Structural determinants of PINK1 topology and dual subcellular distribution

<p>Abstract</p> <p>Background</p> <p>PINK1 is a mitochondria-targeted kinase that constitutively localizes to both the mitochondria and the cytosol. The mechanism of how PINK1 achieves cytosolic localization following mitochondrial processing remains unknown. Understanding PINK1 subcellular localization will give us insights into PINK1 functions and how mutations in PINK1 lead to Parkinson's disease. We asked how the mitochondrial localization signal, the transmembrane domain, and the kinase domain participate in PINK1 localization.</p> <p>Results</p> <p>We confirmed that PINK1 mitochondrial targeting signal is responsible for mitochondrial localization. Once inside the mitochondria, we found that both PINK1 transmembrane and kinase domain are important for membrane tethering and cytosolic-facing topology. We also showed that PINK1 dual subcellular distribution requires both Hsp90 interaction with the kinase domain and the proteolysis at a cleavage site downstream of the transmembrane domain because removal of this cleavage site completely abolished cytosolic PINK1. In addition, the disruption of the Hsp90-PINK1 interaction increased mitochondrial PINK1 level.</p> <p>Conclusion</p> <p>Together, we believe that once PINK1 enters the mitochondria, PINK1 adopts a tethered topology because the transmembrane domain and the kinase domain prevent PINK1 forward movement into the mitochondria. Subsequent proteolysis downstream of the transmembrane domain then releases PINK1 for retrograde movement while PINK1 kinase domain interacts with Hsp90 chaperone. The significance of this dual localization could mean that PINK1 has compartmental-specific functions.</p

Coordinated output control of multiple distributed generation schemes

International audienceThis paper presents candidate strategies for the coordinated output control of multiple distributed generation schemes. The proposed strategies are underpinned by power flow sensitivity factors and allow real-time knowledge of power system thermal ratings to be utilised. This could be of value in situations where distribution network power flows require management as a result of distributed generation proliferation. Through off-line open-loop simulations, using historical data from a section of the UK distribution network, the candidate strategies are evaluated against a benchmark control solution in terms of annual energy yields, component losses and voltages. Furthermore, the individual generator annual energy yields and generator-apportioned losses are used to assess the net present values of candidate control strategies to distributed generation developers. Nomenclature C 1,2,3 Variable costs (£M) C control Cost of the distributed generator output control system (£M

Scenario generation of aggregated wind, photovoltaics and small hydro production for power systems applications

This paper proposes a methodology for an efficient generation of correlated scenarios of Wind, Photovoltaics (PV) and small Hydro production considering the power system application at hand. The merits of scenarios obtained from a direct probabilistic forecast of the aggregated production are compared with those of scenarios arising from separate production forecasts for each energy source, the correlations of which are modeled in a later stage with a multivariate copula. It is found that scenarios generated from separate forecasts reproduce globally better the variability of a multi-source aggregated production. Aggregating renewable power plants can potentially mitigate their uncertainty and improve their reliability when they offer regulation services. In this context, the first application of scenarios consists in devising an optimal day-ahead reserve bid made by a Wind-PV-Hydro Virtual Power Plant (VPP). Scenarios are fed into a two-stage stochastic optimization model, with chance-constraints to minimize the probability of failing to deploy reserve in real-time. Results of a case study show that scenarios generated by separately forecasting the production of each energy source leads to a higher Conditional Value at Risk than scenarios from direct aggregated forecasting. The alternative forecasting methods can also significantly affect the scheduling of future power systems with high penetration of weather-dependent renewable plants. The generated scenarios have a second application here as the inputs of a two-stage stochastic unit commitment model. The case study demonstrates that the direct forecast of aggregated production can effectively reduce the system operational cost, mainly through better covering the extreme cases. The comprehensive application-based assessment of scenario generation methodologies in this paper informs the decision-makers on the optimal way to generate short-term scenarios of aggregated RES production according to their risk aversion and to the contribution of each source in the aggregation

Active Management of MV and LV Distribution Networks

International audienceThe proliferation of distributed generation (DG) is expected to lead to a change in philosophy in the manner that distribution networks are managed and operated. It is envisaged that distribution networks will be transformed from passive to active entities in order to accommodate the connection of DG. This paper presents current research at Durham University relating to the active management of distribution networks at MV and LV levels. A dynamic thermal rating system has been proposed for the control of DG at the MV level. Furthermore, a multi-agent system-based distributed control approach has been presented for the coordinated control of micro-generators, energy storage units and controllable loads at the LV level

Short-term forecast of automatic frequency restoration reserve from a renewable energy based virtual power plant

