db and high-fat diet mice

db and high-fat diet mice

NSC 16124 No. of Pages 11 18 March 2015 Please cite this article in press as: Khang R et al. Dysregulation of parkin in the substantia nigra of db/d...

2MB Sizes 0 Downloads 1 Views

NSC 16124

No. of Pages 11

18 March 2015 Please cite this article in press as: Khang R et al. Dysregulation of parkin in the substantia nigra of db/db and high-fat diet mice. Neuroscience (2015), http://dx.doi.org/10.1016/j.neuroscience.2015.03.017 1

Neuroscience xxx (2015) xxx–xxx

3

DYSREGULATION OF PARKIN IN THE SUBSTANTIA NIGRA OF DB/DB AND HIGH-FAT DIET MICE

4

R. KHANG, a C. PARK b,c AND J.-H. SHIN a,c*

2

by metformin. Taken together, our data suggest that the dysregulation of Parkin–PARIS–PGC-1a pathway by metabolic malregulation may contribute to the pathogenesis of PD and metformin might exert a neuroprotective effect on PD via the restoration of parkin. Ó 2015 Published by Elsevier Ltd. on behalf of IBRO.

a

5 6 7 8

Division of Pharmacology, Department of Molecular Cell Biology, Samsung Biomedical Research Institute, Sungkyunkwan University School of Medicine, Suwon, Republic of Korea

9 10 11 12

b Division of Biochemistry and Molecular Biology, Department of Molecular Cell Biology, Samsung Biomedical Research Institute, Sungkyunkwan University School of Medicine, Suwon, Republic of Korea

13 14 15

c

Mass Spectrometry, Research Core Facility, Samsung Biomedical Research Institute, Sungkyunkwan University School of Medicine, Suwon, Republic of Korea

16

Abstract—Parkinson’s disease (PD) is characterized by selective loss of dopaminergic neurons in the substantia nigra (SN). Epidemiological evidence has suggested a link between type 2 diabetes and PD, although the mechanisms remain largely unknown. We applied LC–MS/MS-based pattern analysis to investigate altered proteomes in the SN of db/db mice (db-SN) and high-fat diet mice (HFD-SN), revealing that the level of mitochondrial proteins has changed in the SN of diabetic mice compared to that of control mice. Since mitochondrial proteins were robustly altered in db-SN and HFD-SN, we performed immunoblot analysis to monitor the level of parkin, PINK1 (phosphatase and tensin homolog-induced putative kinase 1) and DJ-1 that were directly involved in mitochondrial dynamics. As a result, PINK1 and DJ-1 level was unchanged, whereas a significant loss of parkin was found in db-SN and HFD-SN, leading to the accumulation of parkin-interacting substrate (PARIS) and the reduction of peroxisome proliferator-activated receptor gamma coactivator 1-alpha (PGC-1a). Interestingly, these alterations were reversed by the administration of metformin, one of most frequently prescribed antihyperglycemic agents. The slight loss of dopaminergic neurons was found in chronic HFD-SN that was restored

Key words: Parkinson’s disease, parkin, PARIS, type 2 diabetes, metformin. 17

*Correspondence to: J.-H. Shin, Division of Pharmacology, Department of Molecular Cell Biology, Samsung Biomedical Research Institute, Sungkyunkwan University School of Medicine, Suwon, Gyeonggi-do 440-746, Republic of Korea. Tel: +82-031-2996192; fax: +82-031-299-6209. E-mail address: [email protected] (J.-H. Shin). Abbreviations: AIMP2, aminoacyl-tRNA synthetase complexinteracting multifunctional protein 2; CTX, cerebral cortex; Chow-SN, SN of chow-diet mice; DA, dopaminergic neurons; FBP1, far-upstream element (FUSE) binding protein 1; GO, gene ontology; HFD, high-fat diet; HRP, horseradish peroxidase; IR-SH, insulin-resistant SH-SY5Y cells; PARIS, parkin interacting substrate; PBS, phosphate-buffered saline; PD, Parkinson’s disease; PGC-1a, peroxisome proliferatoractivated receptor gamma coactivator 1-alpha; PINK1, phosphatase and tensin homolog-induced putative kinase 1; SN, substantia nigra; STR, striatum; STRAP, software tool for researching annotations of proteins; T2D, type 2 diabetes; TH, tyrosine hydroxylase; WT-SN, SN of wild-type littermate mice. http://dx.doi.org/10.1016/j.neuroscience.2015.03.017 0306-4522/Ó 2015 Published by Elsevier Ltd. on behalf of IBRO. 1

INTRODUCTION

18

Parkinson’s disease (PD) is the most common movement disorder and is characterized by selective and massive loss of dopaminergic neurons (DA) in the substantia nigra pars compacta (SNpc) (Savitt et al., 2006). PD is characterized by a series of classic motor symptoms, including resting tremor, rigidity of the skeletal muscles of the face and hands, bradykinesia, and postural instability (Savitt et al., 2006). Several PD-associated genes, including parkin, a-synuclein, leucine-rich repeat kinase 2 (LRRK2), DJ-1, PINK1, and ATP13A2 have been identified, and an investigation of their biology has shed light on the pathogenesis of PD. Mutation of parkin, an E3 ubiquitin ligase, results in autosomal recessive juvenile Parkinsonism (Kitada et al., 1998). In sporadic PD, posttranslational modification of parkin by nitrosative, oxidative, dopaminergic stress, and c-Abl lead to loss of the catalytic activity of parkin, resulting in the accumulation of toxic substrates and neuronal death (Dawson and Dawson, 2014). Type 2 diabetes (T2D), the most common type of diabetes, is characterized by peripheral insulin resistance and impaired insulin secretion from pancreatic b-cell insulin in response to hyperglycemia (Lu and Hu, 2012). An increasing number of epidemiological studies have focused on the relationship between diabetes and the risk of PD (Lu and Hu, 2012; Santiago and Potashkin, 2013). A recent prospective study following 51,552 Finnish men and women with no history of PD at the baseline showed that T2D is associated with an increased risk of PD (Hu et al., 2007). This observation was strongly supported by the results of another study of 1565 PD patients showing that the risk of PD is 40% higher in diabetic PD patients than in non-diabetic patients (Xu et al., 2011), suggesting that there may be a common physiological pathway between PD and T2D (Schernhammer et al., 2011).

19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54

NSC 16124

No. of Pages 11

18 March 2015

2 55 56 57 58 59 60 61 62 63 64 65

66

R. Khang et al. / Neuroscience xxx (2015) xxx–xxx

In this study, we utilized a proteomic approach to investigate changes of proteome in the SN of two T2D animal models, db/db (db-SN) and high-fat diet mice (HFD-SN). T2D models exhibited a loss of parkin, accumulation of parkin-interacting substrate (PARIS), and suppression of peroxisome proliferator-activated receptor gamma coactivator 1-alpha (PGC-1a) in the SN. Furthermore, the anti-diabetic drug metformin restored levels of parkin and PGC-1a, suggesting that metabolic dysfunction might play a deleterious role in the pathogenesis of PD.

EXPERIMENTAL PROCEDURES

67

Animal experiments

68

85

All animal experiments were approved by the Sungkyunkwan University Ethics Committee, according to international guidelines. All efforts were made to minimize animal suffering and to reduce the number of animals used. All mice were maintained under a 12-h dark/12-h light cycle in air-controlled rooms and fed diet and water ad libitum. Experiments were performed with 3-month-old control (Lepr+/Lepr+ (WT)) and db/db (Leprdb/Leprdb mice, protocol 000697; Jackson Laboratories, Bar Harbor, ME, USA) mice exhibiting severe obesity (n = 10) (Chen et al., 1996). Male C57BL/6J mice (Orient, Sungnam, Republic of Korea) were fed a chow-diet or high-fat diet (60% fat; Research diet, New Brunswick, NJ, USA) for 8 or 20 weeks (n = 10 per group) (Van Heek et al., 1997). Diabetic db/ db and HFD mice were administrated clinical doses of metformin (400 mg/kg once daily for 2 weeks or indicated period) (n = 3) (Martin-Montalvo et al., 2013).

