Literature DB >> 30988163

Inhibition of the deubiquitinase USP8 corrects a Drosophila PINK1 model of mitochondria dysfunction.

Sophia von Stockum1, Alvaro Sanchez-Martinez2, Samantha Corrà3,4, Joy Chakraborty3, Elena Marchesan1, Lisa Locatello3, Caterina Da Rè3,4, Paola Cusumano3,4, Federico Caicci3, Vanni Ferrari3, Rodolfo Costa3,4, Luigi Bubacco3, Maria Berica Rasotto3, Ildiko Szabo3, Alexander J Whitworth2, Luca Scorrano3,5, Elena Ziviani6,3.   

Abstract

Aberrant mitochondrial dynamics disrupts mitochondrial function and contributes to disease conditions. A targeted RNA interference screen for deubiquitinating enzymes (DUBs) affecting protein levels of multifunctional mitochondrial fusion protein Mitofusin (MFN) identified USP8 prominently influencing MFN levels. Genetic and pharmacological inhibition of USP8 normalized the elevated MFN protein levels observed in PINK1 and Parkin-deficient models. This correlated with improved mitochondrial function, locomotor performance and life span, and prevented dopaminergic neurons loss in Drosophila PINK1 KO flies. We identified a novel target antagonizing pathologically elevated MFN levels, mitochondrial dysfunction, and dopaminergic neuron loss of a Drosophila model of mitochondrial dysfunction.
© 2019 von Stockum et al.

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Year:  2019        PMID: 30988163      PMCID: PMC6467245          DOI: 10.26508/lsa.201900392

Source DB:  PubMed          Journal:  Life Sci Alliance        ISSN: 2575-1077


Introduction

Mitochondria dysfunction plays critical role in neurodegenerative conditions affecting the elderly, such as Parkinson’s disease (PD) (Moore et al, 2005; Bueler, 2009; Vives-Bauza et al, 2010a; Ryan et al, 2015). Mitochondria function directly correlates with mitochondria dynamics and balanced remodeling of the mitochondrial network through fission and fusion events to control mitochondria shape and ultrastucture. Intuitively, fusion maintains the mitochondrial network and allows intermixing of matrix contents, such as mtDNA and metabolites; fission is needed to populate new cells with new mitochondria (Twig et al, 2008b; Gomes & Scorrano, 2008; Malena et al, 2009) and plays a substantial role in the mitochondria quality control. A key aspect of mitochondrial quality control is a well-characterized process called mitophagy that segregates and selectively eliminates damaged mitochondria via autophagy (Twig et al, 2008a; Twig & Shirihai, 2011). During stress-induced mitophagy, the cytoplasmic protein Parkin, mutated in familial PD and encoding an E3 ubiquitin ligase (Shimura et al, 2000), translocates in a PINK1-dependent manner to dysfunctional mitochondria (Narendra et al, 2008; Vives-Bauza et al, 2010b; Ziviani et al, 2010). In this process, kinase PINK1, also mutated in familial PD (Silvestri et al, 2005), phosphorylates Parkin (Sha et al, 2010), its targets (Wang et al, 2011; Chen & Dorn, 2013), and ubiquitin itself (Koyano et al, 2014) promoting Parkin translocation (Narendra et al, 2010; Ziviani et al, 2010) and Parkin activity (Lazarou et al, 2013; Koyano et al, 2014; Zhang et al, 2014). On depolarized mitochondria, Parkin ubiquitinates the mitochondrial pro-fusion protein Mitofusin (MFN) (Gegg et al, 2010; Poole et al, 2010; Tanaka et al, 2010; Ziviani et al, 2010; Sarraf et al, 2013) leading to p97/VCP–mediated retrotranslocation and proteosomal degradation (Tanaka et al, 2010). In addition, Parkin ubiquitinates the mitochondrial protein translocase TOM20, mitochondrial VDAC/Porin and Fis1 (Sarraf et al, 2013), and it also promotes the degradation of Miro (Wang et al, 2011), a protein that couples mitochondria to microtubules. Selected mitochondria are, therefore, deprived of their pro-fusion protein MFN, isolating them from the mitochondrial network, before degradation via autophagy. This mechanism is consistent with observations showing that mitochondria cluster around the perinuclear area (Vives-Bauza et al, 2010b) and fragment before mitophagy (Twig et al, 2008a; Poole et al, 2008). Genetic studies in Drosophila showed that down-regulation of MFN or promotion of mitochondrial fission by expressing pro-fission protein DRP1 rescues Parkin KO phenotypes, and those of kinase PINK1 (Deng et al, 2008; Poole et al, 2008), which acts upstream of Parkin (Clark et al, 2006; Park et al, 2006; Yang et al, 2006). This genetic interaction can be in part explained biochemically by the fact that Parkin ubiquitinates MFN to control its steady-state levels (Gegg et al, 2010; Tanaka et al, 2010; Ziviani et al, 2010; Rakovic et al, 2011) that are elevated in Parkin and PINK1 KO models (Ziviani et al, 2010). Thus, interventions that restore MFN levels can ameliorate Parkin and PINK1 phenotypes, presumably by impinging on the numerous MFN functions that in the fruit fly include both promotion of fusion and ER–mitochondria crosstalk (Debattisti et al, 2014). To identify other mechanisms regulating MFN levels, we performed an RNA interference screen for deubiquitinating enzymes (DUBs) that affect steady-state levels of MFN. DUBs participate in important reversible signaling pathways (Salmena & Pandolfi, 2007) and are attractive druggable candidates (Hussain et al, 2009; Colland, 2010). We identified USP8, an evolutionary conserved DUB whose down-regulation correlates with decreased MFN levels. USP8 has previously been linked to PINK1/Parkin–dependent mitophagy in cell culture and under intoxicating conditions (Durcan et al, 2014), but no in vivo studies have been reported. Here, we demonstrate that in vivo under basal conditions, genetic and pharmacological inhibition of USP8 ameliorates Drosophila phenotypes deriving from loss of function of PINK1 and Parkin.

Results

A targeted siRNA screening identifies DUBs affecting MFN protein levels

Steady-state levels of MFN protein in Drosophila PINK1 or Parkin KO background are increased (Ziviani et al, 2010), and interventions that decrease MFN levels can ameliorate Drosophila PINK1 and Parkin phenotypes (Celardo et al, 2016; Deng et al, 2008; Poole et al, 2008). Given the importance of MFN in inter-organellar communication (Cosson et al, 2012; de Brito & Scorrano, 2008; Filadi et al, 2015) and mitophagy (Chen & Dorn, 2013), we set out to identify regulators of its steady-state levels. We designed an unbiased loss-of-function screen using dsRNA to inhibit the expression of 35 known or predicted fly DUBs. Fly DUBs were identified by domain similarity and based on the list of 79 human DUBs (Dupont et al, 2009) (Table 1). We transiently expressed flag-tagged MFN in S2R+ cells to mimic pathologically elevated MFN and down-regulated each of the 35 DUBs. To assess the effect of DUB silencing on steady-state MFN levels, we performed Western blotting analysis on cell lysates and quantified the levels of unmodified MFN normalized for the loading control and expressed it as fold change (Fig 1A). Flag-tagged MFN exhibited mitochondrial subcellular localization, and its expression in S2R+ cells resulted in an elongated mitochondrial network (Fig S1A). We identified two DUBs whose down-regulation resulted in decreased MFN levels (CG5798/USP8 and CG5384/USP14) and two DUBs, whose down-regulation resulted in increased MFN levels (CG5505/USP36, CG2904/Echinus) (Fig 1B). Down-regulation of Parkin or PINK1 increased MFN levels, as previously described (Tanaka et al, 2010; Ziviani et al, 2010). Of the two DUBs causing decreased MFN levels, USP8 was the highest scoring hit that decreased MFN levels (Fig 1B). USP8 interacts with many substrates such as the epidermal growth factor receptor, an essential regulator of proliferation and differentiation, and regulates endosomal trafficking by ubiquitin-mediated sorting of the endocytosed cargoes (Mizuno et al, 2005; Row et al, 2006; Williams & Urbe, 2007). Moreover, USP8 knockdown protects from α-synuclein–induced locomotor deficits and cell loss in an α-synuclein fly model of PD (Alexopoulou et al, 2016). It was also shown that USP8 regulates induced mitophagy by controlling Parkin recruitment to depolarized mitochondria after CCCP treatment (Durcan et al, 2014). More recently, it has been found that it can regulate basal autophagy in the absence of CCCP, although its role has not been thoroughly characterized in this process and it is controversial (Jacomin et al, 2015). USP8 is also highly expressed in the brain and up-regulated in neurodegenerative conditions (Paiardi et al, 2014), which makes it of neurological interest.
Table 1.

Complete list of the 75 human known or predicted DUBs and their fly homologue, when known or predicted, based on sequence similarity. Where available, Entrez/PubMed gene ID and fly gene name is provided.

Gene nameGene IDFly homologueFly gene name
UCHL17345CG4265
UCHL37347CG4265
BAP18314CG8445CALYPSO
UCHL5/UCH3751377CG3431
DUB3377630CG5505USP36/SCRAWNY
USP17398CG15817USP1
USP29099CG14619
USP39960CG5798UBPY/USP8
USP47375CG8334
USP58078CG12082
USP69098CG8334
USP7/HAUSP7874CG1490USP7
USP8/USPY9101CG5798UBPY/USP8
USP9X/FAM8239CG1945FAT FACETS
USP109100CG32479
USP118237CG8334
USP12219333CG7023USP12-46
USP138975CG12082USP5
USP149097CG5384
USP159958CG12082
USP1610600CG4165USP16-45
USP1811274CG5486USP64E/USP47
USP1910869CG8334
USP2010868CG8494
USP2127005CG14619
USP2223326N/A
USP2423358CG1945FAT FACETS
USP2529761CG5794PUF/USP34
USP2683844CG5798USP8/USPY
USP27X389856CG4166NOT
USP2857646CG5794PUF/USP34
USP2957663CG5798USP8/USPY
USP3084749CG3016
USP3157478CG30421USP15-31
USP3284669CG8334
USP3323032CG8494USP20-33
USP349736CG5794PUF/USP34
USP3557558CG8830DUBAI
USP3657602CG5505
USP3757695CG5798USP8/USPY
USP3884640CG8830DUBAI
USP3910713CG7288
USP4055230CG5486USP64E/USP47
USP41373856CG5486USP64E/USP47
USP4284132CG5505USP36/SCRAWNY
USP43124739CG30421USP15-31
USP4484101CG5798USP8/USPY
USP4585015CG4165USP16-45
USP4664854CG7023USP12-46
USP4755031CG5486USP64E/USP47
USP4884196CG1490USP7
USP4925862CG5798USP8/USPY
USP50373509CG5798USP8/USPY
USP51158880CG4166NOT
USP529924CG8232PAN2
USP5354532CG2904ECHINUS
USP54159195CG2904ECHINUS
OTUB155611CG4968
CYLD1540CG5603
TNFAIP3/A207128CG9448TRABID
OTUD1220213CG6091
YOD155432CG4603
OTUD323252CG6091
OTUD454726CG12743OTU
OTUD6A139562CG7857
OTUD6B51633CG7857
OTUD7A161725CG9448TRABID
OTUD7B56957CG9448TRABID
TRABID54764CG9448TRABID
ATXN34287CG13379
ATX3LN.A.CG13379
JOSD19929CG3781
JOSD2126119CG3781
AMSH/STAMBP10617CG2224
AMSH-LP57559CG2224
Figure 1.

A targeted siRNA screening identified DUB USP8 whose down-regulation correlates with decreased MFN levels.

(A) siRNA screen to identify DUBs affecting pathologically elevated MFN protein levels. Protein extracts from Drosophila S2R+ cells expressing equal amounts of Flag-MFN and treated with 2 μg dsRNA probe were separated by SDS–PAGE and immunoblotted using an anti-Flag antibody. Densitometric analysis of MFN signal normalized to loading control and expressed as fold change (FC) versus control dsRNA was used as read out to identify DUBs whose down-regulation affects MFN protein levels. (B) Volcano plot constructed by plotting the negative log of the FDR corrected P value (qval) on the y-axis against the log of the FC calculated in (A). Those points that are found toward the top of the plot far to either the left- or right-hand side represent values with large FC and high statistical significance. A threshold of P < 0.05 and 0.75 < FC > 1.3 led to the identification of four DUBs whose down-regulation resulted in either decreased MFN levels (USP8 FC = 0.345 ± 0.04, qval = 0.024; USP14 FC = 0.537 ± 0.06, qval = 0.044) or increased MFN levels (Echinus FC = 1.784 ± 0.13, qval = 0.024; USP36 FC = 1.524 ± 0.12, qval = 0.040). Down-regulation of PINK1 or Parkin led to increased MFN levels (FC = 2.724 ± 0.44, qval = 0.045; and FC = 1.994 ± 0.28, qval = 0.045, respectively). (C) S2R+ cells were transfected with the indicated siRNA (Ctrl and USP8) and lysed after 3 d. Equal amounts of protein (30 μg) were separated by SDS–PAGE and immunoblotted using the indicated antibodies. Representative of n = 6. Graph bar shows mean ± SEM of ratio between densitometric levels of MFN and those of Actin from at least eight independent experiments. Means are significantly different according to t test; P = 0.0025 (**), n = 6. (D) S2R+ cells were transfected with the indicated plasmid (MFN-Flag, USP8) and siRNA (Ctrl and USP8) and lysed after 3 d. Equal amounts of protein (30 μg) were separated by SDS–PAGE and immunoblotted using the indicated antibodies. Representative of n = 5. Graph bar shows mean ± SEM of ratio between densitometric levels of Flag (MFN) and those of Actin relatively to control from at least four independent experiments. One-way ANOVA; P < 0.0001 (****), followed by Tukey’s multiple comparison test. n = 5. (E) S2R+ cells were transfected with the indicated plasmids (empty vector, ev or USP8) and lysed after 3 d. Equal amounts of protein (30 μg) were separated by SDS–PAGE and immunoblotted using the indicated antibodies. Representative of n = 4. Graph bar shows mean ± SEM of ratio between densitometric levels of MFN and those of Actin relatively to control from at least four independent experiments. Means are significantly different according to the t test; P = 0.0313 (*), n = 4. (F) Equal amounts of protein (70 μg), isolated from wild-type (Ctrl) flies or those down-regulating USP8 (USP8) separated by SDS–PAGE and immunoblotted using the indicated antibodies. Representative of n = 8. Graph bar shows mean ± SEM of ratio between densitometric levels of MFN and those of Actin relatively to control from at least three independent experiments. Means are significantly different according to the t test; P = 0.0044 (**), n = 8. The flies were raised at 29°C to allow efficient down-regulation of USP8. (G) Equal amounts of protein (70 μg), isolated from wild-type (Ctrl) flies and those carrying heterozygous deletion of USP8 (USP8−/+) separated by SDS–PAGE and immunoblotted using the indicated antibodies. Representative of n = 5. Graph bar shows mean ± SEM of ratio between densitometric levels of MFN and those of Actin relatively to control from at least four independent experiments. Means are significantly different according to the t test; P = 0.0069 (**), n = 5.

Source data are available for this figure.

Figure S1.

USP8 down-regulation correlates to decreased MFN protein levels and affects mitochondrial morphology.

(A) Representative images of Drosophila S2R+ cells after transfection with MFN-Flag and MitoDsRed and immunostained with anti-Flag Antibody. (B) Total RNA was extracted from 3-d siRNA-treated S2R+ cells as indicated and retrotranscribed into cDNA. Specific USP8 and endogenous control oligonucleotides primers were used to perform quantitative RT-PCR. Bar graph indicates USP8 mRNA levels relatively to endogenous control in siRNA-treated cells as indicated. t test, P < 0.0001 (****), n = 3. (C) S2R+ cells were treated with the indicated siRNA (MFN) and lysed after 3 d. Equal amounts of protein (30 μg) were separated by SDS–PAGE and immunoblotted using the indicated antibodies. Representative of n = 7. Graph bar shows mean ± SEM of ratio between densitometric levels of MFN and those of Actin relatively to control from at least four independent experiments. Means are significantly different according to the t test; P = 0.0290 (*), n = 7. (D) Representative confocal images of MitoTracker Red–stained S2R+ cells transfected for 3 d with the indicated siRNA. Graph represents mean ± SEM of three independent experiments (at least 1,100 cells per condition). Means are significantly different according to the t test; P = 0.03 (*), n = 3. (E) Representative images of Drosophila S2R+ cells mitochondrial morphology after transfection with the indicated plasmids (empty vector, ev and USP8), stained with MitoTracker Red and imaged live. Graph bar shows quantification of mitochondria morphology according to Pogson et al (2014). Data represent mean ± SDEV. Means are significantly different according to the t test; P < 0.0001 (****), n = 1, minimum number of cells n = 60. (F) Total RNA was extracted from flies of the indicated phenotype and retrotranscribed into cDNA. Specific USP8 and endogenous control oligonucleotides primers were used to perform quantitative RT-PCR. Bar graph indicates USP8 mRNA levels relatively to endogenous control in flies from the indicated genotypes, which were raised at 25°C or 29°C degrees, respectively. At 25°C, t test; P = 0.0072 (**), n = 4. At 29°C, t test; P < 0.0001 (****), n = 4.

Complete list of the 75 human known or predicted DUBs and their fly homologue, when known or predicted, based on sequence similarity. Where available, Entrez/PubMed gene ID and fly gene name is provided.

A targeted siRNA screening identified DUB USP8 whose down-regulation correlates with decreased MFN levels.

(A) siRNA screen to identify DUBs affecting pathologically elevated MFN protein levels. Protein extracts from Drosophila S2R+ cells expressing equal amounts of Flag-MFN and treated with 2 μg dsRNA probe were separated by SDS–PAGE and immunoblotted using an anti-Flag antibody. Densitometric analysis of MFN signal normalized to loading control and expressed as fold change (FC) versus control dsRNA was used as read out to identify DUBs whose down-regulation affects MFN protein levels. (B) Volcano plot constructed by plotting the negative log of the FDR corrected P value (qval) on the y-axis against the log of the FC calculated in (A). Those points that are found toward the top of the plot far to either the left- or right-hand side represent values with large FC and high statistical significance. A threshold of P < 0.05 and 0.75 < FC > 1.3 led to the identification of four DUBs whose down-regulation resulted in either decreased MFN levels (USP8 FC = 0.345 ± 0.04, qval = 0.024; USP14 FC = 0.537 ± 0.06, qval = 0.044) or increased MFN levels (Echinus FC = 1.784 ± 0.13, qval = 0.024; USP36 FC = 1.524 ± 0.12, qval = 0.040). Down-regulation of PINK1 or Parkin led to increased MFN levels (FC = 2.724 ± 0.44, qval = 0.045; and FC = 1.994 ± 0.28, qval = 0.045, respectively). (C) S2R+ cells were transfected with the indicated siRNA (Ctrl and USP8) and lysed after 3 d. Equal amounts of protein (30 μg) were separated by SDS–PAGE and immunoblotted using the indicated antibodies. Representative of n = 6. Graph bar shows mean ± SEM of ratio between densitometric levels of MFN and those of Actin from at least eight independent experiments. Means are significantly different according to t test; P = 0.0025 (**), n = 6. (D) S2R+ cells were transfected with the indicated plasmid (MFN-Flag, USP8) and siRNA (Ctrl and USP8) and lysed after 3 d. Equal amounts of protein (30 μg) were separated by SDS–PAGE and immunoblotted using the indicated antibodies. Representative of n = 5. Graph bar shows mean ± SEM of ratio between densitometric levels of Flag (MFN) and those of Actin relatively to control from at least four independent experiments. One-way ANOVA; P < 0.0001 (****), followed by Tukey’s multiple comparison test. n = 5. (E) S2R+ cells were transfected with the indicated plasmids (empty vector, ev or USP8) and lysed after 3 d. Equal amounts of protein (30 μg) were separated by SDS–PAGE and immunoblotted using the indicated antibodies. Representative of n = 4. Graph bar shows mean ± SEM of ratio between densitometric levels of MFN and those of Actin relatively to control from at least four independent experiments. Means are significantly different according to the t test; P = 0.0313 (*), n = 4. (F) Equal amounts of protein (70 μg), isolated from wild-type (Ctrl) flies or those down-regulating USP8 (USP8) separated by SDS–PAGE and immunoblotted using the indicated antibodies. Representative of n = 8. Graph bar shows mean ± SEM of ratio between densitometric levels of MFN and those of Actin relatively to control from at least three independent experiments. Means are significantly different according to the t test; P = 0.0044 (**), n = 8. The flies were raised at 29°C to allow efficient down-regulation of USP8. (G) Equal amounts of protein (70 μg), isolated from wild-type (Ctrl) flies and those carrying heterozygous deletion of USP8 (USP8−/+) separated by SDS–PAGE and immunoblotted using the indicated antibodies. Representative of n = 5. Graph bar shows mean ± SEM of ratio between densitometric levels of MFN and those of Actin relatively to control from at least four independent experiments. Means are significantly different according to the t test; P = 0.0069 (**), n = 5. Source data are available for this figure. Source Data for Figure 1

USP8 down-regulation correlates to decreased MFN protein levels and affects mitochondrial morphology.

