Both Ligand- and Cell-Specific Parameters Control Ligand Agonism in a Kinetic Model of G Protein–Coupled Receptor Signaling

G protein–coupled receptors (GPCRs) exist in multiple dynamic states (e.g., ligand-bound, inactive, G protein–coupled) that influence G protein activation and ultimately response generation. In quantitative models of GPCR signaling that incorporate these varied states, parameter values are often uncharacterized or varied over large ranges, making identification of important parameters and signaling outcomes difficult to intuit. Here we identify the ligand- and cell-specific parameters that are important determinants of cell-response behavior in a dynamic model of GPCR signaling using parameter variation and sensitivity analysis. The character of response (i.e., positive/neutral/inverse agonism) is, not surprisingly, significantly influenced by a ligand's ability to bias the receptor into an active conformation. We also find that several cell-specific parameters, including the ratio of active to inactive receptor species, the rate constant for G protein activation, and expression levels of receptors and G proteins also dramatically influence agonism. Expressing either receptor or G protein in numbers several fold above or below endogenous levels may result in system behavior inconsistent with that measured in endogenous systems. Finally, small variations in cell-specific parameters identified by sensitivity analysis as significant determinants of response behavior are found to change ligand-induced responses from positive to negative, a phenomenon termed protean agonism. Our findings offer an explanation for protean agonism reported in β2-adrenergic and α2A-adrenergic receptor systems

Lipid Raft-Mediated Regulation of G-Protein Coupled Receptor Signaling by Ligands which Influence Receptor Dimerization: A Computational Study

G-protein coupled receptors (GPCRs) are the largest family of cell surface receptors; they activate heterotrimeric G-proteins in response to ligand stimulation. Although many GPCRs have been shown to form homo- and/or heterodimers on the cell membrane, the purpose of this dimerization is not known. Recent research has shown that receptor dimerization may have a role in organization of receptors on the cell surface. In addition, microdomains on the cell membrane termed lipid rafts have been shown to play a role in GPCR localization. Using a combination of stochastic (Monte Carlo) and deterministic modeling, we propose a novel mechanism for lipid raft partitioning of GPCRs based on reversible dimerization of receptors and then demonstrate that such localization can affect GPCR signaling. Modeling results are consistent with a variety of experimental data indicating that lipid rafts have a role in amplification or attenuation of G-protein signaling. Thus our work suggests a new mechanism by which dimerization-inducing or inhibiting characteristics of ligands can influence GPCR signaling by controlling receptor organization on the cell membrane

A multifaceted approach to modeling the immune response in tuberculosis

Tuberculosis (TB) is a deadly infectious disease caused by Mycobacterium tuberculosis (Mtb). No available vaccine is reliable and, although treatment exists, approximately 2 million people still die each year. The hallmark of TB infection is the granuloma, a self‐organizing structure of immune cells forming in the lung and lymph nodes in response to bacterial invasion. Protective immune mechanisms play a role in granuloma formation and maintenance; these act over different time/length scales (e.g., molecular, cellular, and tissue scales). The significance of specific immune factors in determining disease outcome is still poorly understood, despite incredible efforts to establish several animal systems to track infection progression and granuloma formation. Mathematical and computational modeling approaches have recently been applied to address open questions regarding host–pathogen interaction dynamics, including the immune response to Mtb infection and TB granuloma formation. This provides a unique opportunity to identify factors that are crucial to a successful outcome of infection in humans. These modeling tools not only offer an additional avenue for exploring immune dynamics at multiple biological scales but also complement and extend knowledge gained via experimental tools. We review recent modeling efforts in capturing the immune response to Mtb, emphasizing the importance of a multiorgan and multiscale approach that has tuneable resolution. Together with experimentation, systems biology has begun to unravel key factors driving granuloma formation and protective immune response in TB. WIREs Syst Biol Med 2011 3 479–489 DOI: 10.1002/wsbm.131 For further resources related to this article, please visit the WIREs websitePeer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/86857/1/131_ftp.pd

Quantitative inference of cellular parameters from microfluidic cell culture systems