86

Sample preparation

87

Animals were perfused transcardially with phosphatebuffered saline (PBS) (pH 7.4) under pentobarbital anesthesia (50 mg/kg, intraperitoneal injection). Whole brains were removed and dissected to obtain SN, striatum (STR), and cerebral cortex (CTX). Brain tissues were homogenized in radioimmunoprecipitation assay (RIPA) buffer (Thermo Fisher Scientific, Inc., Waltham, MA, USA) with 100 protease/phosphatase inhibitor cocktail (Sigma–Aldrich, St. Louis, MO, USA) followed by three cycles of freezing/thawing. The concentration of the supernatant was determined by BCA assay.

69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84

88 89 90 91 92 93 94 95 96 97

98 99 100 101 102 103 104 105 106 107 108

LC–MS/MS, quantitative protein profiling, statistics and database searching The lysate of db-SN or HFD-SN was loaded on 1DESDS–PAGE and total protein was visualized by colloidal Coomassie Blue (Novex, San Diego, CA, USA). Each lane was cut into 10 gel pieces and subsequently destained, reduced, alkylated and digested with modified sequencing grade trypsin (Sigma–Aldrich, St. Louis, MO, USA) as described (Shevchenko et al., 2006). We performed LC–MS/MS as described (Khang et al., 2014). Briefly, peptide mixtures were lyophilized,

resuspended in 0.1% TFA, and injected in a Zorbox 300SB-C18 75-lm i.d.  15-cm column (Agilent Technologies, Waldbronn, Germany). Peptides were separated by an UltiMate 3000 nano HPLC system (Dionex, Sunnyvale, CA, USA) and applied on-line to an LTQ (Thermo Finnigan, Waltham, MA, USA) ion-trap mass spectrometer. Spectra were collected in full-scan mode (350–1600 Da) followed by MS/MS scans of the five most intense ion peaks obtained from the full scan using dynamic exclusion criteria. LC/MS runs were analyzed using DeCyder MS software (version 2.0; GE Healthcare, Uppsala, Sweden). The relative abundance of each peptide in the respective gradient fraction was determined by peak integration. The threshold for differentially expressed proteins was defined as an at least 2-fold increase or decrease. MS/MS spectra were searched using MASCOTTM v2.3 (Matrix Science, London, UK). Proteins identified by multiple peptides with a significant MASCOT score (p < 0.05) were used for quantitative protein profiling.

109

In silico analysis of functional associations

129

Software tool for researching annotations of proteins (STRAP, http://www.bumc.bu.edu/cardiovascularproteomics/cpctools/; Boston University School of Medicine, Boston, USA) (Bhatia et al., 2009) was utilized to classify proteins into biological process, cellular component, and molecular function based on gene ontology (GO). A functional association network of proteins identified was generated using STRING 8.3 web server (http:// string-db.org/) (Jensen et al., 2009).

130

Western blot

139

Protein samples (40 lg) were separated on SDS–PAGE (7.5–15%) (Mini Protean II, Bio Rad, Hercules, CA, USA) using the Laemmli sample buffer system (Santa Cruz Biotechnology, Inc., Santa Cruz, CA, USA) and proteins were transferred to nitrocellulose membranes (Hybond ECL, Amersham, Amersham, UK). Membranes were blocked with 5% (w/v) non-fat dried milk in TBS-T for 3 h at room temperature and probed with primary antibodies overnight at 4 °C followed by the appropriate HRP (horseradish peroxidase)-conjugated secondary antibody for 1 h (Santa Cruz Biotechnology, Inc., Santa Cruz, CA, USA). The primary antibodies used in this study were as follows: a-p-AKT (Ser473; Cell Signaling Technology, Danvers, MA, USA), a-AKT (Cell Signaling Technology, Danvers, MA, USA), a-Parkin (Cell signaling Technology, Danvers, MA, USA), a-PINK1 (Novus Biologicals, Littleton, CO, USA), a-DJ-1 (Santa Cruz biotechnology, Inc., Santa Cruz, CA, USA), aFBP1 (BD Transduction Laboratories, San Jose, CA, USA), a-AIMP2 (Proteintech group, Inc., Chicago, IL, USA), a-PARIS (Merck Millipore, Billerica, MA, USA), aPGC-1a (Calbiochem, Merck Millipore, Billerica, MA, USA), and a-actin-HRP (Abcam, Cambridge, UK). Bands were visualized with ECL-system reagents (Amersham, Amersham, UK). Band densities were quantified using NIH Image J and normalized to b-actin.

140

Please cite this article in press as: Khang R et al. Dysregulation of parkin in the substantia nigra of db/db and high-fat diet mice. Neuroscience (2015), http://dx.doi.org/10.1016/j.neuroscience.2015.03.017

110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128

131 132 133 134 135 136 137 138

141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165

NSC 16124

No. of Pages 11

18 March 2015

R. Khang et al. / Neuroscience xxx (2015) xxx–xxx 166

Real-time quantitative RT-PCR (qRT-PCR)

167

182

Total RNA was extracted from mouse brain (SN) with the MiniBEST RNA extraction kit (Takara Bio INC., Otsu, Shiga, Japan). To eliminate DNA, dissolved RNA was treated with DNase I (RNase free, Stratagene, Agilent Technologies, Waldbronn, Germany) for 15 min at 37 °C and purified by RNeasy kit (Qiagen, Hilden, Germany). cDNA was synthesized from total RNA (1.5 lg) using a First-strand cDNA synthesis kit (Invitrogen, Life Technologies, Carlsbad, CA, USA). Real-time qRT-PCR was performed using a RotorgeneQ (Qiagen) and Rotorgene SYBR green PCR kit (Qiagen). The primers used for RT-PCR were as follows: parkin, 50 -CCT GCT GTT CTC TCG CGC-30 (forward) and 50 -GGT CAG AGA CCC GGA CCC-30 (reverse); actin, 50 -TGT TAC CAA CTG GGA CGA CA-30 (forward) and 50 -GGG GTG TTG AAG GTC TCA AA-30 (reverse).

183

Tyrosine hydroxylase (TH) staining

184

198

T2D mice were anesthetized with pentobarbital (60 mg/ kg) and perfused with PBS followed by 4% paraformaldehyde. Brains were post-fixed with 4% paraformaldehyde, cryoprotected in 30% sucrose, and sliced to obtain 40-lm coronal sections. For tyrosine hydroxylase (TH), sections were reacted with a 1:1000 dilution of rabbit polyclonal anti-TH (Novus) and visualized with biotinylated goat anti-rabbit IgG, followed by streptavidin-conjugated HRP (Vectastain ABC kit, Vector Laboratories, Burlingame, CA). TH-positive immunostaining was visualized with 3,30 -diaminobenzidine (DAB, Sigma) after reaction with hydrogen peroxide. The intensity of TH-stained neurons in substantia nigra pars compacta was measured using Image J software.

