Biomedical subjects

Ravi Iyengar

Publications and source records attributed to Ravi Iyengar.

At least 19 recordsLinked to original sources

PubMed2006

Retinoic acid inhibits HIV-1-induced podocyte proliferation through the cAMP pathway.

HIV-associated nephropathy is characterized by renal podocyte proliferation and dedifferentiation. This study found that all-trans retinoic acid (atRA) reverses the effects of HIV-1 infection in podocytes. Treatment with atRA reduced cell proliferation rate by causing G1 arrest and restored the expression of the differentiation markers (synaptopodin, nephrin, podocin, and WT-1) in HIV-1-infected podocytes. It is interesting that both atRA and 9-cis RA increased intracellular cAMP levels in podocytes. Podocytes expressed most isoforms of retinoic acid receptors (RAR) and retinoid X receptors (RXR) with the exception of RXRgamma. RARalpha antagonists blocked atRA-induced cAMP production and its antiproliferative and prodifferentiation effects on podocytes, suggesting that RARalpha is required. For determination of the effect of increased intracellular cAMP on HIV-infected podocytes, cells were stimulated with either forskolin or 8-bromo-cAMP. Both compounds inhibited cell proliferation significantly and restored synaptopodin expression in HIV-infected podocytes. The effects of atRA were abolished by Rp-cAMP, an inhibitor of the cAMP/protein kinase A pathway and were enhanced by rolipram, an inhibitor of phosphodiesterase 4, suggesting that the antiproliferative and prodifferentiation effects of atRA on HIV-infected podocytes are cAMP dependent. Furthermore, both atRA and forskolin suppressed HIV-induced mitogen-activated protein kinase 1 and 2 and Stat3 phosphorylation. In vivo, atRA reduced proteinuria, cell proliferation, and glomerulosclerosis in HIV-1-transgenic mice. These findings suggest that atRA reverses the abnormal phenotype in HIV-1-infected podocytes by stimulating RARalpha-mediated intracellular cAMP production. These results demonstrate the mechanism by which atRA reverses the proliferation of podocytes that is induced by HIV-1.

AIDS-Associated Nephropathy↗

PubMed2006

Compartment-specific feedback loop and regulated trafficking can result in sustained activation of Ras at the Golgi.

Imaging experiments have shown that cell signaling components such as Ras can be activated by growth factors at distinct subcellular locations. Trafficking between these subcellular locations is a regulated dynamic process. The effects of trafficking and the molecular mechanisms underlying compartment-specific Ras activation were studied using numerical simulations of an ordinary differential equation-based multi-compartment model. The simulations show that interplay between two distinct mechanisms, a palmitoylation cycle that controls Ras trafficking and a phospholipase C-epsilon (PLC-epsilon) driven feedback loop, can convert a transient calcium signal into prolonged Ras activation at the Golgi. Detailed analysis of the network identified PLC-epsilon as a key determinant of "compartment switching". Modulation of PLC-epsilon activity switches the location of activated Ras between the plasma membrane and Golgi through a new mechanism termed "kinetic scaffolding". These simulations indicate that multiple biochemical mechanisms, when appropriately coupled, can give rise to an intracellular compartment-specific sustained Ras activation in response to stimulation of growth factor receptors at the plasma membrane.

Calcium Signaling↗

PubMed2006

Topology of resultant networks shaped by evolutionary pressure.

Understanding the topology of complex systems abstracted to networks is important for unraveling their functional capabilities. Many such networks follow the small-world and scale-free regimes. Several models of artificially growing networks lead to this observed network topology. Most previously proposed models for growing networks, such as rich-get-richer and duplication-divergence, produce realistic network topologies but do not consider the effects of exogenous forces such as optimization for adaptation in shaping network topology. It is likely that such forces have shaped complex systems throughout their evolution. To develop further insights into possible mechanisms that shape networks, a model that uses several previously proposed network growth algorithms was developed to grow networks that adapt under exogenous stress. A decision tree problem was used to generate a complex Boolean function. Growing networks were required to adapt to correctly decode this function using an evolutionary selection process. Under this growth regimen all growing network models are similarly adaptable. The newly added nodes tend to cluster into pathways emanating from few inputs, regardless of the growth algorithm. Distribution of redundant pathways from inputs to the output follow a power-law function with a scaling exponent (approximately 1.3). Similar distribution of redundant pathways was observed from inputs in a cell signaling network and an air traffic control network. A flat distribution of redundant pathways from inputs was observed in growing networks that do not attempt to adapt. This analysis provides initial insights into distribution of pathways in naturally evolving complex systems that have defined input-output relationships.

