Models Of Cell Signaling Research Articles

IL7 receptor signaling in T cells: A mathematical modeling perspective.

Interleukin-7 (IL7) plays a nonredundant role in T cell survival and homeostasis, which is illustrated in the severe T cell lymphopenia of IL7-deficient mice, or demonstrated in animals or humans that lack expression of either the IL7Rα or γ c chain, the two subunits that constitute the functional IL7 receptor. Remarkably, IL7 is not expressed by T cells themselves, but produced in limited amounts by radio-resistant stromal cells. Thus, T cells need to constantly compete for IL7 to survive. How T cells maintain homeostasis and further maximize the size of the peripheral T cell pool in face of such competition are important questions that have fascinated both immunologists and mathematicians for a long time. Exceptionally, IL7 downregulates expression of its own receptor, so that IL7-signaled T cells do not consume extracellular IL7, and thus, the remaining extracellular IL7 can be shared among unsignaled T cells. Such an altruistic behavior of the IL7Rα chain is quite unique among members of the γ c cytokine receptor family. However, the consequences of this altruistic signaling behavior at the molecular, single cell and population levels are less well understood and require further investigation. In this regard, mathematical modeling of how a limited resource can be shared, while maintaining the clonal diversity of the T cell pool, can help decipher the molecular or cellular mechanisms that regulate T cell homeostasis. Thus, the current review aims to provide a mathematical modeling perspective of IL7-dependent T cell homeostasis at the molecular, cellular and population levels, in the context of recent advances in our understanding of the IL7 biology. This article is categorized under: Models of Systems Properties and Processes > Organ, Tissue, and Physiological Models Biological Mechanisms > Cell Signaling Models of Systems Properties and Processes > Mechanistic Models Analytical and Computational Methods > Computational Methods.

Integrating molecular networks with genetic variant interpretation for precision medicine.

More reliable and cheaper sequencing technologies have revealed the vast mutational landscapes characteristic of many phenotypes. The analysis of such genetic variants has led to successful identification of altered proteins underlying many Mendelian disorders. Nevertheless the simple one‐variant one‐phenotype model valid for many monogenic diseases does not capture the complexity of polygenic traits and disorders. Although experimental and computational approaches have improved detection of functionally deleterious variants and important interactions between gene products, the development of comprehensive models relating genotype and phenotypes remains a challenge in the field of genomic medicine. In this context, a new view of the pathologic state as significant perturbation of the network of interactions between biomolecules is crucial for the identification of biochemical pathways associated with complex phenotypes. Seminal studies in systems biology combined the analysis of genetic variation with protein–protein interaction networks to demonstrate that even as biological systems evolve to be robust to genetic variation, their topologies create disease vulnerabilities. More recent analyses model the impact of genetic variants as changes to the “wiring” of the interactome to better capture heterogeneity in genotype–phenotype relationships. These studies lay the foundation for using networks to predict variant effects at scale using machine‐learning or algorithmic approaches. A wealth of databases and resources for the annotation of genotype–phenotype relationships have been developed to support developments in this area. This overview describes how study of the molecular interactome has generated insights linking the organization of biological systems to disease mechanism, and how this information can enable precision medicine.This article is categorized under: Translational, Genomic, and Systems Medicine > Translational MedicineBiological Mechanisms > Cell SignalingModels of Systems Properties and Processes > Mechanistic ModelsAnalytical and Computational Methods > Computational Methods

Context-dependent regulation of receptor tyrosine kinases: Insights from systems biology approaches.

Receptor tyrosine kinases (RTKs) are cell membrane proteins that provide cells with the ability to sense proteins in their environments. Many RTKs are essential to development and organ growth. Derangement of RTKs-by mutation or by overexpression-is central to several developmental and adult disorders including cancer, short stature, and vascular pathologies. The mechanism of action of RTKs is complex and is regulated by contextual components, including the existence of multiple competing ligands and receptors in many families, the intracellular location of the RTK, the dynamic and cell-specific coexpression of other RTKs, and the commonality of downstream signaling pathways. This means that both the state of the cell and the microenvironment outside the cell play a role, which makes sense given the pivotal location of RTKs as the nexus linking the extracellular milieu to intracellular signaling and modification of cell behavior. In this review, we describe these different contextual components through the lens of systems biology, in which both computational modeling and experimental "omics" approaches have been used to better understand RTK networks. The complexity of these networks is such that using these systems biology approaches is necessary to get a handle on the mechanisms of pathology and the design of therapeutics targeting RTKs. In particular, we describe in detail three concrete examples (involving ErbB3, VEGFR2, and AXL) that illustrate how systems approaches can reveal key mechanistic and therapeutic insights. This article is categorized under: Biological Mechanisms > Cell Signaling Models of Systems Properties and Processes > Mechanistic Models Translational, Genomic, and Systems Medicine > Therapeutic Methods.