199

RESULTS

200

Proteomic profiling of SN of T2D model by label-free pattern analysis

168 169 170 171 172 173 174 175 176 177 178 179 180 181

185 186 187 188 189 190 191 192 193 194 195 196 197

201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222

Total proteins of db-SN and HFD-SN were separated in 1DE gels (Fig. 1A, B). With label-free LC–MS/MS-based pattern analysis, 1155 proteins from db-SN and 1145 proteins from HFD-SN were identified. For reliable comparison between groups, proteins identified by only one peptide or by both up-regulated and down-regulated peptides in the same experiment were excluded. STRAP analysis was utilized to understand the physiological relevance of proteomic alteration (Fig. 1C). Graphical representations of gene ontology (GO)associated categories were displayed in terms of cellular components and molecular function (Fig. 1C). In db-SN, 69 proteins were upregulated and 36 proteins were downregulated as compared to the SN of wild-type littermate mice (WT-SN). We found that 20.5% of upregulated proteins in the db-SN were localized in the mitochondria, 13% in the cytoplasm, and 8% in the nucleus. In addition, 19 proteins were upregulated and 29 proteins were downregulated in HFD-SN mice as compared to the SN of chow-diet mice (Chow-SN), of which 6.3% of upregulated proteins were assigned to

3

mitochondria and 9.5% were assigned to the nucleus. Interestingly, four proteins alone, namely, NADdependent protein deacetylase sirtuin-2 (SIRT2), neuronal membrane glycoprotein M6-a (GPM6A), serine/threonine-protein phosphatase PP1-alpha catalytic subunit (PPP1CA), and transitional endoplasmic reticulum ATPase (VCP) were upregulated in both db-SN and HFD-SN, whereas enolase (ENO2) and pyruvate kinase isozymes M1/M2 (PKM2) were downregulated in both models (Table 1). Overall, there appeared to be an absence of common alterations between the db-SN and HFD-SN, even though both db/ db and HFD mice are models of T2D. Notably, 19 of 69 (27.5%) upregulated proteins and nine of 36 (25%) downregulated proteins in db-SN were assigned to a mitochondrial-related component, suggesting that metabolic stress contributes to mitochondrial alteration in the SN (Table 1). Using STRING software, all but three mitochondrial proteins methylglutaconyl-CoA hydratase (Auh), longchain-fatty-acid-CoA ligase 6 (Acs16), and uncharacterized protein (Gm10108) had strong edge representation, with functional associations, including fusion (red), neighborhood (green), cooccurrence (blue), experimental (purple), text mining (yellow), database (light blue), and coexpression (black line) (Fig. 1D). Although two PD proteins, DJ-1 and a-synuclein, were identified in both the db-SN and HFD-SN, their levels were unchanged as compared to WT-SN and Chow-SN.

223

Robust reduction of parkin in db-SN and HFD-SN

252

Since mitochondrial proteins were dysregulated in db-SN and HFD-SN, we next decided to monitor levels of mitochondria-related PD proteins, parkin, PINK1 (phosphatase and tensin homolog-induced putative kinase 1), and DJ-1 in the SN of T2D animals. Interestingly, the level of parkin was robustly decreased, whereas PINK1 and DJ-1 levels were unchanged in the db-SN. Furthermore, the ratio of p-AKT to total AKT, a marker of metabolic dysregulation was significantly decreased in the db-SN (Fig. 2A, B). A similar observation was made for the HFD-SN as compared to Chow-SN (Fig. 2D, E) with a 57% reduction of parkin in the HFD-SN. However, this was not as great as the complete loss of parkin observed for the db-SN. To monitor whether the reduction of parkin attributes to the expression of parkin mRNA, we performed real-time qRT-PCR to see if the relative level of mRNA for parkin is altered in both db-SN and HFD-SN as compared to WT-SN and chow-SN, respectively. There is a trend toward increased mRNA of parkin in db-SN and no alteration of parkin was found in HFD-SN (revised Fig. 2C, F). These results indicate that there might be a positive feedback to induce the transcription of parkin in db-SN but not in HFD-SN. In order to determine whether the reduction of parkin in the db-SN was region-specific, we evaluated parkin expression in the STR and CTX. We found that parkin expression was significantly decreased in the STR and CTX of db/db mice (Fig. 2G, H). In addition, we investigated if the decrease of parkin in soluble lysate was due to a shift of

253

Please cite this article in press as: Khang R et al. Dysregulation of parkin in the substantia nigra of db/db and high-fat diet mice. Neuroscience (2015), http://dx.doi.org/10.1016/j.neuroscience.2015.03.017

224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251

254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282

NSC 16124

No. of Pages 11

18 March 2015

4 283 284 285 286 287 288 289

R. Khang et al. / Neuroscience xxx (2015) xxx–xxx

parkin localization, finding that parkin was absent in both the soluble and insoluble fractions (Fig. 2G). Interestingly, the expression of parkin in the STR and CTX of HFD mice was unchanged and there was no alteration of parkin in the insoluble fraction, suggesting the possibility of regional specificity for parkin loss in the HFD model (Fig. 2I, J).

290

Alteration of parkin substrates in T2D brain

291

Several substrates of parkin have been identified to date (Dawson and Dawson, 2010), including aminoacyl-tRNA synthetase complex-interacting multifunctional protein 2 (AIMP2), far upstream binding protein 1 (FBP1), and PARIS, all of which are considered pathogenic substrates that accumulate in patients with sporadic PD (Dawson and Dawson, 2010). We recently reported that PARIS functions as a transcriptional repressor of PGC-1a, a master regulator of mitochondrial biogenesis and respiration (Shin et al., 2011). Based on the lack of parkin in the db-SN and HFD-SN, we determined if levels of AIMP2, FBP1, and PARIS accumulate in the db-SN and HFD-SN. We found that these substrates were

292 293 294 295 296 297 298 299 300 301 302 303

significantly increased in the SN but not in the STR and CTX (Fig. 3A–D). In addition, the upregulation of PARIS in db-SN and HFD-SN was accompanied by downregulation of PGC-1a. Interestingly, we failed to detect the accumulation of PARIS, FBP1, and AIMP2 in the STR and CTX of db/db mice despite the parkin deficiency, suggesting that there may be a region-specific mechanism underlying the ubiquitination of parkin substrates for degradation. No changes in levels of AIMP2, FBP1, PARIS, and PGC-1a were observed in the STR and CTX of HFD mice (Fig. 3C, D). Since diabetic db/db and dietary HFD mice both share a severe insulin resistance phenotype, we generated insulin-resistant SH-SY5Y cells (IR-SH) by chronic treatment of SH-SY5Y cells with insulin (low, 10 nm/L; high, 1 lM/L) for 48 h. We found that attenuation of insulin-stimulated phospho-AKT activation in IR-SH cells with high insulin (Fig. 3E, F) was accompanied by decreased parkin, increased PARIS, and downregulated PGC-1a. Together, these results indicated that insulin resistance (IR) might be a physiological mechanism for parkin loss in the SN of T2D models, although further studies will be required to determine the mechanisms by

Fig. 1. Altered mitochondrial proteome in the SN of db/db and HFD mice. Colloidal blue-stained 1DE gel containing the SN proteome of db/db mice (A) and HFD mice (B). (C) Venn diagram of dysregulated proteins in db/db vs. WT mice (top left, upregulated protein; bottom left, downregulated proteins) and HFD vs. chow-diet mice (top right, upregulated protein; bottom right, downregulated proteins). Proteins were classified by the cellular component. (D) Protein–protein interaction network generated by STRING software. Up- and down-regulated proteins in the db-SN are shown, and the edges were drawn with different colored lines to depict different types of evidence. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.) Please cite this article in press as: Khang R et al. Dysregulation of parkin in the substantia nigra of db/db and high-fat diet mice. Neuroscience (2015), http://dx.doi.org/10.1016/j.neuroscience.2015.03.017

304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326

NSC 16124

No. of Pages 11

18 March 2015

5

R. Khang et al. / Neuroscience xxx (2015) xxx–xxx Table 1. List of proteins that were significantly altered in db-SN or HFD-SN Acc. #

