Signalling of cAMP at the centrosome

The compartmentalisation of cAMP/PKA signalling pathway within specific regions of the cell plays a critical role to achieve the specificity of response. Adenylyl cyclases (AC) are localised at discrete regions of the plasma membrane and phosphodiesterases (PDEs), the only enzymes that degrade cAMP, have been shown to be pivotal in generating spatially restricted pools of cAMP, therefore underpinning spatial control of this second messenger signal. In addition, A-kinase anchoring proteins (AKAPs) are of key importance as they anchor PKA in proximity of its specific targets, thus favouring target selective phosphorylation. Such organisation leads to local activation of PKA subsets through the generation of confined intracellular gradients of cAMP. Interestingly it has been shown that AKAP450 localises to the centrosome, the major microtubule-organising centre, where it functions as a ‘multi-scaffolding’ protein by simultaneously associating PKA with PDE4D3 as well as other kinases and phosphatases. Beside this a large body of evidence suggests that the centrosome is essential for the regulation of the cell cycle progression by acting as a scaffold protein for a network of signalling pathways which in turn trigger cellular division. In the past few years the development of FRET-based sensors has allowed the study of cAMP dynamics with high spatial-temporal resolution. By using this approach it is now possible to monitor real-time fluctuations of cAMP and PKA activity in distinct subcellular compartments and to investigate their physiological role. The aim of the research presented in this dissertation is to exploit FRET-based sensor to investigate the signalling of cAMP at the centrosome and to define the role of PDE4D3 anchored to AKAP450 in shaping a cAMP pool in such specific compartment. The centrosomal AKAP450/PKA/PDE4D3 macromolecular complex may play a role in the control of cell cycle progression. To this purpose a CHO clone stably expressing the FRET sensor based on PKA was generated. As expected fluorescence microscopy analysis of this clone indicated that the sensor anchors to endogenous centrosomal AKAPs. Further real-time imaging of basal cAMP provided evidence that the centrosome is a domain with lower cAMP concentration as compared to the bulk cytosol and that PDE4D3 activity is required to maintain a low cAMP level in the centrosomal area. Interestingly the same cells challenged with the cAMP raising agent forskolin show a larger FRET change at the centrosome as compared to the bulk cytosol. By using the unimolecular FRET EPAC-based sensor for cAMP, targeted to the centrosome, it was possible to exclude that the level of cAMP generated at the centrosome by forskolin was higher than the level of cAMP generated in the cytosol. Thus, it has been hypothesised that anchoring of PKA to AKAP450 lowers the activation constant of the enzyme leading to a higher FRET change at the centrosome as compare to the bulk cytosol. This hypothesis has been confirmed by expressing in the cytosol the fragment of AKAP450 that anchors PKA and by showing that binding of PKA to the cytosolic fragment also results in increased sensitivity of the enzyme to cAMP. Eventually analysis of PKA activity, by using a FRET-based A-kinase activity reporter (AKAR), indicated that anchoring of PKA to the cytosolic fragment of AKAP450 accounts also for an increased PKA activity. The molecular mechanism involved in the increased sensitivity of PKA-bound to AKAP450 was also investigated. Interestingly anchoring of PKA to AKAP450 increases the auto-phosphorylation of PKA. Generation of a non-phosphorylatable version of PKA-RII subunit (mutRII) and further generation of a CHO clone stably expressing the mutPKA FRET based sensor strongly indicates that the high sensitivity of PKA bound to AKAP450 is mediated by the auto-phosphorylation site and more specifically the binding of PKA to AKAP450 seems to favour the auto-phosphorylation of PKA. Finally the role of AKAP450/PKA/PDE4D3 macromolecular complex in the regulation of cell cycle progression was analysed. Displacement of endogenous PDE4D3 from the centrosome by over-expression of a catalytically dead version of PDE4D3 (dnPDE4D3), results not only in the abolishment of difference in cAMP concentration between centrosome and cytosol, but also in an altered cell cycle progression, suggesting that PDE4D3 plays a key role in the regulation of the cell cycle. In conclusion this study provided evidence for a novel mechanism by which anchoring of PKA to AKAPs modulate the activation constant of the enzyme, thereby providing a mean to regulate enzyme activity locally

Cardiac hypertrophy is inhibited by a local pool of cAMP regulated by phosphodiesterase 2

