Chronic Sleep Deprivation-Induced Proteome Changes in Astrocytes

Article pubs.acs.org/jpr

Chronic Sleep Deprivation-Induced Proteome Changes in Astrocytes of the Rat Hypothalamus Jae-Hong Kim,†,⊥ Jong-Heon Kim,†,⊥ Young-Eun Cho,‡ Moon-Chang Baek,‡ Ji-Young Jung,† Maan-Gee Lee,† Il-Sung Jang,∥ Ho-Won Lee,§ and Kyoungho Suk*,† †

Department of Pharmacology, Brain Science & Engineering Institute, BK21 PLUS KNU Biomedical Convergence Program for Creative Talent, ‡Department of Molecular Medicine, Cell & Matrix Research Institute, §Department of Neurology, Brain Science & Engineering Institute, Kyungpook National University School of Medicine, Daegu 700-422, Republic of Korea ∥ Department of Pharmacology, Brain Science and Engineering Institute, Kyungpook National University School of Dentistry, Daegu 700-422, Republic of Korea S Supporting Information *

ABSTRACT: Sleep deprivation (SD) can influence cognition, memory, and sleep/wake homeostasis and can cause impairments in many physiological processes. Because the homeostatic control of the sleep/wake cycle is closely associated with the hypothalamus, the current study was undertaken to examine proteomic changes occurring in hypothalamic astrocytes following chronic partial SD. After chronic partial SD for 7 days, astrocytes were prepared from rat hypothalamus using a Percoll gradient method, and their proteome profiles were determined by LC−MS/MS. Comparisons of the proteome profiles of hypothalamic astrocytes revealed that chronic partial SD increased (≥1.5-fold) 89 proteins and decreased (≤0.7-fold) 50 proteins; these changes in protein expression were validated by western blot or immunohistochemistry. DAVID and IPA analyses of these proteins suggested that SD may influence gliotransmission and astrocyte activation. PPP2R1A, RTN4, VAMP-2, LGI-1, and SLC17A7 were identified and validated as the main targets of SD in astrocytes. Our results suggest that SD may modulate gliotransmission in the hypothalamus, thereby disturbing sleep/wake homeostasis and increasing susceptibility to neurological disease; however, further studies are required to confirm whether the proteome changes are specific to SD. KEYWORDS: Astrocyte, chronic sleep deprivation, hypothalamus, neurological disease

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tolerance,10 hypertension,11 anxiety symptoms,12 depressed mood,13 movement disorders,14 and mortality.15 The hypothalamus is the primary brain region responsible for the homeostatic control of various physiological processes, and it is a central area for the regulation of the sleep/wake cycle. GABAergic neurons in the ventrolateral preoptic nucleus (VLPO) expressing galanin are known as sleep-promoting neurons,16 whereas the activation of orexin/hypocretin neurons in the lateral hypothalamic area (LH) regulates arousal.17 Sleep/ arousal cycle regulation is associated with the accumulation of adenosine and the activation of the adenosine receptor.18 Recently, astrocytic modulation has emerged as a potential mechanism of regulating sleep/wake homeostasis.19 It has been established that astrocytes are involved in water and ionic balance,20 energy metabolism,21 neurovascular interaction,22 and synaptic transmission,23 and these physiological functions of astrocytes can be altered by sleep deprivation.24 Furthermore, it

INTRODUCTION

Sleep of sufficient duration and depth is functionally associated with physiological homeostasis, with respect to thermoregulation,1 energy conservation,2 immune defense,3 tissue restoration,4 and brain plasticity.5 Sleep deprivation (SD) can be defined as not having enough sleep, and depending on the nature of this restriction, SD can be classified as partial, total, acute, or chronic. Acute total SD may cause the deterioration of various neurological functions and even death, whereas chronic partial SD is closer to the real situation that is common in everyday life.6 Mild or moderate chronic partial SD is sufficient to prolong the effect of SD7 and may stabilize and habituate brain adaptation to sleep deprivation if insufficient time for recovery is given, whereas alterations due to acute total SD can be restored if a suitable recovery time is given. Although the adverse effects of total SD or acute SD have been extensively reported, few studies have been conducted on chronic partial SD. Long-term sleep loss, like chronic partial SD, is known to be associated with neurocognitive deficits,8 obesity,9 diabetes and impaired glucose © XXXX American Chemical Society