Protein name

Intensity WT

db/db

Molecular Chaperones A2A5N1 14-3-3 protein beta/alpha P62259 14-3-3 protein epsilon P68510 14-3-3 protein eta P61982 14-3-3 protein gamma F6VW30 14-3-3 protein theta P63101 14-3-3 protein zeta/delta P20029 78 kDa glucose-regulated protein D3YW43 Heat shock cognate 71 kDa protein A2AL12 Heterogeneous nuclear ribonucleoprotein A3 B2M1R6 Heterogeneous nuclear ribonucleoprotein K O88569 Heterogeneous nuclear ribonucleoproteins A2/B1 A2A813 Protein DJ-1 Q60864 Stress-induced-phosphoprotein 1 P11983 T-complex protein 1 subunit alpha P42932 T-complex protein 1 subunit theta P17751 Triosephosphate isomerase

15.40 14.03 16.89 15.64 17.47 17.55 18.20 21.82 12.96 18.75 15.78 18.16 18.07 16.51 18.50 ND

11.42 16.46 15.55 14.06 16.26 15.35 15.96 20.61 16.55 16.97 17.15 18.34 16.55 14.17 16.97 ND

Cytoskeletal proteins P28663 Beta-soluble NSF attachment protein Q5SXR6 Clathrin heavy chain 1 B1AWD8 Clathrin light chain A Q9CQI6 Coactosin-like protein P97427 Dihydropyrimidinase-related protein 1 D3YUS0 Dihydropyrimidinase-related protein 3 P39053 Dynamin-1 P03995 Glial fibrillary acidic protein P14733 Lamin-B1 A2ARP8 Microtubule-associated protein 1A A2A5Y6 Microtubule-associated protein tau F6RT34 Myelin basic protein P35802 Neuronal membrane glycoprotein M6-a P60879 Synaptosomal-associated protein 25 P46096 Synaptotagmin-1 P61264 Syntaxin-1B P05213 Tubulin alpha-1B chain Q7TMM9 Tubulin beta-2A chain P68372 Tubulin beta-4B chain

11.09 17.27 12.60 14.69 19.00 18.03 ND ND 13.83 ND ND 23.37 14.17 18.03 18.84 15.83 17.28 12.50 16.87

Metabolic enzymes B0QZL1 Enolase 1 Q04447 Creatine kinase B-type D3Z6E4 Enolase 2 P05063 Fructose-bisphosphate aldolase C P48318 Glutamate decarboxylase 1 D3YU05 Glyceraldehyde-3-phosphate dehydrogenase Q8CI94 Glycogen phosphorylase, brain form Q9CPU0 Lactoylglutathione lyase P24527 Leukotriene A-4 hydrolase D3Z7F0 L-lactate dehydrogenase P16125 L-lactate dehydrogenase B chain P14152 Malate dehydrogenase, cytoplasmic E9PZF0 Nucleoside diphosphate kinase Q8K183 Pyridoxal kinase P60487 Pyridoxal phosphate phosphatase P52480 Pyruvate kinase isozymes M1/M2 Q3UJQ9 Succinyl-CoA:3-ketoacid-coenzyme A transferase Q01853 Transitional endoplasmic reticulum ATPase P62814 V-type proton ATPase subunit B, brain isoform Q9Z1G3 V-type proton ATPase subunit C 1 P50518 V-type proton ATPase subunit E 1

17.53 19.13 20.22 ND 18.85 15.63 ND 17.85 18.93 14.29 13.64 17.33 ND 10.34 12.32 18.52 ND 14.89 ND ND 15.46

Av. Diff. (2log)

Intensity

Av. Diff. (2log)

Chow

HFD

3.98 2.43 1.34 1.58 1.21 2.20 2.24 1.21 3.59 1.78 1.37 0.18 1.52 2.33 1.53 ND

ND 19.98 ND ND ND ND ND ND ND ND ND ND ND ND ND 19.40

ND 17.95 ND ND ND ND ND ND ND ND ND ND ND ND ND 20.72

ND 2.03 ND ND ND ND ND ND ND ND ND ND ND ND ND 1.32

15.35 18.68 16.48 16.25 16.48 16.57 ND ND 14.87 ND ND 24.59 17.14 16.62 16.92 18.53 18.64 16.39 17.92

4.26 1.41 3.88 1.56 2.52 1.46 ND ND 1.03 ND ND 1.22 2.97 1.41 1.93 2.70 1.36 3.89 1.05

ND ND ND ND ND ND 19.10 18.17 ND 13.24 16.74 ND 17.54 ND ND ND ND ND ND

ND ND ND ND ND ND 20.56 17.12 ND 11.69 13.94 ND 18.86 ND ND ND ND ND ND

ND ND ND ND ND ND 1.46 1.05 ND 1.55 2.80 ND 1.32 ND ND ND ND ND ND

18.79 17.61 19.21 ND 16.60 19.59 ND 18.94 16.67 16.85 17.85 18.88 ND 14.84 15.31 16.88 ND 16.02 ND ND 16.67

1.27 1.52 1.01 ND 2.26 3.96 ND 1.09 2.26 2.57 4.21 1.55 ND 4.50 2.99 1.64 ND 1.14 ND ND 1.22

20.12 ND 19.14 19.66 ND ND 18.41 ND ND ND ND ND 16.58 19.21 ND 20.60 17.45 16.66 17.54 18.81 ND

17.25 ND 18.10 18.60 ND ND 19.90 ND ND ND ND ND 17.87 18.00 ND 19.08 16.01 18.05 15.66 17.69 ND

2.87 ND 1.04 1.06 ND ND 1.49 ND ND ND ND ND 1.29 1.20 ND 1.52 1.44 1.39 1.88 1.13 ND

(continued on next page)

Please cite this article in press as: Khang R et al. Dysregulation of parkin in the substantia nigra of db/db and high-fat diet mice. Neuroscience (2015), http://dx.doi.org/10.1016/j.neuroscience.2015.03.017

NSC 16124

No. of Pages 11

18 March 2015

6

R. Khang et al. / Neuroscience xxx (2015) xxx–xxx

Table 1 (continued) Acc. #

Protein name

Mitochondrial proteins Q99L13 3-hydroxyisobutyrate dehydrogenase, mitochondrial P63038 60 kDa heat shock protein, mitochondrial Q8QZT1 Acetyl-CoA acetyltransferase, mitochondrial Q9CR21 Acyl carrier protein, mitochondria P56480 ATP synthase subunit beta, mitochondrial Q06185 ATP synthase subunit e, mitochondrial A2AKU9 ATP synthase subunit gamma Q9CZ13 Cytochrome b-c1 complex subunit 1, mitochondrial Q9DB77 Cytochrome b-c1 complex subunit 2, mitochondrial P12787 Cytochrome c oxidase subunit 5A, mitochondrial Q9CPQ1 Cytochrome c oxidase subunit 6C Q9D0M3 Cytochrome c1, heme protein, mitochondrial O08749 Dihydrolipoyl dehydrogenase, mitochondrial Q8BMF4 Dihydrolipoyllysine-residue acetyltransferase component of pyruvate dehydrogenase complex, mitochondrial Q99LC5 Electron transfer flavoprotein subunit alpha, mitochondrial P26443 Glutamate dehydrogenase 1, mitochondrial A2AQR0 Glycerol-3-phosphate dehydrogenase, mitochondrial Q9CPV4 Glyoxalase domain-containing protein 4 Q9D6R2 Isocitrate dehydrogenase [NAD] subunit alpha, mitochondrial Q91WC3 Long-chain-fatty-acid–CoA ligase 6 P08249 Malate dehydrogenase, mitochondrial Q9JLZ3 Methylglutaconyl-CoA hydratase, mitochondrial Q5SX46 Mitochondrial 2-oxoglutarate/malate carrier protein Q9CZW5 Mitochondrial import receptor subunit TOM70 Q9ERS2 NADH dehydrogenase [ubiquinone] 1 alpha subcomplex subunit 13 Q9DC69 NADH dehydrogenase [ubiquinone] 1 alpha subcomplex subunit 9, mitochondrial Q91VD9 NADH-ubiquinone oxidoreductase 75 kDa subunit, mitochondrial Q9D051 Pyruvate dehydrogenase E1 component subunit beta, mitochondrial Q9WUM5 Succinyl-CoA ligase [ADP/GDP-forming] subunit alpha, mitochondrial Q60932 Voltage-dependent anion-selective channel protein 1 Q60930 Voltage-dependent anion-selective channel protein 2 Q60931 Voltage-dependent anion-selective channel protein 3 G3UWG1 Uncharacterized protein MCG115977 Signaling transduction P48036 Annexin A5 F8WHB5 Calcium/calmodulin-dependent protein kinase type II subunit alpha P62204 Calmodulin D3Z3G6 Mitogen-activated protein kinase 3 Q9Z0E0 Neurochondrin P60761 Neurogranin A2A7R5 Neuron-specific calcium-binding protein hippocalcin P62715 Serine/threonine-protein phosphatase 2A catalytic subunit beta isoform P63328 Serine/threonine-protein phosphatase 2B catalytic subunit alpha isoform P62137 Serine/threonine-protein phosphatase PP1-alpha catalytic subunit D3YVX6 Sodium/potassium-transporting ATPase subunit alpha-2 Q6PIC6 Sodium/potassium-transporting ATPase subunit alpha-3 Transcription & Translation D3YUG3 40S ribosomal protein S19 Q91XV3 Brain acid-soluble protein 1 P58252 Elongation factor 2 H3BKR2 Guanine nucleotide-binding protein G(I)/G(S)/G(T) subunit beta-1 (Fragment) D3YZX3 Guanine nucleotide-binding protein G(I)/G(S)/G(T) subunit beta-2 D3Z2M7 Guanine nucleotide-binding protein G(o) subunit alpha (Fragment)