Algorithms↗

PubMed2006

From components to regulatory motifs in signalling networks.

The developments in biochemistry and molecular biology over the past 30 years have produced an impressive parts list of cellular components. It has become increasingly clear that we need to understand how components come together to form systems. One area where this approach has been growing is cell signalling research. Here, instead of focusing on individual or small groups of signalling proteins, researchers are now using a more holistic perspective. This approach attempts to view how many components are working together in concert to process information and to orchestrate cellular phenotypic changes. Additionally, the advancements in experimental techniques to measure and visualize many cellular components at once gradually grow in diversity and accuracy. The multivariate data, produced by experiments, introduce new and exciting challenges for computational biologists, who develop models of cellular systems made up of interacting cellular components. The integration of high-throughput experimental results and information from legacy literature is expected to produce computational models that would rapidly enhance our understanding of the detail workings of mammalian cells.

Animals↗

PubMed2006

The cognitive phenotype of Down syndrome: insights from intracellular network analysis.

Down syndrome (DS) is caused by trisomy of chromosome 21. All individuals with DS exhibit some level of cognitive dysfunction. It is generally accepted that these abnormalities are a result of the upregulation of genes encoded by chromosome 21. Many chromosome 21 proteins are known or predicted to function in critical neurological processes, but typically they function as modulators of these processes, not as key regulators. Thus, upregulation in DS is expected to cause only modest perturbations of normal processes. Systematic approaches such as intracellular network construction and analysis have not been generally applied in DS research. Networks can be assembled from high-throughput experiments or by text-mining of experimental literature. We survey some new developments in constructing such networks, focusing on newly developed network analysis methodologies. We propose how these methods could be integrated with creation and manipulation of mouse models of DS to advance our understanding of the perturbed cell signaling pathways in DS. This understanding could lead to potential therapeutics.

Animals↗

PubMed2006

Role of the Go/i signaling network in the regulation of neurite outgrowth.

Neurite outgrowth is a complex differentiation process stimulated by many neuronal growth factors and transmitters and by electrical activity. Among these stimuli are ligands for G-protein-coupled receptors (GPCR) that function as neurotransmitters. The pathways involved in GPCR-triggered neurite outgrowth are not fully understood. Many of these receptors couple to Galphao, one of the most abundant proteins in the neuronal growth cones. We have studied the Go signaling network involved in neurite outgrowth in Neuro2A cells. Galphao can induce neurite outgrowth. The CB1 cannabinoid receptor, a Go/i-coupled receptor expressed endogenously in Neuro2A cells, triggers neurite outgrowth by activating Rap1, which promotes the Galphao-stimulated proteasomal degradation of Rap1GAPII. CB1-receptor-mediated Rap1 activation leads to the activation of a signaling network that includes the small guanosine triphosphate (GTP)ases Ral and Rac, the protein kinases Src, and c-Jun N-terminal kinase (JNK), which converge onto the activation of signal transducer and activator of transcription 3 (Stat3), a key transcription factor that mediates the gene expression process of neurite outgrowth in Neuro2A cells. This review describes current findings from our laboratory and also discusses alternative pathways that Go/i might mediate to trigger neurite outgrowth. We also analyze the role neurotransmitters, which stimulate Go/i to activate a complex signaling network controlling neurite outgrowth, play in regeneration after neuronal injury.

Animals↗

PubMed2005

Formation of regulatory patterns during signal propagation in a Mammalian cellular network.

We developed a model of 545 components (nodes) and 1259 interactions representing signaling pathways and cellular machines in the hippocampal CA1 neuron. Using graph theory methods, we analyzed ligand-induced signal flow through the system. Specification of input and output nodes allowed us to identify functional modules. Networking resulted in the emergence of regulatory motifs, such as positive and negative feedback and feedforward loops, that process information. Key regulators of plasticity were highly connected nodes required for the formation of regulatory motifs, indicating the potential importance of such motifs in determining cellular choices between homeostasis and plasticity.