Received: April 29, 2014

A

dx.doi.org/10.1021/pr500431j | J. Proteome Res. XXXX, XXX, XXX−XXX

Journal of Proteome Research

Article

Chronic Partial Sleep Deprivation

has been proposed that astrocytic ATP, as a precursor of adenosine, modulates sleep homeostasis19c and that sleep lossinduced deficits in hippocampal synaptic plasticity and memory result from alterations in the activities of astrocytic adenosine and the A1 receptor.25 These findings suggest that cellular and molecular changes in astrocytes can lead to sleep/wake cycle disruption. However, the molecular mechanisms responsible for astrocytic changes following SD are not clearly understood. Because the hypothalamus plays a central role in the homeostatic control of sleep, we investigated the proteome profile of hypothalamic astrocytes after sleep deprivation. Liquid chromatography−electrospray ionization/multistage mass spectrometry (LC−ESI−MS/MS) and in silico analysis using the Database for Annotation, Visualization, and Integrated Discovery (DAVID) and Ingenuity Pathway Analysis (IPA) were performed on the proteome of astrocytes isolated from the hypothalamic area following chronic restriction to 4 h of sleep per day for 7 days. Selected nuclei from the hypothalamus have been previously subjected to proteomic analysis.26 Our current results of hypothalamic astrocyte-focused proteomic analysis indicate that astrocytic proteins of altered abundance after SD are mainly associated with astrocytic activation, gliotransmission, and neurological disease. Further studies are, however, necessary to determine whether the proteome changes are specific to SD and to confirm the in vivo relevance of the current findings.

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Sleep deprivation was conducted by classic flower pot method, which is a well-established method to abolish rapid eye movement (REM) sleep.28 Briefly, rats were randomly divided into two groups: experimental versus control. Animals in the experimental group were placed individually onto a small circular platform (diameter, 5.3 cm) located in a plastic container (60 × 60 × 60 cm3) filled with room-temperature water (depth of 5 cm) at 1 cm above the water line. During sleep, muscle hypotonia caused animals to fall into the water, forcing them to climb back on the platform and remain awake. Control rats were placed individually onto a larger circular platform (diameter, 8.0 cm) to allow the animals to sleep under the same conditions. Experiments were conducted at 22 ± 1 °C. Platform exposures were conducted 20 h/day (23:00−19:00) for 7 days, and animals were transferred to home cages for the remaining 4 h/day (19:00−23:00). During the 4 h in home cages, food and water were supplied to animals. Daily food and water intakes and body weights were measured at 23:00. The physiological effects of sleep deprivation were confirmed by low body weights as compared with that of the control animals.29 For sleep recovery experiments, three rats were similarly subjected to SD and allowed to recover for 7 days in home cages. At the end of the recovery period, the rats were sacrificed for analysis. Isolation of Hypothalamic Astrocytes

Anesthetized rats were perfused through the left ventricle with ice-cold Hank’s balanced salt solution (HBSS) without calcium and magnesium (Gibco-BRL, Grand Island, NY, USA). Dissected brains were maintained in calcium- and magnesiumfree HBSS until all animals were sacrificed. Astrocytes were isolated from hypothalami using a previously described Percoll gradient method after sleep deprivation.30 Experiments were performed at the same time of day to reduce variation. In brief, in each case, the hypothalamus was dissected, and hypothalamic tissues were chopped, treated with 0.25% trypsin−EDTA (Gibco-BRL) solution for 5 min at 37 °C, and dissociated using a nylon mesh to obtain a single-cell suspension. This suspension was then loaded on a discontinuous Percoll density gradient consisting of 60, 30, 20, and 10% Percoll layers (in calcium- and magnesium-free HBSS) and centrifuged (2000g for 15 min). Astrocytes were then collected from the central layer (usually, the 30% layer and a portion of the 20% layer), and purity was confirmed by immunocytochemical staining with an antiGFAP antibody (purities were greater than 95%) (Supporting Information Figure 2). Collected astrocytes were then resuspended in ice-cold lysis buffer (50 mM Tris-HCl, pH 8.0, 150 mM NaCl, 0.02% sodium azide, 0.1% SDS, 1% Nonidet P40, 0.5% deoxycholate) containing a mixture of protease inhibitors (Amersham Biosciences, Piscataway, NJ, USA). After cell lysis, samples were centrifuged at 15 700g for 10 min, and supernatants were used for further analysis.