(A) Representative images of Drosophila S2R+ cells after transfection with MFN-Flag and MitoDsRed and immunostained with anti-Flag Antibody. (B) Total RNA was extracted from 3-d siRNA-treated S2R+ cells as indicated and retrotranscribed into cDNA. Specific USP8 and endogenous control oligonucleotides primers were used to perform quantitative RT-PCR. Bar graph indicates USP8 mRNA levels relatively to endogenous control in siRNA-treated cells as indicated. t test, P < 0.0001 (****), n = 3. (C) S2R+ cells were treated with the indicated siRNA (MFN) and lysed after 3 d. Equal amounts of protein (30 μg) were separated by SDS–PAGE and immunoblotted using the indicated antibodies. Representative of n = 7. Graph bar shows mean ± SEM of ratio between densitometric levels of MFN and those of Actin relatively to control from at least four independent experiments. Means are significantly different according to the t test; P = 0.0290 (*), n = 7. (D) Representative confocal images of MitoTracker Red–stained S2R+ cells transfected for 3 d with the indicated siRNA. Graph represents mean ± SEM of three independent experiments (at least 1,100 cells per condition). Means are significantly different according to the t test; P = 0.03 (*), n = 3. (E) Representative images of Drosophila S2R+ cells mitochondrial morphology after transfection with the indicated plasmids (empty vector, ev and USP8), stained with MitoTracker Red and imaged live. Graph bar shows quantification of mitochondria morphology according to Pogson et al (2014). Data represent mean ± SDEV. Means are significantly different according to the t test; P < 0.0001 (****), n = 1, minimum number of cells n = 60. (F) Total RNA was extracted from flies of the indicated phenotype and retrotranscribed into cDNA. Specific USP8 and endogenous control oligonucleotides primers were used to perform quantitative RT-PCR. Bar graph indicates USP8 mRNA levels relatively to endogenous control in flies from the indicated genotypes, which were raised at 25°C or 29°C degrees, respectively. At 25°C, t test; P = 0.0072 (**), n = 4. At 29°C, t test; P < 0.0001 (****), n = 4.

USP8 down-regulation correlates with decreased MFN protein levels

We next validated if USP8 down-regulation correlated with changes in MFN protein levels. Upon efficient USP8 down-regulation in fly cells, as assessed by qPCR (Fig S1B), steady-state levels of endogenous (Figs 1C and S1C) or exogenously expressed tagged MFN were decreased (Fig 1D) and mitochondria appeared accordingly fragmented (Fig S1D). The effect was specific for USP8 because re-expression of USP8 in USP8 RNAi cells restored MFN levels (Fig 1D). In contrast, in cells overexpressing USP8, levels of exogenously expressed (Fig 1D) and endogenous MFN were increased (Fig 1E) and mitochondria were elongated and clumped, accumulating in the perinuclear area (Fig S1E). We next assessed the impact of USP8 down-regulation on MFN levels in vivo. To this aim, we drove efficient whole body USP8 knockdown (KD) by using the Actin5C driver (Act-GAL4>USP8-RNAi), achieving significant USP8 down-regulation at 29°C (Fig S1F). Attempts to increase USP8 down-regulation efficiency by using the stronger GAL4 driver daughterless (da) caused larvae lethality, suggesting that USP8 expression levels in vivo are tightly regulated. Act-GAL4>USP8-RNAi on the other hand was viable with no apparent locomotor defects. As previously observed in vitro, levels of MFN were reduced in vivo in USP8 down-regulating flies (Fig 1F). We also found decreased MFN levels in protein extracts coming from flies carrying heterozygous USP8 gene deletion (USP8−/+) (Mukai et al, 2010), further supporting that the effect is specific for USP8 (Fig 1G).

USP8 down-regulation ameliorates the phenotype of PINK1 KO flies

We addressed whether USP8 knockdown in PINK1 KO flies prevented the multiple phenotypes recapitulating key features of locomotor and cellular defects manifested in the flies as degeneration of dopaminergic (DA) neurons and reduced climbing ability. We also assessed the flight muscle, mitochondria ultrastructure, male fertility, and life span, all degenerated or affected in PINK1 KO flies (Clark et al, 2006; Park et al, 2006; Yang et al, 2006). Immunostaining for the specific DA neuronal marker tyrosine hydroxylase (TH) allowed the inspection of the DA neuronal network composed of well-characterized DA neuron clusters (PPM1, PPM2, PPM3, PPL1, PPL2, and VUM) in brains (Fig 2A). PINK1 KO showed the expected reduction in TH staining and exhibited a small but significant decrease in the number of DA neurons in the PPL1 DA neuronal cluster (Fig 2B and C) (Park et al, 2006; Wang et al, 2006; Yang et al, 2006). Accordingly, dopamine levels measured from PINK1 KO heads were significantly lower compared with control flies (Fig 2D). USP8 down-regulation completely prevented the loss of PINK1 KO DA neurons (Fig 2B and C), restoring dopamine to wild-type levels (Fig 2D). Moreover, USP8 down-regulation ameliorated the shorter longevity (Fig 2E), corrected thoracic muscle fiber disorganization with enlarged electron transparent mitochondria and irregular myofibril arrays (Park et al, 2006) (Fig 2F) typical of the PINK1 KO flies (Park et al, 2006). More importantly, ultrastructural transmission electron microscopy (TEM) analysis showed that the mitochondrial cristae, fragmented and sparely packed in PINK1 mutants, were recovered with highly increased electron-dense staining intensity (Fig 2G). USP8 knockdown also ameliorated the PINK1 climbing defect (Fig 2H).
Figure 2.

USP8 down-regulation corrects DA neuron loss, life span, muscle degeneration, and locomotor impairment of PINK1-deficient flies.

(A) Confocal images (projection, Z stack) of whole-mount adult brain (left panel) showing DA neuron clusters marked with an anti-TH antibody. Immunostaining for the specific DA neuronal marker TH allows the inspection of the DA neuronal network composed by well-characterized DA neuron clusters (PPM1, PPM2, PPM3, PPL1, PPL2, and VUM) in brains (right panel). (B) Whole brains of 15-d-old male flies of the indicated genotypes were immunostained with anti-TH antibody. Panel shows confocal images of PPL1 cluster DA neurons of the indicated genotypes. Representative of n = 15. (C) Bar graph shows the number of DA neurons in the PPL1 cluster of the brains of the indicated genotypes. One-way ANOVA, P < 0.0001 (****) followed by Tukey’s multiple comparison test; n = 15. (D) Relative dopamine amount from 15-d-old adult heads of the indicated genotype normalized to control flies. One-way ANOVA, P = 0.0073 (**) followed by Tukey’s multiple comparison test. n = 4. (E) Life span analysis of adult males of the indicated genotypes. Male flies of the indicated genotypes were collected during 12 h after hatching and transferred to fresh food every 2 d and dead flies were counted in the same interval. At least 100 flies per genotype were used for the analysis. Log-rank, Mantel–Cox test (Ctrl versus PINK1 KO P < 0.0001; Ctrl versus PINK1 KO USP8 RNAi P < 0.0001; Ctrl versus USP8 RNAi P > 0.05; PINK1 KO versus PINK1 KO USP8 RNAi P < 0.0001; PINK1 KO versus USP8 RNAi P < 0.0001; and PINK1 KO USP8 RNAi versus USP8 RNAi P < 0.0001 P < 0.0001). (F) Ultrastructural analysis of the indirect flight muscles from fly thoraces of the indicated genotypes. Images show TEM images of thorax muscles from flies of the indicated genotypes. Representative of n = 3. (G) Enlarged TEM images of flight muscle mitochondria of the indicated genotypes. Representative of n = 3. (H) Graph bar shows mean ± SEM of the climbing performance of flies of the indicated genotype from at least three independent experiments. One-way ANOVA, P < 0.0001 (****); Tukey’s multiple comparison test; n = 3.

USP8 down-regulation corrects DA neuron loss, life span, muscle degeneration, and locomotor impairment of PINK1-deficient flies.

(A) Confocal images (projection, Z stack) of whole-mount adult brain (left panel) showing DA neuron clusters marked with an anti-TH antibody. Immunostaining for the specific DA neuronal marker TH allows the inspection of the DA neuronal network composed by well-characterized DA neuron clusters (PPM1, PPM2, PPM3, PPL1, PPL2, and VUM) in brains (right panel). (B) Whole brains of 15-d-old male flies of the indicated genotypes were immunostained with anti-TH antibody. Panel shows confocal images of PPL1 cluster DA neurons of the indicated genotypes. Representative of n = 15. (C) Bar graph shows the number of DA neurons in the PPL1 cluster of the brains of the indicated genotypes. One-way ANOVA, P < 0.0001 (****) followed by Tukey’s multiple comparison test; n = 15. (D) Relative dopamine amount from 15-d-old adult heads of the indicated genotype normalized to control flies. One-way ANOVA, P = 0.0073 (**) followed by Tukey’s multiple comparison test. n = 4. (E) Life span analysis of adult males of the indicated genotypes. Male flies of the indicated genotypes were collected during 12 h after hatching and transferred to fresh food every 2 d and dead flies were counted in the same interval. At least 100 flies per genotype were used for the analysis. Log-rank, Mantel–Cox test (Ctrl versus PINK1 KO P < 0.0001; Ctrl versus PINK1 KO USP8 RNAi P < 0.0001; Ctrl versus USP8 RNAi P > 0.05; PINK1 KO versus PINK1 KO USP8 RNAi P < 0.0001; PINK1 KO versus USP8 RNAi P < 0.0001; and PINK1 KO USP8 RNAi versus USP8 RNAi P < 0.0001 P < 0.0001). (F) Ultrastructural analysis of the indirect flight muscles from fly thoraces of the indicated genotypes. Images show TEM images of thorax muscles from flies of the indicated genotypes. Representative of n = 3. (G) Enlarged TEM images of flight muscle mitochondria of the indicated genotypes. Representative of n = 3. (H) Graph bar shows mean ± SEM of the climbing performance of flies of the indicated genotype from at least three independent experiments. One-way ANOVA, P < 0.0001 (****); Tukey’s multiple comparison test; n = 3. To independently validate the previous results, we analyzed a bona fide genetic mutant for USP8. Heterozygous USP8 gene deletion (USP8−/+) in PINK1 KO background also completely prevented the loss of DA neurons (Fig 3A and B), restored dopamine levels to wild-type (Fig 3C), corrected thoracic muscle fiber disorganization (Fig 3D) and mitochondrial structure (Fig 3E), ameliorated the shorter longevity (Fig 3F), and completely corrected the locomotor defects (Fig 3G). Thus, these observations support the specificity of the previous results and confirm that loss of USP8 ameliorates PINK1 KO phenotypes.
Figure 3.

Heterozygous USP8 gene deletion corrects DA neuron loss, life span, muscle degeneration, and locomotor impairment of PINK1-deficient flies.

(A) Whole brains of 15-d-old male flies of the indicated genotypes were immunostained with anti-TH antibody. Panel shows confocal images of DA neuron of the PPL1 cluster of the indicated genotypes. Representative of n = 11. (B) Bar graph shows the number of DA neurons in the PPL1 cluster of the brains of the indicated genotypes. One-way ANOVA, P < 0.0001 (****); Tukey’s multiple comparison test; n = 11. (C) Relative dopamine amount from 15-d-old adult heads of the indicated genotype normalized to control flies. One-way ANOVA, P = 0.0002 (***); Tukey’s multiple comparison test; n = 5. (D) TEM images of thorax muscles from flies of the indicated genotypes. Representative of n = 3. (E) Enlarged TEM image of flight muscle mitochondria of the indicated genotypes. Representative of n = 3. (F) Life span analysis of adult males of the indicated genotypes. Male flies of the indicated genotypes were collected during 12 h after hatching and transferred to fresh food every 2 d and dead flies were counted in the same interval. At least 100 flies per genotype were used for the analysis. Log-rank, Mantel–Cox test (Ctrl versus PINK1 KO P < 0.0001; Ctrl versus PINK1 KO USP8−/+ P < 0.0001; Ctrl versus USP8−/+ P > 0.05; PINK1 KO versus PINK1 KO USP8−/+ P < 0.0001; PINK1 KO versus USP8−/+ P < 0.0001; and PINK1 KO USP8−/+ versus USP8−/+ P < 0.0001 P < 0.0001). (G) Graph bar shows mean ± SEM of the climbing performance of flies of the indicated genotype from at least three independent experiments. One-way ANOVA, P < 0.0001 (****); Tukey’s multiple comparison test; n = 3.

Heterozygous USP8 gene deletion corrects DA neuron loss, life span, muscle degeneration, and locomotor impairment of PINK1-deficient flies.

(A) Whole brains of 15-d-old male flies of the indicated genotypes were immunostained with anti-TH antibody. Panel shows confocal images of DA neuron of the PPL1 cluster of the indicated genotypes. Representative of n = 11. (B) Bar graph shows the number of DA neurons in the PPL1 cluster of the brains of the indicated genotypes. One-way ANOVA, P < 0.0001 (****); Tukey’s multiple comparison test; n = 11. (C) Relative dopamine amount from 15-d-old adult heads of the indicated genotype normalized to control flies. One-way ANOVA, P = 0.0002 (***); Tukey’s multiple comparison test; n = 5. (D) TEM images of thorax muscles from flies of the indicated genotypes. Representative of n = 3. (E) Enlarged TEM image of flight muscle mitochondria of the indicated genotypes. Representative of n = 3. (F) Life span analysis of adult males of the indicated genotypes. Male flies of the indicated genotypes were collected during 12 h after hatching and transferred to fresh food every 2 d and dead flies were counted in the same interval. At least 100 flies per genotype were used for the analysis. Log-rank, Mantel–Cox test (Ctrl versus PINK1 KO P < 0.0001; Ctrl versus PINK1 KO USP8−/+ P < 0.0001; Ctrl versus USP8−/+ P > 0.05; PINK1 KO versus PINK1 KO USP8−/+ P < 0.0001; PINK1 KO versus USP8−/+ P < 0.0001; and PINK1 KO USP8−/+ versus USP8−/+ P < 0.0001 P < 0.0001). (G) Graph bar shows mean ± SEM of the climbing performance of flies of the indicated genotype from at least three independent experiments. One-way ANOVA, P < 0.0001 (****); Tukey’s multiple comparison test; n = 3.

USP8 down-regulation rescues mitochondria defects of PINK1 KO flies

To verify if USP8 down-regulation also correlates to the amelioration of mitochondrial function, impaired in PINK1 KO/KD models (Clark et al, 2006; Gandhi et al, 2009; Morais et al, 2014; Park et al, 2006), we measured mitochondrial respiration in digitonin-permeabilized cells, where mitochondria are directly accessible to substrates. In line with what has been previously reported (Gandhi et al, 2009; Morais et al, 2009), we found that ADP-stimulated glutamate-supported respiration (state 3) was significantly reduced in cells lacking PINK1 (Fig S2A). State 3/basal (state 4) respiration ratio, also known as respiratory control ratio (RCR), was reduced (Fig S2B). USP8 down-regulation did not perturb mitochondrial respiration per se; however, it corrected the respiration defects of the PINK1-deficient cells (Fig S2A and B). In cells lacking PINK1, mitochondrial dysfunction is mirrored also by changes in mitochondrial membrane potential (Δψm) (Gandhi et al, 2009; Morais et al, 2009; Mortiboys et al, 2008). When we measured latent mitochondrial dysfunction using a well-established assay based on the response of Δψm to the ATPase inhibitor oligomycin, as expected (Gandhi et al, 2009; Morais et al, 2009), we noticed that PINK1-deficient mitochondria sustain their Δψm by hydrolyzing cytosolic ATP and therefore depolarize after oligomycin treatment (Fig S2C–E). Although down-regulation of USP8 had no effect on Δψm, in PINK1-deficient cells, it fully prevented the oligomycin-induced depolarization, further confirming its beneficial effects on mitochondrial function (Fig S2C–E). Because USP8 participates in a multiplicity of pathways (Alexopoulou et al, 2016; Durcan & Fon, 2015; Mizuno et al, 2005; Row et al, 2006), the beneficial effects on mitochondrial function measured in situ might be indirect. We, therefore, compared the function of mitochondria purified from PINK1-mutant (KO) flies with that recorded in mitochondria isolated from PINK1 KO flies where we down-regulated USP8 (Fig 4A and B) or from double heterozygous USP8-deficient (USP8−/+), PINK1 KO flies (Fig 4C and D). As expected, glutamate-supported ADP-stimulated respiration was reduced, resulting in lower RCR in isolated PINK1 KO mitochondria (Gandhi et al, 2009; Morais et al, 2009) (Fig 4A–D). On the other hand, USP8 RNAi (Fig 4A and B) or heterozygous USP8 gene deletion (Fig 4C and D) in PINK1 KO flies normalized ADP-stimulated respiration and RCR.
Figure S2.

UPS8 down-regulation rescues PINK1-deficient mitochondria respiratory defects.

(A) Representative traces of oxygen consumption of digitonin-permeabilized S2R+ cells treated with the indicated dsRNA probes and subjected to 10 mM/5 mM pyruvate/malate 200 μM ADP, 2 μg/ml oligomycin, and 200 nM FCCP, 2 μM antimycinA, respectively. Representative of n = 3. (B) Quantitative analysis of respiratory fitness of digitonin permeabilized S2R+ cells treated as in (A). Graph shows mean ± SEM (n = 3 independent experiments) of the ratio between oxygen consumption rate after addition of ADP (state 3 respiration) and that after addition of ATP synthase inhibitor oligomycin (state 4 respiration), also known as RCR. One-way ANOVA, P = 0.0001 (***); Tukey’s multiple comparison test; n = 3. (C) Representative snapshots at the indicated time of TMRM loaded S2R+ cells treated with the indicated siRNA for 3 d. 5 min after recording, the cells were treated with 2.5 μg/ml oligomycin. 10 μM FCCP was added after 40 min. (D) Quantitative analysis of TMRM fluorescence intensity over mitochondrial regions in S2R+ cells treated with the indicated siRNA for 3 d. Where indicated, 2.5 μg/ml oligomycin (Oligo) and 10 μM CCCP were added. (E) Bar graph shows relative TMRM fluorescence intensity in S2R+ cells exposed to the indicated siRNA for 3 d after 30 min 2.5 μg/ml oligomycin treatment. Graph shows mean ± SEM of three independent experiments. One -way ANOVA, P < 0.0001 (****); Tukey’s multiple comparison test; n = 6.