Algorithms↗

PubMed2005

The G alpha(o/i)-coupled cannabinoid receptor-mediated neurite outgrowth involves Rap regulation of Src and Stat3.

The study of the signaling pathways regulating neurite outgrowth in culture is important because of their potential role in neuronal differentiation in vivo. We have previously shown that the G alpha(o/i)-coupled CB1 cannabinoid receptor (CB1R) activates Rap1 to induce neurite outgrowth. G alpha(o/i) also activates the Src-Stat3 pathway. Here, we studied the relationship between the G alpha(o/i)-Rap1 and Src-Stat3 pathways and the role of these signaling pathways in CB1R-mediated neurite outgrowth in Neuro-2A cells. The CB1 agonist HU-210 induced pertussis toxin-sensitive Src and Stat3 phosphorylation. Dominant negative (DN) mutants of Src and Stat3 blocked CB1R-induced neurite outgrowth. Constitutively active Rap 1B and Ral-activated Src and CB1R-induced Src phosphorylation was inhibited by Rap1-DN and Ral-DN, indicating that both Rap1 and Ral mediate downstream signaling from G alpha(o/i) for Src activation. Rap1-activated Ral and Ral-DN blocked Rap-induced Src phosphorylation. G alpha(o)-induced Stat3 activation was blocked by Ral-DN, whereas v-Src-induced Stat3 activation was not inhibited by Ral-DN, indicating that the CB1R, through G alpha(o), mediates the sequential activation of Rap1 to Ral to Src to Stat3 in Neuro-2A cells. Downstream of Src, the CB1R also activated Rac1 and JNK, which enhanced CBR1-mediated Stat3 activation. Rac-DN blocked CB1R-induced activation of JNK. Pharmacological inhibition of JNK blocked Src and CB1R activation of Stat3, indicating that Rac and JNK are also involved in CB1R-mediated neurite outgrowth. Overall, this study demonstrated that G alpha(o/i)-coupled CB1R triggers neurite outgrowth in Neuro-2A through the activation of a signaling network containing two pathways that bifurcate at Src and converge at Stat3.

Animals↗

PubMed2005

Local protein synthesis mediates a rapid increase in dendritic elongation factor 1A after induction of late long-term potentiation.

The maintenance of long-term potentiation (LTP) requires a brief period of accelerated protein synthesis soon after synaptic stimulation, suggesting that an early phase of enhanced translation contributes to stable LTP. The mechanism regulating protein synthesis and the location and identities of mRNAs translated are not well understood. Here, we show in acute brain slices that the induction of protein synthesis-dependent hippocampal LTP increases the expression of elongation factor 1A (eEF1A), the mRNA of which contains a 5' terminal oligopyrimidine tract. This effect is blocked by rapamycin, indicating that the increase in EF1A expression is mediated by the mammalian target of rapamycin (mTOR) pathway. We find that mRNA for eEF1A is present in pyramidal cell dendrites and that the LTP-associated increase in eEF1A expression was intact in dendrites that had been severed from their cell bodies before stimulation. eEF1A levels increased within 5 min after stimulation in a translation-dependent manner, and this effect remained stable for 3 h. These results suggest a mechanism whereby synaptic stimulation, by signaling through the mTOR pathway, produces an increase in dendritic translational capacity that contributes to LTP maintenance.

Animals↗

PubMed2005

Teaching resources. Structure of G-protein-coupled receptors and G proteins.

This Teaching Resource provides lecture notes and slides for a class covering the structure and function of G protein-coupled receptors and is part of the course "Cell Signaling Systems: A Course for Graduate Students." The lecture begins with a discussion of the crystal structure of rhodopsin and G protein subunits and then proceeds to describe the molecular mechanisms of receptor activation and the subsequent release of G proteins.

Animals↗

PubMed2005

Teaching resources. Introduction: Overview of pathways and networks and GPCR signaling.