Intensity WT

db/db

13.50 12.02 18.11 16.90 13.40 19.47 16.86 ND ND ND 19.61 15.96 ND 20.67

15.82 14.08 19.26 15.76 16.55 18.18 18.25 ND ND ND 17.78 18.79 ND 19.11

16.56 16.37 18.43 14.20 15.10 18.29 ND 14.65 14.28 19.22 ND 16.06

Av. Diff. (2log)

Intensity

Av. Diff. (2log)

Chow

HFD

2.32 2.06 1.15 1.14 3.15 1.29 1.39 ND ND ND 1.84 2.83 ND 1.55

ND 18.94 ND ND ND ND 20.16 18.46 18.95 16.06 ND ND 18.95 ND

ND 17.48 ND ND ND ND 19.14 16.84 17.53 17.09 ND ND 17.05 ND

ND 1.46 ND ND ND ND 1.02 1.62 1.43 1.03 ND ND 1.90 ND

17.91 17.55 17.21 15.42 17.11 16.16 ND 17.06 17.90 16.99 ND 17.59

1.35 1.18 1.23 1.22 2.01 2.12 ND 2.41 3.63 2.22 ND 1.54

ND ND ND ND 20.03 ND 21.34 ND ND ND 16.30 ND

ND ND ND ND 18.98 ND 19.48 ND ND ND 17.68 ND

ND ND ND ND 1.05 ND 1.86 ND ND ND 1.37 ND

18.06 13.25 16.19

16.19 15.98 17.82

1.87 2.74 1.63

ND ND ND

ND ND ND

ND ND ND

14.76 13.56 13.52 17.17

16.77 17.31 18.47 16.12

2.02 3.75 4.94 1.05

ND ND ND ND

ND ND ND ND

ND ND ND ND

12.79 ND ND ND 19.52 ND 12.85 15.50

16.58 ND ND ND 18.14 ND 14.83 17.35

3.79 ND ND ND 1.39 ND 1.98 1.85

ND 16.99 16.83 18.92 ND 18.58 ND ND

ND 12.91 15.50 17.88 ND 16.91 ND ND

ND 4.08 1.33 1.04 ND 1.67 ND ND

ND

ND

ND

20.18

17.93

2.25

10.44 16.22 17.54

14.81 18.69 20.06

4.37 2.47 2.53

15.31 ND ND

18.59 ND ND

3.27 ND ND

17.28 16.04 ND 16.24

15.52 17.92 ND 17.40

1.75 1.88 ND 1.16

ND ND 16.46 ND

ND ND 17.83 ND

ND ND 1.38 ND

14.88 13.79

16.52 15.42

1.64 1.63

ND ND

ND ND

ND ND

Please cite this article in press as: Khang R et al. Dysregulation of parkin in the substantia nigra of db/db and high-fat diet mice. Neuroscience (2015), http://dx.doi.org/10.1016/j.neuroscience.2015.03.017

NSC 16124

No. of Pages 11

18 March 2015

7

R. Khang et al. / Neuroscience xxx (2015) xxx–xxx Table 1 (continued) Acc. #

G3X9D5 P62806 Q8VDQ8 O35129 Miscellaneous P16330 D3Z0Y2 P08228 H3BIY9 G3UWN5 Q29ZQ5 E9Q1Z0 E9Q1Y9 O55125 E9Q6Q4 E9Q1G8 D3YWF6 P61089 J3QNR5

Protein name

Intensity WT

db/db

Histone H2B type 2-B Histone H4 NAD-dependent protein deacetylase sirtuin-2 Prohibitin-2

20.41 16.23 14.55 15.09

19.22 12.70 18.02 16.26

20 ,30 -cyclic-nucleotide 30 -phosphodiesterase Peroxiredoxin-6 Superoxide dismutase [Cu-Zn] AP-2 complex subunit beta Apolipoprotein E MOG-alpha-2 Protein 4732456N10Rik Protein 5430421N21Rik Protein NipSnap homolog 1 Protein Rap1gds1 Septin-7 Ubiquitin thioesterase OTUB1 Ubiquitin-conjugating enzyme E2N Uncharacterized protein

18.11 16.85 ND ND 14.39 17.14 ND 16.89 ND ND ND 12.98 ND 13.55

15.92 18.78 ND ND 15.85 18.45 ND 12.78 ND ND ND 15.58 ND 16.86

Av. Diff. (2log)

Intensity

Av. Diff. (2log)

Chow

HFD

1.18 3.53 3.48 1.18

ND ND 17.65 ND

ND ND 18.71 ND

ND ND 1.06 ND

2.19 1.93 ND ND 1.46 1.31 ND 4.11 ND ND ND 2.60 ND 3.31

ND ND 18.65 17.58 ND ND 18.89 18.49 17.92 18.30 19.22 ND 16.81 18.93

ND ND 19.67 19.07 ND ND 19.98 15.73 19.03 17.07 18.21 ND 18.28 17.88

ND ND 1.02 1.50 ND ND 1.08 2.77 1.11 1.22 1.01 ND 1.48 1.05

Acc. #, Accession number; Av. Diff. (2Log), average difference, positive or negative value indicates downregulation or upregulation, respectively; ND, no significant difference.

Fig. 2. Parkin is deficient in the SN of diabetic mice. (A) Immunoblot analysis showing the level of phospho-AKT, total AKT, and PD-associated genes PINK1, parkin, and DJ-1 in db-SN (n = 3). (B) Quantitation of the immunoblots in panel B normalized to b-actin, n = 3. Data = mean ± SEM, ⁄p < 0.05, ⁄⁄p < 0.01, Student’s t-test. (C) Real-time qRT-PCR of parkin in db-SN compared to age-matched WT-SN, n = 3. (D) Immunoblot analysis showing the level of phospho-AKT, total AKT, and PD-associated genes in HFD-SN (n = 3). (E) Quantitation of the immunoblots in panel C normalized to b-actin, n = 3. (F) Real-time qRT-PCR of parkin in HFD-SN compared to Chow-SN, n = 3. Data = mean ± SEM, ⁄p < 0.05, Student’s t-test. Levels of parkin in the SN, STR, and CTX of db/db mice (G) and HFD mice (I). Quantitation of immunoblots normalized to b-actin (H and J), n = 3. Data = mean ± SEM, ⁄p < 0.05, ⁄⁄p < 0.01, ⁄⁄⁄p < 0.001, Student’s t-test.