Figure 4.

USP8 down-regulation rescues PINK1-deficient mitochondria respiratory defects ex vivo.

(A) Representative traces of oxygen consumption of intact isolated mitochondria extracted from flies of the indicated genotype and subjected to 10 mM/5 mM pyruvate/malate 200 μM ADP, 2 μg/ml oligomycin, and 200 nM FCCP, 2 μM antimycinA, respectively. Representative of n = 5. (B) Quantitative analysis of respiratory fitness of isolated mitochondria extracted from flies of the indicated genotype treated as in (A). Graph shows mean ± SEM (n = 5 independent experiments) of RCR relative to ctrl. One-way ANOVA, P = 0.0074 (**); Tukey’s multiple comparison test; n = 5. (C) Representative traces of oxygen consumption of intact isolated mitochondria extracted from flies of the indicated genotype and subjected to 10 mM/5 mM pyruvate/malate 200 μM ADP, 2 μg/ml oligomycin, and 200 nM FCCP, 2 μM antimycinA, respectively. Representative of n = 5. (D) Quantitative analysis of respiratory fitness of isolated mitochondria extracted from flies of the indicated genotype treated as in (G). Graph shows mean ± SEM (n = 5 independent experiments) of RCR relative to ctrl. One-way ANOVA, P = 0.0064 (**); Tukey’s multiple comparison test; n = 5. (E) Blue Native PAGE of mitochondrial extracts from flies of the indicated genotypes. Respiratory complexes were separated in a non-denaturing polyacrylamide gel. Representative of n = 3. (F) Densitometric analysis of (E). Graph bar shows mean ± SEM of ratio between densitometric levels of complex I (CI) and those of complex V (CV). One-way ANOVA, P = 0.0282 (**); Tukey’s multiple comparison test; n = 3. (G) Graph shows mean ± SEM (n = 4 independent experiments) of complex I activity relatively to citrate synthase (CS) activity in isolated 2.5 μM alamethicin-treated mitochondria extracted from flies of the indicated genotype. One-way ANOVA, P = 0.0012 (**); Tukey’s multiple comparison test; n = 4. (H) Graph shows mean ± SEM (n = 7 independent experiments) of complex I activity relatively to CS activity in isolated 2.5 μM alamethicin-treated mitochondria extracted from flies of the indicated genotype. One-way ANOVA, P < 0.0001 (****); Tukey’s multiple comparison test; n = 7.

UPS8 down-regulation rescues PINK1-deficient mitochondria respiratory defects.

(A) Representative traces of oxygen consumption of digitonin-permeabilized S2R+ cells treated with the indicated dsRNA probes and subjected to 10 mM/5 mM pyruvate/malate 200 μM ADP, 2 μg/ml oligomycin, and 200 nM FCCP, 2 μM antimycinA, respectively. Representative of n = 3. (B) Quantitative analysis of respiratory fitness of digitonin permeabilized S2R+ cells treated as in (A). Graph shows mean ± SEM (n = 3 independent experiments) of the ratio between oxygen consumption rate after addition of ADP (state 3 respiration) and that after addition of ATP synthase inhibitor oligomycin (state 4 respiration), also known as RCR. One-way ANOVA, P = 0.0001 (***); Tukey’s multiple comparison test; n = 3. (C) Representative snapshots at the indicated time of TMRM loaded S2R+ cells treated with the indicated siRNA for 3 d. 5 min after recording, the cells were treated with 2.5 μg/ml oligomycin. 10 μM FCCP was added after 40 min. (D) Quantitative analysis of TMRM fluorescence intensity over mitochondrial regions in S2R+ cells treated with the indicated siRNA for 3 d. Where indicated, 2.5 μg/ml oligomycin (Oligo) and 10 μM CCCP were added. (E) Bar graph shows relative TMRM fluorescence intensity in S2R+ cells exposed to the indicated siRNA for 3 d after 30 min 2.5 μg/ml oligomycin treatment. Graph shows mean ± SEM of three independent experiments. One -way ANOVA, P < 0.0001 (****); Tukey’s multiple comparison test; n = 6.

USP8 down-regulation rescues PINK1-deficient mitochondria respiratory defects ex vivo.

(A) Representative traces of oxygen consumption of intact isolated mitochondria extracted from flies of the indicated genotype and subjected to 10 mM/5 mM pyruvate/malate 200 μM ADP, 2 μg/ml oligomycin, and 200 nM FCCP, 2 μM antimycinA, respectively. Representative of n = 5. (B) Quantitative analysis of respiratory fitness of isolated mitochondria extracted from flies of the indicated genotype treated as in (A). Graph shows mean ± SEM (n = 5 independent experiments) of RCR relative to ctrl. One-way ANOVA, P = 0.0074 (**); Tukey’s multiple comparison test; n = 5. (C) Representative traces of oxygen consumption of intact isolated mitochondria extracted from flies of the indicated genotype and subjected to 10 mM/5 mM pyruvate/malate 200 μM ADP, 2 μg/ml oligomycin, and 200 nM FCCP, 2 μM antimycinA, respectively. Representative of n = 5. (D) Quantitative analysis of respiratory fitness of isolated mitochondria extracted from flies of the indicated genotype treated as in (G). Graph shows mean ± SEM (n = 5 independent experiments) of RCR relative to ctrl. One-way ANOVA, P = 0.0064 (**); Tukey’s multiple comparison test; n = 5. (E) Blue Native PAGE of mitochondrial extracts from flies of the indicated genotypes. Respiratory complexes were separated in a non-denaturing polyacrylamide gel. Representative of n = 3. (F) Densitometric analysis of (E). Graph bar shows mean ± SEM of ratio between densitometric levels of complex I (CI) and those of complex V (CV). One-way ANOVA, P = 0.0282 (**); Tukey’s multiple comparison test; n = 3. (G) Graph shows mean ± SEM (n = 4 independent experiments) of complex I activity relatively to citrate synthase (CS) activity in isolated 2.5 μM alamethicin-treated mitochondria extracted from flies of the indicated genotype. One-way ANOVA, P = 0.0012 (**); Tukey’s multiple comparison test; n = 4. (H) Graph shows mean ± SEM (n = 7 independent experiments) of complex I activity relatively to CS activity in isolated 2.5 μM alamethicin-treated mitochondria extracted from flies of the indicated genotype. One-way ANOVA, P < 0.0001 (****); Tukey’s multiple comparison test; n = 7. Blue Native PAGE (BN-PAGE) of mitochondrial extracts lent further biochemical support to the measured functional amelioration. Extracts from PINK1-deficient flies displayed reduced levels of respiratory complex I, which was corrected by heterozygous deletion of USP8 (Fig 4E and F). PINK1 mutants show reduced enzymatic activity of complex I (Morais et al, 2014; Pogson et al, 2014). Both USP8 fly lines (USP8+/− and USP8 RNAi) restored complex I activity of PINK1 mutants (Fig 4G and H). PINK1-null mutant males are sterile, as a consequence of spermatogenesis defects deriving from mitochondrial dysfunction (Clark et al, 2006; Deng et al, 2008; Greene et al, 2003; Park et al, 2006). Of note, heterozygous USP8 gene deletion favours the restoring of sperm production of the PINK1 KO, rescuing male sterility (Fig S3). The seminal vesicles of Ctrl and USP8−/+ males were well developed, swollen, and brownish in color (Fig S3A and B), whereas those of PINK1 KO were reduced in volume and more transparent (Fig S3C). Puncturing the vesicles of Ctrl and USP8−/+ males released a large amount of sperm (Fig S3E and F), whereas sperm was almost absent in PINK1 KO vesicles (Fig S3G). Rescued males (PINK1 KO, USP8−/+) showed an intermediate pattern, with swollen, opaque vesicles (Fig S3D) releasing some sperm groups (Fig S3H). The fluorescence staining revealed a difference among the four male groups also in the accessory glands’ wall, whose cells appeared alive (green) in ctrl and USP8−/+ males (Fig S3I and J) and dead (red) in PINK1 KO (Fig S3K). In rescued males (PINK1 KO, USP8−/+), part of the accessory glands’ cells was alive (Fig S3L). The result of fluorescence staining proves that the effect is not limited to sperm production, but it is also extended to the functionality of the accessory glands, that play a crucial role on both male fertilization success and female fertility (Simmons & Fitzpatrick, 2012).
Figure S3.

Heterozygous USP8 gene deletion corrects sperm production of PINK1− deficient flies.

(A–D) Images show the seminal vesicles of (A) wild-type, (B) USP8−/+, (C) PINK1 KO, and (D) rescued males (PINK1 KO, USP8−/+). (E–H) Images show sperm released upon puncturing of seminal vesicles of (E) wild-type, (F) USP8−/+, (G) PINK1 KO, and (H) rescued males (PINK1 KO, USP8−/+). (I–L) Images show the fluorescence staining of the accessory glands’ wall, whose cells appeared alive (green) in wild-type (I) and USP8−/+ males (J), dead (red) in PINK1 KO (K), and with an intermediate pattern in (L) rescued males (PINK1 KO, USP8−/+).

Heterozygous USP8 gene deletion corrects sperm production of PINK1− deficient flies.

(A–D) Images show the seminal vesicles of (A) wild-type, (B) USP8−/+, (C) PINK1 KO, and (D) rescued males (PINK1 KO, USP8−/+). (E–H) Images show sperm released upon puncturing of seminal vesicles of (E) wild-type, (F) USP8−/+, (G) PINK1 KO, and (H) rescued males (PINK1 KO, USP8−/+). (I–L) Images show the fluorescence staining of the accessory glands’ wall, whose cells appeared alive (green) in wild-type (I) and USP8−/+ males (J), dead (red) in PINK1 KO (K), and with an intermediate pattern in (L) rescued males (PINK1 KO, USP8−/+). Taken together, these analyses show that the mitochondrial-defective phenotype of PINK1 KO flies can be recovered by decreasing USP8 expression, including complex I levels and activity.

Pharmacological inhibition of USP8 corrects PINK1-deficient flies

The genetic experiments showed that USP8 inhibition ameliorates all the phenotypes that we tested that are associated to Drosophila PINK1 KO. We, therefore, decided to test in vivo the effect of DUBs-IN-2 (ChemScene LLC), a potent and membrane-permeant USP8 drug inhibitor. DUBs-IN-2 is highly selective for USP8 with a half maximal inhibitory concentration (IC50) of 0.28 μM (Colombo et al, 2010) and small or no effect on USP7 (IC50 > 100 μM for USP7). The compound has been described as an inhibitor of human USP8, which shares about ∼45% sequence homology to the fly ortholog. DUBs-IN-2 was mixed in the fly food with the food-coloring patent blue V (E131) to monitor drug ingestion (Fig S4A). Increasing inhibitor concentrations did not affect the food uptake of flies as measured by E131 absorbance in fly lysates (Fig S4B) and did not affect locomotor behavior in a control background (Fig S4C). Remarkably, DUBs-IN-2 administered to adult PINK1-deficient flies significantly suppressed the locomotor deficits (Fig 5A). Dose–response curve indicated the best rescue of PINK1 KO climbing performance upon 10 μM DUBs-IN-2 administration (Fig S4C). DUBs-IN-2 administration to PINK1 KO flies also prevented loss of DA neurons (Fig 5B and C), restored dopamine levels (Fig 5D), and it modestly ameliorated longevity (Fig 5E).
Figure S4.

USP8 inhibition corrects DA neuron loss, life span, muscle degeneration, and locomotor impairment of PINK1-deficient flies.

(A) Image of fly gut showing the ingested food. (B) Graph bar shows quantification of fly food uptake as measured by E131 absorbance in fly lysates. (C) Graph bar shows mean ± SEM of the climbing performance of flies of the indicated genotype or treated with DUBs-IN-2 for 15 d from at least three independent experiments. Two-way ANOVA; P < 0.0001 (****); Tukey’s multiple comparison test. n = 7.

Figure 5.

Pharmacological USP8 inhibition corrects DA neuron loss, life span, muscle degeneration, and locomotor impairment of PINK1-deficient flies.

(A) Graph bar shows mean ± SEM of the climbing performance of 3-d-old flies of the indicated genotype or treated with DUBs-IN-2 or DMSO for 48 h from at least four independent experiments. Two-way ANOVA P < 0.0001 (****); Tukey’s multiple comparison test; n = 8. (B) Whole brains of 15-d-old male flies of the indicated genotypes or treated with DUBs-IN-2 for 15 d were immunostained with anti-TH antibody. Panel shows (projection, Z stack) confocal images of PPL1 cluster DA neurons of the indicated genotypes. Representative of n = 9. (C) Bar graph shows the number of PPL1 cluster DA neurons in brains of the indicated genotypes treated with DUBs-IN-2 or DMSO for 15 d. Two-way ANOVA, P = 0.0004 (***); Tukey’s multiple comparison test; n = 15. (D) Relative dopamine amount from 15 d old adult heads of the indicated genotype treated with DUBs-IN-2 or DMSO for 15 d normalized to control flies. Two-way ANOVA P = 0.0217 (*); Tukey’s multiple comparison test; n = 3. (E) Life span analysis of male flies of the indicated genotypes treated with DUBs-IN-2 or DMSO. At least 100 flies were used for the analysis. Log-rank, Mantel–Cox test (Ctrl versus PINK1 KO P < 0.0001; Ctrl versus PINK1 KO+DUBs-IN-2, P < 0.0001; Ctrl versus Ctrl+DUBs-IN-2 P > 0.05; PINK1 KO versus PINK1 KO+DUBs-IN-2 P < 0.001; PINK1 KO versus Ctrl+DUBs-IN-2 P < 0.0001; and PINK1 KO+DUBs-IN-2 versus Ctrl+DUBs-IN-2 P < 0.0001).

USP8 inhibition corrects DA neuron loss, life span, muscle degeneration, and locomotor impairment of PINK1-deficient flies.

(A) Image of fly gut showing the ingested food. (B) Graph bar shows quantification of fly food uptake as measured by E131 absorbance in fly lysates. (C) Graph bar shows mean ± SEM of the climbing performance of flies of the indicated genotype or treated with DUBs-IN-2 for 15 d from at least three independent experiments. Two-way ANOVA; P < 0.0001 (****); Tukey’s multiple comparison test. n = 7.

Pharmacological USP8 inhibition corrects DA neuron loss, life span, muscle degeneration, and locomotor impairment of PINK1-deficient flies.

(A) Graph bar shows mean ± SEM of the climbing performance of 3-d-old flies of the indicated genotype or treated with DUBs-IN-2 or DMSO for 48 h from at least four independent experiments. Two-way ANOVA P < 0.0001 (****); Tukey’s multiple comparison test; n = 8. (B) Whole brains of 15-d-old male flies of the indicated genotypes or treated with DUBs-IN-2 for 15 d were immunostained with anti-TH antibody. Panel shows (projection, Z stack) confocal images of PPL1 cluster DA neurons of the indicated genotypes. Representative of n = 9. (C) Bar graph shows the number of PPL1 cluster DA neurons in brains of the indicated genotypes treated with DUBs-IN-2 or DMSO for 15 d. Two-way ANOVA, P = 0.0004 (***); Tukey’s multiple comparison test; n = 15. (D) Relative dopamine amount from 15 d old adult heads of the indicated genotype treated with DUBs-IN-2 or DMSO for 15 d normalized to control flies. Two-way ANOVA P = 0.0217 (*); Tukey’s multiple comparison test; n = 3. (E) Life span analysis of male flies of the indicated genotypes treated with DUBs-IN-2 or DMSO. At least 100 flies were used for the analysis. Log-rank, Mantel–Cox test (Ctrl versus PINK1 KO P < 0.0001; Ctrl versus PINK1 KO+DUBs-IN-2, P < 0.0001; Ctrl versus Ctrl+DUBs-IN-2 P > 0.05; PINK1 KO versus PINK1 KO+DUBs-IN-2 P < 0.001; PINK1 KO versus Ctrl+DUBs-IN-2 P < 0.0001; and PINK1 KO+DUBs-IN-2 versus Ctrl+DUBs-IN-2 P < 0.0001).

USP8 down-regulation corrects pathologically elevated MFN levels of PINK1 and Parkin KO flies

PINK1 loss-of-function results in increased MFN protein levels (Tanaka et al, 2010; Ziviani et al, 2010), altered mitochondrial morphology (Mortiboys et al, 2008; Narendra et al, 2008; Tanaka et al, 2010; Ziviani et al, 2010), impaired mitophagy (Gegg et al, 2010; Narendra et al, 2008; Ziviani et al, 2010), and oxidative phosphorylation (Morais et al, 2009, 2014), with mitochondrial Ca2+ overload and increased reactive oxygen species production (Gandhi et al, 2009). Similar phenotypes are caused by altered MFN, which prompted us to investigate whether USP8 down-regulation corrected pathologically elevated MFN levels of PINK1 KO flies. Indeed, USP8 down-regulation in vivo completely normalized increased MFN levels of PINK1 KO (Fig 6A). Pharmacological inhibition of USP8 also led to reduced PINK1 KO MFN protein levels in flies, indicating that the inhibitor phenocopied genetic inhibition of USP8 (Fig 6B). Like PINK1, Parkin KO/KD also results in increased MFN protein levels (Gegg et al, 2010; Tanaka et al, 2010; Ziviani et al, 2010). We, therefore, assessed the effect of USP8 KD in a Parkin loss-of-function model of pathologically elevated MFN levels. USP8 KD corrected elevated MFN levels of Parkin KO flies (Fig 6C). It also recovered the disorganized muscle fibers with irregular arrangement of myofibrils and the swollen mitochondria of Parkin flies (Fig 6D), and normalized the number of DA neurons that are decreased in Parkin KO background (Fig 6E). Interestingly, USP8 KD or inhibition did not correct climbing defects in Parkin KO flies (Fig 6F), nor in PINK1:Parkin double KO (Fig 6G).
Figure 6.

USP8 down-regulation corrects pathologically elevated MFN levels of PINK1 and Parkin KO flies.

(A) Equal amounts of protein (70 μg), isolated from flies of the indicated phenotype were separated by SDS–PAGE and immunoblotted using the indicated antibodies. Representative of n = 6. Graph bar shows mean ± SEM of ratio between densitometric levels of MFN and those of Actin from at least six independent experiments. One-way ANOVA, P = 0.0003 (***); Tukey’s multiple comparison test; n = 6. (B) Equal amounts of protein (70 μg), isolated from flies treated with DUBs-IN-2 or DMSO for 48 h were separated by SDS–PAGE and immunoblotted using the indicated antibodies. Representative of n = 3. Graph bar shows mean ± SEM of ratio between densitometric levels of MFN and those of Actin from at least three independent experiments. Two-way ANOVA, P < 0.00001 (****); Tukey’s multiple comparison test; n = 3. (C) Equal amounts of protein (70 μg), isolated from flies of the indicated phenotype were separated by SDS–PAGE and immunoblotted using the indicated antibodies. Representative of n = 9. Graph bar shows mean ± SEM of ratio between densitometric levels of MFN and those of Actin from at least nine independent experiments. One-way ANOVA, P < 0.0001 (****); Tukey’s multiple comparison test; n = 9. (D) TEM images of thorax muscles from flies of the indicated genotypes. Thoraces were dissected from 3-d-old adult flies and fixed in 2% paraformaldehyde and 2.5% gluteraldehyde. The samples were rinsed, dehydrated, and embedded using Epon. Ultrathin sections were examined using TEM. Representative of n = 3. (E) Bar graph shows the number of DA neurons in the PPL1 cluster of the brains of the indicated genotypes. One-way ANOVA, P < 0.0001 (****); Tukey’s multiple comparison test; n = 10. (F) Graph bar shows mean ± SEM of the climbing performance of flies of the indicated genotype from at least three independent experiments. One-way ANOVA, P < 0.0001 (****); n = 3. (G) Graph bar shows mean ± SEM of the climbing performance of flies of the indicated genotype from at least three independent experiments. Two-way ANOVA, P < 0.0001 (****); Tukey’s multiple comparison test; n = 7.