This paper presents the initial findings on a new forecast approach for ancillary services delivered by aggregated renewable power plants. The increasing penetration of distributed variable generators challenges grid reliability. Wind and photovoltaic power plants are technically able to provide ancillary services, but their stochastic behavior currently impedes their integration into reserve mechanisms. A methodology is developed to forecast the flexibility that a wind-photovoltaic aggregate can provide. A bivariate Kernel Density Estimator forecasts the probability to provide reserve. The methodology is tested on a case study where volumes of automatic Frequency Restoration Reserve (aFRR) are forecasted on a day-ahead horizon. It is found that the wind-photovoltaic aggregate can dedicate a limited share of its forecast production to aFRR. The frequency of insufficient reserve capacity is assessed, by comparing the capacities offered with the measured production

Investigation into the influence of environmental conditions on power system ratings

International audienceThis article presents research that seeks to assist distribution network operators in the adoption of real-time thermal rating (RTR) systems. The exploitation of power system rating variations is challenging because of the complex nature of environmental conditions such as wind speed. The adoption of an RTR system may overcome this challenge and offers perceived benefits such as increased distributed generation (DG) accommodation and avoidance of component damage or premature ageing. Simulations, using lumped parameter component models, are used to investigate the influence of environmental conditions on overhead line, electric cable, and power transformer ratings. Key findings showed that the average rating of overhead lines, electric cables, and power transformers ranged from 1.70 to 2.53, 1.00 to 1.06, and 1.06 to 1.10 times the static rating, respectively. Since overhead lines were found to have the greatest potential for rating exploitation, the influence of environmental conditions on four overhead line types was investigated and it was shown that the value of an RTR system is location dependent. Furthermore, the additional annual energy yield from DG that could potentially be accommodated through deployment of an RTR system was found to be 54 per cent for the case considered

A subcellular analysis of genetic modulation of PINK1 on mitochondrial alterations, autophagy and cell death

Mutations in the PTEN-induced putative kinase1 (PINK1) represent the second most frequent cause of autosomal recessive Parkinson’s disease. The PINK1 protein mainly localizes to mitochondria and interacts with a variety of proteins, including the pro-autophagy protein beclin1 and the ubiquitin-ligase parkin. Upon stress conditions, PINK1 is known to recruit parkin at the surface of dysfunctional mitochondria and to activate the mitophagy cascade. Aim of this study was to use a simple and highly reproducible catecholamine cell model and transmission electron microscopy to characterize whether PINK1 could affect mitochondrial homeostasis, the recruitment of specific proteins at mitochondria, mitophagy and apoptosis. Samples were analyzed both in baseline conditions and following treatment with methamphetamine (METH), a neurotoxic compound which strongly activates autophagy and produces mitochondrial damage. Our data provide robust sub-cellular evidence that the modulation of PINK1 levels dramatically affects the morphology and number of mitochondria and the amount of cell death. In particular, especially upon METH exposure, PINK1 is able to increase the total number of mitochondria, concurrently recruit beclin1, parkin and ubiquitin and enhance the clearance of damaged mitochondria. In the absence of functional PINK1 and upon autophagy stress, we observe a failure of the autophagy system at large, with marked accumulation of dysfunctional mitochondria and dramatic increase of apoptotic cell death. These findings highlight the strong neuroprotective role of PINK1 as a key protein in the surveillance and regulation of mitochondrial homeostasis

The use of chromosome microarray analysis as a first-line test in low risk pregnancies

OBJECTIVE: To assess the feasibility of offering array-based comparative genomic hybridization testing for prenatal diagnosis as a first-line test, a prospective study was performed, comparing the results achieved from array comparative genomic hybridization (aCGH) with those obtained from conventional karyotype. METHOD: Women undergoing amniocentesis or chorionic villus sampling were offered aCGH analysis. A total of 1037 prenatal samples were processed in parallel using both aCGH and G-banding for standard karyotyping. Specimen types included amniotic fluid (89.0%), chorionic villus sampling (9.5%) and cultured amniocytes (1.5%). RESULTS: Chromosomal abnormalities were identified in 34 (3.3%) samples; in 9 out of 34 cases (26.5%) aCGH detected pathogenic copy number variations that would not have been found if only a standard karyotype had been performed. aCGH was also able to detect chromosomal mosaicism at as low as a 10% level. There was complete concordance between the conventional karyotyping and aCGH results, except for 2 cases that were only correctly diagnosed by aCGH. CONCLUSIONS: This study demonstrates that aCGH represents an improved diagnostic tool for prenatal detection of chromosomal abnormalities. Although larger studies are needed, our results provide further evidence on the feasibility of introducing aCGH as a first-line diagnostic test in routine prenatal diagnosis practice