327 328 329 330

which IR dysregulates parkin expression. Furthermore, we investigate whether IR induces the toxicity of SHSY5Y cells, showing that there was no obvious cell toxicity due to IR. Thus, IR-SH cells were treated with

MPP+ to demonstrate if IR-SH cells are more vulnerable to neuronal toxin or stress. We observed mild toxicity in SH-SY5Y (No IR-SH) cells treated with MPP+ (500 lM for 12 h), whereas significant toxicity

Please cite this article in press as: Khang R et al. Dysregulation of parkin in the substantia nigra of db/db and high-fat diet mice. Neuroscience (2015), http://dx.doi.org/10.1016/j.neuroscience.2015.03.017

331 332 333 334

NSC 16124

No. of Pages 11

18 March 2015

8

R. Khang et al. / Neuroscience xxx (2015) xxx–xxx

Fig. 3. Alteration of the parkin substrates PARIS, FBP1, and AIMP2 in T2D models. (A) Immunoblot analysis showing the level of PARIS, FBP1, AIMP2, and PGC-1a in the SN, STR, and CTX of db/db mice (n = 3). (B) Quantitation of the immunoblots in panel A normalized to b-actin, n = 3. Data = mean ± SEM, ⁄p < 0.05, ⁄⁄p < 0.01, Student’s t-test. (C) Levels of parkin substrates and PGC-1a in the SN, STR, and CTX of HFD mice measured by immunoblot analysis (n = 3). (D) Quantitation of the immunoblots in panel C normalized to b-actin, n = 3. Data = mean ± SEM, ⁄⁄ p < 0.01, Student’s t-test. (E) Immunoblot analysis showing levels of phospho-AKT, total AKT, parkin, PARIS, FBP1, and PGC-1a in insulinresistant SH-SY5Y cells generated by treatment with insulin (low, 10 nm/L; high, 1 lM/L) for 48 h. (n = 3). (F) Quantitation of the immunoblots in panel E normalized to b-actin, n = 3. Data = mean ± SEM, ⁄p < 0.05, ⁄⁄p < 0.01, ANOVA with Student–Newman–Keuls post hoc analysis. (G). Insulin-resistant SH-SY5Y cells were exposed to MPP+ (500 lM) for 12 h and then analyzed for cytotoxicity using the Trypan Blue exclusion assay, n = 3. Data = mean ± SEM, ⁄p < 0.05, ⁄⁄p < 0.01, Student’s t-test.

339

was observed for IR-SH treated with MPP+ (Fig. 3G). These results may suggest that IR increases the sensitivity of cells to mitochondrial stress and ultimately leads to neuronal cell death in IR severity-dependent manner (Fig. 3G).

340

Metformin restores parkin level in db-SN and HFD-SN

341

The most popular anti-diabetic drug, metformin is a widely known insulin-sensitizing drug used to lower blood glucose concentrations in patients with T2D (Kirpichnikov et al., 2002). Moreover, metformin has a low level of side effects, robustly improves learning behavior, and decreases the level of oxidative stress in the brains of HFD rats (Pintana et al., 2012). In order to assess if metformin affects the level of parkin in vivo, 8week-old mice were given metformin (400 mg/kg) daily by oral route for 2 weeks and the expression of parkin was monitored. Levels of parkin were significantly increased in a dose-dependent manner in the SN of mice treated with metformin, and slight upregulation of parkin was observed in the STR as well (Fig. 4A, B). On the

335 336 337 338

342 343 344 345 346 347 348 349 350 351 352 353 354

other hand, there was no detectable change in the expression of parkin in the CTX of metformin-administrated mice, suggesting that metformin exerts its pharmacological effects in a region-specific manner (Fig. 4A, B). Interestingly, metformin increased levels of parkin in db-SN and HFD-SN, which was accompanied by downregulation of PARIS and upregulation of PGC1a (Fig. 4C–F), together suggesting that metformin may modulate Parkin–PARIS–PGC-1a pathway in vivo. A similar observation was made in vitro for IR-SH cells, whereby parkin and PGC-1a were upregulated and PARIS was downregulated by metformin (Fig. 4E, F). Lastly, to determine if metformin has a neuroprotective effect, IR-SH cells were treated simultaneously with MPP+ and metformin (0.4 mM). We found that metformin successfully protected IR-SH cells from MPP+-mediated toxicity (Fig. 4G).

355

Mild degeneration of DA in chronic HFD mice

372

Since metabolic dysregulation led to the loss of parkin and accumulation of parkin’s substrates, we examined

373

Please cite this article in press as: Khang R et al. Dysregulation of parkin in the substantia nigra of db/db and high-fat diet mice. Neuroscience (2015), http://dx.doi.org/10.1016/j.neuroscience.2015.03.017

356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371

374

NSC 16124

No. of Pages 11

18 March 2015

R. Khang et al. / Neuroscience xxx (2015) xxx–xxx

9

Fig. 4. Metformin restores parkin expression. (A) Immunoblot analysis showing levels of parkin in mice administered metformin (mid, 200 mg/ kg/day; high, 400 mg/kg/day) for 2 weeks. (n = 3). (B) Quantitation of the immunoblots in panel A normalized to b-actin, n = 3. Data are the mean ± SEM, ⁄p < 0.05, ⁄⁄p < 0.01 and ⁄⁄⁄p < 0.001, ANOVA with Student–Newman–Keuls post hoc analysis. (C) Levels of parkin, phosphoAKT, total AKT, PARIS, and PGC-1a in the SN, STR, and CTX of metformin-administrated db/db mice (400 mg/kg/day) measured by immunoblot analysis (n = 3). (D) Quantitation of the immunoblots in panel C normalized to b-actin, n = 3. Data = mean ± SEM, ⁄p < 0.05, ⁄⁄p < 0.01, Student’s t-test. (E) Immunoblot showing levels of parkin, phospho-AKT, total AKT, PARIS, and PGC-1a in the SN, STR, and CTX of metforminadministrated HFD mice. (F) Quantitation of the immunoblots in panel E normalized to b-actin, n = 3. Data = mean ± SEM, ⁄⁄p < 0.01, Student’s t-test. (G) Immunoblot analysis showing the level of phospho-AKT, total AKT, parkin, PARIS, FBP1, and PGC-1a in insulin-resistant SH-SY5Y treated with metformin. (H) Quantitation of the immunoblots in panel G normalized to b-actin, n = 3. Data = mean ± SEM, ⁄p < 0.05, ⁄⁄p < 0.01, Student’s t-test. (I) Insulin-resistant SH-SY5Y cells were exposed to MPP+ (500 lM) as well as metformin and cytotoxicity was analyzed using the Trypan Blue exclusion assay, n = 3. Data = mean ± SEM, ⁄p < 0.05, ⁄⁄p < 0.01, Student’s t-test. 375 376 377 378 379 380 381 382 383 384 385 386 387

whether there was a DA degeneration in the db/db and HFD mice. The optical density of TH-positive DA in the SN of 3-month-old db/db, 8 week-HFD fed, and 20 week-HFD fed mice were compared to those of agematched control mice. No significant DA degeneration was found in db-SN and HFD-SN (8 weeks) as compared to WT-SN and Chow-SN (Fig. 5A–D). However, mild degeneration of DA was detected in the SN of 20 week-HFD fed mice as compared to agematched chow diet-fed mice. Interestingly, chronic administration of metformin protected against DA degeneration observed in the SN of 20 week-HFD-fed mice (Fig. 5C, D).