USP8 down-regulation corrects pathologically elevated MFN levels of PINK1 and Parkin KO flies.

(A) Equal amounts of protein (70 μg), isolated from flies of the indicated phenotype were separated by SDS–PAGE and immunoblotted using the indicated antibodies. Representative of n = 6. Graph bar shows mean ± SEM of ratio between densitometric levels of MFN and those of Actin from at least six independent experiments. One-way ANOVA, P = 0.0003 (***); Tukey’s multiple comparison test; n = 6. (B) Equal amounts of protein (70 μg), isolated from flies treated with DUBs-IN-2 or DMSO for 48 h were separated by SDS–PAGE and immunoblotted using the indicated antibodies. Representative of n = 3. Graph bar shows mean ± SEM of ratio between densitometric levels of MFN and those of Actin from at least three independent experiments. Two-way ANOVA, P < 0.00001 (****); Tukey’s multiple comparison test; n = 3. (C) Equal amounts of protein (70 μg), isolated from flies of the indicated phenotype were separated by SDS–PAGE and immunoblotted using the indicated antibodies. Representative of n = 9. Graph bar shows mean ± SEM of ratio between densitometric levels of MFN and those of Actin from at least nine independent experiments. One-way ANOVA, P < 0.0001 (****); Tukey’s multiple comparison test; n = 9. (D) TEM images of thorax muscles from flies of the indicated genotypes. Thoraces were dissected from 3-d-old adult flies and fixed in 2% paraformaldehyde and 2.5% gluteraldehyde. The samples were rinsed, dehydrated, and embedded using Epon. Ultrathin sections were examined using TEM. Representative of n = 3. (E) Bar graph shows the number of DA neurons in the PPL1 cluster of the brains of the indicated genotypes. One-way ANOVA, P < 0.0001 (****); Tukey’s multiple comparison test; n = 10. (F) Graph bar shows mean ± SEM of the climbing performance of flies of the indicated genotype from at least three independent experiments. One-way ANOVA, P < 0.0001 (****); n = 3. (G) Graph bar shows mean ± SEM of the climbing performance of flies of the indicated genotype from at least three independent experiments. Two-way ANOVA, P < 0.0001 (****); Tukey’s multiple comparison test; n = 7.

Discussion

Interventions that decrease MFN levels in PINK1 or Parkin KO flies can ameliorate the multiple phenotypes that are associated with the KO backgrounds (Deng et al, 2008; Poole et al, 2008; Liu et al, 2011; Vilain et al, 2012; Celardo et al, 2016). We, therefore, conducted an RNAi-based screening to identify DUBs that regulate MFN protein levels. We found USP8, a DUB previously identified in the regulation of endosomal trafficking (Mizuno et al, 2005; Row et al, 2006), CCCP-induced mitophagy (Durcan et al, 2014) and basal autophagy (Jacomin et al, 2015), and which down-regulation is protective from α-synuclein–induced locomotor deficits in flies (Alexopoulou et al, 2016). Our data show that inhibition of USP8 in vitro and in vivo correlated with decreased mitochondrial fusion protein MFN, one of the bona fide Parkin targets (Gegg et al, 2010; Poole et al, 2010; Tanaka et al, 2010; Ziviani et al, 2010; Sarraf et al, 2013) (Fig 1), ameliorated PINK1 KO phenotypes in vivo (Figs 2, 3, and 5) and PINK1 KO mitochondrial dysfunction (Fig 4), and corrected MFN protein levels, increased in PINK1 KO models (Fig 6). Interestingly, USP8 KD also corrected MFN protein levels of Parkin KO flies, indicating that the effect on the levels of MFN is Parkin independent. USP8 KD also prevented Parkin KO DA neurons loss and normalized mitochondrial morphological defects, although it did not ameliorate Parkin climbing performance (Fig 6). It has been shown that the knockdown of MFN is able to rescue the mitochondrial defects and the overall phenotypes of Drosophila PINK1 KO flies (Deng et al, 2008; Poole et al, 2008). More recently, it was shown that MFN knockdown can suppress loss of DA neurons of the PPL1 cluster and thorax deformation resulting from crushed thoracic muscle of the PINK1 KO flies, but not the mitochondrial defects (Celardo et al, 2016). We found that normalizing MFN levels of PINK1 KO flies by driving efficient whole body MFN KD (Debattisti et al, 2014) ameliorated the disorganized muscle fibers and mitochondria ultrastructure of PINK1 KO flies, but dopamine content and climbing performance were only modestly recovered, even if MFN levels of PINK1 KO flies were completely corrected (Fig S5). This result indicates that MFN normalization deriving from USP8 KD likely contributes to the amelioration of the PINK1 phenotype but does not explain the full recovery of the multiple phenotypes that are associated with PINK1 loss. Indeed, our in vivo analysis indicates that USP8 KD has a broader protective effect than MFN KD and unlike MFN KD (Celardo et al, 2016; Vilain et al, 2012), it correlates with full correction of mitochondrial respiratory defects, complex I content and activity, and mitochondrial membrane potential of PINK1 KO flies (Figs 4 and S2). Previous examination of the PINK1-mutant phenotype demonstrated that although decreasing mitochondrial fusion rescues morphological mitochondrial defects of PINK1 flies, manipulation of mitochondrial fusion (or fission) does not rescue other PINK1-related phenotypes such as the reduced activity of complex I, loss of mitochondrial membrane potential, ATP content, and defective neurotransmitter release (Vilain et al, 2012; Vos et al, 2012). In light of this, we hypothesize that the protective effect of USP8 inhibition comes from a combination of signaling pathways, which directly or indirectly impinges on MFN levels and mitochondrial function. In mammals, it is established that USP8 is involved in endosomal trafficking (Clague et al, 2013), although its activity can have opposing effects. For instance, deubiquitination by USP8 was reported to slow the degradation of substrates (Mizuno et al, 2005; Mukai et al, 2010), but also to facilitate endosomal trafficking and lysosomal degradation (Row et al, 2007; Ali et al, 2013). shRNA against USP8 in SH-SY5Y neuroblastoma cells promotes α-synuclein degradation by the lysosome, which exerts a protective effect in vivo in an α-synuclein fly model of PD (Alexopoulou et al, 2016). It was also reported that USP8 is required for lysosomal biogenesis and productive autophagy in Drosophila larval fat body but inhibits basal autophagy in vitro in HeLa cells (Jacomin et al, 2015). Finally, deubiquitination of Parkin by USP8 is required for Parkin recruitment to CCCP-intoxicated mitochondria and to promote stress-induced mitophagy in vitro (Durcan et al, 2014). Thus, USP8 down-regulation in this context inhibits Parkin recruitment to mitochondria, causing a delay in mitochondria clearance by mitophagy. In light of these seemingly opposing phenotypic outcomes, it is clear that USP8 has pleiotropic effects that depends on the specific genetic repertoire of the cell/tissue, varies in response to physiological versus pathological conditions, or might simply operate differently in cell lines versus the whole organism. Our model is consistent with a role of USP8 in controlling mitochondrial function via Parkin-independent regulation of pathologically elevated MFN protein levels. Yet, it does not exclude MFN-unrelated pathways that nevertheless impinge on mitochondrial function via Parkin, like the mitochondrial-derived vesicle pathway regulating mitochondria quality control (McLelland et al, 2014), or the endosomal–lysosomal pathway that can also play a role in selective degradation of dysfunctional mitochondria (Hammerling et al, 2017a, 2017b). Interestingly, it was shown in the latter that the autophagic activity is increased when the endosomal activity is impaired, sustaining the hypothesis that there is crosstalk between the various degradation pathways to ensure effective clearance. It is tempting to hypothesis an enhancement of autophagy deriving from USP8 KD to complement for impaired endosomal-mediated quality control. For these reasons, future studies need to be conducted in vivo to validate this hypothesis and clearly dissect coordination and timing of activation of these pathways in different tissues under physiological and pathological conditions.
Figure S5.

Effect of MFN KD in PINK1 KO background.

(A) TEM images of thorax muscles from flies of the indicated genotypes. Thoraces were dissected from 3-d-old adult flies and fixed in 2% paraformaldehyde and 2.5% gluteraldehyde. The samples were rinsed, dehydrated, and embedded using Epon. Ultrathin sections were examined using TEM. Representative of n = 3. (B) Enlarged TEM images of flight muscle mitochondria of the indicated genotypes. Representative of n = 3. (C) Relative dopamine amount from 15-d-old adult heads of the indicated genotype normalized to control flies. One-way ANOVA, P = 0.05 (*); Tukey’s multiple comparison test; n = 4. (D) Graph bar shows mean ± SEM of the climbing performance of flies of the indicated genotype from at least four independent experiments. One-way ANOVA, P < 0.0001 (****); Tukey’s multiple comparison test; n = 4. (E) Equal amounts of protein (70 μg), isolated from flies of the indicated phenotype were separated by SDS–PAGE and immunoblotted using the indicated antibodies. Representative of n = 4. Graph bar shows mean ± SEM of ratio between densitometric levels of MFN and those of Actin from at least four independent experiments. One-way ANOVA, P < 0.0001 (****); Tukey’s multiple comparison test; n = 4.

Effect of MFN KD in PINK1 KO background.

(A) TEM images of thorax muscles from flies of the indicated genotypes. Thoraces were dissected from 3-d-old adult flies and fixed in 2% paraformaldehyde and 2.5% gluteraldehyde. The samples were rinsed, dehydrated, and embedded using Epon. Ultrathin sections were examined using TEM. Representative of n = 3. (B) Enlarged TEM images of flight muscle mitochondria of the indicated genotypes. Representative of n = 3. (C) Relative dopamine amount from 15-d-old adult heads of the indicated genotype normalized to control flies. One-way ANOVA, P = 0.05 (*); Tukey’s multiple comparison test; n = 4. (D) Graph bar shows mean ± SEM of the climbing performance of flies of the indicated genotype from at least four independent experiments. One-way ANOVA, P < 0.0001 (****); Tukey’s multiple comparison test; n = 4. (E) Equal amounts of protein (70 μg), isolated from flies of the indicated phenotype were separated by SDS–PAGE and immunoblotted using the indicated antibodies. Representative of n = 4. Graph bar shows mean ± SEM of ratio between densitometric levels of MFN and those of Actin from at least four independent experiments. One-way ANOVA, P < 0.0001 (****); Tukey’s multiple comparison test; n = 4. Because of their involvement in the regulation of important signaling pathways, DUBs are emerging as extremely attractive druggable candidates (Sugiura et al, 2013). In recent years, many DUBs emerged as therapeutic targets to compensate for impaired mitophagy in PD (Bingol et al, 2014; Cornelissen et al, 2014; Wang et al, 2015; Chakraborty et al, 2018). Mitophagy is triggered by ubiquitin modification of mitochondrial proteins, which is in principle subject to suppression by deubiquitination. It is, therefore, reasonable that inhibition of specific DUBs should induce mitophagy and that it does so by deubiquitination mitochondrial proteins. Clinical trials for specific inhibitors of the ubiquitin–proteosome system have already been approved in cancer therapy for the treatment of multiple myeloma (Colland, 2010). Moreover, high-throughput screening of small chemical libraries identified non-selective DUB inhibitors as potent inducers of apoptosis in various cancer cells (Liu et al, 2003; Brancolini, 2008; Engels et al, 2009; Hussain et al, 2009; Py et al, 2013). Similarly, specific DUB inhibitors (or activators) can affect cellular response to stimuli that induce cell death. In this respect, the identification of a specific DUB that normalizes mitochondrial function might be instrumental to develop specific isopeptidase inhibitors that can modulate the fundamental biological process of mitochondria physiology and fitness, supporting the potential of USP8 inhibitors as therapeutics.

Online methods

Cell culture and transfection

Drosophila S2R+ cells were cultured in Schneider’s medium (Invitrogen) supplemented with 10% heat-inactivated fetal calf serum (Sigma-Aldrich). The cells were maintained at 25°C and passaged routinely before they reached confluence, to maintain a logarithmic growth. The cells were transfected using TransFectin lipid reagent (Bio-Rad) or Effectene (QIAGEN) following the manufacturer’s instructions. In brief, 0.6 million cells were plated in six-well plate and transfected with 2 μg DNA/5 μl TransFectin or 1 μg DNA/10 μl Effectene + 8 μl Enhancer, 1 d after plating. The cells were collected 24–48 h after transfection. 500 μM copper sulfate solution was added to the cells to induce plasmid expression when required.

Plasmids

MitoDsRed was subcloned from pDsRed2-Mito vector (Clontech) into pAct-PPA expression plasmid. C-terminal Flag tag MFN was obtained by amplification from cDNA clone (RE04414) and subcloned into pAct-PPA expression plasmid. CG5798/USP8 was amplified from cDNA clone and subcloned into pMt copper-inducible vector (Invitrogen).

Gene silencing

Drosophila dsRNA probes were prepared using MEGA script kit (Ambion) following the manufacturer’s instructions. The following primers have been used to prepare the RNAi probes: PINK1 CAATGTGACTTCTCCAGCGA and TCGTAGCGTTTCATCAGCAG; Parkin CTGTTGCAATTTGGAGGGA and CTTTGGCACGGACTCTTTCT; and MFN GGAACCTCTTTATTCTCTAT and GGTTTGCTTTGCCCCAACAT. CG5798/USP8 dsRNA probe was acquired from the Sheffield RNAi Screening Facility. 1.2 millions cells were plated on a six-well plate and treated with 7 μg RNAi probe in serum-free medium. 2 h after the probe treatment, complete medium was added to the wells, and the cells were cultured for 2 d before being transfected with indicated fly expression plasmids as previously described.

Immunoblotting

Western blotting was performed using standard techniques. In brief, the cells were collected in lysis buffer (50 mM Tris–HCl, pH 8, 150 mM HCl, 1 mM MgCl2, 2 mM EGTA, 1% Triton X, 10% glycerol, 10 mM NEM, 10 μM MG132 and protease inhibitor cocktail by Roche) and incubated on ice for 30 min before being centrifuged at maximum speed at 4°C. Ten to twelve flies were homogenized using a mortar and pestle in protein extraction buffer (200–300 μl, 150 mM NaCl, 5 mM EDTA, pH 8.0, 50 mM Tris, pH 8.0, 1% NP-40, 0.1% SDS 0.1, supplemented with 10 μM MG132, 10 mM NEM, and protease inhibitor cocktail). The following commercial antibodies were used: anti-Flag (1:1,000; Cell Signaling Technology), anti-Actin (1:10,000; Chemicon) has been described before. Anti-Drosophila Mitofusin (1:2000) was raised in rabbit against an N-terminal peptide, DTVDKSGPGSPLSRF. For detection, secondary antibodies conjugated with HRP (Chemicon) were used (1:3,000), and immunoreactivity was visualized with ECL chemiluminescence (Amersham).

Live imaging

Cells were grown on imaging dishes (Chamber Slide Lab-Tek II 8; Thermo Fisher Scientific) or coverslips. After appropriate treatment, when indicated, the cells were treated with the selective mitochondrial dye Mitotracker (50 nM; Molecular Probe) for 10 min, washed three times with PBS, and imaged live in growing medium under ambient conditions on an Andromeda iMIC spinning disk live cell microscope with confocal resolution (TILL Photonics, 60X objective). For confocal z-axis stacks, 40 images separated by 0.2 μm along the z-axis were acquired. For measurements of mitochondrial membrane potential, the cells were loaded with 25 nM tetramethylrhodamine methyl ester (TMRM) for 30 min at room temperature, and the dye was present during the experiment together with the multidrug resistance inhibitor cyclosporine H (1 μM). The cells were then observed using an Olympus IX81 inverted microscope equipped with a cell imaging system. Sequential images of TMRM fluorescence were acquired every 60 s with a 40× objective (Olympus). Where indicated, oligomycin (2.5 μg/ml; Sigma-Aldrich) or the uncoupler carbonyl cyanide p-trifluoromethoxyphenylhydrazone (CCCP, 10 μM; Sigma-Aldrich) was added. TMRM fluorescence analysis over the mitochondrial regions of interest was performed using ImageJ. A reduction in TMRM fluorescence represents mitochondrial membrane depolarization. In the graph bars, we indicated TMRM fluorescence after 30-min oligomycin administration in the cells of the indicated genotypes. The cells were always loaded in the presence of the multidrug resistance inhibitor cyclosporine H.

Mitochondria morphology analysis

Quantification of mitochondria length was performed by using ImageJ software. To measure mitochondrial length, we created maximum-intensity projections of z-series with 0.2-μm increments. Quantification was then performed by using “Squassh” (Segmentation and QUAntification of Subcellular SHapes), a plugin compatible with the image processing software ImageJ or Fiji, freely available from http://mosaic.mpi-cbg.de/?q=downloads/imageJ. Squassh is a segmentation method that enables both colocalization and shape analyses of subcellular structures in fluorescence microscopy images (Rizk et al, 2014). For our analysis, segmentation was performed with the minimum intensity threshold set to 0.15 and the regularization weight to 0.015. The mitochondria morphology score was assigned as in Pogson et al (2014). Briefly, a morpho score is assigned to each imaged cell according to the morphology of its mitochondrial network. Numbers represent the designated “morphology score”: 0 = cell with a full complement of mitochondria; 1 = cell with a full complement of mitochondria and some clumped mitochondria; 2 = cell with a reduced mitochondrial network and some clumped mitochondria; 3 = cell with a clumped mitochondrial network; and 4 = cell with a complete clumped mitochondrial network.

Total RNA extraction and qRT-PCR

Total RNA was extracted from Drosophila S2R+ cells using TRI Reagent (Sigma-Aldrich) according to the manufacturer’s instructions. The RNA pellet was dissolved in 5–10 μl RNAase-free water. Total RNA was extracted from approximately 10 flies using Trizol (Life Technologies) and further purified by precipitation with LiCl 8M. RNA samples were checked for integrity by capillary electrophoresis (RNA 6000Nano LabChip; Agilent Technologies). For each sample, 1 μg of RNA was used for first-strand cDNA synthesis, using 10 μM deoxynucleotides, 10 μM oligo-dT, and SuperScript II (Life Technologies). qRT-PCRs were performed in triplicate in a 7500 Real-Time PCR System (Life Technologies) using SYBR Green chemistry (Promega). The 2−ΔΔCt (RQ, relative quantification) method implemented in the 7500 Real-Time PCR System software was used to calculate the relative expression ratio (ref.). The USP8 oligonucleotides primer used were USP8_F (CACCCATTCAAATTGTCGAG) and USP8_R (TCGATGGTCTCAATGTCGTT). Rp49 was used as endogenous control and the oligonucleotides used were Rp49 F (ATCGGTTACGGATCGAACAA) and R (GACAATCTCCTTGCGCTTCT).

