dynamics.
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Topology and dynamics of the canonical NFκB signal transduction network. TNF binds to its cognate receptor causing recruitment and activation of various factors in the receptor proximal module resulting in activation of kinase IKK. IKK functions as part of an adaptive regulatory cycle comprising inactive (Ikki), active (Ikka), and refractory (ikkr) states. Active IKK phosphorylates IκBs causing its rapid degradation. Free NFκB translocates to the nucleus where it regulates expression of target genes, including negative regulators IκBα, IκBαϵ, and A20. The signal is modulated by these regulatory mechanisms as it propagates through the network.
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NFκB signaling mediates the cellular response to many environmental stimuli and cellular stress. (a) Nuclear accumulation of NFκB, a transcription factor, modulate the expression of genes involved in cell death, proliferation, differentiation, as well as activation of immune function such as the release of cytokines. NFκB also plays roles in lymphoid organ development and immune selection. (b) Typical bulk NFκB response to TNF (red) and LPS (blue) as measured by electrophoretic mobility shift assays (EMSA) in 3T3 murine cells. (c) Sketch of NFκB responses to TNF measured as nuclear accumulation in individual 3 T3 cells. Dephasing of secondary peaks produces average activity reminiscent of bulk measurements.
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Models of Systems Properties and Processes > Mechanistic Models
Biological Mechanisms > Regulatory Biology
Biological Mechanisms > Cell Signaling

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