MATERIALS AND METHODS

Animals

Adult male Sprague−Dawley rats (Samtaco, Osan, Korea) weighing from 250 to 300 g were used in the experiments. Animals were housed individually in Plexiglas cages under an ambient temperature of 23 ± 2 °C and a strict light cycle (light on from 07:00 to 19:00). Animals were given a commercial chow diet (Hyochang Science, Daegu, Korea) ad libitum. All procedures were conducted in accordance with the guideline issued by the Kyungpook National University Animal Experiment Ethics Committee. Experimental Design

Proteomic analysis was performed using the following five steps (Supporting Information Figure 1A). Step 1: rats (n = 9) were subjected to sleep deprivation for 20 h/day for 7 days. NSD, nonsleep deprivation controls (n = 9). Step 2: hypothalami of rat brains were dissected and pooled into groups of three for each condition, and astrocytes were isolated. Samples were pooled to obtain the amount of proteins required for the LC−MS analysis. In the previous studies on the hypothalamic region, pooled samples were similarly used.27 Step 3: proteins were extracted from hypothalamic astrocytes and digested for proteomic analysis. Step 4: 2D- or 1D-LC−MS/MS analysis was performed in triplicate. Step 5: proteins were identified and quantified by database search and bioinformatic analysis using DAVID and IPA. Eighteen rats (12 animals for 2D-LC−MS; 6 animals for 1D-LC−MS) were divided into two groups (9 animals for each condition) (Supporting Information Figure 1B). For each condition, 9 hypothalamic tissues were pooled into groups of three (three biological replicates), astrocytes were isolated, and proteomic analysis was performed, which was repeated three times (three technical replicates). An additional 6 rats for western blot validation (n = 3 for each condition) and 9 animals for immunohistochemistry (IHC, n = 3 for each condition) were used.

Gel-Assisted Protein Digestion

The protein concentrations of isolated astrocytes were determined using a bicinchoninic acid (BCA) assay. Protein digestion was conducted using a previously described gel-assisted digestion protocol.31 Briefly, total protein was chemically reduced with 10 mM dithiothreitol (DTT) and alkylated with 50 mM iodoacetamide. This protein solution was then added, with mixing, to 15 μL of acrylamide/bis(acrylamide) solution (30%, v/v, 29:1), 2.5 μL of 10% (w/v) ammonium persulfate (APS), and 1 μL of 100% TEMED in an Eppendorf vial to produce a small gel. This gel was cut into small pieces and B



Article

Oxidation (Met) and carbamidomethyl (Cys) were specified as a variable modification. Proteins identified with >95% confidence (for those identified with two or more peptides) or 99% confidence (for those identified by a single peptide) were included in the final data analysis. The peptide identification was accepted if they could be assigned at a probability greater than 95%. Only proteins meeting these criteria and identified in at least two independent experiments were used.33 For evaluation of the protein identification false discovery rate (FDR), data were searched against a combined database consisting of both normal and decoy created by MASCOT. In this study, FDRs for each experiment were ≤1%. MS/MS spectra and assignment for single peptide identification are included in Supporting Information Figure 3. Functional categorization of proteins was performed according to subcellular localization and molecular function using the DAVID program.

proteolytically digested with trypsin. Peptides were extracted from the gel by sequential extraction using 0.1% (v/v) trifluoroacetic acid (TFA) in water, 0.1% (v/v) TFA in acetonitrile (ACN), and 100% ACN. Peptide solutions were then combined, concentrated in a SpeedVac, and stored at −20 °C until required. LC−ESI−MS/MS Analysis