Automated Extension of Cell Signaling Models with Genetic Algorithm.

The number of published results in biology and medicine is growing at an exceeding rate, and thus, extracting relevant information for building useful models is becoming very laborious. Furthermore, with the newly published information, previously built models need to be extended and updated, and with the voluminous literature, it is necessary to automate the model extension process. In this work, we introduce a methodology for extending logical models of cell signaling networks using a Genetic Algorithm (GA). The proposed procedure is developed to optimally search for a subset of biological interactions that extend logical models while preserving their desired behavior. To evaluate the effectiveness of the proposed methodology, we randomly removed a subset of elements from an existing T cell differentiation model, and mixed them with randomly created interactions to mimic the output of literature reading. We then used the GA to search for the extensions that optimally reconstructed the model. The simulation results showed that the GA was able to find a set of extensions that preserved the desired behavior of the model with fewer elements than the original model. The results demonstrate that the GA is an efficient tool for model extension, and suggest that it can be used for model reduction as well.

Grip and slip of L1-CAM on adhesive substrates direct growth cone haptotaxis

Chemical cues presented on the adhesive substrate direct cell migration, a process termed haptotaxis. To migrate, cells must generate traction forces upon the substrate. However, how cells probe substrate-bound cues and generate directional forces for migration remains unclear. Here, we show that the cell adhesion molecule (CAM) L1-CAM is involved in laminin-induced haptotaxis of axonal growth cones. L1-CAM underwent grip and slip on the substrate. The ratio of the grip state was higher on laminin than on the control substrate polylysine; this was accompanied by an increase in the traction force upon laminin. Our data suggest that the directional force for laminin-induced growth cone haptotaxis is generated by the grip and slip of L1-CAM on the substrates, which occur asymmetrically under the growth cone. This mechanism is distinct from the conventional cell signaling models for directional cell migration. We further show that this mechanism is disrupted in a human patient with L1-CAM syndrome, suffering corpus callosum agenesis and corticospinal tract hypoplasia.

Models of cell signaling uncover molecular mechanisms of high-risk neuroblastoma and predict disease outcome

BackgroundDespite the progress in neuroblastoma therapies the mortality of high-risk patients is still high (40–50%) and the molecular basis of the disease remains poorly known. Recently, a mathematical model was used to demonstrate that the network regulating stress signaling by the c-Jun N-terminal kinase pathway played a crucial role in survival of patients with neuroblastoma irrespective of their MYCN amplification status. This demonstrates the enormous potential of computational models of biological modules for the discovery of underlying molecular mechanisms of diseases.ResultsSince signaling is known to be highly relevant in cancer, we have used a computational model of the whole cell signaling network to understand the molecular determinants of bad prognostic in neuroblastoma. Our model produced a comprehensive view of the molecular mechanisms of neuroblastoma tumorigenesis and progression.ConclusionWe have also shown how the activity of signaling circuits can be considered a reliable model-based prognostic biomarker.ReviewersThis article was reviewed by Tim Beissbarth, Wenzhong Xiao and Joanna Polanska. For the full reviews, please go to the Reviewers’ comments section.

Systems biology of cellular membranes: a convergence with biophysics.

Systems biology and systems medicine have played an important role in the last two decades in shaping our understanding of biological processes. While systems biology is synonymous with network maps and '-omics' approaches, it is not often associated with mechanical processes. Here, we make the case for considering the mechanical and geometrical aspects of biological membranes as a key step in pushing the frontiers of systems biology of cellular membranes forward. We begin by introducing the basic components of cellular membranes, and highlight their dynamical aspects. We then survey the functions of the plasma membrane and the endomembrane system in signaling, and discuss the role and origin of membrane curvature in these diverse cellular processes. We further give an overview of the experimental and modeling approaches to study membrane phenomena. We close with a perspective on the converging futures of systems biology and membrane biophysics, invoking the need to include physical variables such as location and geometry in the study of cellular membranes. WIREs Syst Biol Med 2017, 9:e1386. doi: 10.1002/wsbm.1386 For further resources related to this article, please visit the WIREs website.