388

DISCUSSION

389

Metabolic syndrome refers to a collection of interconnected disorders, including obesity, insulin resistance, glucose intolerance, hyperlipidemia, and hypertension. Obesity is a driver of metabolic syndrome components and is a well-recognized risk factor for the

390 391 392 393

development of T2D. Recent evidence suggests that obesity leads to a complicated neurological process, including dysregulation of neurohormones and neurotransmitters (Elmquist and Flier, 2004; Belgardt and Bruning, 2010). Although there is still a great deal to be discovered, several mechanistic lines of evidence have suggested a close relationship between metabolic diseases and neurodegenerative diseases such as PD (Lees et al., 2009; Lu et al., 2009). Here, we applied an LC–MS/MS-based proteomic approach to identify a shared molecular pathway linking T2D to PD pathogenesis. We found that expression of parkin was significantly diminished in the SN of T2D mouse models contributing subsequently PGC-1a downregulation along with PARIS accumulation. These molecular features were restored by metformin, suggesting that metformin might be a therapeutic drug not only for T2D, but also DA death triggered by metabolic dysfunction. Prior to this study, there have been no reports of profiling and systemic comparison of the SN proteome in db/db or HFD mice. Interestingly, we identified few

Please cite this article in press as: Khang R et al. Dysregulation of parkin in the substantia nigra of db/db and high-fat diet mice. Neuroscience (2015), http://dx.doi.org/10.1016/j.neuroscience.2015.03.017

394 395 396 397 398 399 400 401 402 403 404 405 406 407 408 409 410 411 412 413 414

NSC 16124

No. of Pages 11

18 March 2015

10

R. Khang et al. / Neuroscience xxx (2015) xxx–xxx

Fig. 5. Mild degeneration of dopaminergic neuron in old HFD-SN. (A) TH immunostaining of representative sections from WT-SN and db-SN. (B) The relative optical intensity of TH-positive neurons in db-SN (n = 4 per group). Data = mean ± S.E.M. (C) Representative TH-stained sections from Chow-SN and HFD-SN. (D) The relative intensity of TH-positive neurons in panel C (n = 5 per group). Data are the mean ± SEM, ⁄p < 0.05, ANOVA with Student–Newman–Keuls post hoc analysis.

415 416 417 418 419 420 421 422 423 424 425 426 427 428 429 430 431 432 433 434 435 436 437 438 439 440 441 442 443 444 445 446 447 448 449 450 451 452 453 454 455 456 457

proteins commonly altered in both models, indicating that there were significant differences in the characteristics of db/db and HFD mouse models. Although both models are characterized by high blood glucose and insulin levels, dyslipidemia, and obesity, different mechanisms may be responsible for their phenotype. In support of this possibility, db/db mice exhibit severe glucose intolerance, hyperglycemia, and hyperinsulinemia, whereas HFD mice have milder glucose intolerance and other metabolic features that can be reversed by a lowfat diet (Lee et al., 1996; Parekh et al., 1998). Likely owing to the differences between db/db and HFD mice, decreased parkin expression was observed in the SN, STR, and CTX of db/db mice and SN, but not the STR or CTX, of HFD mice. Thus, the SN may be more vulnerable to glucose signaling as compared to the STR and CTX. Likewise, accumulation of AIMP2, FBP1, and PARIS was observed in the SN of HFD mice, but not STR and CTX, indicating the presence of region-specific changes in levels of parkin. Unexpectedly, levels of parkin substrates were unchanged in the STR and CTX of db/db mice, although parkin was robustly diminished in the STR and CTX of db/db mice, suggesting that there may be differential regulatory mechanisms underlying the degradation of AIMP2, FBP1, and PARIS. In sporadic PD, PARIS only accumulated in the STR and SN, since parkin was selectively inactivated in the STR and SN by nitrosative and dopaminergic stress as well as c-Abl phosphorylation. Consistent with these observations, we previously showed that only PARIS is upregulated in the STR and SN of parkin knockout mice (Shin et al., 2011). With respect to the T2D models used in this study, we cannot be certain that PARIS is the sole substrate contributing to PD pathogenesis in the absence of parkin. However, the earliest feature of IR is the reduction of PGC-1a and mitochondrial gene, nuclear respiratory factor 1 (NRF1), and reduced PGC-1a and mitochondrial DNA contents are observed in patients with T2D, suggesting that PARIS may be a useful molecular marker for understanding the relationship between T2D and PD. Although FBP1 and AIMP2 are undoubtedly relevant to DA toxicity in PD, it is clear that the accumulation

of PARIS in the context of parkin deficiency leads to the downregulation of PGC-1a in IR and pathogenesis of PD. Extensive studies have demonstrated that metformin can be used as a disease-modifying drug for neurodegeneration (Patrone et al., 2014). For example, metformin protects against ethanol-induced neuronal toxicity in rat cortical neurons and etoposide-induced cytotoxicity in primary neurons (El-Mir et al., 2008; Ullah et al., 2012). Furthermore ischemic cell death in the hippocampus is attenuated by pre-treatment with metformin, which sensitizes insulin receptors to facilitate enhanced neuronal viability under hypoxic conditions (Mielke et al., 2006; Ashabi et al., 2014). Our phosphoproteomic analysis revealed that the level of phospho-AMPK was reduced in the brain by the administration of metformin and that levels of phosphorylated a-synuclein were significantly decreased (Khang et al., 2014). Interestingly, phosphorylation of metabolic enzymes is decreased compared with that of mitochondrial proteins upon treatment with metformin (Khang et al., 2014). It is likely that metformin restores levels of parkin and PGC-1a, and alters the phosphoproteome through an as yet unidentified mechanism, ultimately producing a neuroprotective effect. As previously reported (Wang et al., 2014), there is no significant DA degeneration in the SN of 3-month-old db/ db as compared to age-matched control mice. However, mild degeneration of DA was detected in the SN of 20 week-HFD fed mice but not in that of 8 week-HFD fed mice, suggesting that the loss of DA by metabolic dysregulation might require chronic metabolic abnormalities and aging-associated secondary hit such as the accumulation of ROS and mitochondrial dysfunction. Indeed, 10week-old db/db showed robust activation of microglia and increased ER stress in the SN (Wang et al., 2014), assuming that cellular events are not sufficient to cause DA death in early stages of metabolic disorder. In addition, chronic HFD consumption induced neuronal adaptation, impaired elementary cognitive functions, and led to presynaptic dopaminergic abnormalities (Labouesse et al., 2013). Further studies will address whether db/db mice show DA degeneration in an age-dependent manner.

Please cite this article in press as: Khang R et al. Dysregulation of parkin in the substantia nigra of db/db and high-fat diet mice. Neuroscience (2015), http://dx.doi.org/10.1016/j.neuroscience.2015.03.017

458 459 460 461 462 463 464 465 466 467 468 469 470 471 472 473 474 475 476 477 478 479 480 481 482 483 484 485 486 487 488 489 490 491 492 493 494 495 496 497 498 499 500

NSC 16124

No. of Pages 11

18 March 2015

R. Khang et al. / Neuroscience xxx (2015) xxx–xxx 501 502 503 504 505 506 507 508 509 510 511

In conclusion, we showed that metabolic dysfunction leads to a reduction of parkin, accumulation of PARIS, and downregulation of PGC-1a in the SN. The Parkin– PARIS–PGC-1a pathway is a potential contributor to PD pathogenesis, and its dysregulation in T2D may selectively increase the vulnerability of dopamine neurons to account, at least in part, for PD pathogenesis. Although further study is required to understand the Parkin-PARIS-PGC-1a pathway in T2D, our results suggest that abnormal regulation of parkin may be shared between T2D and PD.

516

Acknowledgments—This research was supported by grants from the NRF (NRF-2012R1A1A1012435) funded by the Korea Ministry of Science, ICT & Future Planning (MSIP) and was also supported by a Samsung Biomedical Research Institute grant (SBRI, SMX1132521).