Peptide samples were reconstituted in 0.1% (v/v) FA in H2O and analyzed by two-dimensional liquid chromatography (2D-LC)− MS/MS using Waters Q-TOF Premier (Waters Corporation, Manchester, UK). Peptide concentration was measured using a BCA assay. Five micrograms of the peptides was analyzed by a nanoACQUITY system (Waters) using a hybrid silica XTerra MS C18 column (100 mm × 300 μm, 5 mm) as the firstdimension column and using a Symmetry C18 precolumn (5 μm, 5 mm × 300 μm) and a BEH C18 analytical reverse-phase column (1.7 μm, 25 cm × 75 μm) (Waters) as the seconddimension column. The samples were initially transferred, with an aqueous 0.1% formic acid solution, to the first-dimension column at a flow rate of 0.5 μL/min for 5 min. Mobile phase A consisted of ammonium hydroxide/water, pH 10.0, and mobile phase B consisted of ACN for the first-dimension column. Mobile phase A consisted of water with 0.1% formic acid and mobile phase B consisted of 0.1% formic acid in ACN, pH 2.0, for the second-dimension column. Peptides were separated with a stepwise gradient of 0, 21, and 45% mobile phase B in the firstdimension column, and each elute was separated in the seconddimension column with a gradient of 3−55% mobile phase B over a period of 60 min at a flow rate of 300 nL/min, followed by rinsing for 5 min with 90% of mobile phase B. The MS system was operated in ESI positive V mode, with a resolving power of 10 000. The NanoLockSpray source was used for an accurate mass measurement, and the lock mass channel was sampled every 60 s. All analyses were performed in the data dependent analysis (DDA) mode. MS scans were sequentially selected for collision-induced dissociation (CID) using a normalized collision energy of 35%. Dynamic exclusion was applied to minimize repeated selection of peptides that were previously selected for CID. In this way, if two peptide ions are present in the TOF mass spectrum, then the most intense will be selected for the first experiment and the less intense will be selected for the second MS/MS experiment. The exclusion duration was 150 s, and the mass tolerance was 200 mDa. Capillary voltage and cone voltage were set to 3500 and 30 V, respectively. The lock mass was delivered from the auxiliary nanoACQUITY pump, with a constant flow rate of 200 nL/min, at a concentration of 50 fmol [Glu1]-Fibrinopeptide B/μL, to the reference sprayer of the NanoLockSpray source of the mass spectrometer. Analysis of all samples was performed in triplicate. The method included a full sequential MS scan (m/z 150−1600, 0.6 s) and eight MS/MS scans (m/z 100−1990, 1.2 s per scan) on the eight most intense ions present in the full-scan mass spectrum.

Label-Free Quantification

For label-free quantification, data analysis was performed using IDEAL-Q software (version 1.0.1.1) provided by Prof. Yu-Ju Chen.34 Recently, label-free quantification has been performed for the hypothalamic proteome.35 Raw data files from the Waters Q-TOF premier mass spectrometer were converted into files of the mzXML format using Masswolf software (Institute for Systems Biology, Seattle, WA, USA). For quantification of the relative peptide abundance of these identified and assigned peptides, extracted ion chromatography (XIC) areas of each peptide normalized by the XIC area of the internal standard were calculated. IDEAL-Q software was used to sequentially process all peptides in each LC−MS/MS run, both identified and unidentified, to quantify as many peptides as possible. The software first integrates all protein and peptide identification results from all LC−MS/MS runs and performs peptide alignment and identification assignment according to the commonly and confidently (p < 0.05) identified peptides. The unidentified peptides, which were the result of either a low identification score or an absence of MS/MS sequencing data, can be retrieved based on predicted elution times and m/z values. To ensure accurate peptide detection and assignment, IDEAL-Q further validated the detected peak clusters by three criteria, including signal-to-noise ratio > 3, a correct charge state, and a good isotope pattern. The protein ratio was determined by a weighted average of the same abundance of the corresponding peptides. The peptides identified with abundance CV ≥ 20% and unusual ratios were not considered for quantification, as previously described.36 The final results of protein quantification were exported into an output file in the XML data format. Pathway and Network Analyses

Functional categorization of proteins was carried out with respect to subcellular localization and molecular function using DAVID (http://david.abcc.ncifcrf.gov/). After protein identification and quantification, the accession numbers and fold changes of differentially expressed proteins were imported into IPA (Ingenuity Systems) for network analysis. The statistical significance of each network or list was determined by IPA using Fisher’s exact test (p < 0.05). IPA was also used to construct networks of interacting proteins. The IPA database uses current knowledge available on genes, proteins, chemicals, normal cellular and disease processes, signaling, and metabolic pathways for pathway construction. The two programs (DAVID and IPA) were used to take advantage of each program.