PD33-02 PROSTATE CANCER AGGRESSIVENESS IS MEDIATED BY AKT AND NF-κB SIGNALING PATHWAYS: A SYSTEMS BIOLOGY APPROACH

You have accessJournal of UrologyProstate Cancer: Basic Research & Pathophysiology I1 Apr 2017PD33-02 PROSTATE CANCER AGGRESSIVENESS IS MEDIATED BY AKT AND NF-κB SIGNALING PATHWAYS: A SYSTEMS BIOLOGY APPROACH Eswar Shankar, Rajnee Kanwal, Aditi Goel, Xiaoping Yang, Sanjeev Shukla, Gregory MacLennan, Pingfu Fu, Jing Li, Anant Madabhushi, and Sanjay Gupta Eswar ShankarEswar Shankar More articles by this author , Rajnee KanwalRajnee Kanwal More articles by this author , Aditi GoelAditi Goel More articles by this author , Xiaoping YangXiaoping Yang More articles by this author , Sanjeev ShuklaSanjeev Shukla More articles by this author , Gregory MacLennanGregory MacLennan More articles by this author , Pingfu FuPingfu Fu More articles by this author , Jing LiJing Li More articles by this author , Anant MadabhushiAnant Madabhushi More articles by this author , and Sanjay GuptaSanjay Gupta More articles by this author View All Author Informationhttps://doi.org/10.1016/j.juro.2017.02.3316AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookTwitterLinked InEmail INTRODUCTION AND OBJECTIVES Prostate cancer remains the second leading cause of cancer-related deaths in American men. Often an indolent disease, patients remain asymptomatic for years. Easily treatable tumors and other, often fatal, highly aggressive forms are difficult to distinguish. Current prognosis and treatment stratification do not accurately predict clinical outcome. Hence there is an urgent need for improved markers to determine prognosis and appropriate treatments. We identified two key signaling pathways (PI3K-Akt and NF-κB) whose constitutive activation correlates with prostate cancer progression. Using an integrated approach of quantitative experimentation and mathematical modeling, we seek to develop a multi-level, hierarchical, quantitative systems biology model - where the lower level captures the dynamic molecular processes of the signaling pathways and the higher level models the cancer phenotype. METHODS p-Akt (Ser473) and NF-κB/p65 protein expression was analyzed in benign and cancer specimens of various Gleason grades and their co-localization by immunohistochemistry. We also utilized androgen-responsive LNCaP cells (possessing increased Akt activity due to mutation in PTEN gene) and androgen-refractory PC-3 cells with constitutive activation of Akt and NF-κB and their treatment with specific inhibitors. Western blotting was performed to determine the expression of native/active forms of Akt and NF-κB and their effector proteins. Subsequent work include connecting the model of cell signaling to the physiologically ″higher″ levels using mechanistic details or statistical models. RESULTS Compared to benign tissue, cancer specimens exhibited constitutive activation of p-Akt (Ser473) and NF-κB/p65 which was more pronounced in high-grade cancer (Gleason grade 7-10). Immunohistochemical analyses further demonstrated co-localization of these proteins in a subset of aggressive cancer tissues. Individual treatment of cell lines with Akt Inhibitor VIII (0.075-1.8μM) and NF-κB inhibitor Parthenolide (0.32-60μM) for 24-72 h demonstrated partial suppressive effect in cancer cell growth; whereas concurrent blocking of Akt and NF-κB/p65 at 1:10μM ratio resulted in potentiated toxicity and inhibition of downstream effector proteins in both cell lines. The categorical behaviors were explored by extensive simulations conducted to explore possible parameterizations of the model and to define the range of potential responses. A differential equation based (mass action and Michaelis-Menten) mathematical model was constructed and structurally calibrated/validated using experimental data. The resulting behaviors were identified and categorized according to the severity of pathway activity. Model parameterization (numerical values of reaction rates and basal protein levels) was accomplished by adopting portions of the models estimating the remaining unknowns from available experimental data. CONCLUSIONS Our results suggest that Akt activation provides long-term cell survival by activating pathways that influence NF-κB-dependent gene transcription, and hence plays a role in prostate cancer aggression. © 2017FiguresReferencesRelatedDetails Volume 197Issue 4SApril 2017Page: e594 Advertisement Copyright & Permissions© 2017MetricsAuthor Information Eswar Shankar More articles by this author Rajnee Kanwal More articles by this author Aditi Goel More articles by this author Xiaoping Yang More articles by this author Sanjeev Shukla More articles by this author Gregory MacLennan More articles by this author Pingfu Fu More articles by this author Jing Li More articles by this author Anant Madabhushi More articles by this author Sanjay Gupta More articles by this author Expand All Advertisement Advertisement PDF downloadLoading ...