Drosophila stocks and procedures

Drosophila were raised under standard conditions at 25°C unless differently stated on agar, cornmeal, yeast food. park mutants and UAS-Parkin have been described before (Greene et al, 2003). PINK1 mutants (Park et al, 2006) were provided by Dr. J Chung (KAIST). w and Act-GAL4 strains were obtained from the Bloomington Drosophila Stock Center. UAS-USP8 RNAi and UAS-Marf RNAi lines were obtained from the VDRC Stock Center. Usp8−/+ and UAS-Usp8 (uspy) lines were kindly provided by S Goto (Mukai et al, 2010).

Climbing assays

Climbing assays were performed as previously described (Greene et al, 2003). For the climbing assay upon drug treatment, groups of 10 flies were collected and placed into an empty vial (12 × 5 cm) with a line drawn at 6 cm from the bottom of the tube. The flies were gently tapped to the bottom of the tube, and the number of flies that successfully climbed above the 6-cm mark after 10 s was noted. Fifteen separate and consecutive trials were performed for each experiment, and the results were averaged. At least 40 flies were tested for each genotype or condition. Data collection and analysis were performed blind to the conditions of the experiments unless otherwise indicated.

Isolation of mitochondria

Mitochondria were extracted from whole flies by differential centrifugation. Each sample was homogenized using a Dounce glass–glass potter and a loose-fitting pestle in a mannitolsucrose buffer (225 mM mannitol, 75 mM sucrose, 5 mM Hepes, and 0.1 mM EGTA, pH 7.4) supplemented with 2% BSA. The samples were then centrifuged at 1,500 g at 4°C for 6 min. The pellet was discarded by filtering the sample through a fine mesh, and the supernatant was centrifuged at 7,000 g at 4°C for 6 min. The resulting pellet was resuspended in mannitolsucrose buffer without BSA before being centrifuged at 7,000 g under the same conditions as above and resuspended in a small volume of mannitolsucrose buffer. Protein concentration was measured using the biuret test.

Mitochondrial respiration

Rates of mitochondrial respiration were measured using the Oxytherm System (Hansatech) with magnetic stirring and thermostatic control maintained at 25°C. Isolated Drosophila mitochondria (1 mg/ml) were incubated in 120 mM KCl, 5 mM Pi-Tris, 3 mM Hepes, 1 mM EGTA, and 1 mM MgCl2, pH 7.2, and additions were made as indicated in the figure legends. O2 consumption was calculated according to the slope of the registered graph and plotted as ng atoms: O2 × min−1 × mg−1. RCR (ADP-stimulated respiration over basal respiration) was calculated.

Immunostaining of whole-mounted brains

Brains of 15-d-old male control or mutant flies were dissected in ice-cold PBS and fixed in 4% PFA at room temperature for 20 min. Samples were washed six times for 10 min with PBS + 0.3% Triton X-100, permeabilized with PBS + 1% Triton X-100 for 10 min, and blocked with PBS + 0.3% Triton X-100 containing 1% BSA overnight at 4°C. For immunostaining of DA neurons, rabbit anti-TH antibody (Millipore) diluted 1:100 in PBS + 0.3% Triton X-100 containing 0.3% BSA was added and incubated over three nights at 4°C. Brains were washed and blocked again as described above, despite the blocking this time being carried out at RT for 1 h. The immunoreaction was revealed with Cy3-conjugated anti-rabbit IgG (Jackson ImmunoResearch) at a working dilution of 1:500 in PBS + 0.3% Triton X-100 containing 0.3% BSA overnight at 4°C. After another six washing steps, whole brains were mounted with Vectashield (Vector Laboratories). Z-stack images were obtained by a Zeiss LSM700 confocal microscope.

Drug treatment

The specific USP8 inhibitor DUBs-IN-2 (ChemScene LLC) was administered to flies in the food. DUBs-IN-2 (or DMSO) was diluted in water to the desired concentration and used to reconstitute dry Formula 4-24 Instant Drosophila Medium (Carolina Biological Supply). 1-d-old male mutant or control flies in groups of 10 were fed on the supplemented food for 48 h and subsequently climbing assay was performed. In the case of DA neuron staining and measurement of dopamine levels, mutant and control flies were aged for 15 d on the supplemented food that was exchanged every 2 d adding fresh drug or vehicle. The use of non-harmful food coloring demonstrated food uptake and excluded the possibility that smell or taste of the drug prevented the latter. Toxic concentrations were excluded beforehand by performing dose-dependent viability curves on control flies.

Drosophila head dopamine amount measurement (HPLC)

Drosophila heads of 15-d-old male flies were dissected out and collected separately in 10 μl of ice-cold 0.2 N perchloric acid. The tissue was homogenized by sonication for 15 s and kept on ice for 20 min, then centrifuged at 12,000 g for 10 min, and the supernatant was collected. The samples were further diluted and 5 μl was injected into a HPLC system equipped with a rheodyne injector and a guard cell, set to +350 mV (E1 = +150 mV, E2 = −350 mV, s: 2 nA). A C18 ion-pair, reverse phase analytical column (4.6 × 250 mm; 5 μm particle size; Agilent Technologies) was used for the separation of biogenic amines with a flow rate of 0.8 ml/min. Composition of the mobile phase was 75 mM sodium phosphate monobasic monohydrate, 6% acetonitrile, 1.7 mM 1-octane sulfonic acid, and 25 μM EDTA (pH 3 ± 0.01). Dopamine values were determined by comparing with the standard peak value.

Electron microscopy

Thoraces were prepared from 3-d-old adult flies and fixed overnight in 2% paraformaldehyde and 2.5% gluteraldehyde. After rinsing in 0.1 M cacodylate buffer with 1% tannic acid, the samples were postfixed in 1:1 2% OsO4 and 0.2 M cacodylate buffer for 1 h. The samples were rinsed, dehydrated in an ethanol series, and embedded using Epon. Ultrathin sections were examined using a transmission electron microscope.

Life span analysis

Male flies of the indicated genotypes were collected during 12 h after hatching and grouped into 20 flies per food vial. At least 100 flies were used for the analysis (exact numbers are indicated in the figure legends). The flies were transferred to fresh food (and fresh drug for the inhibitor treatment) every 2 d, and dead flies were counted in the same interval.

Measurement of food uptake

Dry Formula 4-24 Instant Drosophila Medium (Carolina Biological Supply) was reconstituted with a mix of water and food-coloring patent blue V (E131) (1:1) previously supplemented with DMSO or the desired DUBs-IN-2 concentration. Three groups of 10 male 1–3-d-old w1118 flies were kept in the food vials for 48 h. Afterward, the flies were weighed and homogenized in 20 volumes of PBS with an electric potter. The homogenate was centrifuged for 10 min at 15.000 g and absorbance of the supernatant was measured at 640 nm.

BN PAGE

Pellets of mitochondria isolated from adult male flies of the indicated genotypes were suspended at 10 mg × ml−1 in 1× native PAGE sample buffer (Invitrogen) supplemented with protease inhibitor mixture (Sigma-Aldrich), solubilized with 2% (wt/vol) digitonin and immediately centrifuged at 100,000 g for 25 min at 4°C. The supernatants were supplemented with native PAGE 5% G-250 sample additive (Invitrogen) and quickly loaded onto a blue native polyacrylamide 3–12% gradient gel (Invitrogen). After electrophoresis, the gels were fixed in 50% methanol + 10% acetic acid for 20 min at RT, stained in 0,025% Coomassie + 10% acetic acid overnight at RT and destained with 10% acetic acid.

Sperm content and reproductive apparatus viability assay

The anatomy of male reproductive apparatus was analyzed on 10 males per group. To this aim, the reproductive apparatus was removed, placed on a slide with few drops of Drosophila Ringer’s solution (182 mM KCl, 46 mM NaCl, 3 mM CaCl2 2H2O, and 10 mM Tris–HCl, pH 7.2) and freshly examined under a light microscope. To verify the presence of sperm inside the seminal vesicles, these were then removed from the whole apparatus and gently punctured with a needle to let the sperm pouring out. Five more intact apparatuses per group were stained with a dead/alive cell viability kit (Molecular Probes) that allows differentiation between live green cells, permeable to green SYBR 14 nucleic acid stain, and red dead cells, permeable to propidium iodide nucleic acid stain, which penetrates through compromised membranes.

