The internal state of medium spiny neurons varies in response to different input signals

DARPP-32 in the orchestration of responses to positive natural stimuli

Dopamine- and cAMP-regulated phosphoprotein (M_r 32 kDa, DARPP-32) is an integrator of multiple neuronal signals and plays a crucial role particularly in mediating the dopaminergic component of the systems involved in the evaluation of stimuli and the ensuing elaboration of complex behavioral responses (e.g., responses to reinforcers and stressors). Dopamine neurons can fire tonically or phasically in distinct timescales and in specific brain regions to code different behaviorally relevant information. Dopamine signaling is mediated mainly through the regulation of adenylyl cyclase activity, stimulated by D1-like or inhibited by D2-like receptors, respectively, that modulates cAMP-dependent protein kinase (PKA) function. The activity of DARPP-32 is finely regulated by its phosphorylation at multiple sites. Phosphorylation at the threonine (Thr) 34 residue by PKA converts DARPP-32 into an inhibitor of protein phosphatase 1, while the phosphorylation at the Thr75 residue turns it into an inhibitor of PKA. Thus, DARPP-32 is critically implicated in regulating striatal output in response to the convergent pathways that influence signaling of the cAMP/PKA pathway. This review summarizes some of the landmark and recent studies of DARPP-32-mediated signaling in the attempt to clarify the role played by DARPP-32 in the response to rewarding natural stimuli. Particularly, the review deals with data derived from rodents studies and discusses the involvement of the cAMP/PKA/DARPP-32 pathway in: 1) appetitive food-sustained motivated behaviors, 2) motivated behaviors sustained by social reward, 3) sexual behavior, and 4) responses to environmental enrichment.

Nonparametric dynamic modeling

Challenging as it typically is, the estimation of parameter values seems to be an unavoidable step in the design and implementation of any dynamic model. Here, we demonstrate that it is possible to set up, diagnose, and simulate dynamic models without the need to estimate parameter values, if the situation is favorable. Specifically, it is possible to establish nonparametric models for nonlinear compartment models, including metabolic pathway models, if sufficiently many high-quality time series data are available that describe the biological phenomenon under investigation in an appropriate and representative manner. The proposed nonparametric strategy is a variant of the method of Dynamic Flux Estimation (DFE), which permits the estimation of numerical flux profiles from metabolic time series data. However, instead of attempting to formulate these numerical profiles as explicit functions and to optimize their parameter values, as it is done in DFE, the metabolite and flux profiles are used here directly as a scaffold for a library from which values are interpolated and retrieved for the simulation of the differential equations describing the model. Beyond simulations, the proposed methods render it possible to determine steady states from non-steady state data, perform sensitivity analyses, and estimate the Jacobian of the system at a steady state.

Cyclin-dependent kinase 5, a node protein in diminished tauopathy: a systems biology approach

Alzheimer's disease (AD) is the most common cause of dementia worldwide. One of the main pathological changes that occurs in AD is the intracellular accumulation of hyperphosphorylated Tau protein in neurons. Cyclin-dependent kinase 5 (CDK5) is one of the major kinases involved in Tau phosphorylation, directly phosphorylating various residues and simultaneously regulating various substrates such as kinases and phosphatases that influence Tau phosphorylation in a synergistic and antagonistic way. It remains unknown how the interaction between CDK5 and its substrates promotes Tau phosphorylation, and systemic approaches are needed that allow an analysis of all the proteins involved. In this review, the role of the CDK5 signaling pathway in Tau hyperphosphorylation is described, an in silico model of the CDK5 signaling pathway is presented. The relationship among these theoretical and computational models shows that the regulation of Tau phosphorylation by PP2A and glycogen synthase kinase 3β (GSK3β) is essential under basal conditions and also describes the leading role of CDK5 under excitotoxic conditions, where silencing of CDK5 can generate changes in these enzymes to reverse a pathological condition that simulates AD.