Vessel Network Architecture of Adult Human Islets Promotes Distinct Cell-Cell Interactions In Situ and Is Altered After Transplantation.

Islet-cell hormone release is modulated by signals from endothelial and endocrine cells within the islet. However, models of intraislet vascularization and paracrine cell signaling are mostly based on the rodent pancreas. We assessed the architecture and endocrine cell interaction of the vascular network in unperturbed human islets in situ and their potential to re-establish their endogenous vascular network after transplantation in vivo. We prepared slices of fresh pancreas tissue obtained from nondiabetic patients undergoing partial pancreatectomy. In addition, we transplanted human donor islets into the anterior chamber of the mouse eye. Next, we performed three-dimensional in situ and in vivo imaging of islet cell and vessel architecture at cellular resolution and compared our findings with mouse and porcine islets. Our data reveal a significantly different vascular architecture with decreased vessel diameter, reduced vessel branching, and shortened total vessel network in human compared with mouse islets. Together with the distinct cellular arrangement in human islets, this limits β to endothelial cell interactions, facilitates connection of α and β cells, and promotes the formation of independent β-cell clusters within islets. Furthermore, our results show that the endogenous vascular network of islets is significantly altered after transplantation in a donor age-related mechanism. Thus, our study provides insight into the vascular architecture and cellular arrangement of human islets with apparent consequences for intercellular islet signaling. Moreover, our findings suggest that human islet engraftment after transplantation can be improved by using alternative, less mature islet-cell sources.

Analysis of a dynamic model of guard cell signaling reveals the stability of signal propagation.

BackgroundAnalyzing the long-term behaviors (attractors) of dynamic models of biological systems can provide valuable insight into biological phenotypes and their stability. In this paper we identify the allowed long-term behaviors of a multi-level, 70-node dynamic model of the stomatal opening process in plants.ResultsWe start by reducing the model’s huge state space. We first reduce unregulated nodes and simple mediator nodes, then simplify the regulatory functions of selected nodes while keeping the model consistent with experimental observations. We perform attractor analysis on the resulting 32-node reduced model by two methods: 1. converting it into a Boolean model, then applying two attractor-finding algorithms; 2. theoretical analysis of the regulatory functions. We further demonstrate the robustness of signal propagation by showing that a large percentage of single-node knockouts does not affect the stomatal opening level.ConclusionsCombining both methods with analysis of perturbation scenarios, we conclude that all nodes except two in the reduced model have a single attractor; and only two nodes can admit oscillations. The multistability or oscillations of these four nodes do not affect the stomatal opening level in any situation. This conclusion applies to the original model as well in all the biologically meaningful cases. In addition, the stomatal opening level is resilient against single-node knockouts. Thus, we conclude that the complex structure of this signal transduction network provides multiple information propagation pathways while not allowing extensive multistability or oscillations, resulting in robust signal propagation. Our innovative combination of methods offers a promising way to analyze multi-level models.Electronic supplementary materialThe online version of this article (doi:10.1186/s12918-016-0327-7) contains supplementary material, which is available to authorized users.

Mechanically‐Induced Osteocyte/Th17 Cell Signaling and Subsequent Osteoclast Recruitment