Protein Identification

For protein identification, the peak list resulting from the MS/ MS spectra was exported to the mgf format using Mascot Distiller software (Matrix Science; version 2.3.2), as previously described.31,32 Mascot (Matrix Science; version 2.2.1) was used in performance of analyses of all MS/MS samples. Mascot was set up to search the IPI_Rat_3.70 database (version 3.70; 68,161 entries), assuming trypsin as the digestion enzyme with a parent ion tolerance of 0.1 Da and a fragment ion mass tolerance of 0.05 Da. Two missed cleavages were allowed during trypsin digestion. C



Article

Table 1. Alteration in the Proteomic Profiles of Hypothalamic Astrocytes Following Sleep Deprivationa no.

accession no.

symbols

description

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17

IPI00198371 IPI00763565 IPI00195372 IPI00231864 IPI00213571 IPI00199636 IPI00368457 IPI00198550 IPI00325281 IPI00950329 IPI00781205 IPI00382191 IPI00421392 IPI00196508 IPI00231641 IPI00189995 IPI00551702

Ap2s1 LOC682397 Eef1a1 Cycs Acot7 Canx Gspt1 Uba25 Eef1a2 Gpd2 Gspt2 Pgd LOC500959 Amph Pgm1 Calb2 Dlst

18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39

IPI00231978 IPI00194731 IPI00471523 IPI00212314 IPI00382194 IPI00475911 IPI00325146 IPI00189813 IPI00780102 IPI00200437 IPI00363930 IPI00950128 IPI00364621 IPI00365600 IPI00231346 IPI00555287 IPI00200661 IPI00365985 IPI00192246 IPI00231615 IPI00206624 IPI00204843

Atp5i Pi4ka Tuba3a Msn Mtap RGD1564290 Anxa2 Acta1 Myh1 Gna11 Sept11 Iqgap Anxa11 Prkar2b Rpl30 Sptbn1 Fasn Tra1 Cox5a Anxa1 Hspa5 Gnao1

40 41 42 43 44 45

IPI00231984 IPI00369496 IPI00358537 IPI00896761 IPI00194875 IPI00205018

Fn1 Rap1gds1 Hspa12a LOC683788 Atp2b2 Aldh6a1

46 47

IPI00202238 IPI00768039

Ndufb10 LOC684425

48 49 50 51 52 53 54 55

IPI00949661 IPI00365286 IPI00373246 IPI00207065 IPI00230986 IPI00202616 IPI00197568 IPI00765011

Vamp2 Vcl Anp32e Slc17a7 Rtn4 Ndufs3 Gdi2 LOC295810

AP-2 complex subunit sigma Similar to polyubiquitin Elongation factor 1-alpha 1 Cytochrome c, somatic Isoform 1 of Cytosolic acyl coenzyme A thioester hydrolase Calnexin G1 to S phase transition 1 Ubiquitin Elongation factor 1-alpha 2 83 kDa protein G1 to S phase transition 2 6-phosphogluconate dehydrogenase, decarboxylating Triosephosphate isomerase Amphiphysin Phosphoglucomutase-1 Calretinin Dihydrolipoyllysine-residue succinyltransferase component of 2oxoglutarate dehydrogenase complex, mitochondrial ATP synthase subunit e, mitochondrial 232 kDa protein Tubulin alpha-3 chain Moesin Cc1-6 Similar to ribosomal protein S27a Isoform Short of Annexin A2 Actin, alpha skeletal muscle Myosin, heavy polypeptide 1, skeletal muscle, adult Guanine nucleotide-binding protein subunit alpha-11 Isoform 1 of Septin-11 Iqgap1 protein Annexin A11 cAMP-dependent protein kinase type II-beta regulatory subunit 60S ribosomal protein L30 Nonerythroid spectrin beta Fatty acid synthase Isoform 1 of Endoplasmin Cytochrome c oxidase subunit 5A, mitochondrial Annexin A1 78 kDa glucose-regulated protein Isoform Alpha-2 of Guanine nucleotide-binding protein G(o) subunit alpha Isoform 4 of Fibronectin RAP1, GTP-GDP dissociation stimulator 1 Heat shock 70 kDa protein 12A Fascin Isoform WB of Plasma membrane calcium-transporting A Methylmalonate-semialdehyde dehydrogenase [acylating], mitochondrial NADH dehydrogenase (ubiquinone) 1 beta subcomplex, 10 Similar to Adenylosuccinate synthetase isozyme 1 (Adenylosuccinate synthetase, muscle isozyme) (IMP–aspartate ligase 1) (AdSS 1) (AMPSase 1) isoform 1 18 kDa protein Vinculin Acidic leucine-rich nuclear phosphoprotein 32 family member E Isoform 1 of Vesicular glutamate transporter 1 Isoform 2 of Reticulon-4 NADH dehydrogenase (ubiquinone) Fe−S protein 3 Rab GDP dissociation inhibitor beta Similar to Actin, cytoplasmic 2

