Modeling Systems-Level Regulation of Host Immune Responses

Thakar, Juilee; Pilione, Mylisa; Kirimanjeswara, Girish S.; Harvill, Eric T.; Albert, Réka

doi:10.1371/journal.pcbi.0030109

Cited by 120 publications

(108 citation statements)

References 62 publications

(84 reference statements)

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“…Network-based discrete dynamic modelling has been successfully applied in a great variety of biological systems (reviewed in [89]–[92]). These models enabled the understanding of the systems and generated insightful predictions that were subsequently validated experimentally; recent examples include [24], [93]–[97].…”

Section: Discussionmentioning

confidence: 99%

Multi-level Modeling of Light-Induced Stomatal Opening Offers New Insights into Its Regulation by Drought

et al. 2014

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Plant guard cells gate CO2 uptake and transpirational water loss through stomatal pores. As a result of decades of experimental investigation, there is an abundance of information on the involvement of specific proteins and secondary messengers in the regulation of stomatal movements and on the pairwise relationships between guard cell components. We constructed a multi-level dynamic model of guard cell signal transduction during light-induced stomatal opening and of the effect of the plant hormone abscisic acid (ABA) on this process. The model integrates into a coherent network the direct and indirect biological evidence regarding the regulation of seventy components implicated in stomatal opening. Analysis of this signal transduction network identified robust cross-talk between blue light and ABA, in which [Ca2+]c plays a key role, and indicated an absence of cross-talk between red light and ABA. The dynamic model captured more than 1031 distinct states for the system and yielded outcomes that were in qualitative agreement with a wide variety of previous experimental results. We obtained novel model predictions by simulating single component knockout phenotypes. We found that under white light or blue light, over 60%, and under red light, over 90% of all simulated knockouts had similar opening responses as wild type, showing that the system is robust against single node loss. The model revealed an open question concerning the effect of ABA on red light-induced stomatal opening. We experimentally showed that ABA is able to inhibit red light-induced stomatal opening, and our model offers possible hypotheses for the underlying mechanism, which point to potential future experiments. Our modelling methodology combines simplicity and flexibility with dynamic richness, making it well suited for a wide class of biological regulatory systems.

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Section: Discussionmentioning

confidence: 99%

Multi-level Modeling of Light-Induced Stomatal Opening Offers New Insights into Its Regulation by Drought

et al. 2014

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“…Boolean Network Analysis of Cytokine Secretion-Boolean network analysis can facilitate the understanding of combinatorial interactions (14,19,20). We developed a Boolean network model of these interactions in an effort to simplify interpretation of these data.…”

Section: Differential Regulation Of Nfat and Cytokine Secretion By Itmentioning

confidence: 99%

Absence of Tec Family Kinases Interleukin-2 Inducible T cell Kinase (Itk) and Bruton's Tyrosine Kinase (Btk) Severely Impairs FcϵRI-dependent Mast Cell Responses

Iyer

Morales

Huang

et al. 2011

Journal of Biological Chemistry

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Here we investigate the role of Tec kinases, Itk, and Btk as modulators of these processes. Itk is activated in mast cells upon Fc⑀RI-mediated signaling and Itk Ϫ/Ϫ mice have been reported to display decreased mast cell degranulation and histamine release in vivo (2, 4). However, our analysis of Itk-null mast cells revealed that the absence of Itk does not intrinsically affect mast cell degranulation either in vitro or in vivo (5). Although Itk is critical for TCR-mediated induction of intracellular Ca 2ϩ mobilization and Erk activation, Itk is not required for intracellular calcium signaling in response to Fc⑀RI-mediated signaling in mast cells, and Itkdeficient mast cells secrete elevated cytokines upon activation(5). Collectively, these data strongly suggests that Itk has cell type-specific functions.In mast cells, Btk is activated by the Fc⑀RI, c-Kit, and IL-3 receptors (6 -8). Its function has been well studied in B cells where it is activated downstream of the BCR (9, 10). Loss of Btk function in humans causes X-linked agammaglobulinemia (XLA), a condition where patients do not have sufficient immunoglobulins, with a milder phenotype observed in Btk-deficient mice (11,12). Mast cell development appears normal in the absence of Btk, both in vivo and in vitro. However, more bone marrow-derived mast cells (BMMCs) cells are produced from Btk-deficient mice in response to IL-3 (7). Btk Ϫ/Ϫ BMMCs also exhibit mild to moderate impairment of early and late Fc⑀RI-mediated responses such as degranulation, histamine release, * This work was supported, in whole or in part, by National Institutes of Health Grants AI051626 and AI065566 (to A. A.), and AI051626-S1 (to A. A.) (for J. L. M. BMMCs, bone marrow-derived mast cells; Bmx, bone marrow kinase on X-chromosome; Btk, Bruton's tyrosine kinase; Itk, interleukin-2 inducible T cell kinase; SAPK/JNK, stress-activated protein kinase/c-Jun N-terminal kinase; NFATc1, nuclear factor of activated T-cells cytoplasmic 1; Rlk, resting lymphocyte kinase; Syk, spleen tyrosine kinase; Tec, tyrosine kinase expressed in hepatocellular carcinoma; Txk, T and X cell-expressed kinase; XLA, X-linked agammaglobulinemia.

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“…Given the scarcity of kinetic and quantitative characterization of the processes involved in the interaction network (figure 1), we employed a hybrid method that provides a bridge between discrete and continuous approaches. This method is especially suited to the problem because the model in Thakar et al (2007) indicates that the decay and/or desensitization of immune components is crucial for their dynamics. The hybrid method allows us to describe node concentrations and activities by using coarse-grained parameters instead of molecular-level kinetic or binding parameters, which are unknown.…”

Section: Development Of the Dynamic Modelmentioning

confidence: 99%

Constraint-based network model of pathogen–immune system interactions

Thakar

Saadatpour-Moghaddam

Harvill

et al. 2008

J. R. Soc. Interface.

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Pathogenic bacteria such as Bordetella bronchiseptica modulate host immune responses to enable their establishment and persistence; however, the immune response is generally successful in clearing these bacteria. Here, we model the dynamic outcome of the interplay between host immune components and B. bronchiseptica virulence factors. The model extends our previously published interaction network of B. bronchiseptica and includes the existing experimental information on the relative timing of IL10 and IFNg activation in the form of qualitative inequalities. The current model improves the previous one in two directions: (i) by augmenting the network with new nodes with specific function in T helper cell differentiation and effector mechanisms and (ii) by using a dynamic approach that allows us to quantify node states and mechanisms revealed to be important from our previous model. The model makes predictions about the time scales of each process, the activity thresholds of each node and novel regulatory interactions. For example, the model predicts that the activity threshold of IL4 is higher than that of IL12 and that pro-inflammatory cytokines regulate the activity of Th2 cells. Some of these predictions are supported by the literature, and many can serve as targets of future experiments.

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Modeling Systems-Level Regulation of Host Immune Responses

Cited by 120 publications

References 62 publications

Multi-level Modeling of Light-Induced Stomatal Opening Offers New Insights into Its Regulation by Drought

Multi-level Modeling of Light-Induced Stomatal Opening Offers New Insights into Its Regulation by Drought

Absence of Tec Family Kinases Interleukin-2 Inducible T cell Kinase (Itk) and Bruton's Tyrosine Kinase (Btk) Severely Impairs FcϵRI-dependent Mast Cell Responses

Constraint-based network model of pathogen–immune system interactions

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