This Teaching Resource provides the overview to the course "Cell Signaling Systems: A Course for Graduate Students" and lays out the general principles that can be deduced from the current understanding of the organization of cell signaling pathways and networks and how information flows through these pathways and networks. In addition, the lecture provides an overview of G protein-coupled receptor (GPCR) signaling. A description of the lecture, along with a set of slides (http://stke.sciencemag.org/cgi/content/full/sigtrans;2005/270/tr4/DC1) used to present this information, is provided.

Animals↗

PubMed2005

Teaching resources. Cell signaling systems: a course for graduate students.

This course uses the primary literature to develop a systems-level understanding of the information flow through the various cell signaling pathways and networks. Current areas of research activities in the experimental and theoretical understanding of cell signaling research are highlighted. This Teaching Resource describes a sample syllabus and organization for this course. Each lecture is 2 hours. After each set of lectures, there is a 2-hour discussion period during which students present an in-depth analysis of a primary literature article, selected in consultation with the lecturer.

Curriculum↗

PubMed2005

Cannabinoid receptor-induced neurite outgrowth is mediated by Rap1 activation through G(alpha)o/i-triggered proteasomal degradation of Rap1GAPII.

The G(alpha)o/i-coupled CB1 cannabionoid receptor induces neurite outgrowth in Neuro-2A cells. The mechanisms of signaling through G(alpha)o/i to induce neurite outgrowth were studied. The expression of G(alpha)o/i reduces the stability of its direct interactor protein, Rap1GAPII, by targeting it for ubiquitination and proteasomal degradation. This results in the activation of Rap1. G(alpha)o/i-induced activation of endogenous Rap1 in Neuro-2A cells is blocked by the proteasomal inhibitor lactacystin. G(alpha)o/i stimulates neurite outgrowth that is blocked by the expression of dominant negative Rap1. Expression of Rap1GAPII also blocks the G(alpha)o/i-induced neurite outgrowth and treatment with proteasomal inhibitors potentiates this inhibition. The endogenous G(alpha)o/i-coupled cannabinoid (CB1) receptor in Neuro-2A cells stimulates the degradation of Rap1GAPII; activation of Rap1 and treatment with pertussis toxin or lactacystin blocks these effects. The CB1 receptor-stimulated neurite outgrowth is blocked by treatment with pertussis toxin, small interfering RNA for Rap, lactacystin, and expression of Rap1GAPII. Thus, the G(alpha)o/i-coupled cannabinoid receptor, by regulating the proteasomal degradation of Rap1GAPII, activates Rap1 to induce neurite outgrowth.

Amino Acid Sequence↗

PubMed2005

Postsynaptic signaling networks: cellular cogwheels underlying long-term plasticity.

Learning depends on positive or negative changes in synaptic transmission that are synapse-specific and sustained. Synaptic signals can be directly measured and respond to certain kinds of stimulation by becoming persistently enhanced (long-term potentiation, LTP) or decreased (long-term depression, LTD). Studying LTP and LTD opens a window on to the molecular mechanisms of memory. Although changes in both pre- and postsynaptic strength have been implicated in LTP and LTD, most attention has been focused on changes in postsynaptic glutamate receptor density. This is controlled by intracellular Ca(2+) ions via a network of signaling molecules. Changes in postsynaptic Ca(2+) concentration depend on the coincidence of appropriate synaptic signals, as is found in learning situations. The long-term persistence of LTP and LTD requires gene transcription and translation. It is posited that local translation at the synapse, in a self-sustaining manner, mediates the persistence of long-term changes despite constant turnover of the synaptic components.

Animals↗

PubMed2005

Toward predictive models of mammalian cells.

Progress in experimental and theoretical biology is likely to provide us with the opportunity to assemble detailed predictive models of mammalian cells. Using a functional format to describe the organization of mammalian cells, we describe current approaches for developing qualitative and quantitative models using data from a variety of experimental sources. Recent developments and applications of graph theory to biological networks are reviewed. The use of these qualitative models to identify the topology of regulatory motifs and functional modules is discussed. Cellular homeostasis and plasticity are interpreted within the framework of balance between regulatory motifs and interactions between modules. From this analysis we identify the need for detailed quantitative models on the basis of the representation of the chemistry underlying the cellular process. The use of deterministic, stochastic, and hybrid models to represent cellular processes is reviewed, and an initial integrated approach for the development of large-scale predictive models of a mammalian cell is presented.