D

SD/NSD protein ratioc (mean ± standard deviation)

protein score

peptide no.b

72 65 58 97 55 52 41 65 60 76 43 100 138 93 49 58 40

2 1 2 3 1 1 1 1 1 1 1 2 2 1 2 1 1

SD SD SD SD SD SD SD SD SD SD SD SD SD SD SD SD SD

51 47 138 134 52 63 96 305 121 50 77 142 45 60 57 230 49 63 62 147 156 431

1 1 3 3 1 2 2 5 2 2 2 2 1 1 1 2 1 1 1 3 1 6

SD unique SD unique SD unique SD unique SD unique SD unique 19.0 ± 0.10 10.8 ± 1.60 9.5 ± 0.01 6.7 ± 0.01 6.5 ± 0.01 5.2 ± 0.01 5.2 ± 0.01 4.0 ± 0.01 3.6 ± 0.01 3.5 ± 0.01 3.4 ± 0.01 3.3 ± 0.01 3.3 ± 0.01 3.3 ± 0.01 3.2 ± 0.01 3.2 ± 0.01

70 62 118 149 134 62

1 3 4 3 2 2

3.1 3.0 2.9 2.9 2.8 2.7

62 42

2 1

2.6 ± 0.01 2.5 ± 0.01

77 110 50 135 50 93 288 48

1 4 2 2 1 2 10 2

2.4 2.4 2.3 2.2 2.2 2.2 2.1 2.1

% CVd

unique unique unique unique unique unique unique unique unique unique unique unique unique unique unique unique unique

± ± ± ± ± ±

± ± ± ± ± ± ± ±

0.01 0.01 2.70 0.01 0.01 0.01

0.01 0.01 0.01 0.01 0.01 0.01 4.00 0.01

16 3 9 16 18 6

16

12 4

8 5 12 16 18 8

8 16 3 10 3 16



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Table 1. continued no.

accession no.

symbols

56 57 58 59 60 61

IPI00948886 IPI00210444 IPI00656453 IPI00896224 IPI00364046 IPI00365423

Atp1a2 Hmgcs2 Rps27a Actg1 Tuba1c Ppp2r1a

62 63 64

IPI00202111 IPI00387771 IPI00393034

Usmg5 Ppia LOC685778

65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83

IPI00204644 IPI00421888 IPI00210566 IPI00558079 IPI00200069 IPI00203823 IPI00231102 IPI00955175 IPI00781221 IPI00567919 IPI00209908 IPI00230859 IPI00209071 IPI00198327 IPI00231502 IPI00373076 IPI00230868 IPI00199465 IPI00362992

Snap25 Anxa6 Hsp90aa1 RGD1559704 Sfxn3 RGD1562690 Plp1 Atp2b2 ?? Ap2a1 Mt-co2 Akr1a1 Dppp6 Vdac2 Ap2b1 Atp6v1a Gnaq Gls Aldh5a1

84 85 86 87 88 89 90 91

IPI00215580 IPI00948912 IPI00231265 IPI00189795 IPI00951420 IPI00366218 IPI00214665 IPI00421711

Atp6v0c LOC683655 Mbp Tuba1a Nln Cct2 Acly Atp5l

92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110

IPI00206054 IPI00200466 IPI00563431 IPI00213457 IPI00231602 IPI00212320 IPI00203250 IPI00372388 IPI00202283 IPI00373403 IPI00194042 IPI00204128 IPI00193151 IPI00199076 IPI00208061 IPI00209162 IPI00203726 IPI00231303 IPI00231247