Mechanical loading of bone triggers bone modeling/formation, via osteocyte signaling. However, when mechanical loads of extreme force or repetition create tissue damage, osteocytes stimulate the targeted remodeling of the damaged bone matrix. We have previously reported an up regulation of the pro-inflammatory cytokine GRO/KC, T cell recruiting cytokines (IL-2, MCP-1), and an increase in mRANKL and osteoclast number within fatigue loaded rat ulna compared to non-loaded controls. These findings suggests a relationship between bone fatigue and the subsequent recruitment of both T cells and osteoclasts. We examined a novel, mechanically-induced signaling pathway between osteocytes and Th17 cells, and hypothesized that repetitive fluid shear stress (FSS) would induce osteocyte production of cytokines, IL-6 and TGF-β1, known to stimulate Th17 cell development and their secretion of osteoclastogenic cytokines, IL-17 and sRANKL. MLO-Y4 osteocyte-like cells were exposed to FSS (7±3 dynes and 10±3 dynes, at 1Hz) or Static control. The cells and medium were collected after 30 or 60 minutes of FSS exposure or static conditions. ELISA analysis of MLO-Y4 medium revealed greater IL-6 and TGF-β1 in FSS versus Static groups. MLO-Y4 medium also revealed less sRANKL in FSS versus Static groups. Murine spleen cells were then cultured in T cell supportive conditions and treated with 25% FSS or Static MLO-Y4 medium for 72 hours. ELISA analysis of T cell culture medium revealed greater IL-17 in T cell cultures treated with FSS medium versus Static medium. MLO-Y4 cells were then co-cultured with murine spleen cells in osteoclast supportive conditions and treated with 25% T cell medium (FSS TX or Static TX) for 10 days. ELISA and TRAP stain analysis of osteoclast cultures revealed greater sRANKL and TRAP+ osteoclasts in cultures treated with T cell medium (FSS TX) versus T cell medium (Static TX). To our knowledge these data are the first to support a novel, mechanically-induced osteocyte/Th17 cell signaling pathway. Our data illustrates that mechanically-stimulated MLO-Y4 cells secrete greater amounts of cytokines (IL-6 and TGF-β1) known to induce Th17 cell development, that T cell cultures treated with MLO-Y4 FSS medium produced greater amounts of IL-17, and that the addition of T cell medium (FSS TX) to osteoclast cultures leads to greater osteoclast formation; thus suggesting that repetitive loading of osteocytes potentiates Th17 cell activity and the subsequent recruitment of osteoclasts. Future in vivo studies examining the osteoclast response in relation to our osteocyte/Th17 cell signaling model would provide a new paradigm for targeted bone remodeling in response to mechanical stress. Support or Funding Information NASA Nebraska Space Grant A. Proposed mechanically-induced osteocyte/Th17 cell signaling model. B. Increased TRAP+ osteoclasts in cultures treated with T cell medium (FSS TX: 7+/−3 & 10+/−3) versus T cell medium (Static TX).

Integrin-mediated adhesion as self-sustained waves of enzymatic activation.

Integrin receptors mediate interaction between the cellular actin-cytoskeleton and extracellular matrix. Based on their activation properties, we propose a reaction-diffusion model where the kinetics of the two-state receptors is modulated by their lipidic environment. This environment serves as an activator variable, while a second variable plays the role of a scaffold protein and controls the self-sustained activation of the receptors. Due to receptor diffusion which couples dynamically the activator and the inhibitor, our model connects major classes of reaction diffusion systems for excitable media. Spot and rosette solutions, characterized by receptor clustering into localized static or dynamic structures, are organized into a phase diagram. It is shown that diffusion and kinetics of receptors determines the dynamics and the stability of these structures. We discuss this model as a precursor model for cell signaling in the context of podosomes forming actoadhesive metastructures, and we study how generic signaling defects influence their organization.

Modeling the Effect of Direct PKA-PDE Binding in the Formation of Localized Microdomains of Camp in Adult Cardiomyocytes

The β-adrenergic pathway in cardiomyocytes activates protein kinase A (PKA) to phosphoregulate several Ca2+ handling proteins, including the L-type Ca channel, ryanodine receptor, and sarco/endoplasmic reticulum Ca2+-ATPase (SERA) (via phospholamban), resulting in inotropic, lusitropic and chronotropic responses. Recent studies have postulated a role of direct phosphodiesterases (PDE)/PKA-Regulator (R) subunit interaction to regulate PKA activation in various compartments of the cardiac cell. This interaction is control by A kinase anchoring proteins (AKAP)s that select for specific isoforms. In this study we used in vitro kinetic experiments with 3H tagged cAMP, purified R-subunits, and PDEs to quantify this interaction and explore its specificity both for RIα and RIIβ with PDE3 and PDE4 isoforms. The experimental results were combined with a new Markov Model of PKA activation using Virtual Cell, a finite volume solver, to suggest the physiological impact of including this interaction. This new regulatory pathway and PKA Markov Model will be included in a whole cell signaling model of cardiomyocyte activation in response to beta-adrenergic stimulation.

Is the model of signal amplification by GPCRs/GEFs activating multiple GTPases relevant to a broad spectrum of heterotrimeric and RAS superfamily GTPases?