517

REFERENCES

518 519 520 521 522 523 524 525 526 527 528 529 530 531 532 533 534 535 536 537 538 539 540 541 542 543 544 545 546 547 548 549 550 551 552 553 554 555 556 557

Ashabi G, Khodagholi F, Khalaj L, Goudarzvand M, Nasiri M (2014) Activation of AMP-activated protein kinase by metformin protects against global cerebral ischemia in male rats: interference of AMPK/PGC-1a pathway. Metab Brain Dis 29:47–58. Belgardt BF, Bruning JC (2010) CNS leptin and insulin action in the control of energy homeostasis. Ann N Y Acad Sci 1212:97–113. Bhatia VN, Perlman DH, Costello CE, McComb ME (2009) Software tool for researching annotations of proteins: open-source protein annotation software with data visualization. Anal Chem 81:9819–9823. Chen H, Charlat O, Tartaglia LA, Woolf EA, Weng X, Ellis SJ, Lakey ND, Culpepper J, Moore KJ, Breitbart RE, Duyk GM, Tepper RI, Morgenstern JP (1996) Evidence that the diabetes gene encodes the leptin receptor: identification of a mutation in the leptin receptor gene in db/db mice. Cell 84:491–495. Dawson TM, Dawson VL (2010) The role of parkin in familial and sporadic Parkinson’s disease. Mov Disord 25(Suppl. 1):S32–S39. Dawson TM, Dawson VL (2014) Parkin plays a role in sporadic Parkinson’s disease. Neurodegener Dis 13:69–71. El-Mir MY, Detaille D, Villanueva GR, Delgado-Esteban M, Guigas B, Attia S, Fontaine E, Almeida A, Leverve X (2008) Neuroprotective role of antidiabetic drug metformin against apoptotic cell death in primary cortical neurons. J Mol Neurosci 34:77–87. Elmquist JK, Flier JS (2004) The fat-brain axis enters a new dimension. Science 304:63–64. Hu G, Jousilahti P, Bidel S, Antikainen R, Tuomilehto J (2007) Type 2 diabetes and the risk of Parkinson’s disease. Diabetes Care 30:842–847. Jensen LJ, Kuhn M, Stark M, Chaffron S, Creever C, Muller J, Doerks T, Julien P, Roth A, Simonovic M, Bork P, von Mering C (2009) STRING 8 – a global view on proteins and their functional interactions in 630 organisms. Nucleic Acids Res 37:D412–D416. Khang R, Park C, Shin JH (2014) The biguanide metformin alters phosphoproteomic profiling in mouse brain. Neurosci Lett 579:145–150. Kirpichnikov D, McFarlane SI, Sowers JR (2002) Metformin: an update. Ann Intern Med 137:25–33. Kitada T, Asakawa S, Hattori N (1998) Mutations in the parkin gene cause autosomal recessive juvenile parkinsonism. Nature 392:605–608.

512 513 514 515

622 623 624

11

Labouesse MA, Stadlbauer U, Langhans W, Meyer U (2013) Chronic high fat diet consumption impairs sensorimotor gating in mice. Psychoneuroendocrinology 38:2562–2574. Lee GH, Proenca R, Montez JM, Carroll KM, Darvishzadeh JG, Lee JI, Friedman JM (1996) Abnormal splicing of the leptin receptor in diabetic mice. Nature 379:632–635. Lees AJ, Hardy J, Revesz T (2009) Parkinson’s disease. Lancet 373:2055–2066. Lu M, Hu G (2012) Targeting metabolic inflammation in Parkinson’s disease: implications for prospective therapeutic strategies. Clin Exp Pharmacol Physiol 39:577–585. Lu FP, Lin KP, Kuo HK (2009) Diabetes and the risk of multi-system aging phenotypes: a systematic review and meta-analysis. PLoS One 4:e4144. Martin-Montalvo A, Mercken EM, Mitchell SJ, Palacios HH, Mote PL, Scheibye-Knudsen M, Gomes AP, Ward TM, Minor RK, Blouin MJ, Schwab M, Pollak M, Zhang Y, Yu Y, Becker KG, Bohr VA, Ingram DK, Sinclair DA, Wolf NS, Spindler SR, Bernier M, de Cabo R (2013) Metformin improves healthspan and lifespan in mice. Nat Commun 4:2192. Mielke JG, Taghibiglou C, Wang YT (2006) Endogenous insulin signaling protects cultured neurons from oxygen–glucose deprivation-induced cell death. Neuroscience 143:165–173. Parekh PI, Petro AE, Tiller JM, Feinglos MN, Surwit RS (1998) Reversal of diet-induced obesity and diabetes in C57BL/6J mice. Metabolism 47:1089–1096. Patrone C, Eriksson O, Lindholm D (2014) Diabetes drugs and neurological disorders: new views and therapeutic possibilities. Lancet Diabetes Endocrinol 2:256–262. Pintana H, Apaijai N, Pratchayasakul W, Chattipakorn N, Chattipakorn SC (2012) Effects of metformin on learning and memory behaviors and brain mitochondrial functions in high fat diet induced insulin resistant rats. Life Sci 91:409–414. Santiago JA, Potashkin JA (2013) Shared dysregulated pathways lead to Parkinson’s disease and diabetes. Trends Mol Med 19:176–186. Savitt JM, Dawson VL, Dawson TM (2006) Diagnosis and treatment of Parkinson disease: molecules to medicine. J Clin Invest 116:1744–1754. Schernhammer E, Hansen J, Rugbjerg K, Wermuth L, Ritz B (2011) Diabetes and the risk of developing Parkinson’s disease in Denmark. Diabetes Care 34:1102–1108. Shevchenko A, Tomas H, Havlis J, Olsen JV, Mann M (2006) In-gel digestion for mass spectrometric characterization of proteins and proteomes. Nat Protoc 1:2856–2860. Shin JH, Ko HS, Kang H, Lee Y, Lee YI, Pletinkova O, Troconso JC, Dawson VL, Dawson TM (2011) PARIS (ZNF746) repression of PGC-1a contributes to neurodegeneration in Parkinson’s disease. Cell 144:689–702. Ullah I, Ullah N, Naseer MI, Lee HY, Kim MO (2012) Neuroprotection with metformin and thymoquinone against ethanol-induced apoptotic neurodegeneration in prenatal rat cortical neurons. BMC Neurosci 13:11. Van Heek M, Compton DS, France CF, Tedesco RP, Fawzi AB, Graziano MP, Sybertz EJ, Strader Jr CD, Davis HR (1997) Dietinduced obese mice develop peripheral, but not central, resistance to leptin. J Clin Invest 99:385–390. Wang L, Zhai YQ, Xu LL, Qiao C, Sun XL, Ding JH, Lu M, Hu G (2014) Metabolic inflammation exacerbates dopaminergic neuronal degeneration in response to acute MPTP challenge in type 2 diabetes mice. Exp Neurol 251:22–29. Xu Q, Park Y, Huang X, Hollenbeck A, Blair A, Schatzkin A, Chen H (2011) Diabetes and risk of Parkinson’s disease. Diabetes Care 34:910–915.

(Accepted 7 March 2015) (Available online xxxx)

Please cite this article in press as: Khang R et al. Dysregulation of parkin in the substantia nigra of db/db and high-fat diet mice. Neuroscience (2015), http://dx.doi.org/10.1016/j.neuroscience.2015.03.017

558 559 560 561 562 563 564 565 566 567 568 569 570 571 572 573 574 575 576 577 578 579 580 581 582 583 584 585 586 587 588 589 590 591 592 593 594 595 596 597 598 599 600 601 602 603 604 605 606 607 608 609 610 611 612 613 614 615 616 617 618 619 620 621