A heuristic model of alcohol dependence

Background

Substance dependence poses a critical health problem. Sadly, its neurobiological mechanisms are still unclear, and this lack of real understanding is reflected in insufficient treatment options. It has been hypothesized that alcohol effects are due to an imbalance between neuroexcitatory and neuroinhibitory amino acids. However, glutamate and GABA interact with other neurotransmitters, which form a complicated network whose functioning evades intuition and should be investigated systemically with methods of biomedical systems analysis.

Methods and Results

We present a heuristic model of neurotransmitters that combines a neurochemical interaction matrix at the biochemical level with a mobile describing the balances between pairs of neurotransmitters at the physiological and behavioral level. We investigate the effects of alcohol on the integrated neurotransmitter systems at both levels. The model simulation results are consistent with clinical and experimental observations. The model demonstrates that the drug diazepam for symptoms of alcohol withdrawal effectively reduces the imbalances between neurotransmitters. Moreover, the acetylcholine signal is suggested as a novel target for treatment of symptoms associated with alcohol withdrawal.

Conclusions

Efficient means of integrating clinical symptoms across multiple levels are still scarce and difficult to establish. We present a heuristic model of systemic neurotransmitter functionality that permits the assessment of genetic, biochemical, and pharmacological perturbations. The model can serve as a tool to represent clinical and biological observations and explore various scenarios associated with alcohol dependence and its treatments. It also is very well suited for educational purposes.

Rotenone and paraquat perturb dopamine metabolism: A computational analysis of pesticide toxicity

Pesticides, such as rotenone and paraquat, are suspected in the pathogenesis of Parkinson's disease (PD), whose hallmark is the progressive loss of dopaminergic neurons in the substantia nigra pars compacta. Thus, compounds expected to play a role in the pathogenesis of PD will likely impact the function of dopaminergic neurons. To explore the relationship between pesticide exposure and dopaminergic toxicity, we developed a custom-tailored mathematical model of dopamine metabolism and utilized it to infer potential mechanisms underlying the toxicity of rotenone and paraquat, asking how these pesticides perturb specific processes. We performed two types of analyses, which are conceptually different and complement each other. The first analysis, a purely algebraic reverse engineering approach, analytically and deterministically computes the altered profile of enzyme activities that characterize the effects of a pesticide. The second method consists of large-scale Monte Carlo simulations that statistically reveal possible mechanisms of pesticides. The results from the reverse engineering approach show that rotenone and paraquat exposures lead to distinctly different flux perturbations. Rotenone seems to affect all fluxes associated with dopamine compartmentalization, whereas paraquat exposure perturbs fluxes associated with dopamine and its breakdown metabolites. The statistical results of the Monte-Carlo analysis suggest several specific mechanisms. The findings are interesting, because no a priori assumptions are made regarding specific pesticide actions, and all parameters characterizing the processes in the dopamine model are treated in an unbiased manner. Our results show how approaches from computational systems biology can help identify mechanisms underlying the toxicity of pesticide exposure.

The neurobiology of alcohol consumption and alcoholism: an integrative history

Studies of the neurobiological predisposition to consume alcohol (ethanol) and to transition to uncontrolled drinking behavior (alcoholism), as well as studies of the effects of alcohol on brain function, started a logarithmic growth phase after the repeal of the 18th Amendment to the United States Constitution. Although the early studies were primitive by current technological standards, they clearly demonstrated the effects of alcohol on brain structure and function, and by the end of the 20th century left little doubt that alcoholism is a "disease" of the brain. This review traces the history of developments in the understanding of ethanol's effects on the most prominent inhibitory and excitatory systems of brain (GABA and glutamate neurotransmission). This neurobiological information is integrated with knowledge of ethanol's actions on other neurotransmitter systems to produce an anatomical and functional map of ethanol's properties. Our intent is limited in scope, but is meant to provide context and integration of the actions of ethanol on the major neurobiologic systems which produce reinforcement for alcohol consumption and changes in brain chemistry that lead to addiction. The developmental history of neurobehavioral theories of the transition from alcohol drinking to alcohol addiction is presented and juxtaposed to the neurobiological findings. Depending on one's point of view, we may, at this point in history, know more, or less, than we think we know about the neurobiology of alcoholism.