Rationale: Chronic elevation of 3'-5'-cyclic adenosine monophosphate (cAMP) levels has been associated with cardiac remodelling and cardiac hypertrophy. However, enhancement of particular aspects of cAMP/protein kinase A (PKA) signalling appears to be beneficial for the failing heart. cAMP is a pleiotropic second messenger with the ability to generate multiple functional outcomes in response to different extracellular stimuli with strict fidelity, a feature that relies on the spatial segregation of the cAMP pathway components in signalling microdomains. Objective: How individual cAMP microdomains impact on cardiac pathophysiology remains largely to be established. The cAMP-degrading enzymes phosphodiesterases (PDEs) play a key role in shaping local changes in cAMP. Here we investigated the effect of specific inhibition of selected PDEs on cardiac myocyte hypertrophic growth. Methods and Results: Using pharmacological and genetic manipulation of PDE activity we found that the rise in cAMP resulting from inhibition of PDE3 and PDE4 induces hypertrophy whereas increasing cAMP levels via PDE2 inhibition is anti-hypertrophic. By real-time imaging of cAMP levels in intact myocytes and selective displacement of PKA isoforms we demonstrate that the anti-hypertrophic effect of PDE2 inhibition involves the generation of a local pool of cAMP and activation of a PKA type II subset leading to phosphorylation of the nuclear factor of activated T cells (NFAT). Conclusions: Different cAMP pools have opposing effects on cardiac myocyte cell size. PDE2 emerges as a novel key regulator of cardiac hypertrophy in vitro and in vivo and its inhibition may have therapeutic applications

PKA and PDE4D3 anchoring to AKAP9 provides distinct regulation of cAMP signals at the centrosome

Previous work has shown that the protein kinase A (PKA)–regulated phosphodiesterase (PDE) 4D3 binds to A kinase–anchoring proteins (AKAPs). One such protein, AKAP9, localizes to the centrosome. In this paper, we investigate whether a PKA–PDE4D3–AKAP9 complex can generate spatial compartmentalization of cyclic adenosine monophosphate (cAMP) signaling at the centrosome. Real-time imaging of fluorescence resonance energy transfer reporters shows that centrosomal PDE4D3 modulated a dynamic microdomain within which cAMP concentration selectively changed over the cell cycle. AKAP9-anchored, centrosomal PKA showed a reduced activation threshold as a consequence of increased autophosphorylation of its regulatory subunit at S114. Finally, disruption of the centrosomal cAMP microdomain by local displacement of PDE4D3 impaired cell cycle progression as a result of accumulation of cells in prophase. Our findings describe a novel mechanism of PKA activity regulation that relies on binding to AKAPs and consequent modulation of the enzyme activation threshold rather than on overall changes in cAMP levels. Further, we provide for the first time direct evidence that control of cell cycle progression relies on unique regulation of centrosomal cAMP/PKA signals

Compartmentalized Phosphodiesterase-2 Activity Blunts β-Adrenergic Cardiac Inotropy via an NO/cGMP-Dependent Pathway

β-Adrenergic signaling via cAMP generation and PKA activation mediates the positive inotropic effect of catecholamines on heart cells. Given the large diversity of protein kinase A targets within cardiac cells, a precisely regulated and confined activity of such signaling pathway is essential for specificity of response. Phosphodiesterases (PDEs) are the only route for degrading cAMP and are thus poised to regulate intracellular cAMP gradients. Their spatial confinement to discrete compartments and functional coupling to individual receptors provides an efficient way to control local [cAMP] i in a stimulus-specific manner. By performing real-time imaging of cyclic nucleotides in living ventriculocytes we identify a prominent role of PDE2 in selectively shaping the cAMP response to catecholamines via a pathway involving β 3 -adrenergic receptors, NO generation and cGMP production. In cardiac myocytes, PDE2, being tightly coupled to the pool of adenylyl cyclases activated by β-adrenergic receptor stimulation, coordinates cGMP and cAMP signaling in a novel feedback control loop of the β-adrenergic pathway. In this, activation of β 3 -adrenergic receptors counteracts cAMP generation obtained via stimulation of β 1 /β 2 -adrenoceptors. Our study illustrates the key role of compartmentalized PDE2 in the control of catecholamine-generated cAMP and furthers our understanding of localized cAMP signaling

PGE1 stimulation of HEK293 cells generates multiple contiguous domains with different [cAMP]: role of compartmentalized phosphodiesterases

There is a growing appreciation that the cyclic adenosine monophosphate (cAMP)–protein kinase A (PKA) signaling pathway is organized to form transduction units that function to deliver specific messages. Such organization results in the local activation of PKA subsets through the generation of confined intracellular gradients of cAMP, but the mechanisms responsible for limiting the diffusion of cAMP largely remain to be clarified. In this study, by performing real-time imaging of cAMP, we show that prostaglandin 1 stimulation generates multiple contiguous, intracellular domains with different cAMP concentration in human embryonic kidney 293 cells. By using pharmacological and genetic manipulation of phosphodiesterases (PDEs), we demonstrate that compartmentalized PDE4B and PDE4D are responsible for selectively modulating the concentration of cAMP in individual subcellular compartments. We propose a model whereby compartmentalized PDEs, rather than representing an enzymatic barrier to cAMP diffusion, act as a sink to drain the second messenger from discrete locations, resulting in multiple and simultaneous domains with different cAMP concentrations irrespective of their distance from the site of cAMP synthesis

DOPAL initiates αSynuclein-dependent impaired proteostasis and degeneration of neuronal projections in Parkinson’s disease