Concepts or models of biological processes shape how we think about them, discuss them, and design experiments to test aspects of them. Because of the importance of our models of cell signaling by regulatory GTPases and the desire to extend those models to related signaling modules, I have throughout my career been fascinated by the similarities and differences between the modeling of heterotrimeric G protein and monomeric RAS superfamily GTPases. Recent discussions with colleagues led me to conclude that there is a growing divergence in how researchers model the activation and signaling processes of monomeric and trimeric GTPases and also a surprising lack of consensus within each camp. This series of articles arose in response to these discussions and is intended to spark new ones.

Characterization of Recombinant ELMOD (Cell Engulfment and Motility Domain) Proteins as GTPase-activating Proteins (GAPs) for ARF Family GTPases

The ARF family of regulatory GTPases, within the RAS superfamily, is composed of ~30 members in mammals, including up to six ARF and at least 18 ARF-like (ARL) proteins. They exhibit significant structural and biochemical conservation and regulate a variety of essential cellular processes, including membrane traffic, cell division, and energy metabolism; each with links to human diseases. We previously identified members of the ELMOD family as GTPase-activating proteins (GAPs) for ARL2 that displayed crossover activity for ARFs as well. To further characterize the GAP activities of the three human ELMODs as GAPs we developed new preparations of each after overexpression in human embryonic kidney (HEK293T) cells. This allowed much higher specific activities and enhanced stability and solubility of the purified proteins. The specificities of ELMOD1-3 as GAPs for six different members of the ARF family were determined and found to display wide variations, which we believe will reveal differences in cellular functions of family members. The non-opioid sigma-1 receptor (S1R) was identified as a novel effector of GAP activity of ELMOD1-3 proteins as its direct binding to either ELMOD1 or ELMOD2 resulted in loss of GAP activity. These findings are critical to understand the roles of ELMOD proteins in cell signaling in general and in the inner ear specifically, and open the door to exploration of the regulation of their GAP activities via agonists or antagonists of the S1R.

Amplification without instability: applying fluid dynamical insights in chemistry and biology

While amplification of small perturbations often arises from instability, transient amplification is possible locally even in asymptotically stable systems. That is, knowledge of a system's stability properties can mislead one's intuition for its transient behaviors. This insight, which has an interesting history in fluid dynamics, has more recently been rediscovered in ecology. Surprisingly, many nonlinear fluid dynamical and ecological systems share linear features associated with transient amplification of noise. This paper aims to establish that these features are widespread in many other disciplines concerned with noisy systems, especially chemistry, cell biology and molecular biology. Here, using classic nonlinear systems and the graphical language of network science, we explore how the noise amplification problem can be reframed in terms of activatory and inhibitory interactions between dynamical variables. The interaction patterns considered here are found in a great variety of systems, ranging from autocatalytic reactions and activator–inhibitor systems to influential models of nerve conduction, glycolysis, cell signaling and circadian rhythms.

Stroke Literature Synopses : Basic Sciences

There remains some plasticity even in adult brain, and after stroke, the brain tries to remodel damaged neuronal circuits. Neuronal precursor cells (NPCs) may participate in this process, but how NPCs move to lesion areas from subventricular zone (SVZ) remains to be fully understood. Three recent studies provide new fundamental mechanisms for neural migration in the central nervous system. Itoh et al (Scratch regulates neuronal migration onset via an epithelial-mesenchymal transition-like mechanism. Nature Neurosci . 2013;16:416–425) proposed a novel mechanism for the conversion of neuroepithelial cells to migrating neurons or intermediate NPCs. During development, NPCs in the SVZ form a pseudostratified epithelial structure, and once they commit to becoming neurons (or intermediate NPCs), they delaminate and start migration. To reveal the underlying regulatory mechanisms, the authors focused on roles of Scratch1 and Scratch2, which are members of the Snail superfamily of transcription factors. They knocked down Scratch1 and Scratch2 in the neocortical NPCs during neocortical development by …

Non-Recessive Bt Toxin Resistance Conferred by an Intracellular Cadherin Mutation in Field-Selected Populations of Cotton Bollworm