Cntn1 Slc25a5 LOC499896 Atp6v1c1 Synj1 Gap43 Dpysl3 Cct3 Psmd13 Ahcyl1 Cox6a RGD1561381 Qdpr Pde2a Atp1b3 Fgf12 Lgi1 LOC314140 Map2k1

description 112 kDa protein Hydroxymethylglutaryl-CoA synthase, mitochondrial Ubiquitin Actin, cytoplasmic 2 Tubulin alpha-1C chain Protein phosphatase 2 (Formerly 2A), regulatory subunit A (PR 65), alpha isoform, isoform CRA_a Up-regulated during skeletal muscle growth protein 5 Peptidyl-prolyl cis−trans isomerase A Similar to Pyruvate dehydrogenase E1 component alpha subunit, somatic form, mitochondrial precursor (PDHE1-A type I) isoform 2 Isoform SNAP-25b of Synaptosomal-associated protein 25 Annexin A6 Heat shock protein HSP 90-alpha Similar to glyceraldehyde-3-phosphate dehydrogenase Sideroflexin-3 Similar to L-lactate dehydrogenase A chain Myelin proteolipid protein Isoform 2 of Plasma membrane calcium-transporting ATPase 2 37 kDa protein 105 kDa protein Cytochrome c oxidase subunit 2 Alcohol dehydrogenase [NADP+] Isoform DPPX-L of Dipeptidyl aminopeptidase-like protein 6 Voltage-dependent anion-selective channel protein 2 Isoform 2 of AP-2 complex subunit beta ATPase, H+ transporting, lysosomal V1 subunit A Guanine nucleotide-binding protein G(q) subunit alpha Glutaminase kidney isoform, mitochondrial Isoform Long of Succinate-semialdehyde dehydrogenase, mitochondrial V-type proton ATPase 16 kDa proteolipid subunit Similar to ADAM 22 precursor Isoform 5 of Myelin basic protein S Tubulin alpha-1A chain 80 kDa protein T-complex protein 1 subunit beta ATP-citrate synthase isoform 1 ATP synthase, H+ transporting, mitochondrial F0 complex, subunit G Contactin-1 ADP/ATP translocase 2 Glyceraldehyde 3-phosphate dehydrogenase (Fragment) V-type proton ATPase subunit C 1 Isoform 2 of Synaptojanin-1 Neuromodulin Isoform 2 of Dihydropyrimidinase-related protein 3 T-complex protein 1 subunit gamma 26S proteasome non-ATPase regulatory subunit 13 Adenosylhomocysteinase Cytochrome c oxidase subunit 6A1, mitochondrial Similar to microsomal glutathione S-transferase 3 Dihydropteridine reductase cGMP-dependent 3′,5′-cyclic phosphodiesterase Sodium/potassium-transporting ATPase subunit beta-3 Isoform 1 of Fibroblast growth factor 12 Leucine-rich glioma-inactivated protein 1 Ribose-phosphate pyrophosphokinase I-like Dual specificity mitogen-activated protein kinase kinase 1

E


protein score

peptide no.b

657 52 76 641 918 219

1 2 2 3 1 4

2.1 2.1 2.1 2.0 2.0 2.0

41 145 111

1 4 2

1.9 ± 0.19 1.8 ± 0.01 1.8 ± 0.01

146 45 175 383 192 339 225 150 276 179 204 44 56 132 571 238 128 148 49

3 2 10 1 3 3 13 3 1 3 4 1 2 4 12 12 4 4 2

1.8 1.8 1.8 1.8 1.8 1.7 1.7 1.7 1.7 1.7 1.6 1.6 1.6 1.6 1.6 1.6 1.6 1.6 1.6

± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ±

0.95 0.01 1.36 0.10 0.23 0.01 2.90 0.01 0.01 0.01 0.96 0.01 0.01 2.93 2.0 2.24 0.01 1.56 0.01

41 103 79 856 42 45 172 54

1 2 6 8 1 1 2 1

1.5 1.5 1.5 1.5 1.5 1.5 0.6 0.6

± ± ± ± ± ± ± ±

0.01 0.01 0.40 1.59 0.01 0.01 0.11 0.01

55 109 87 161 107 79 200 45 43 62 46 65 69 69 63 48 71 85 78

5 8 2 4 2 2 1 1 1 2 1 1 3 1 1 1 2 1 1

0.6 ± 0.01 0.6 ± 0.01 0.6 ± 0.01 0.6 ± 0.63 0.6 ± 0.01 0.6 ± 0.01 0.5 ± 0.01 0.5 ± 0.02 0.5 ± 0.01 0.4 ± 0.01 0.4 ± 0.01 0.4 ± 0.01 0.4 ± 0.01 0.3 ± 0.01 0.3 ± 0.01 0.3 ± 0.01 0.2 ± 0.01 NSD unique NSD unique