Dopamine dyshomeostasis has been acknowledged among the determinants of nigrostriatal neuron degeneration in Parkinson’s disease (PD). Several studies in experimental models and postmortem PD patients underlined increasing levels of the dopamine metabolite 3,4-dihydroxyphenylacetaldehyde (DOPAL), which is highly reactive towards proteins. DOPAL has been shown to covalently modify the presynaptic protein αSynuclein (αSyn), whose misfolding and aggregation represent a major trait of PD pathology, triggering αSyn oligomerization in dopaminergic neurons. Here, we demonstrated that DOPAL elicits αSyn accumulation and hampers αSyn clearance in primary neurons. DOPAL-induced αSyn buildup lessens neuronal resilience, compromises synaptic integrity, and overwhelms protein quality control pathways in neurites. The progressive decline of neuronal homeostasis further leads to dopaminergic neuron loss and motor impairment, as showed in in vivo models. Finally, we developed a specific antibody which detected increased DOPAL-modified αSyn in human striatal tissues from idiopathic PD patients, corroborating the translational relevance of αSyn-DOPAL interplay in PD neurodegeneration

Cyclic Nucleotide Phosphodiesterases and Compartmentation in Normal and Diseased Heart

International audienceCyclic nucleotide phosphodiesterases (PDEs) degrade the second messengers cAMP and cGMP, thereby regulating multiple aspects of cardiac function. This highly diverse class of enzymes encoded by 21 genes encompasses 11 families which are not only responsible for the termination of cyclic nucleotide signalling, but are also involved in the generation of dynamic microdomains of cAMP and cGMP controlling specific cell functions in response to various neurohormonal stimuli. In myocardium, the PDE3 and PDE4 families are predominant to degrade cAMP and thereby regulate cardiac excitation-contraction coupling. PDE3 inhibitors are positive inotropes and vasodilators in human, but their use is limited to acute heart failure and intermittent claudication. PDE5 is particularly important to degrade cGMP in vascular smooth muscle, and PDE5 inhibitors are used to treat erectile dysfunction and pulmonary hypertension. However, these drugs do not seem efficient in heart failure with preserved ejection fraction. There is experimental evidence that these PDEs as well as other PDE families including PDE1, PDE2 and PDE9 may play important roles in cardiac diseases such as hypertrophy and heart failure. After a brief presentation of the cyclic nucleotide pathways in cardiac cells and the major characteristics of the PDE superfamily, this chapter will present their role in cyclic nucleotide compartmentation and the current use of PDE inhibitors in cardiac diseases together with the recent research progresses that could lead to a better exploitation of the therapeutic potential of these enzymes in the future

Event reconstruction for KM3NeT/ORCA using convolutional neural networks

The KM3NeT research infrastructure is currently under construction at two locations in the Mediterranean Sea. The KM3NeT/ORCA water-Cherenkov neutrino detector off the French coast will instrument several megatons of seawater with photosensors. Its main objective is the determination of the neutrino mass ordering. This work aims at demonstrating the general applicability of deep convolutional neural networks to neutrino telescopes, using simulated datasets for the KM3NeT/ORCA detector as an example. To this end, the networks are employed to achieve reconstruction and classification tasks that constitute an alternative to the analysis pipeline presented for KM3NeT/ORCA in the KM3NeT Letter of Intent. They are used to infer event reconstruction estimates for the energy, the direction, and the interaction point of incident neutrinos. The spatial distribution of Cherenkov light generated by charged particles induced in neutrino interactions is classified as shower- or track-like, and the main background processes associated with the detection of atmospheric neutrinos are recognized. Performance comparisons to machine-learning classification and maximum-likelihood reconstruction algorithms previously developed for KM3NeT/ORCA are provided. It is shown that this application of deep convolutional neural networks to simulated datasets for a large-volume neutrino telescope yields competitive reconstruction results and performance improvements with respect to classical approaches

Event reconstruction for KM3NeT/ORCA using convolutional neural networks

The KM3NeT research infrastructure is currently under construction at two locations in the Mediterranean Sea. The KM3NeT/ORCA water-Cherenkov neutrino de tector off the French coast will instrument several megatons of seawater with photosensors. Its main objective is the determination of the neutrino mass ordering. This work aims at demonstrating the general applicability of deep convolutional neural networks to neutrino telescopes, using simulated datasets for the KM3NeT/ORCA detector as an example. To this end, the networks are employed to achieve reconstruction and classification tasks that constitute an alternative to the analysis pipeline presented for KM3NeT/ORCA in the KM3NeT Letter of Intent. They are used to infer event reconstruction estimates for the energy, the direction, and the interaction point of incident neutrinos. The spatial distribution of Cherenkov light generated by charged particles induced in neutrino interactions is classified as shower-or track-like, and the main background processes associated with the detection of atmospheric neutrinos are recognized. Performance comparisons to machine-learning classification and maximum-likelihood reconstruction algorithms previously developed for KM3NeT/ORCA are provided. It is shown that this application of deep convolutional neural networks to simulated datasets for a large-volume neutrino telescope yields competitive reconstruction results and performance improvements with respect to classical approaches