Amino Acid Motifs↗

PubMed2004

Quantitative information management for the biochemical computation of cellular networks.

Understanding complex protein networks within cells requires the ability to develop quantitative models and to numerically compute the properties and behavior of the networks. To carry out such computational analysis, it is necessary to use modeling tools and information management systems (IMSs) where the quantitative data, associated to its biological context, can be stored, curated, and reliably retrieved. We have focused on the biochemical computation of cellular interactions and developed an IMS that stores both quantitative information on the cellular components and their interactions, and the basic reactions governing those interactions. This information can be used to construct pathways and eventually large-scale networks. This system, SigPath, is available on the Internet (http://www.sigpath.org). Key features of the approach include (i) the use of background information (for example, names of molecules, aliases, and accession codes) to ease data submission and link this quantitative database with other qualitative databases, (ii) a strategy to allow refinement of information over time by multiple users, (iii) the development of a data representation that stores both qualitative and quantitative information, and (iv) features to assist contributors and users in assembling custom quantitative models from the information stored in the IMS. Currently, models assembled in SigPath can be automatically exported to several computing environments, such as Kinetikit/Genesis, Virtual Cell, Jarnac/JDesigner, and JSim. We anticipate that, when appropriately populated, such a system will be useful for large-scale quantitative studies of cell-signaling networks and other cellular networks. SigPath is distributed under the GNU General Public License.

Animals↗

PubMed2004

Functional analysis of the interface regions involved in interactions between the central cytoplasmic loop and the C-terminal tail of adenylyl cyclase.

The mammalian adenylyl cyclase is a membrane-bound enzyme that is predicted to have 12 trans-membrane spans. Between membrane spans 6 and 7 there is a large cytoplasmic loop, which, along with the C-terminal tail, makes up the catalytic site of the enzyme. Crystal structures of these soluble cytoplasmic domains have identified the regions that are involved in interactions with each other. The functional consequences of these interactions in the full-length membrane-embedded enzymes have not been established. In this study, we analyzed the role of various interaction regions within the central cytoplasmic loop (C1) and the C-terminal tail (C2) on basal, Galphas-, forskolin-, and Mn(2+)-stimulated activities of adenylyl cyclases 2 and 6 (AC2 and AC6). We tested synthetic peptides encoding the different interface surfaces of both the C1 and C2 domain on different activities of membrane-bound AC2 and AC6 expressed in insect cells. We found the C1-alpha2-beta2-beta3 and C2-beta2'-beta3' regions to be involved in stimulation by Galphas and forskolin but not in the basal or Mn(2+)-stimulated activities. Both the C1-beta4-beta5-alpha4 region and the C2-alpha3'-beta4' region play a role in the Galphas- and forskolin-stimulated activities as well as in basal activity, because the peptides encoding these regions inhibit basal activity by 30%. In contrast, the C2-alpha2' region peptide inhibits both basal and Mn(2+)-stimulated activity by >50%. These results suggest that the different stimulated activities may involve distinct interface interactions in the intact enzyme and, consequently, the distinct mechanisms by which Mn(2+) activates the enzyme as compared with Galphas and forskolin, leading to the possibility that the full-length adenylyl cyclase may have multiple catalytically competent configurations.

Adenylyl Cyclases↗

PubMed2004

Modeling cell signaling networks.

Cell signaling pathways interact with one another to form networks in mammalian systems. Such networks are complex in their organization and exhibit emergent properties such as bistability and ultrasensitivity. Analysis of signaling networks requires a combination of experimental and theoretical approaches including the development and analysis of models. This review focuses on theoretical approaches to understanding cell signaling networks. Using heterotrimeric G protein pathways an example, we demonstrate how interactions between two pathways can result in a network that contains a positive feedback loop and function as a switch. Different mathematical approaches that are currently used to model signaling networks are described, and future challenges including the need for databases as well as enhanced computing environments are discussed.

Animals↗