Statistical analysis

Where multiple groups were compared, statistical significance was calculated by one-way or two-way ANOVA with a post hoc Tukey or Dunett correction. All statistical significance was calculated at P = 0.05, using GraphPad Prism 8. For all the analysis, the samples were collected and processed simultaneously and, therefore, no randomization was appropriate (GraphPad Prism. ****P < 0.0001, ***P < 0.001, **P < 0.01, and *P < 0.05). Please refer to the enclosed document for detailed statistical tests.
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Authors:  Daniel J Klionsky; Amal Kamal Abdel-Aziz; Sara Abdelfatah; Mahmoud Abdellatif; Asghar Abdoli; Steffen Abel; Hagai Abeliovich; Marie H Abildgaard; Yakubu Princely Abudu; Abraham Acevedo-Arozena; Iannis E Adamopoulos; Khosrow Adeli; Timon E Adolph; Annagrazia Adornetto; Elma Aflaki; Galila Agam; Anupam Agarwal; Bharat B Aggarwal; Maria Agnello; Patrizia Agostinis; Javed N Agrewala; Alexander Agrotis; Patricia V Aguilar; S Tariq Ahmad; Zubair M Ahmed; Ulises Ahumada-Castro; Sonja Aits; Shu Aizawa; Yunus Akkoc; Tonia Akoumianaki; Hafize Aysin Akpinar; Ahmed M Al-Abd; Lina Al-Akra; Abeer Al-Gharaibeh; Moulay A Alaoui-Jamali; Simon Alberti; Elísabet Alcocer-Gómez; Cristiano Alessandri; Muhammad Ali; M Abdul Alim Al-Bari; Saeb Aliwaini; Javad Alizadeh; Eugènia Almacellas; Alexandru Almasan; Alicia Alonso; Guillermo D Alonso; Nihal Altan-Bonnet; Dario C Altieri; Élida M C Álvarez; Sara Alves; Cristine Alves da Costa; Mazen M Alzaharna; Marialaura Amadio; Consuelo Amantini; Cristina Amaral; Susanna Ambrosio; Amal O Amer; Veena Ammanathan; Zhenyi An; Stig U Andersen; Shaida A Andrabi; Magaiver Andrade-Silva; Allen M Andres; Sabrina Angelini; David Ann; Uche C Anozie; Mohammad Y Ansari; Pedro Antas; Adam Antebi; Zuriñe Antón; Tahira Anwar; Lionel Apetoh; Nadezda Apostolova; Toshiyuki Araki; Yasuhiro Araki; Kohei Arasaki; Wagner L Araújo; Jun Araya; Catherine Arden; Maria-Angeles Arévalo; Sandro Arguelles; Esperanza Arias; Jyothi Arikkath; Hirokazu Arimoto; Aileen R Ariosa; Darius Armstrong-James; Laetitia Arnauné-Pelloquin; Angeles Aroca; Daniela S Arroyo; Ivica Arsov; Rubén Artero; Dalia Maria Lucia Asaro; Michael Aschner; Milad Ashrafizadeh; Osnat Ashur-Fabian; Atanas G Atanasov; Alicia K Au; Patrick Auberger; Holger W Auner; Laure Aurelian; Riccardo Autelli; Laura Avagliano; Yenniffer Ávalos; Sanja Aveic; Célia Alexandra Aveleira; Tamar Avin-Wittenberg; Yucel Aydin; Scott Ayton; Srinivas Ayyadevara; Maria Azzopardi; Misuzu Baba; Jonathan M Backer; Steven K Backues; Dong-Hun Bae; Ok-Nam Bae; Soo Han Bae; Eric H Baehrecke; Ahruem Baek; Seung-Hoon Baek; Sung Hee Baek; Giacinto Bagetta; Agnieszka Bagniewska-Zadworna; Hua Bai; Jie Bai; Xiyuan Bai; Yidong Bai; Nandadulal Bairagi; Shounak Baksi; Teresa Balbi; Cosima T Baldari; Walter Balduini; Andrea Ballabio; Maria Ballester; Salma Balazadeh; Rena Balzan; Rina Bandopadhyay; Sreeparna Banerjee; Sulagna Banerjee; Ágnes Bánréti; Yan Bao; Mauricio S Baptista; Alessandra Baracca; Cristiana Barbati; Ariadna Bargiela; Daniela Barilà; Peter G Barlow; Sami J Barmada; Esther Barreiro; George E Barreto; Jiri Bartek; Bonnie Bartel; Alberto Bartolome; Gaurav R Barve; Suresh H Basagoudanavar; Diane C Bassham; Robert C Bast; Alakananda Basu; Henri Batoko; Isabella Batten; Etienne E Baulieu; Bradley L Baumgarner; Jagadeesh Bayry; Rupert Beale; Isabelle Beau; Florian Beaumatin; Luiz R G Bechara; George R Beck; Michael F Beers; Jakob Begun; Christian Behrends; Georg M N Behrens; Roberto Bei; Eloy Bejarano; Shai Bel; Christian Behl; Amine Belaid; Naïma Belgareh-Touzé; Cristina Bellarosa; Francesca Belleudi; Melissa Belló Pérez; Raquel Bello-Morales; Jackeline Soares de Oliveira Beltran; Sebastián Beltran; Doris Mangiaracina Benbrook; Mykolas Bendorius; Bruno A Benitez; Irene Benito-Cuesta; Julien Bensalem; Martin W Berchtold; Sabina Berezowska; Daniele Bergamaschi; Matteo Bergami; Andreas Bergmann; Laura Berliocchi; Clarisse Berlioz-Torrent; Amélie Bernard; Lionel Berthoux; Cagri G Besirli; Sebastien Besteiro; Virginie M Betin; Rudi Beyaert; Jelena S Bezbradica; Kiran Bhaskar; Ingrid Bhatia-Kissova; Resham Bhattacharya; Sujoy Bhattacharya; Shalmoli Bhattacharyya; Md Shenuarin Bhuiyan; Sujit Kumar Bhutia; Lanrong Bi; Xiaolin Bi; Trevor J Biden; Krikor Bijian; Viktor A Billes; Nadine Binart; Claudia Bincoletto; Asa B Birgisdottir; Geir Bjorkoy; Gonzalo Blanco; Ana Blas-Garcia; Janusz Blasiak; Robert Blomgran; Klas Blomgren; Janice S Blum; Emilio Boada-Romero; Mirta Boban; Kathleen Boesze-Battaglia; Philippe Boeuf; Barry Boland; Pascale Bomont; Paolo Bonaldo; Srinivasa Reddy Bonam; Laura Bonfili; Juan S Bonifacino; Brian A Boone; Martin D Bootman; Matteo Bordi; Christoph Borner; Beat C Bornhauser; Gautam Borthakur; Jürgen Bosch; Santanu Bose; Luis M Botana; Juan Botas; Chantal M Boulanger; Michael E Boulton; Mathieu Bourdenx; Benjamin Bourgeois; Nollaig M Bourke; Guilhem Bousquet; Patricia Boya; Peter V Bozhkov; Luiz H M Bozi; Tolga O Bozkurt; Doug E Brackney; Christian H Brandts; Ralf J Braun; Gerhard H Braus; Roberto Bravo-Sagua; José M Bravo-San Pedro; Patrick Brest; Marie-Agnès Bringer; Alfredo Briones-Herrera; V Courtney Broaddus; Peter Brodersen; Jeffrey L Brodsky; Steven L Brody; Paola G Bronson; Jeff M Bronstein; Carolyn N Brown; Rhoderick E Brown; Patricia C Brum; John H Brumell; Nicola Brunetti-Pierri; Daniele Bruno; Robert J Bryson-Richardson; Cecilia Bucci; Carmen Buchrieser; Marta Bueno; Laura Elisa Buitrago-Molina; Simone Buraschi; Shilpa Buch; J Ross Buchan; Erin M Buckingham; Hikmet Budak; Mauricio Budini; Geert Bultynck; Florin Burada; Joseph R Burgoyne; M Isabel Burón; Victor Bustos; Sabrina Büttner; Elena Butturini; Aaron Byrd; Isabel Cabas; Sandra Cabrera-Benitez; Ken Cadwell; Jingjing Cai; Lu Cai; Qian Cai; Montserrat Cairó; Jose A Calbet; Guy A Caldwell; Kim A Caldwell; Jarrod A Call; Riccardo Calvani; Ana C Calvo; Miguel Calvo-Rubio Barrera; Niels Os Camara; Jacques H Camonis; Nadine Camougrand; Michelangelo Campanella; Edward M Campbell; François-Xavier Campbell-Valois; Silvia Campello; Ilaria Campesi; Juliane C Campos; Olivier Camuzard; Jorge Cancino; Danilo Candido de Almeida; Laura Canesi; Isabella Caniggia; Barbara Canonico; Carles Cantí; Bin Cao; Michele Caraglia; Beatriz Caramés; Evie H Carchman; Elena Cardenal-Muñoz; Cesar Cardenas; Luis Cardenas; Sandra M Cardoso; Jennifer S Carew; Georges F Carle; Gillian Carleton; Silvia Carloni; Didac Carmona-Gutierrez; Leticia A Carneiro; Oliana Carnevali; Julian M Carosi; Serena Carra; Alice Carrier; Lucie Carrier; Bernadette Carroll; A Brent Carter; Andreia Neves Carvalho; Magali Casanova; Caty Casas; Josefina Casas; Chiara Cassioli; Eliseo F Castillo; Karen Castillo; Sonia Castillo-Lluva; Francesca Castoldi; Marco Castori; Ariel F Castro; Margarida Castro-Caldas; Javier Castro-Hernandez; Susana Castro-Obregon; Sergio D Catz; Claudia Cavadas; Federica Cavaliere; Gabriella Cavallini; Maria Cavinato; Maria L Cayuela; Paula Cebollada Rica; Valentina Cecarini; Francesco Cecconi; Marzanna Cechowska-Pasko; Simone Cenci; Victòria Ceperuelo-Mallafré; João J Cerqueira; Janete M Cerutti; Davide Cervia; Vildan Bozok Cetintas; Silvia Cetrullo; Han-Jung Chae; Andrei S Chagin; Chee-Yin Chai; Gopal Chakrabarti; Oishee Chakrabarti; Tapas Chakraborty; Trinad Chakraborty; Mounia Chami; Georgios Chamilos; David W Chan; Edmond Y W Chan; Edward D Chan; H Y Edwin Chan; Helen H Chan; Hung Chan; Matthew T V Chan; Yau Sang Chan; Partha K Chandra; Chih-Peng Chang; Chunmei Chang; Hao-Chun Chang; Kai Chang; Jie Chao; Tracey Chapman; Nicolas Charlet-Berguerand; Samrat Chatterjee; Shail K Chaube; Anu Chaudhary; Santosh Chauhan; Edward Chaum; Frédéric Checler; Michael E Cheetham; Chang-Shi Chen; Guang-Chao Chen; Jian-Fu Chen; Liam L Chen; Leilei Chen; Lin Chen; Mingliang Chen; Mu-Kuan Chen; Ning Chen; Quan Chen; Ruey-Hwa Chen; Shi Chen; Wei Chen; Weiqiang Chen; Xin-Ming Chen; Xiong-Wen Chen; Xu Chen; Yan Chen; Ye-Guang Chen; Yingyu Chen; Yongqiang Chen; Yu-Jen Chen; Yue-Qin Chen; Zhefan Stephen Chen; Zhi Chen; Zhi-Hua Chen; Zhijian J Chen; Zhixiang Chen; Hanhua Cheng; Jun Cheng; Shi-Yuan Cheng; Wei Cheng; Xiaodong Cheng; Xiu-Tang Cheng; Yiyun Cheng; Zhiyong Cheng; Zhong Chen; Heesun Cheong; Jit Kong Cheong; Boris V Chernyak; Sara Cherry; Chi Fai Randy Cheung; Chun Hei Antonio Cheung; King-Ho Cheung; Eric Chevet; Richard J Chi; Alan Kwok Shing Chiang; Ferdinando Chiaradonna; Roberto Chiarelli; Mario Chiariello; Nathalia Chica; Susanna Chiocca; Mario Chiong; Shih-Hwa Chiou; Abhilash I Chiramel; Valerio Chiurchiù; Dong-Hyung Cho; Seong-Kyu Choe; Augustine M K Choi; Mary E Choi; Kamalika Roy Choudhury; Norman S Chow; Charleen T Chu; Jason P Chua; John Jia En Chua; Hyewon Chung; Kin Pan Chung; Seockhoon Chung; So-Hyang Chung; Yuen-Li Chung; Valentina Cianfanelli; Iwona A Ciechomska; Mariana Cifuentes; Laura Cinque; Sebahattin Cirak; Mara Cirone; Michael J Clague; Robert Clarke; Emilio Clementi; Eliana M Coccia; Patrice Codogno; Ehud Cohen; Mickael M Cohen; Tania Colasanti; Fiorella Colasuonno; Robert A Colbert; Anna Colell; Miodrag Čolić; Nuria S Coll; Mark O Collins; María I Colombo; Daniel A Colón-Ramos; Lydie Combaret; Sergio Comincini; Márcia R Cominetti; Antonella Consiglio; Andrea Conte; Fabrizio Conti; Viorica Raluca Contu; Mark R Cookson; Kevin M Coombs; Isabelle Coppens; Maria Tiziana Corasaniti; Dale P Corkery; Nils Cordes; Katia Cortese; Maria do Carmo Costa; Sarah Costantino; Paola Costelli; Ana Coto-Montes; Peter J Crack; Jose L Crespo; Alfredo Criollo; Valeria Crippa; Riccardo Cristofani; Tamas Csizmadia; Antonio Cuadrado; Bing Cui; Jun Cui; Yixian Cui; Yong Cui; Emmanuel Culetto; Andrea C Cumino; Andrey V Cybulsky; Mark J Czaja; Stanislaw J Czuczwar; Stefania D'Adamo; Marcello D'Amelio; Daniela D'Arcangelo; Andrew C D'Lugos; Gabriella D'Orazi; James A da Silva; Hormos Salimi Dafsari; Ruben K Dagda; Yasin Dagdas; Maria Daglia; Xiaoxia Dai; Yun Dai; Yuyuan Dai; Jessica Dal Col; Paul Dalhaimer; Luisa Dalla Valle; Tobias Dallenga; Guillaume Dalmasso; Markus Damme; Ilaria Dando; Nico P Dantuma; April L Darling; Hiranmoy Das; Srinivasan Dasarathy; Santosh K Dasari; Srikanta Dash; Oliver Daumke; Adrian N Dauphinee; Jeffrey S Davies; Valeria A Dávila; Roger J Davis; Tanja Davis; Sharadha Dayalan Naidu; Francesca De Amicis; Karolien De Bosscher; Francesca De Felice; Lucia De Franceschi; Chiara De Leonibus; Mayara G de Mattos Barbosa; Guido R Y De Meyer; Angelo De Milito; Cosimo De Nunzio; Clara De Palma; Mauro De Santi; Claudio De Virgilio; Daniela De Zio; Jayanta Debnath; Brian J DeBosch; Jean-Paul Decuypere; Mark A Deehan; Gianluca Deflorian; James DeGregori; Benjamin Dehay; Gabriel Del Rio; Joe R Delaney; Lea M D Delbridge; Elizabeth Delorme-Axford; M Victoria Delpino; Francesca Demarchi; Vilma Dembitz; Nicholas D Demers; Hongbin Deng; Zhiqiang Deng; Joern Dengjel; Paul Dent; Donna Denton; Melvin L DePamphilis; Channing J Der; Vojo Deretic; Albert Descoteaux; Laura Devis; Sushil Devkota; Olivier Devuyst; Grant Dewson; Mahendiran Dharmasivam; Rohan Dhiman; Diego di Bernardo; Manlio Di Cristina; Fabio Di Domenico; Pietro Di Fazio; Alessio Di Fonzo; Giovanni Di Guardo; Gianni M Di Guglielmo; Luca Di Leo; Chiara Di Malta; Alessia Di Nardo; Martina Di Rienzo; Federica Di Sano; George Diallinas; Jiajie Diao; Guillermo Diaz-Araya; Inés Díaz-Laviada; Jared M Dickinson; Marc Diederich; Mélanie Dieudé; Ivan Dikic; Shiping Ding; Wen-Xing Ding; Luciana Dini; Jelena Dinić; Miroslav Dinic; Albena T Dinkova-Kostova; Marc S Dionne; Jörg H W Distler; Abhinav Diwan; Ian M C Dixon; Mojgan Djavaheri-Mergny; Ina Dobrinski; Oxana Dobrovinskaya; Radek Dobrowolski; Renwick C J Dobson; Jelena Đokić; Serap Dokmeci Emre; Massimo Donadelli; Bo Dong; Xiaonan Dong; Zhiwu Dong; Gerald W Dorn Ii; Volker Dotsch; Huan Dou; Juan Dou; Moataz Dowaidar; Sami Dridi; Liat Drucker; Ailian Du; Caigan Du; Guangwei Du; Hai-Ning Du; Li-Lin Du; André du Toit; Shao-Bin Duan; Xiaoqiong Duan; Sónia P Duarte; Anna Dubrovska; Elaine A Dunlop; Nicolas Dupont; Raúl V Durán; Bilikere S Dwarakanath; Sergey A Dyshlovoy; Darius Ebrahimi-Fakhari; Leopold Eckhart; Charles L Edelstein; Thomas Efferth; Eftekhar Eftekharpour; Ludwig Eichinger; Nabil Eid; Tobias Eisenberg; N Tony Eissa; Sanaa Eissa; Miriam Ejarque; Abdeljabar El Andaloussi; Nazira El-Hage; Shahenda El-Naggar; Anna Maria Eleuteri; Eman S El-Shafey; Mohamed Elgendy; Aristides G Eliopoulos; María M Elizalde; Philip M Elks; Hans-Peter Elsasser; Eslam S Elsherbiny; Brooke M Emerling; N C Tolga Emre; Christina H Eng; Nikolai Engedal; Anna-Mart Engelbrecht; Agnete S T Engelsen; Jorrit M Enserink; Ricardo Escalante; Audrey Esclatine; Mafalda Escobar-Henriques; Eeva-Liisa Eskelinen; Lucile Espert; Makandjou-Ola Eusebio; Gemma Fabrias; Cinzia Fabrizi; Antonio Facchiano; Francesco Facchiano; Bengt Fadeel; Claudio Fader; Alex C Faesen; W Douglas Fairlie; Alberto Falcó; Bjorn H Falkenburger; Daping Fan; Jie Fan; Yanbo Fan; Evandro F Fang; Yanshan Fang; Yognqi Fang; Manolis Fanto; Tamar Farfel-Becker; Mathias Faure; Gholamreza Fazeli; Anthony O Fedele; Arthur M Feldman; Du Feng; Jiachun Feng; Lifeng Feng; Yibin Feng; Yuchen Feng; Wei Feng; Thais Fenz Araujo; Thomas A Ferguson; Álvaro F Fernández; Jose C Fernandez-Checa; Sonia Fernández-Veledo; Alisdair R Fernie; Anthony W Ferrante; Alessandra Ferraresi; Merari F Ferrari; Julio C B Ferreira; Susan Ferro-Novick; Antonio Figueras; Riccardo Filadi; Nicoletta Filigheddu; Eduardo Filippi-Chiela; Giuseppe Filomeni; Gian Maria Fimia; Vittorio Fineschi; Francesca Finetti; Steven Finkbeiner; Edward A Fisher; Paul B Fisher; Flavio Flamigni; Steven J Fliesler; Trude H Flo; Ida Florance; Oliver Florey; Tullio Florio; Erika Fodor; Carlo Follo; Edward A Fon; Antonella Forlino; Francesco Fornai; Paola Fortini; Anna Fracassi; Alessandro Fraldi; Brunella Franco; Rodrigo Franco; Flavia Franconi; Lisa B Frankel; Scott L Friedman; Leopold F Fröhlich; Gema Frühbeck; Jose M Fuentes; Yukio Fujiki; Naonobu Fujita; Yuuki Fujiwara; Mitsunori Fukuda; Simone Fulda; Luc Furic; Norihiko Furuya; Carmela Fusco; Michaela U Gack; Lidia Gaffke; Sehamuddin Galadari; Alessia Galasso; Maria F Galindo; Sachith Gallolu Kankanamalage; Lorenzo Galluzzi; Vincent Galy; Noor Gammoh; Boyi Gan; Ian G Ganley; Feng Gao; Hui Gao; Minghui Gao; Ping Gao; Shou-Jiang Gao; Wentao Gao; Xiaobo Gao; Ana Garcera; Maria Noé Garcia; Verónica E Garcia; Francisco García-Del Portillo; Vega Garcia-Escudero; Aracely Garcia-Garcia; Marina Garcia-Macia; Diana García-Moreno; Carmen Garcia-Ruiz; Patricia García-Sanz; Abhishek D Garg; Ricardo Gargini; Tina Garofalo; Robert F Garry; Nils C Gassen; Damian Gatica; Liang Ge; Wanzhong Ge; Ruth Geiss-Friedlander; Cecilia Gelfi; Pascal Genschik; Ian E Gentle; Valeria Gerbino; Christoph Gerhardt; Kyla Germain; Marc Germain; David A Gewirtz; Elham Ghasemipour Afshar; Saeid Ghavami; Alessandra Ghigo; Manosij Ghosh; Georgios Giamas; Claudia Giampietri; Alexandra Giatromanolaki; Gary E Gibson; Spencer B Gibson; Vanessa Ginet; Edward Giniger; Carlotta Giorgi; Henrique Girao; Stephen E Girardin; Mridhula Giridharan; Sandy Giuliano; Cecilia Giulivi; Sylvie Giuriato; Julien Giustiniani; Alexander Gluschko; Veit Goder; Alexander Goginashvili; Jakub Golab; David C Goldstone; Anna Golebiewska; Luciana R Gomes; Rodrigo Gomez; Rubén Gómez-Sánchez; Maria Catalina Gomez-Puerto; Raquel Gomez-Sintes; Qingqiu Gong; Felix M Goni; Javier González-Gallego; Tomas Gonzalez-Hernandez; Rosa A Gonzalez-Polo; Jose A Gonzalez-Reyes; Patricia González-Rodríguez; Ing Swie Goping; Marina S Gorbatyuk; Nikolai V Gorbunov; Kıvanç Görgülü; Roxana M Gorojod; Sharon M Gorski; Sandro Goruppi; Cecilia Gotor; Roberta A Gottlieb; Illana Gozes; Devrim Gozuacik; Martin Graef; Markus H Gräler; Veronica Granatiero; Daniel Grasso; Joshua P Gray; Douglas R Green; Alexander Greenhough; Stephen L Gregory; Edward F Griffin; Mark W Grinstaff; Frederic Gros; Charles Grose; Angelina S Gross; Florian Gruber; Paolo Grumati; Tilman Grune; Xueyan Gu; Jun-Lin Guan; Carlos M Guardia; Kishore Guda; Flora Guerra; Consuelo Guerri; Prasun Guha; Carlos Guillén; Shashi Gujar; Anna Gukovskaya; Ilya Gukovsky; Jan Gunst; Andreas Günther; Anyonya R Guntur; Chuanyong Guo; Chun Guo; Hongqing Guo; Lian-Wang Guo; Ming Guo; Pawan Gupta; Shashi Kumar Gupta; Swapnil Gupta; Veer Bala Gupta; Vivek Gupta; Asa B Gustafsson; David D Gutterman; Ranjitha H B; Annakaisa Haapasalo; James E Haber; Aleksandra Hać; Shinji Hadano; Anders J Hafrén; Mansour Haidar; Belinda S Hall; Gunnel Halldén; Anne Hamacher-Brady; Andrea Hamann; Maho Hamasaki; Weidong Han; Malene Hansen; Phyllis I Hanson; Zijian Hao; Masaru Harada; Ljubica Harhaji-Trajkovic; Nirmala Hariharan; Nigil Haroon; James Harris; Takafumi Hasegawa; Noor Hasima Nagoor; Jeffrey A Haspel; Volker Haucke; Wayne D Hawkins; Bruce A Hay; Cole M Haynes; Soren B Hayrabedyan; Thomas S Hays; Congcong He; Qin He; Rong-Rong He; You-Wen He; Yu-Ying He; Yasser Heakal; Alexander M Heberle; J Fielding Hejtmancik; Gudmundur Vignir Helgason; Vanessa Henkel; Marc Herb; Alexander Hergovich; Anna Herman-Antosiewicz; Agustín Hernández; Carlos Hernandez; Sergio Hernandez-Diaz; Virginia Hernandez-Gea; Amaury Herpin; Judit Herreros; Javier H Hervás; Daniel Hesselson; Claudio Hetz; Volker T Heussler; Yujiro Higuchi; Sabine Hilfiker; Joseph A Hill; William S Hlavacek; Emmanuel A Ho; Idy H T Ho; Philip Wing-Lok Ho; Shu-Leong Ho; Wan Yun Ho; G Aaron Hobbs; Mark Hochstrasser; Peter H M Hoet; Daniel Hofius; Paul Hofman; Annika Höhn; Carina I Holmberg; Jose R Hombrebueno; Chang-Won Hong Yi-Ren Hong; Lora V Hooper; Thorsten Hoppe; Rastislav Horos; Yujin Hoshida; I-Lun Hsin; Hsin-Yun Hsu; Bing Hu; Dong Hu; Li-Fang Hu; Ming Chang Hu; Ronggui Hu; Wei Hu; Yu-Chen Hu; Zhuo-Wei Hu; Fang Hua; Jinlian Hua; Yingqi Hua; Chongmin Huan; Canhua Huang; Chuanshu Huang; Chuanxin Huang; Chunling Huang; Haishan Huang; Kun Huang; Michael L H Huang; Rui Huang; Shan Huang; Tianzhi Huang; Xing Huang; Yuxiang Jack Huang; Tobias B Huber; Virginie Hubert; Christian A Hubner; Stephanie M Hughes; William E Hughes; Magali Humbert; Gerhard Hummer; James H Hurley; Sabah Hussain; Salik Hussain; Patrick J Hussey; Martina Hutabarat; Hui-Yun Hwang; Seungmin Hwang; Antonio Ieni; Fumiyo Ikeda; Yusuke Imagawa; Yuzuru Imai; Carol Imbriano; Masaya Imoto; Denise M Inman; Ken Inoki; Juan Iovanna; Renato V Iozzo; Giuseppe Ippolito; Javier E Irazoqui; Pablo Iribarren; Mohd Ishaq; Makoto Ishikawa; Nestor Ishimwe; Ciro Isidoro; Nahed Ismail; Shohreh Issazadeh-Navikas; Eisuke Itakura; Daisuke Ito; Davor Ivankovic; Saška Ivanova; Anand Krishnan V Iyer; José M Izquierdo; Masanori Izumi; Marja Jäättelä; Majid Sakhi Jabir; William T Jackson; Nadia Jacobo-Herrera; Anne-Claire Jacomin; Elise Jacquin; Pooja Jadiya; Hartmut Jaeschke; Chinnaswamy Jagannath; Arjen J Jakobi; Johan Jakobsson; Bassam Janji; Pidder Jansen-Dürr; Patric J Jansson; Jonathan Jantsch; Sławomir Januszewski; Alagie Jassey; Steve Jean; Hélène Jeltsch-David; Pavla Jendelova; Andreas Jenny; Thomas E Jensen; Niels Jessen; Jenna L Jewell; Jing Ji; Lijun Jia; Rui Jia; Liwen Jiang; Qing Jiang; Richeng Jiang; Teng Jiang; Xuejun Jiang; Yu Jiang; Maria Jimenez-Sanchez; Eun-Jung Jin; Fengyan Jin; Hongchuan Jin; Li Jin; Luqi Jin; Meiyan Jin; Si Jin; Eun-Kyeong Jo; Carine Joffre; Terje Johansen; Gail V W Johnson; Simon A Johnston; Eija Jokitalo; Mohit Kumar Jolly; Leo A B Joosten; Joaquin Jordan; Bertrand Joseph; Dianwen Ju; Jeong-Sun Ju; Jingfang Ju; Esmeralda Juárez; Delphine Judith; Gábor Juhász; Youngsoo Jun; Chang Hwa Jung; Sung-Chul Jung; Yong Keun Jung; Heinz Jungbluth; Johannes Jungverdorben; Steffen Just; Kai Kaarniranta; Allen Kaasik; Tomohiro Kabuta; Daniel Kaganovich; Alon Kahana; Renate Kain; Shinjo Kajimura; Maria Kalamvoki; Manjula Kalia; Danuta S Kalinowski; Nina Kaludercic; Ioanna Kalvari; Joanna Kaminska; Vitaliy O Kaminskyy; Hiromitsu Kanamori; Keizo Kanasaki; Chanhee Kang; Rui Kang; Sang Sun Kang; Senthilvelrajan Kaniyappan; Tomotake Kanki; Thirumala-Devi Kanneganti; Anumantha G Kanthasamy; Arthi Kanthasamy; Marc Kantorow; Orsolya Kapuy; Michalis V Karamouzis; Md Razaul Karim; Parimal Karmakar; Rajesh G Katare; Masaru Kato; Stefan H E Kaufmann; Anu Kauppinen; Gur P Kaushal; Susmita Kaushik; Kiyoshi Kawasaki; Kemal Kazan; Po-Yuan Ke; Damien J Keating; Ursula Keber; John H Kehrl; Kate E Keller; Christian W Keller; Jongsook Kim Kemper; Candia M Kenific; Oliver Kepp; Stephanie Kermorgant; Andreas Kern; Robin Ketteler; Tom G Keulers; Boris Khalfin; Hany Khalil; Bilon Khambu; Shahid Y Khan; Vinoth Kumar Megraj Khandelwal; Rekha Khandia; Widuri Kho; Noopur V Khobrekar; Sataree Khuansuwan; Mukhran Khundadze; Samuel A Killackey; Dasol Kim; Deok Ryong Kim; Do-Hyung Kim; Dong-Eun Kim; Eun Young Kim; Eun-Kyoung Kim; Hak-Rim Kim; Hee-Sik Kim; Jeong Hun Kim; Jin Kyung Kim; Jin-Hoi Kim; Joungmok Kim; Ju Hwan Kim; Keun Il Kim; Peter K Kim; Seong-Jun Kim; Scot R Kimball; Adi Kimchi; Alec C Kimmelman; Tomonori Kimura; Matthew A King; Kerri J Kinghorn; Conan G Kinsey; Vladimir Kirkin; Lorrie A Kirshenbaum; Sergey L Kiselev; Shuji Kishi; Katsuhiko Kitamoto; Yasushi Kitaoka; Kaio Kitazato; Richard N Kitsis; Josef T Kittler; Ole Kjaerulff; Peter S Klein; Thomas Klopstock; Jochen Klucken; Helene Knævelsrud; Roland L Knorr; Ben C B Ko; Fred Ko; Jiunn-Liang Ko; Hotaka Kobayashi; Satoru Kobayashi; Ina Koch; Jan C Koch; Ulrich Koenig; Donat Kögel; Young Ho Koh; Masato Koike; Sepp D Kohlwein; Nur M Kocaturk; Masaaki Komatsu; Jeannette König; Toru Kono; Benjamin T Kopp; Tamas Korcsmaros; Gözde Korkmaz; Viktor I Korolchuk; Mónica Suárez Korsnes; Ali Koskela; Janaiah Kota; Yaichiro Kotake; Monica L Kotler; Yanjun Kou; Michael I Koukourakis; Evangelos Koustas; Attila L Kovacs; Tibor Kovács; Daisuke Koya; Tomohiro Kozako; Claudine Kraft; Dimitri Krainc; Helmut Krämer; Anna D Krasnodembskaya; Carole Kretz-Remy; Guido Kroemer; Nicholas T Ktistakis; Kazuyuki Kuchitsu; Sabine Kuenen; Lars Kuerschner; Thomas Kukar; Ajay Kumar; Ashok Kumar; Deepak Kumar; Dhiraj Kumar; Sharad Kumar; Shinji Kume; Caroline Kumsta; Chanakya N Kundu; Mondira Kundu; Ajaikumar B Kunnumakkara; Lukasz Kurgan; Tatiana G Kutateladze; Ozlem Kutlu; SeongAe Kwak; Ho Jeong Kwon; Taeg Kyu Kwon; Yong Tae Kwon; Irene Kyrmizi; Albert La Spada; Patrick Labonté; Sylvain Ladoire; Ilaria Laface; Frank Lafont; Diane C Lagace; Vikramjit Lahiri; Zhibing Lai; Angela S Laird; Aparna Lakkaraju; Trond Lamark; Sheng-Hui Lan; Ane Landajuela; Darius J R Lane; Jon D Lane; Charles H Lang; Carsten Lange; Ülo Langel; Rupert Langer; Pierre Lapaquette; Jocelyn Laporte; Nicholas F LaRusso; Isabel Lastres-Becker; Wilson Chun Yu Lau; Gordon W Laurie; Sergio Lavandero; Betty Yuen Kwan Law; Helen Ka-Wai Law; Rob Layfield; Weidong Le; Herve Le Stunff; Alexandre Y Leary; Jean-Jacques Lebrun; Lionel Y W Leck; Jean-Philippe Leduc-Gaudet; Changwook Lee; Chung-Pei Lee; Da-Hye Lee; Edward B Lee; Erinna F Lee; Gyun Min Lee; He-Jin Lee; Heung Kyu