Transgenic crops producing Bacillus thuringiensis (Bt) toxins have been planted widely to control insect pests, yet evolution of resistance by the pests can reduce the benefits of this approach. Recessive mutations in the extracellular domain of toxin-binding cadherin proteins that confer resistance to Bt toxin Cry1Ac by disrupting toxin binding have been reported previously in three major lepidopteran pests, including the cotton bollworm, Helicoverpa armigera. Here we report a novel allele from cotton bollworm with a deletion in the intracellular domain of cadherin that is genetically linked with non-recessive resistance to Cry1Ac. We discovered this allele in each of three field-selected populations we screened from northern China where Bt cotton producing Cry1Ac has been grown intensively. We expressed four types of cadherin alleles in heterologous cell cultures: susceptible, resistant with the intracellular domain mutation, and two complementary chimeric alleles with and without the mutation. Cells transfected with each of the four cadherin alleles bound Cry1Ac and were killed by Cry1Ac. However, relative to cells transfected with either the susceptible allele or the chimeric allele lacking the intracellular domain mutation, cells transfected with the resistant allele or the chimeric allele containing the intracellular domain mutation were less susceptible to Cry1Ac. These results suggest that the intracellular domain of cadherin is involved in post-binding events that affect toxicity of Cry1Ac. This evidence is consistent with the vital role of the intracellular region of cadherin proposed by the cell signaling model of the mode of action of Bt toxins. Considered together with previously reported data, the results suggest that both pore formation and cell signaling pathways contribute to the efficacy of Bt toxins.

Multiscale Systems Biology: A Special Issue Devoted to Understanding Biology and Medicine Across Multiple Scales

The central goal of Systems Biology is to understand and quantitatively predict biological phenomena at a global level, where biological functions result from complex mechanisms that occur across diverse scales, from the atomic and molecular to the organelle and cellular level, and then extended to the tissue, organism, and population level. In bioengineering applications, unique challenges include: (1) the regulatory and kinetic complexity of gene and metabolic and signaling pathways, (2) generation or response to physical forces, and (3) complex transport physics. The task of identifying disease mechanism, disease severity, or response to therapy (i.e., phenotype) remains difficult if the only data set available were a patient’s genome sequence. Even with increasingly powerful supercomputers, brute force approaches at a single scale often prove inadequate to tackle these multiscale problems, especially when physical or thermodynamic criteria are also imposed. With potentially many scales and many variables associated with problems of interest, the need for systematic approaches to modeling multiscale systems motivates this Special Issue. This collection of 16 papers from leading laboratories highlights these advances in distinct medical arenas. Modeling and the discovery of emergent properties, for instance cellular processes arising from cell signaling networks, are best addressed by following a systems biology approach. One important theme in multiscale modeling is coarse graining, where some of the fine detail of low-level models has been smoothed over or averaged out. Another important concept in multiscale modeling is linking between scales; that is, how one reconciles coupling fine-scale and coarsergrained models in an accurate, predictive, and unambiguous way. In this Special Issue, a variety of approaches and methodologies are presented for the use of multiscale computational models to study and predict the behavior of complex systems. The goal of this special issue is to highlight advances in the field of biomedical engineering that tackle multiscale problems. The field has advanced rapidly and the National Institutes of Health has supported several initiatives related to Multiscale Systems Biology to address clinical needs, including the establishment of a Multiscale Modeling Consortium. The Annals of Biomedical Engineering is an ideal platform to communicate these advances and state of the art approaches. This special issue highlights bioengineering research that emphasizes molecular-cellular-tissue scale simulation and measurement, for instance when combined with aspects of high throughput experiments, physical biology, ormechanobiology.Many of the papers in this issue describe computational biology approaches that are combined with experimental validation or confirmation. The articles featured in this special issue address several different physiological systems and cellular phenomena. Signal transduction at the molecular level is considered in papers by Radakrishnan and colleagues, and by Wilson and colleagues. Janes and colleagues describe multiscale models of cell signaling. Calvetti and colleagues discuss the metabolism of Michael R. King.

Dynamics of bone cell signaling and PTH treatments of osteoporosis

In this paper we analyze and generalize the dynamical system introduced by Lemaire and co-workers [14] as a model of cell signaling in bone remodeling. We show that for large classes of parameter values, including the physically-realistic baseline values, the system has a unique physically relevant equilibrium which is a global attractor. We generalize that model, minimally, to incorporate a mechanism by which parathyroid hormone (PTH) retards osteoblast apoptosis. We show that with this mechanism, which is a simplified version of that proposed by Bellido and co-workers [4], the model exhibits a well-known phenomenon that has puzzled researchers: the system responds catabolically to the continuous administration of PTH andally to appropriately pulsed administration of PTH.