Microfluidic cell culture systems offer a convenient way to measure cell biophysical parameters in conditions close to the physiological environment. We demonstrate the application of a mathematical model describing the spatial distribution of nutrient and growth factor concentrations in inferring cellular oxygen uptake rates from experimental measurements. We use experimental measurements of oxygen concentrations in a poly(dimethylsiloxane) (PDMS) microreactor culturing human hepatocellular liver carcinoma cells (HepG2) to infer quantitative information on cellular oxygen uptake rates. We use a novel microchannel design to avoid the parameter correlation problem associated with simultaneous cellular uptake and diffusion of oxygen through the PDMS surface. We find that the cellular uptake of oxygen is dependent on the cell density and can be modeled using a logistic term in the Michaelis–Menten equation. Our results are significant not only for the development of novel assays to quantitatively infer cell response to stimuli, but also for the development, design, and optimization of novel in vitro systems for drug discovery and tissue engineering. Biotechnol. Bioeng. 2009;103: 966–974. © 2009 Wiley Periodicals, Inc.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/63052/1/22334_ftp.pd

In silico evaluation and exploration of antibiotic tuberculosis treatment regimens

Abstract Background Improvement in tuberculosis treatment regimens requires selection of antibiotics and dosing schedules from a large design space of possibilities. Incomplete knowledge of antibiotic and host immune dynamics in tuberculosis granulomas impacts clinical trial design and success, and variations among clinical trials hamper side-by-side comparison of regimens. Our objective is to systematically evaluate the efficacy of isoniazid and rifampin regimens, and identify modifications to these antibiotics that improve treatment outcomes. Results We pair a spatio-temporal computational model of host immunity with pharmacokinetic and pharmacodynamic data on isoniazid and rifampin. The model is calibrated to plasma pharmacokinetic and granuloma bacterial load data from non-human primate models of tuberculosis and to tissue and granuloma measurements of isoniazid and rifampin in rabbit granulomas. We predict the efficacy of regimens containing different doses and frequencies of isoniazid and rifampin. We predict impacts of pharmacokinetic/pharmacodynamic modifications on antibiotic efficacy. We demonstrate that suboptimal antibiotic concentrations within granulomas lead to poor performance of intermittent regimens compared to daily regimens. Improvements from dose and frequency changes are limited by inherent antibiotic properties, and we propose that changes in intracellular accumulation ratios and antimicrobial activity would lead to the most significant improvements in treatment outcomes. Results suggest that an increased risk of drug resistance in fully intermittent as compared to daily regimens arises from higher bacterial population levels early during treatment. Conclusions Our systems pharmacology approach complements efforts to accelerate tuberculosis therapeutic development.http://deepblue.lib.umich.edu/bitstream/2027.42/116019/1/12918_2015_Article_221.pd

A Comprehensive Analysis of CXCL12 Isoforms in Breast Cancer1,2

AbstractCXCL12-CXCR4-CXCR7 signaling promotes tumor growth and metastasis in breast cancer. Alternative splicing of CXCL12 produces isoforms with distinct structural and biochemical properties, but little is known about isoform-specific differences in breast cancer subtypes and patient outcomes. We investigated global expression profiles of the six CXCL12 isoforms, CXCR4, and CXCR7 in The Cancer Genome Atlas breast cancer cohort using next-generation RNA sequencing in 948 breast cancer and benign samples and seven breast cancer cell lines. We compared expression levels with several clinical parameters, as well as metastasis, recurrence, and overall survival (OS). CXCL12-α, -β, and -γ are highly co-expressed, with low expression correlating with more aggressive subtypes, higher stage disease, and worse clinical outcomes. CXCL12-δ did not correlate with other isoforms but was prognostic for OS and showed the same trend for metastasis and recurrence-free survival. Effects of CXCL12-δ remained independently prognostic when taking into account expression of CXCL12, CXCR4, and CXCR7. These results were also reflected when comparing CXCL12-α, -β, and -γ in breast cancer cell lines. We summarized expression of all CXCL12 isoforms in an important chemokine signaling pathway in breast cancer in a large clinical cohort and common breast cancer cell lines, establishing differences among isoforms in multiple clinical, pathologic, and molecular subgroups. We identified for the first time the clinical importance of a previously unstudied isoform, CXCL12-δ

Neutrophil Dynamics Affect Mycobacterium tuberculosis Granuloma Outcomes and Dissemination