Lee; Jae Man Lee; Jason S Lee; Jin-A Lee; Joo-Yong Lee; Jun Hee Lee; Michael Lee; Min Goo Lee; Min Jae Lee; Myung-Shik Lee; Sang Yoon Lee; Seung-Jae Lee; Stella Y Lee; Sung Bae Lee; Won Hee Lee; Ying-Ray Lee; Yong-Ho Lee; Youngil Lee; Christophe Lefebvre; Renaud Legouis; Yu L Lei; Yuchen Lei; Sergey Leikin; Gerd Leitinger; Leticia Lemus; Shuilong Leng; Olivia Lenoir; Guido Lenz; Heinz Josef Lenz; Paola Lenzi; Yolanda León; Andréia M Leopoldino; Christoph Leschczyk; Stina Leskelä; Elisabeth Letellier; Chi-Ting Leung; Po Sing Leung; Jeremy S Leventhal; Beth Levine; Patrick A Lewis; Klaus Ley; Bin Li; Da-Qiang Li; Jianming Li; Jing Li; Jiong Li; Ke Li; Liwu Li; Mei Li; Min Li; Min Li; Ming Li; Mingchuan Li; Pin-Lan Li; Ming-Qing Li; Qing Li; Sheng Li; Tiangang Li; Wei Li; Wenming Li; Xue Li; Yi-Ping Li; Yuan Li; Zhiqiang Li; Zhiyong Li; Zhiyuan Li; Jiqin Lian; Chengyu Liang; Qiangrong Liang; Weicheng Liang; Yongheng Liang; YongTian Liang; Guanghong Liao; Lujian Liao; Mingzhi Liao; Yung-Feng Liao; Mariangela Librizzi; Pearl P Y Lie; Mary A Lilly; Hyunjung J Lim; Thania R R Lima; Federica Limana; Chao Lin; Chih-Wen Lin; Dar-Shong Lin; Fu-Cheng Lin; Jiandie D Lin; Kurt M Lin; Kwang-Huei Lin; Liang-Tzung Lin; Pei-Hui Lin; Qiong Lin; Shaofeng Lin; Su-Ju Lin; Wenyu Lin; Xueying Lin; Yao-Xin Lin; Yee-Shin Lin; Rafael Linden; Paula Lindner; Shuo-Chien Ling; Paul Lingor; Amelia K Linnemann; Yih-Cherng Liou; Marta M Lipinski; Saška Lipovšek; Vitor A Lira; Natalia Lisiak; Paloma B Liton; Chao Liu; Ching-Hsuan Liu; Chun-Feng Liu; Cui Hua Liu; Fang Liu; Hao Liu; Hsiao-Sheng Liu; Hua-Feng Liu; Huifang Liu; Jia Liu; Jing Liu; Julia Liu; Leyuan Liu; Longhua Liu; Meilian Liu; Qin Liu; Wei Liu; Wende Liu; Xiao-Hong Liu; Xiaodong Liu; Xingguo Liu; Xu Liu; Xuedong Liu; Yanfen Liu; Yang Liu; Yang Liu; Yueyang Liu; Yule Liu; J Andrew Livingston; Gerard Lizard; Jose M Lizcano; Senka Ljubojevic-Holzer; Matilde E LLeonart; David Llobet-Navàs; Alicia Llorente; Chih Hung Lo; Damián Lobato-Márquez; Qi Long; Yun Chau Long; Ben Loos; Julia A Loos; Manuela G López; Guillermo López-Doménech; José Antonio López-Guerrero; Ana T López-Jiménez; Óscar López-Pérez; Israel López-Valero; Magdalena J Lorenowicz; Mar Lorente; Peter Lorincz; Laura Lossi; Sophie Lotersztajn; Penny E Lovat; Jonathan F Lovell; Alenka Lovy; Péter Lőw; Guang Lu; Haocheng Lu; Jia-Hong Lu; Jin-Jian Lu; Mengji Lu; Shuyan Lu; Alessandro Luciani; John M Lucocq; Paula Ludovico; Micah A Luftig; Morten Luhr; Diego Luis-Ravelo; Julian J Lum; Liany Luna-Dulcey; Anders H Lund; Viktor K Lund; Jan D Lünemann; Patrick Lüningschrör; Honglin Luo; Rongcan Luo; Shouqing Luo; Zhi Luo; Claudio Luparello; Bernhard Lüscher; Luan Luu; Alex Lyakhovich; Konstantin G Lyamzaev; Alf Håkon Lystad; Lyubomyr Lytvynchuk; Alvin C Ma; Changle Ma; Mengxiao Ma; Ning-Fang Ma; Quan-Hong Ma; Xinliang Ma; Yueyun Ma; Zhenyi Ma; Ormond A MacDougald; Fernando Macian; Gustavo C MacIntosh; Jeffrey P MacKeigan; Kay F Macleod; Sandra Maday; Frank Madeo; Muniswamy Madesh; Tobias Madl; Julio Madrigal-Matute; Akiko Maeda; Yasuhiro Maejima; Marta Magarinos; Poornima Mahavadi; Emiliano Maiani; Kenneth Maiese; Panchanan Maiti; Maria Chiara Maiuri; Barbara Majello; Michael B Major; Elena Makareeva; Fayaz Malik; Karthik Mallilankaraman; Walter Malorni; Alina Maloyan; Najiba Mammadova; Gene Chi Wai Man; Federico Manai; Joseph D Mancias; Eva-Maria Mandelkow; Michael A Mandell; Angelo A Manfredi; Masoud H Manjili; Ravi Manjithaya; Patricio Manque; Bella B Manshian; Raquel Manzano; Claudia Manzoni; Kai Mao; Cinzia Marchese; Sandrine Marchetti; Anna Maria Marconi; Fabrizio Marcucci; Stefania Mardente; Olga A Mareninova; Marta Margeta; Muriel Mari; Sara Marinelli; Oliviero Marinelli; Guillermo Mariño; Sofia Mariotto; Richard S Marshall; Mark R Marten; Sascha Martens; Alexandre P J Martin; Katie R Martin; Sara Martin; Shaun Martin; Adrián Martín-Segura; Miguel A Martín-Acebes; Inmaculada Martin-Burriel; Marcos Martin-Rincon; Paloma Martin-Sanz; José A Martina; Wim Martinet; Aitor Martinez; Ana Martinez; Jennifer Martinez; Moises Martinez Velazquez; Nuria Martinez-Lopez; Marta Martinez-Vicente; Daniel O Martins; Joilson O Martins; Waleska K Martins; Tania Martins-Marques; Emanuele Marzetti; Shashank Masaldan; Celine Masclaux-Daubresse; Douglas G Mashek; Valentina Massa; Lourdes Massieu; Glenn R Masson; Laura Masuelli; Anatoliy I Masyuk; Tetyana V Masyuk; Paola Matarrese; Ander Matheu; Satoaki Matoba; Sachiko Matsuzaki; Pamela Mattar; Alessandro Matte; Domenico Mattoscio; José L Mauriz; Mario Mauthe; Caroline Mauvezin; Emanual Maverakis; Paola Maycotte; Johanna Mayer; Gianluigi Mazzoccoli; Cristina Mazzoni; Joseph R Mazzulli; Nami McCarty; Christine McDonald; Mitchell R McGill; Sharon L McKenna; BethAnn McLaughlin; Fionn McLoughlin; Mark A McNiven; Thomas G McWilliams; Fatima Mechta-Grigoriou; Tania Catarina Medeiros; Diego L Medina; Lynn A Megeney; Klara Megyeri; Maryam Mehrpour; Jawahar L Mehta; Alfred J Meijer; Annemarie H Meijer; Jakob Mejlvang; Alicia Meléndez; Annette Melk; Gonen Memisoglu; Alexandrina F Mendes; Delong Meng; Fei Meng; Tian Meng; Rubem Menna-Barreto; Manoj B Menon; Carol Mercer; Anne E Mercier; Jean-Louis Mergny; Adalberto Merighi; Seth D Merkley; Giuseppe Merla; Volker Meske; Ana Cecilia Mestre; Shree Padma Metur; Christian Meyer; Hemmo Meyer; Wenyi Mi; Jeanne Mialet-Perez; Junying Miao; Lucia Micale; Yasuo Miki; Enrico Milan; Małgorzata Milczarek; Dana L Miller; Samuel I Miller; Silke Miller; Steven W Millward; Ira Milosevic; Elena A Minina; Hamed Mirzaei; Hamid Reza Mirzaei; Mehdi Mirzaei; Amit Mishra; Nandita Mishra; Paras Kumar Mishra; Maja Misirkic Marjanovic; Roberta Misasi; Amit Misra; Gabriella Misso; Claire Mitchell; Geraldine Mitou; Tetsuji Miura; Shigeki Miyamoto; Makoto Miyazaki; Mitsunori Miyazaki; Taiga Miyazaki; Keisuke Miyazawa; Noboru Mizushima; Trine H Mogensen; Baharia Mograbi; Reza Mohammadinejad; Yasir Mohamud; Abhishek Mohanty; Sipra Mohapatra; Torsten Möhlmann; Asif Mohmmed; Anna Moles; Kelle H Moley; Maurizio Molinari; Vincenzo Mollace; Andreas Buch Møller; Bertrand Mollereau; Faustino Mollinedo; Costanza Montagna; Mervyn J Monteiro; Andrea Montella; L Ruth Montes; Barbara Montico; Vinod K Mony; Giacomo Monzio Compagnoni; Michael N Moore; Mohammad A Moosavi; Ana L Mora; Marina Mora; David Morales-Alamo; Rosario Moratalla; Paula I Moreira; Elena Morelli; Sandra Moreno; Daniel Moreno-Blas; Viviana Moresi; Benjamin Morga; Alwena H Morgan; Fabrice Morin; Hideaki Morishita; Orson L Moritz; Mariko Moriyama; Yuji Moriyasu; Manuela Morleo; Eugenia Morselli; Jose F Moruno-Manchon; Jorge Moscat; Serge Mostowy; Elisa Motori; Andrea Felinto Moura; Naima Moustaid-Moussa; Maria Mrakovcic; Gabriel Muciño-Hernández; Anupam Mukherjee; Subhadip Mukhopadhyay; Jean M Mulcahy Levy; Victoriano Mulero; Sylviane Muller; Christian Münch; Ashok Munjal; Pura Munoz-Canoves; Teresa Muñoz-Galdeano; Christian Münz; Tomokazu Murakawa; Claudia Muratori; Brona M Murphy; J Patrick Murphy; Aditya Murthy; Timo T Myöhänen; Indira U Mysorekar; Jennifer Mytych; Seyed Mohammad Nabavi; Massimo Nabissi; Péter Nagy; Jihoon Nah; Aimable Nahimana; Ichiro Nakagawa; Ken Nakamura; Hitoshi Nakatogawa; Shyam S Nandi; Meera Nanjundan; Monica Nanni; Gennaro Napolitano; Roberta Nardacci; Masashi Narita; Melissa Nassif; Ilana Nathan; Manabu Natsumeda; Ryno J Naude; Christin Naumann; Olaia Naveiras; Fatemeh Navid; Steffan T Nawrocki; Taras Y Nazarko; Francesca Nazio; Florentina Negoita; Thomas Neill; Amanda L Neisch; Luca M Neri; Mihai G Netea; Patrick Neubert; Thomas P Neufeld; Dietbert Neumann; Albert Neutzner; Phillip T Newton; Paul A Ney; Ioannis P Nezis; Charlene C W Ng; Tzi Bun Ng; Hang T T Nguyen; Long T Nguyen; Hong-Min Ni; Clíona Ní Cheallaigh; Zhenhong Ni; M Celeste Nicolao; Francesco Nicoli; Manuel Nieto-Diaz; Per Nilsson; Shunbin Ning; Rituraj Niranjan; Hiroshi Nishimune; Mireia Niso-Santano; Ralph A Nixon; Annalisa Nobili; Clevio Nobrega; Takeshi Noda; Uxía Nogueira-Recalde; Trevor M Nolan; Ivan Nombela; Ivana Novak; Beatriz Novoa; Takashi Nozawa; Nobuyuki Nukina; Carmen Nussbaum-Krammer; Jesper Nylandsted; Tracey R O'Donovan; Seónadh M O'Leary; Eyleen J O'Rourke; Mary P O'Sullivan; Timothy E O'Sullivan; Salvatore Oddo; Ina Oehme; Michinaga Ogawa; Eric Ogier-Denis; Margret H Ogmundsdottir; Besim Ogretmen; Goo Taeg Oh; Seon-Hee Oh; Young J Oh; Takashi Ohama; Yohei Ohashi; Masaki Ohmuraya; Vasileios Oikonomou; Rani Ojha; Koji Okamoto; Hitoshi Okazawa; Masahide Oku; Sara Oliván; Jorge M A Oliveira; Michael Ollmann; James A Olzmann; Shakib Omari; M Bishr Omary; Gizem Önal; Martin Ondrej; Sang-Bing Ong; Sang-Ging Ong; Anna Onnis; Juan A Orellana; Sara Orellana-Muñoz; Maria Del Mar Ortega-Villaizan; Xilma R Ortiz-Gonzalez; Elena Ortona; Heinz D Osiewacz; Abdel-Hamid K Osman; Rosario Osta; Marisa S Otegui; Kinya Otsu; Christiane Ott; Luisa Ottobrini; Jing-Hsiung James Ou; Tiago F Outeiro; Inger Oynebraten; Melek Ozturk; Gilles Pagès; Susanta Pahari; Marta Pajares; Utpal B Pajvani; Rituraj Pal; Simona Paladino; Nicolas Pallet; Michela Palmieri; Giuseppe Palmisano; Camilla Palumbo; Francesco Pampaloni; Lifeng Pan; Qingjun Pan; Wenliang Pan; Xin Pan; Ganna Panasyuk; Rahul Pandey; Udai B Pandey; Vrajesh Pandya; Francesco Paneni; Shirley Y Pang; Elisa Panzarini; Daniela L Papademetrio; Elena Papaleo; Daniel Papinski; Diana Papp; Eun Chan Park; Hwan Tae Park; Ji-Man Park; Jong-In Park; Joon Tae Park; Junsoo Park; Sang Chul Park; Sang-Youel Park; Abraham H Parola; Jan B Parys; Adrien Pasquier; Benoit Pasquier; João F Passos; Nunzia Pastore; Hemal H Patel; Daniel Patschan; Sophie Pattingre; Gustavo Pedraza-Alva; Jose Pedraza-Chaverri; Zully Pedrozo; Gang Pei; Jianming Pei; Hadas Peled-Zehavi; Joaquín M Pellegrini; Joffrey Pelletier; Miguel A Peñalva; Di Peng; Ying Peng; Fabio Penna; Maria Pennuto; Francesca Pentimalli; Cláudia Mf Pereira; Gustavo J S Pereira; Lilian C Pereira; Luis Pereira de Almeida; Nirma D Perera; Ángel Pérez-Lara; Ana B Perez-Oliva; María Esther Pérez-Pérez; Palsamy Periyasamy; Andras Perl; Cristiana Perrotta; Ida Perrotta; Richard G Pestell; Morten Petersen; Irina Petrache; Goran Petrovski; Thorsten Pfirrmann; Astrid S Pfister; Jennifer A Philips; Huifeng Pi; Anna Picca; Alicia M Pickrell; Sandy Picot; Giovanna M Pierantoni; Marina Pierdominici; Philippe Pierre; Valérie Pierrefite-Carle; Karolina Pierzynowska; Federico Pietrocola; Miroslawa Pietruczuk; Claudio Pignata; Felipe X Pimentel-Muiños; Mario Pinar; Roberta O Pinheiro; Ronit Pinkas-Kramarski; Paolo Pinton; Karolina Pircs; Sujan Piya; Paola Pizzo; Theo S Plantinga; Harald W Platta; Ainhoa Plaza-Zabala; Markus Plomann; Egor Y Plotnikov; Helene Plun-Favreau; Ryszard Pluta; Roger Pocock; Stefanie Pöggeler; Christian Pohl; Marc Poirot; Angelo Poletti; Marisa Ponpuak; Hana Popelka; Blagovesta Popova; Helena Porta; Soledad Porte Alcon; Eliana Portilla-Fernandez; Martin Post; Malia B Potts; Joanna Poulton; Ted Powers; Veena Prahlad; Tomasz K Prajsnar; Domenico Praticò; Rosaria Prencipe; Muriel Priault; Tassula Proikas-Cezanne; Vasilis J Promponas; Christopher G Proud; Rosa Puertollano; Luigi Puglielli; Thomas Pulinilkunnil; Deepika Puri; Rajat Puri; Julien Puyal; Xiaopeng Qi; Yongmei Qi; Wenbin Qian; Lei Qiang; Yu Qiu; Joe Quadrilatero; Jorge Quarleri; Nina Raben; Hannah Rabinowich; Debora Ragona; Michael J Ragusa; Nader Rahimi; Marveh Rahmati; Valeria Raia; Nuno Raimundo; Namakkal-Soorappan Rajasekaran; Sriganesh Ramachandra Rao; Abdelhaq Rami; Ignacio Ramírez-Pardo; David B Ramsden; Felix Randow; Pundi N Rangarajan; Danilo Ranieri; Hai Rao; Lang Rao; Rekha Rao; Sumit Rathore; J Arjuna Ratnayaka; Edward A Ratovitski; Palaniyandi Ravanan; Gloria Ravegnini; Swapan K Ray; Babak Razani; Vito Rebecca; Fulvio Reggiori; Anne Régnier-Vigouroux; Andreas S Reichert; David Reigada; Jan H Reiling; Theo Rein; Siegfried Reipert; Rokeya Sultana Rekha; Hongmei Ren; Jun Ren; Weichao Ren; Tristan Renault; Giorgia Renga; Karen Reue; Kim Rewitz; Bruna Ribeiro de Andrade Ramos; S Amer Riazuddin; Teresa M Ribeiro-Rodrigues; Jean-Ehrland Ricci; Romeo Ricci; Victoria Riccio; Des R Richardson; Yasuko Rikihisa; Makarand V Risbud; Ruth M Risueño; Konstantinos Ritis; Salvatore Rizza; Rosario Rizzuto; Helen C Roberts; Luke D Roberts; Katherine J Robinson; Maria Carmela Roccheri; Stephane Rocchi; George G Rodney; Tiago Rodrigues; Vagner Ramon Rodrigues Silva; Amaia Rodriguez; Ruth Rodriguez-Barrueco; Nieves Rodriguez-Henche; Humberto Rodriguez-Rocha; Jeroen Roelofs; Robert S Rogers; Vladimir V Rogov; Ana I Rojo; Krzysztof Rolka; Vanina Romanello; Luigina Romani; Alessandra Romano; Patricia S Romano; David Romeo-Guitart; Luis C Romero; Montserrat Romero; Joseph C Roney; Christopher Rongo; Sante Roperto; Mathias T Rosenfeldt; Philip Rosenstiel; Anne G Rosenwald; Kevin A Roth; Lynn Roth; Steven Roth; Kasper M A Rouschop; 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Alberto Sanz; Pascual Sanz; Shweta Saran; Marco Sardiello; Timothy J Sargeant; Apurva Sarin; Chinmoy Sarkar; Sovan Sarkar; Maria-Rosa Sarrias; Surajit Sarkar; Dipanka Tanu Sarmah; Jaakko Sarparanta; Aishwarya Sathyanarayan; Ranganayaki Sathyanarayanan; K Matthew Scaglione; Francesca Scatozza; Liliana Schaefer; Zachary T Schafer; Ulrich E Schaible; Anthony H V Schapira; Michael Scharl; Hermann M Schatzl; Catherine H Schein; Wiep Scheper; David Scheuring; Maria Vittoria Schiaffino; Monica Schiappacassi; Rainer Schindl; Uwe Schlattner; Oliver Schmidt; Roland Schmitt; Stephen D Schmidt; Ingo Schmitz; Eran Schmukler; Anja Schneider; Bianca E Schneider; Romana Schober; Alejandra C Schoijet; Micah B Schott; Michael Schramm; Bernd Schröder; Kai Schuh; Christoph Schüller; Ryan J Schulze; Lea Schürmanns; Jens C Schwamborn; Melanie Schwarten; Filippo Scialo; Sebastiano Sciarretta; Melanie J Scott; Kathleen W Scotto; A Ivana Scovassi; Andrea Scrima; Aurora Scrivo; David Sebastian; Salwa Sebti; Simon Sedej; 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Bruno J de Andrade Silva; Johnatas D Silva; Eduardo Silva-Pavez; Sandrine Silvente-Poirot; Rachel E Simmonds; Anna Katharina Simon; Hans-Uwe Simon; Matias Simons; Anurag Singh; Lalit P Singh; Rajat Singh; Shivendra V Singh; Shrawan K Singh; Sudha B Singh; Sunaina Singh; Surinder Pal Singh; Debasish Sinha; Rohit Anthony Sinha; Sangita Sinha; Agnieszka Sirko; Kapil Sirohi; Efthimios L Sivridis; Panagiotis Skendros; Aleksandra Skirycz; Iva Slaninová; Soraya S Smaili; Andrei Smertenko; Matthew D Smith; Stefaan J Soenen; Eun Jung Sohn; Sophia P M Sok; Giancarlo Solaini; Thierry Soldati; Scott A Soleimanpour; Rosa M Soler; Alexei Solovchenko; Jason A Somarelli; Avinash Sonawane; Fuyong Song; Hyun Kyu Song; Ju-Xian Song; Kunhua Song; Zhiyin Song; Leandro R Soria; Maurizio Sorice; Alexander A Soukas; Sandra-Fausia Soukup; Diana Sousa; Nadia Sousa; Paul A Spagnuolo; Stephen A Spector; M M Srinivas Bharath; Daret St Clair; Venturina Stagni; Leopoldo Staiano; Clint A Stalnecker; Metodi V Stankov; 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Motomasa Tanaka; Daolin Tang; Jingfeng Tang; Tie-Shan Tang; Isei Tanida; Zhipeng Tao; Mohammed Taouis; Lars Tatenhorst; Nektarios Tavernarakis; Allen Taylor; Gregory A Taylor; Joan M Taylor; Elena Tchetina; Andrew R Tee; Irmgard Tegeder; David Teis; Natercia Teixeira; Fatima Teixeira-Clerc; Kumsal A Tekirdag; Tewin Tencomnao; Sandra Tenreiro; Alexei V Tepikin; Pilar S Testillano; Gianluca Tettamanti; Pierre-Louis Tharaux; Kathrin Thedieck; Arvind A Thekkinghat; Stefano Thellung; Josephine W Thinwa; V P Thirumalaikumar; Sufi Mary Thomas; Paul G Thomes; Andrew Thorburn; Lipi Thukral; Thomas Thum; Michael Thumm; Ling Tian; Ales Tichy; Andreas Till; Vincent Timmerman; Vladimir I Titorenko; Sokol V Todi; Krassimira Todorova; Janne M Toivonen; Luana Tomaipitinca; Dhanendra Tomar; Cristina Tomas-Zapico; Sergej Tomić; Benjamin Chun-Kit Tong; Chao Tong; Xin Tong; Sharon A Tooze; Maria L Torgersen; Satoru Torii; Liliana Torres-López; Alicia Torriglia; Christina G Towers; Roberto Towns; Shinya Toyokuni; Vladimir Trajkovic; Donatella Tramontano; Quynh-Giao Tran; Leonardo H Travassos; Charles B Trelford; Shirley Tremel; Ioannis P Trougakos; Betty P Tsao; Mario P Tschan; Hung-Fat Tse; Tak Fu Tse; Hitoshi Tsugawa; Andrey S Tsvetkov; David A Tumbarello; Yasin Tumtas; María J Tuñón; Sandra Turcotte; Boris Turk; Vito Turk; Bradley J Turner; Richard I Tuxworth; Jessica K Tyler; Elena V Tyutereva; Yasuo Uchiyama; Aslihan Ugun-Klusek; Holm H Uhlig; Marzena Ułamek-Kozioł; Ilya V Ulasov; Midori Umekawa; Christian Ungermann; Rei Unno; Sylvie Urbe; Elisabet Uribe-Carretero; Suayib Üstün; Vladimir N Uversky; Thomas Vaccari; Maria I Vaccaro; Björn F Vahsen; Helin Vakifahmetoglu-Norberg; Rut Valdor; Maria J Valente; Ayelén Valko; Richard B Vallee; Angela M Valverde; Greet Van den Berghe; Stijn van der Veen; Luc Van Kaer; Jorg van Loosdregt; Sjoerd J L van Wijk; Wim Vandenberghe; Ilse Vanhorebeek; Marcos A Vannier-Santos; Nicola Vannini; M Cristina Vanrell; Chiara Vantaggiato; Gabriele Varano; Isabel Varela-Nieto; Máté Varga; M Helena Vasconcelos; Somya Vats; Demetrios G Vavvas; Ignacio Vega-Naredo; Silvia Vega-Rubin-de-Celis; Guillermo Velasco; Ariadna P Velázquez; Tibor Vellai; Edo Vellenga; Francesca Velotti; Mireille Verdier; Panayotis Verginis; Isabelle Vergne; Paul Verkade; Manish Verma; Patrik Verstreken; Tim Vervliet; Jörg Vervoorts; Alexandre T Vessoni; Victor M Victor; Michel Vidal; Chiara Vidoni; Otilia V Vieira; Richard D Vierstra; Sonia Viganó; Helena Vihinen; Vinoy Vijayan; Miquel Vila; Marçal Vilar; José M Villalba; Antonio Villalobo; Beatriz Villarejo-Zori; Francesc Villarroya; Joan Villarroya; Olivier Vincent; Cecile Vindis; Christophe Viret; Maria Teresa Viscomi; Dora Visnjic; Ilio Vitale; David J Vocadlo; Olga V Voitsekhovskaja; Cinzia Volonté; Mattia Volta; Marta Vomero; Clarissa Von Haefen; Marc A Vooijs; Wolfgang Voos; Ljubica Vucicevic; Richard Wade-Martins; Satoshi Waguri; Kenrick A Waite; Shuji Wakatsuki; David W Walker; Mark J Walker; Simon A Walker; Jochen Walter; Francisco G Wandosell; Bo Wang; Chao-Yung Wang; Chen Wang; Chenran Wang; Chenwei Wang; Cun-Yu Wang; Dong Wang; Fangyang Wang; Feng Wang; Fengming Wang; Guansong Wang; Han Wang; Hao Wang; Hexiang Wang; Hong-Gang Wang; Jianrong Wang; Jigang Wang; Jiou Wang; Jundong Wang; Kui Wang; Lianrong Wang; Liming Wang; Maggie Haitian Wang; Meiqing Wang; Nanbu Wang; Pengwei Wang; Peipei Wang; Ping Wang; Ping Wang; Qing Jun Wang; Qing Wang; Qing Kenneth Wang; Qiong A Wang; Wen-Tao Wang; Wuyang Wang; Xinnan Wang; Xuejun Wang; Yan Wang; Yanchang Wang; Yanzhuang Wang; Yen-Yun Wang; Yihua Wang; Yipeng Wang; Yu Wang; Yuqi Wang; Zhe Wang; Zhenyu Wang; Zhouguang Wang; Gary Warnes; Verena Warnsmann; Hirotaka Watada; Eizo Watanabe; Maxinne Watchon; Anna Wawrzyńska; Timothy E Weaver; Grzegorz Wegrzyn; Ann M Wehman; Huafeng Wei; Lei Wei; Taotao Wei; Yongjie Wei; Oliver H Weiergräber; Conrad C Weihl; Günther Weindl; Ralf Weiskirchen; Alan Wells; Runxia H Wen; Xin Wen; Antonia Werner; Beatrice Weykopf; Sally P Wheatley; J Lindsay Whitton; Alexander J Whitworth; Katarzyna Wiktorska; Manon E Wildenberg; Tom Wileman; Simon Wilkinson; Dieter Willbold; Brett Williams; Robin S B Williams; Roger L Williams; Peter R Williamson; Richard A Wilson; Beate Winner; Nathaniel J Winsor; Steven S Witkin; Harald Wodrich; Ute Woehlbier; Thomas Wollert; Esther Wong; Jack Ho Wong; Richard W Wong; Vincent Kam Wai Wong; W Wei-Lynn Wong; An-Guo Wu; Chengbiao Wu; Jian Wu; Junfang Wu; Kenneth K Wu; Min Wu; Shan-Ying Wu; Shengzhou Wu; Shu-Yan Wu; Shufang Wu; William K K Wu; Xiaohong Wu; Xiaoqing Wu; Yao-Wen Wu; Yihua Wu; Ramnik J Xavier; Hongguang Xia; Lixin Xia; Zhengyuan Xia; Ge Xiang; Jin Xiang; Mingliang Xiang; Wei Xiang; Bin Xiao; Guozhi Xiao; Hengyi Xiao; Hong-Tao Xiao; Jian Xiao; Lan Xiao; Shi Xiao; Yin Xiao; Baoming Xie; Chuan-Ming Xie; Min Xie; Yuxiang Xie; Zhiping Xie; Zhonglin Xie; Maria Xilouri; Congfeng Xu; En Xu; Haoxing Xu; Jing Xu; JinRong Xu; Liang Xu; Wen Wen Xu; Xiulong Xu; Yu Xue; Sokhna M S Yakhine-Diop; Masamitsu Yamaguchi; Osamu Yamaguchi; Ai Yamamoto; Shunhei Yamashina; Shengmin Yan; Shian-Jang Yan; Zhen Yan; Yasuo Yanagi; Chuanbin Yang; Dun-Sheng Yang; Huan Yang; Huang-Tian Yang; Hui Yang; Jin-Ming Yang; Jing Yang; Jingyu Yang; Ling Yang; Liu Yang; Ming Yang; Pei-Ming Yang; Qian Yang; Seungwon Yang; Shu Yang; Shun-Fa Yang; Wannian Yang; Wei Yuan Yang; Xiaoyong Yang; Xuesong Yang; Yi Yang; Ying Yang; Honghong Yao; Shenggen Yao; Xiaoqiang Yao; Yong-Gang Yao; Yong-Ming Yao; Takahiro Yasui; Meysam Yazdankhah; Paul M Yen; Cong Yi; Xiao-Ming Yin; Yanhai Yin; Zhangyuan Yin; Ziyi Yin; Meidan Ying; Zheng Ying; Calvin K Yip; Stephanie Pei Tung Yiu; Young H Yoo; Kiyotsugu Yoshida; Saori R Yoshii; Tamotsu Yoshimori; Bahman Yousefi; Boxuan Yu; Haiyang Yu; Jun Yu; Jun Yu; Li Yu; Ming-Lung Yu; Seong-Woon Yu; Victor C Yu; W Haung Yu; Zhengping Yu; Zhou Yu; Junying Yuan; Ling-Qing Yuan; Shilin Yuan; Shyng-Shiou F Yuan; Yanggang Yuan; Zengqiang Yuan; Jianbo Yue; Zhenyu Yue; Jeanho Yun; Raymond L Yung; David N Zacks; Gabriele Zaffagnini; Vanessa O Zambelli; Isabella Zanella; Qun S Zang; Sara Zanivan; Silvia Zappavigna; Pilar Zaragoza; Konstantinos S Zarbalis; Amir Zarebkohan; Amira Zarrouk; Scott O Zeitlin; Jialiu Zeng; Ju-Deng Zeng; Eva Žerovnik; Lixuan Zhan; Bin Zhang; Donna D Zhang; Hanlin Zhang; Hong Zhang; Hong Zhang; Honghe Zhang; Huafeng Zhang; Huaye Zhang; Hui Zhang; Hui-Ling Zhang; Jianbin Zhang; Jianhua Zhang; Jing-Pu Zhang; Kalin Y B Zhang; Leshuai W Zhang; Lin Zhang; Lisheng Zhang; Lu Zhang; Luoying Zhang; Menghuan Zhang; Peng Zhang; Sheng Zhang; Wei Zhang; Xiangnan Zhang; Xiao-Wei Zhang; Xiaolei Zhang; Xiaoyan Zhang; Xin Zhang; Xinxin Zhang; Xu Dong Zhang; Yang Zhang; Yanjin Zhang; Yi Zhang; Ying-Dong Zhang; Yingmei Zhang; Yuan-Yuan Zhang; Yuchen Zhang; Zhe Zhang; Zhengguang Zhang; Zhibing Zhang; Zhihai Zhang; Zhiyong Zhang; Zili Zhang; Haobin Zhao; Lei Zhao; Shuang Zhao; Tongbiao Zhao; Xiao-Fan Zhao; Ying Zhao; Yongchao Zhao; Yongliang Zhao; Yuting Zhao; Guoping Zheng; Kai Zheng; Ling Zheng; Shizhong Zheng; Xi-Long Zheng; Yi Zheng; Zu-Guo Zheng; Boris Zhivotovsky; Qing Zhong; Ao Zhou; Ben Zhou; Cefan Zhou; Gang Zhou; Hao Zhou; Hong Zhou; Hongbo Zhou; Jie Zhou; Jing Zhou; Jing Zhou; Jiyong Zhou; Kailiang Zhou; Rongjia Zhou; Xu-Jie Zhou; Yanshuang Zhou; Yinghong Zhou; Yubin Zhou; Zheng-Yu Zhou; Zhou Zhou; Binglin Zhu; Changlian Zhu; Guo-Qing Zhu; Haining Zhu; Hongxin Zhu; Hua Zhu; Wei-Guo Zhu; Yanping Zhu; Yushan Zhu; Haixia Zhuang; Xiaohong Zhuang; Katarzyna Zientara-Rytter; Christine M Zimmermann; Elena Ziviani; Teresa Zoladek; Wei-Xing Zong; Dmitry B Zorov; Antonio Zorzano; Weiping Zou; Zhen Zou; Zhengzhi Zou; Steven Zuryn; Werner Zwerschke; Beate Brand-Saberi; X Charlie Dong; Chandra Shekar Kenchappa; Zuguo Li; Yong Lin; Shigeru Oshima; Yueguang Rong; Judith C Sluimer; Christina L Stallings; Chun-Kit Tong
Journal:  Autophagy       Date:  2021-02-08       Impact factor: 13.391