Manganese-exposed developing rats display motor deficits and striatal oxidative stress that are reversed by Trolox

While manganese (Mn) is essential for proper central nervous system (CNS) development, excessive Mn exposure may lead to neurotoxicity. Mn preferentially accumulates in the basal ganglia, and in adults it may cause Parkinson's disease-like disorder. Compared to adults, younger individuals accumulate greater Mn levels in the CNS and are more vulnerable to its toxicity. Moreover, the mechanisms mediating developmental Mn-induced neurotoxicity are not completely understood. The present study investigated the developmental neurotoxicity elicited by Mn exposure (5, 10 and 20 mg/kg; i.p.) from postnatal day 8 to PN27 in rats. Neurochemical analyses were carried out on PN29, with a particular focus on striatal alterations in intracellular signaling pathways (MAPKs, Akt and DARPP-32), oxidative stress generation and cell death. Motor alterations were evaluated later in life at 3, 4 or 5 weeks of age. Mn exposure (20 mg/kg) increased p38(MAPK) and Akt phosphorylation, but decreased DARPP-32-Thr-34 phosphorylation. Mn (10 and 20 mg/kg) increased caspase activity and F2-isoprostane production (a biological marker of lipid peroxidation). Paralleling the changes in striatal biochemical parameters, Mn (20 mg/kg) also caused motor impairment, evidenced by increased falling latency in the rotarod test, decreased distance traveled and motor speed in the open-field test. Notably, the antioxidant Trolox™ reversed the Mn (20 mg/kg)-dependent augmentation in p38(MAPK) phosphorylation and reduced the Mn (20 mg/kg)-induced caspase activity and F2-isoprostane production. Trolox™ also reversed the Mn-induced motor coordination deficits. These findings are the first to show that long-term exposure to Mn during a critical period of neurodevelopment causes motor coordination dysfunction with parallel increment in oxidative stress markers, p38(MAPK) phosphorylation and caspase activity in the striatum. Moreover, we establish Trolox™ as a potential neuroprotective agent given its efficacy in reversing the Mn-induced neurodevelopmental effects.

Transfer functions for protein signal transduction: application to a model of striatal neural plasticity

We present a novel formulation for biochemical reaction networks in the context of protein signal transduction. The model consists of input-output transfer functions, which are derived from differential equations, using stable equilibria. We select a set of “source” species, which are interpreted as input signals. Signals are transmitted to all other species in the system (the “target” species) with a specific delay and with a specific transmission strength. The delay is computed as the maximal reaction time until a stable equilibrium for the target species is reached, in the context of all other reactions in the system. The transmission strength is the concentration change of the target species. The computed input-output transfer functions can be stored in a matrix, fitted with parameters, and even recalled to build dynamical models on the basis of state changes. By separating the temporal and the magnitudinal domain we can greatly simplify the computational model, circumventing typical problems of complex dynamical systems. The transfer function transformation of biochemical reaction systems can be applied to mass-action kinetic models of signal transduction. The paper shows that this approach yields significant novel insights while remaining a fully testable and executable dynamical model for signal transduction. In particular we can deconstruct the complex system into local transfer functions between individual species. As an example, we examine modularity and signal integration using a published model of striatal neural plasticity. The modularizations that emerge correspond to a known biological distinction between calcium-dependent and cAMP-dependent pathways. Remarkably, we found that overall interconnectedness depends on the magnitude of inputs, with higher connectivity at low input concentrations and significant modularization at moderate to high input concentrations. This general result, which directly follows from the properties of individual transfer functions, contradicts notions of ubiquitous complexity by showing input-dependent signal transmission inactivation.

Biochemical Systems Theory: A Review

Biochemical systems theory (BST) is the foundation for a set of analytical andmodeling tools that facilitate the analysis of dynamic biological systems. This paper depicts major developments in BST up to the current state of the art in 2012. It discusses its rationale, describes the typical strategies and methods of designing, diagnosing, analyzing, and utilizing BST models, and reviews areas of application. The paper is intended as a guide for investigators entering the fascinating field of biological systems analysis and as a resource for practitioners and experts.