Neutrophil infiltration into tuberculous granulomas is often associated with higher bacteria loads and severe disease but the basis for this relationship is not well understood. To better elucidate the connection between neutrophils and pathology in primate systems, we paired data from experimental studies with our next generation computational model GranSim to identify neutrophil-related factors, including neutrophil recruitment, lifespan, and intracellular bacteria numbers, that drive granuloma-level outcomes. We predict mechanisms underlying spatial organization of neutrophils within granulomas and identify how neutrophils contribute to granuloma dissemination. We also performed virtual deletion and depletion of neutrophils within granulomas and found that neutrophils play a nuanced role in determining granuloma outcome, promoting uncontrolled bacterial growth in some and working to contain bacterial growth in others. Here, we present three key results: We show that neutrophils can facilitate local dissemination of granulomas and thereby enable the spread of infection. We suggest that neutrophils influence CFU burden during both innate and adaptive immune responses, implying that they may be targets for therapeutic interventions during later stages of infection. Further, through the use of uncertainty and sensitivity analyses, we predict which neutrophil processes drive granuloma severity and structure

Characterizing heterogeneous single-cell dose responses computationally and experimentally using threshold inhibition surfaces and dose-titration assays

Single cancer cells within a tumor exhibit variable levels of resistance to drugs, ultimately leading to treatment failures. While tumor heterogeneity is recognized as a major obstacle to cancer therapy, standard dose-response measurements for the potency of targeted kinase inhibitors aggregate populations of cells, obscuring intercellular variations in responses. In this work, we develop an analytical and experimental framework to quantify and model dose responses of individual cancer cells to drugs. We first explore the connection between population and single-cell dose responses using a computational model, revealing that multiple heterogeneous populations can yield nearly identical population dose responses. We demonstrate that a single-cell analysis method, which we term a threshold inhibition surface, can differentiate among these populations. To demonstrate the applicability of this method, we develop a dose-titration assay to measure dose responses in single cells. We apply this assay to breast cancer cells responding to phosphatidylinositol-3-kinase inhibition (PI3Ki), using clinically relevant PI3Kis on breast cancer cell lines expressing fluorescent biosensors for kinase activity. We demonstrate that MCF-7 breast cancer cells exhibit heterogeneous dose responses with some cells requiring over ten-fold higher concentrations than the population average to achieve inhibition. Our work reimagines dose-response relationships for cancer drugs in an emerging paradigm of single-cell tumor heterogeneity

Simple transporter trafficking model for amphetamine-induced dopamine efflux

Amphetamine and its derivatives are important drugs of abuse causing both short-term excitatory and long-term addictive effects. The short-term excitatory effects are linked to amphetamine's ability to maintain high levels of dopamine (DA) outside the cell both by inhibiting DA reuptake after synaptic transmission and by enhancing the efflux of DA from the dopaminergic cells. The molecular mechanisms by which amphetamine elicits the efflux of DA and similar monoamines are still unclear. Recent literature data suggest that trafficking of the monoamine transporters is a phenomenon that underlies observed changes in amphetamine-induced monoamine reuptake and efflux. We develop an ordinary differential equation model incorporating the diverse mechanistic details behind amphetamine-induced DA efflux and demonstrate its utility in describing our experimental data. We also demonstrate an experimental method to track the time-varying concentration of membrane-bound transporter molecules from the DA efflux data. The good fit between our model and the experimental data supports the hypothesis that amphetamine-induced transporter trafficking is necessary to produce extended efflux of DA. This model can explain the relative significance of different processes associated with DA efflux at different times and at different concentration ranges of amphetamine and DA. Synapse 61:500–514, 2007. © 2007 Wiley-Liss, Inc.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/56075/1/20390_ftp.pd

Externally Applied Cyclic Strain Regulates Localization of Focal Contact Components in Cultured Smooth Muscle Cells

Mechanical signals are critical regulators of cellular gene expression, yet little is understood of the mechanism whereby cells sense mechanical forces. In this study we have tested the hypothesis that mechanical strain applied to populations of cells via their adhesion substrate rapidly alters the cellular distribution of focal contact proteins. Focal contact-associated components (vinculin, α-actinin, paxillin) were assayed by immunofluorescence microscopy and quantitative western blotting. Application of a single step increase in strain in multiple experiments caused overall a small change in focal contact-associated vinculin. In contrast, cyclic strain induced a large and very reproducible increase in detergent-insoluble vinculin (52% relative to static) after just 1 min of strain. Insoluble paxillin was transiently enriched with a similar time course, whereas insoluble α-actinin did not change significantly in response to cyclic strain. Rhodamine-labeled chicken vinculin added to permeabilized cells preferentially localized to focal contacts in response to cyclic strain, but not a single step increase in strain. These findings establish that insoluble levels of focal contact components are altered rapidly following application of an appropriate number of mechanical perturbations, and suggest that at least one component of the mechanism does not involve soluble intermediates. © 2002 Biomedical Engineering Society.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/44000/1/10439_2004_Article_482739.pd