3.  The Michael J. Fox Foundation for Parkinson's Research Strategy to Advance Therapeutic Development of PINK1 and Parkin.

Authors:  Shalini Padmanabhan; Nicole K Polinski; Liliana B Menalled; Marco A S Baptista; Brian K Fiske
Journal:  Biomolecules       Date:  2019-07-24

Review 4.  Ubiquitin-specific protease 8 (USP8/UBPy): a prototypic multidomain deubiquitinating enzyme with pleiotropic functions.

Authors:  Almut Dufner; Klaus-Peter Knobeloch
Journal:  Biochem Soc Trans       Date:  2019-12-20       Impact factor: 5.407

5.  UbiBrowser 2.0: a comprehensive resource for proteome-wide known and predicted ubiquitin ligase/deubiquitinase-substrate interactions in eukaryotic species.

Authors:  Xun Wang; Yang Li; Mengqi He; Xiangren Kong; Peng Jiang; Xi Liu; Lihong Diao; Xinlei Zhang; Honglei Li; Xinping Ling; Simin Xia; Zhongyang Liu; Yuan Liu; Chun-Ping Cui; Yan Wang; Liujun Tang; Lingqiang Zhang; Fuchu He; Dong Li
Journal:  Nucleic Acids Res       Date:  2022-01-07       Impact factor: 16.971

Review 6.  Mitophagy and Neurodegeneration: Between the Knowns and the Unknowns.

Authors:  Cuckoo Teresa Jetto; Akshaya Nambiar; Ravi Manjithaya
Journal:  Front Cell Dev Biol       Date:  2022-03-22

7.  Loss of Fis1 impairs proteostasis during skeletal muscle aging in Drosophila.

Authors:  Tai-Ting Lee; Po-Lin Chen; Matthew P Su; Jian-Chiuan Li; Yi-Wen Chang; Rei-Wen Liu; Hsueh-Fen Juan; Jinn-Moon Yang; Shih-Peng Chan; Yu-Chen Tsai; Sophia von Stockum; Elena Ziviani; Azusa Kamikouchi; Horng-Dar Wang; Chun-Hong Chen
Journal:  Aging Cell       Date:  2021-06-01       Impact factor: 9.304

8.  A new target for an old DUB: UCH-L1 regulates mitofusin-2 levels, altering mitochondrial morphology, function and calcium uptake.

Authors:  Fernanda M Cerqueira; Sophia von Stockum; Marta Giacomello; Inna Goliand; Pamela Kakimoto; Elena Marchesan; Diego De Stefani; Alicia J Kowaltowski; Elena Ziviani; Orian S Shirihai
Journal:  Redox Biol       Date:  2020-08-07       Impact factor: 11.799

  8 in total

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