In vivo manganese exposure modulates Erk, Akt and Darpp-32 in the striatum of developing rats, and impairs their motor function

Manganese (Mn) is an essential metal for development and metabolism. However, exposures to high Mn levels may be toxic, especially to the central nervous system (CNS). Neurotoxicity is commonly due to occupational or environmental exposures leading to Mn accumulation in the basal ganglia and a Parkinsonian-like disorder. Younger individuals are more susceptible to Mn toxicity. Moreover, early exposure may represent a risk factor for the development of neurodegenerative diseases later in life. The present study was undertaken to investigate the developmental neurotoxicity in an in vivo model of immature rats exposed to Mn (5, 10 and 20 mg/kg; i.p.) from postnatal day 8 (PN8) to PN12. Neurochemical analysis was carried out on PN14. We focused on striatal alterations in intracellular signaling pathways, oxidative stress and cell death. Moreover, motor alterations as a result of early Mn exposure (PN8-12) were evaluated later in life at 3-, 4- and 5-weeks-of-age. Mn altered in a dose-dependent manner the activity of key cell signaling elements. Specifically, Mn increased the phosphorylation of DARPP-32-Thr-34, ERK1/2 and AKT. Additionally, Mn increased reactive oxygen species (ROS) production and caspase activity, and altered mitochondrial respiratory chain complexes I and II activities. Mn (10 and 20 mg/kg) also impaired motor coordination in the 3^rd, 4^th and 5^th week of life. Trolox™, an antioxidant, reversed several of the Mn altered parameters, including the increased ROS production and ERK1/2 phosphorylation. However, Trolox™ failed to reverse the Mn (20 mg/kg)-induced increase in AKT phosphorylation and motor deficits. Additionally, Mn (20 mg/kg) decreased the distance, speed and grooming frequency in an open field test; Trolox™ blocked only the decrease of grooming frequency. Taken together, these results establish that short-term exposure to Mn during a specific developmental window (PN8-12) induces metabolic and neurochemical alterations in the striatum that may modulate later-life behavioral changes. Furthermore, some of the molecular and behavioral events, which are perturbed by early Mn exposure are not directly related to the production of oxidative stress.

Distribution of GABAergic interneurons and dopaminergic cells in the functional territories of the human striatum

Background

The afferent projections of the striatum (caudate nucleus and putamen) are segregated in three territories: associative, sensorimotor and limbic. Striatal interneurons are in part responsible for the integration of these different types of information. Among them, GABAergic interneurons are the most abundant, and can be sorted in three populations according to their content in the calcium binding proteins calretinin (CR), parvalbumin (PV) and calbindin (CB). Conversely, striatal dopaminergic cells (whose role as interneurons is still unclear) are scarce. This study aims to analyze the interneuron distribution in the striatal functional territories, as well as their organization regarding to the striosomal compartment.

Methodology/Principal Findings

We used immunohistochemical methods to visualize CR, PV, CB and tyrosine hydroxylase (TH) positive striatal neurons. The interneuronal distribution was assessed by stereological methods applied to every striatal functional territory. Considering the four cell groups altogether, their density was higher in the associative (2120±91 cells/mm³) than in the sensorimotor (959±47 cells/mm³) or limbic (633±119 cells/mm³) territories. CB- and TH-immunoreactive(-ir) cells were distributed rather homogeneously in the three striatal territories. However, the density of CR and PV interneurons were more abundant in the associative and sensorimotor striatum, respectively. Regarding to their compartmental organization, CR-ir interneurons were frequently found in the border between compartments in the associative and sensorimotor territories, and CB-ir interneurons abounded at the striosome/matrix border in the sensorimotor domain.

Conclusions/Significance

The present study demonstrates that the architecture of the human striatum in terms of its interneuron composition varies in its three functional territories. Furthermore, our data highlight the importance of CR-ir striatal interneurons in the integration of associative information, and the selective role of PV-ir interneurons in the motor territory. On the other hand, the low density of dopaminergic cells casts doubts about their role in the normal human striatum.

