A Computational Model for Early Events in B Cell Antigen Receptor Signaling: Analysis of the Roles of Lyn and Fyn

Barua, Dipak; Hlavacek, William S.; Lipniacki, Tomasz

doi:10.4049/jimmunol.1102003

Cited by 52 publications

(70 citation statements)

References 82 publications

(127 reference statements)

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“…This assumption is a simplification, as the fraction of Lyn available to participate in signaling is regulated and can be expected to change during the response to an antigen stimulus. However, according to a recently developed model for B cell antigen receptor (BCR) signaling, which explicitly accounts for regulation of Lyn autoinhibition [34], the fraction of Lyn in the autoinhibited conformation is expected to remain significant during the response to an antigen stimulus that yields sustained phosphorylation of Syk. Thus, the assumption used here, inherited from the study of Faeder et al [29], seems adequate.…”

Section: Resultsmentioning

confidence: 99%

Single-Cell Measurements of IgE-Mediated FcεRI Signaling Using an Integrated Microfluidic Platform

Barua

Liu

et al. 2013

PLoS ONE

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Heterogeneity in responses of cells to a stimulus, such as a pathogen or allergen, can potentially play an important role in deciding the fate of the responding cell population and the overall systemic response. Measuring heterogeneous responses requires tools capable of interrogating individual cells. Cell signaling studies commonly do not have single-cell resolution because of the limitations of techniques used such as Westerns, ELISAs, mass spectrometry, and DNA microarrays. Microfluidics devices are increasingly being used to overcome these limitations. Here, we report on a microfluidic platform for cell signaling analysis that combines two orthogonal single-cell measurement technologies: on-chip flow cytometry and optical imaging. The device seamlessly integrates cell culture, stimulation, and preparation with downstream measurements permitting hands-free, automated analysis to minimize experimental variability. The platform was used to interrogate IgE receptor (FcεRI) signaling, which is responsible for triggering allergic reactions, in RBL-2H3 cells. Following on-chip crosslinking of IgE-FcεRI complexes by multivalent antigen, we monitored signaling events including protein phosphorylation, calcium mobilization and the release of inflammatory mediators. The results demonstrate the ability of our platform to produce quantitative measurements on a cell-by-cell basis from just a few hundred cells. Model-based analysis of the Syk phosphorylation data suggests that heterogeneity in Syk phosphorylation can be attributed to protein copy number variations, with the level of Syk phosphorylation being particularly sensitive to the copy number of Lyn.

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Section: Resultsmentioning

confidence: 99%

Single-Cell Measurements of IgE-Mediated FcεRI Signaling Using an Integrated Microfluidic Platform

Barua

Liu

et al. 2013

PLoS ONE

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“…A strong advantage of rule-based modeling, which has yet to be fully leveraged, is the ease with which these models can be annotated [38, 41, 42, 86, 96, 119], as there is often a one-to-one correspondence between the formal elements of a model and entries in public databases that collect information about biomolecules and their interactions. Thus, rule-based modeling could provide a foundation for building standard models for well-studied cellular regulatory networks of outstanding interest, such as those implicated in diseases.…”

Section: Discussionmentioning

confidence: 99%

Modeling for (physical) biologists: an introduction to the rule-based approach

et al. 2015

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Models that capture the chemical kinetics of cellular regulatory networks can be specified in terms of rules for biomolecular interactions. A rule defines a generalized reaction, meaning a reaction that permits multiple reactants, each capable of participating in a characteristic transformation and each possessing certain, specified properties, which may be local, such as the state of a particular site or domain of a protein. In other words, a rule defines a transformation and the properties that reactants must possess to participate in the transformation. A rule also provides a rate law. A rule-based approach to modeling enables consideration of mechanistic details at the level of functional sites of biomolecules and provides a facile and visual means for constructing computational models, which can be analyzed to study how system-level behaviors emerge from component interactions.

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“…We constructed a detailed kinetic model of the BCR signaling network parameterized by published signaling responses and protein concentrations. Mathematical models of proximal BCR signaling and downstream transcriptional network have been reported(8–10). But to our knowledge, this is the first kinetic model to reconstruct the entire core BCR signaling network in silico .…”

Section: Introductionmentioning

confidence: 99%

Effective Combination Therapies for B-cell Lymphoma Predicted by a Virtual Disease Model

Goldstein

Jiang

et al. 2017

Cancer Research

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The complexity of cancer signaling networks limits the efficacy of most single agent treatments and brings about challenges in identifying effective combinatorial therapies. In this study, we used chronic active B cell receptor (BCR) signaling in diffuse large B cell lymphoma (DLBCL) as a model system to establish a computational framework to optimize combinatorial therapy in silico. We constructed a detailed kinetic model of the BCR signaling network, which captured the known complex crosstalk between the NFκB, ERK and AKT pathways and multiple feedback loops. Combining this signaling model with a data-derived tumor growth model, we predicted viability responses of many single drug and drug combinations in agreement with experimental data. Under this framework, we exhaustively predicted and ranked the efficacy and synergism of all possible combinatorial inhibitions of eleven currently targetable kinases in the BCR signaling network. Ultimately, our work establishes a detailed kinetic model of the core BCR signaling network and provides the means to explore the large space of possible drug combinations. Major Findings Using chronic active B cell receptor (BCR) signaling in diffuse large B cell lymphoma (DLBCL) as a model system, we developed a kinetic-modeling based computational framework for predicting effective combination therapy in silico. By integrative modeling of signal transduction, drug kinetics and tumor growth, we were able to directly predict drug-induced cell viability responses at various dosages, which were in agreement with published cell line experimental data. We implemented computational screening methods that identified potent and synergistic combinations in silico and validated our independent predictions in vitro. Quick Guide to Equations and Assumptions A kinetic model was constructed for the BCR signaling network according to the following rules. For protein-protein binding interactions, we assumed that this type of reaction were under equilibrium and solved the steady-state level of protein complex analytically in the model, false[ AB false] = 1 ( 1 + K ( [ T A ] + [ T B ] ) ) - false( 1 + K false( false[ T A false] + false[ T B false] false) false) 2 - 4 K 2 [ T A ] [ T B ] 2 K where [TA] and [TB] stand for the total concentration of protein species A and B respectively, [AB] represents the concentration of the protein complex, K is the inverse of the dissociation constant Kd. For kinase catalyzed reactions, we adopted the classic Michaelis-Menten kinetics, j 1 d P d t = 1 k cat [ E ] [ S ] K m + [ S ] where 1dPdt is the rate of catalytic product formation, kcat is the turnover rate, Km is the Michaelis-Menten constant, [E] and [S] are concentration of enzyme and substrate respectively. Each interaction in the BCR signaling network was depicted by corresponding terms according to above rules. The full kinetic model consists of 28 state...

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A Computational Model for Early Events in B Cell Antigen Receptor Signaling: Analysis of the Roles of Lyn and Fyn

Cited by 52 publications

References 82 publications

Single-Cell Measurements of IgE-Mediated FcεRI Signaling Using an Integrated Microfluidic Platform

Single-Cell Measurements of IgE-Mediated FcεRI Signaling Using an Integrated Microfluidic Platform

Modeling for (physical) biologists: an introduction to the rule-based approach

Effective Combination Therapies for B-cell Lymphoma Predicted by a Virtual Disease Model

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