Signaling in striatal neurons: the phosphoproteins of reward, addiction, and dyskinesia

The striatum is a deep region of the forebrain involved in action selection, control of movement, and motivation. It receives a convergent excitatory glutamate input from the cerebral cortex and the thalamus, controlled by dopamine (DA) released in response to unexpected rewards and other salient stimuli. Striatal function and its dysfunction in drug addiction or Parkinson's disease depend on the interplay between these neurotransmitters. Signaling cascades in striatal medium-sized spiny neurons (MSNs) involve multiple kinases, phosphatases, and phosphoproteins, some of which are highly enriched in these neurons. They control the properties of ion channels and the plasticity of MSNs, in part through their effects on gene transcription. This chapter summarizes signaling in MSNs and focuses on the regulation of multiple protein phosphatases through DA and glutamate receptors and the role of ERK. It is hypothesized that these pathways are particularly adapted to the specific computing properties of MSNs and the function of the basal ganglia circuits in which they participate.

DARPP-32, Jack of All Trades… Master of Which?

DARPP-32 (PPP1R1B) was discovered as a substrate of cAMP-dependent protein kinase (PKA) enriched in dopamine-innervated brain areas. It is one of three related, PKA-regulated inhibitors of protein phosphatase-1 (PP1). These inhibitors seem to have appeared in early vertebrate ancestors, possibly Gnathostomes. DARPP-32 has additional important biochemical properties including inhibition of PKA when phosphorylated by Cdk5 and regulation by casein kinases 1 and 2. It is highly enriched in specific neuronal populations, especially striatal medium-size spiny neurons. As PP1 inhibitor DARPP-32 amplifies and/or mediates many actions of PKA at the plasma membrane and in the cytoplasm, with a broad spectrum of potential targets and functions. DARPP-32 also undergoes a continuous and tightly regulated cytonuclear shuttling. This trafficking is controlled by phosphorylation of Ser-97, which is necessary for nuclear export. When phosphorylated on Thr-34 and dephosphorylated on Ser-97, DARPP-32 can inhibit PP1 in the nucleus and modulate signaling pathways involved in the regulation of chromatin response. Recent work with multiple transgenic and knockout mutant mice has allowed the dissection of DARPP-32 function in striato-nigral and striato-pallidal neurons. It is implicated in the action of therapeutic and abused psychoactive drugs, in prefrontal cortex function, and in sexual behavior. However, the contribution of DARPP-32 in human behavior remains poorly understood. Post-mortem studies in humans suggest possible alterations of DARPP-32 levels in schizophrenia and bipolar disorder. Genetic studies have revealed a polymorphism with possible association with psychological and psychopathological traits. In addition, a short isoform of DARPP-32, t-DARPP, plays a role in cancer, indicating additional signaling properties. Thus, DARPP-32 is a non-essential but tightly regulated signaling hub molecule which may improve the general performance of the neuronal circuits in which it is expressed.

Postsynaptic signal transduction models for long-term potentiation and depression

More than a hundred biochemical species, activated by neurotransmitters binding to transmembrane receptors, are important in long-term potentiation (LTP) and long-term depression (LTD). To investigate which species and interactions are critical for synaptic plasticity, many computational postsynaptic signal transduction models have been developed. The models range from simple models with a single reversible reaction to detailed models with several hundred kinetic reactions. In this study, more than a hundred models are reviewed, and their features are compared and contrasted so that similarities and differences are more readily apparent. The models are classified according to the type of synaptic plasticity that is modeled (LTP or LTD) and whether they include diffusion or electrophysiological phenomena. Other characteristics that discriminate the models include the phase of synaptic plasticity modeled (induction, expression, or maintenance) and the simulation method used (deterministic or stochastic). We find that models are becoming increasingly sophisticated, by including stochastic properties, integrating with electrophysiological properties of entire neurons, or incorporating diffusion of signaling molecules. Simpler models continue to be developed because they are computationally efficient and allow theoretical analysis. The more complex models permit investigation of mechanisms underlying specific properties and experimental verification of model predictions. Nonetheless, it is difficult to fully comprehend the evolution of these models because (1) several models are not described in detail in the publications, (2) only a few models are provided in existing model databases, and (3) comparison to previous models is lacking. We conclude that the value of these models for understanding molecular mechanisms of synaptic plasticity is increasing and will be enhanced further with more complete descriptions and sharing of the published models.