± ± ± ± ± ±

0.01 0.01 0.01 0.01 0.01 0.95

% CVd 18 17 7 6

4 16 14 18 3 9 16 3 16 6 4 16 10 4 3 6 5 18

17 8 8

19

6 4 18 10 19 18

16

8

5



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Table 1. continued no.

accession no.

symbols

111 112 113 114 115 116 117 118 119 120 121 122 123 124 125

IPI00210881 IPI00188956 IPI00358206 IPI00201444 IPI00324451 IPI00204417 IPI00325912 IPI00288140 IPI00211968 IPI00417753 IPI00422067 IPI00363718 IPI00392495 IPI00331981 IPI00359981

Dnajc5 Thy1 Cul1 Dynll1 Ddb1 Mpeg1 Ctnnb1 Prps2 Map3k12 Kif5a Gnb4 Enoph1

126 127 128 129

IPI00213644 IPI00476086 IPI00390975 IPI00231267

Ppib Atip6v0d1 Krt10 Atp2b1

130

IPI00559849

Ppp3ca

131 132 133 134

IPI00393046 IPI00551673 IPI00205157 IPI00371266

Krt10 Hadh Naca

135 136 137 138 139

IPI00767129 IPI00947909 IPI00202120 IPI00230848 IPI00201969

RGD1311659 Gpi Atp6v0a1 Mtpn Vat1

Dpysl5 Ndufa13

description DnaJ homologue subfamily C member 5 Thy-1 membrane glycoprotein Cullin 1 (Predicted), isoform CRA_a Dynein light chain 1, cytoplasmic DNA damage-binding protein 1 Macrophage-expressed gene 1 protein Catenin beta-1 Ribose-phosphate pyrophosphokinase 2 Mitogen-activated protein kinase kinase kinase 12 Kinesin heavy chain isoform 5A Guanine nucleotide-binding protein subunit beta-4 Enolase-phosphatase E1 25 kDa protein Dihydropyrimidinase-related protein 5 Similar to NADH dehydrogenase (ubiquinone) 1 alpha subcomplex, 13 Peptidyl-prolyl cis−trans isomerase B RCG51062, isoform CRA_a 57 kDa protein Atp2b1 Isoform A of Plasma membrane calcium-transporting ATPase 1 Isoform 2 of Serine/threonine-protein phosphatase 2B catalytic subunit alpha isoform 35 kDa protein 58 kDa protein Hydroxyacyl-coenzyme A dehydrogenase, mitochondrial Nascent-polypeptide-associated complex alpha polypeptide (Predicted), isoform CRA_b Hypothetical protein LOC364814 39 kDa protein V−H+ATPase subunit a1-IV Myotrophin Vesicle amine transport protein 1 homologue


protein score

peptide no.b

65 59 50 76 46 45 39 102 57 39 64 58 46 68 52

2 1 1 1 1 1 1 1 1 1 2 1 1 1 1

NSD NSD NSD NSD NSD NSD NSD NSD NSD NSD NSD NSD NSD NSD NSD

unique unique unique unique unique unique unique unique unique unique unique unique unique unique unique

50 71 43 126

1 2 3 1

NSD NSD NSD NSD

unique unique unique unique

103

1

NSD unique

128 62 44 71

1 1 1 1

NSD NSD NSD NSD

unique unique unique unique

51 130 59 56 45

1 1 2 1 1

NSD NSD NSD NSD NSD

unique unique unique unique unique

% CVd

a

For the 2D-RP-LC, we performed quantification for the biological duplicates and technical triplicates. For label-free quantification using IDEAL-Q software, three files from three analytical replicates were merged into one file, and average ratios from two biological replicates are shown. bPeptides with ion scores above the 95% confidence level. cSD/NSD ratio represents the ratio of proteins detected under sleep deprivation (SD) and non-sleep deprivation (NSD) conditions. Increased expression, fold change ≥ 1.5; decreased expression, fold change ≤ 0.7. dCV indicates coefficient of variation among different peptides of the same protein.

Western Blot Analysis

system (Amersham Biosciences). Data was analyzed using SPSS version 17.0 followed by Tukey’s HSD posthoc test.

In order to validate the results of LC−MS/MS quantification, proteins (50 μg) from each sample were separated on 8 or 15% SDS-PAGE gels and transferred to PVDF membranes (Bio-Rad, Hercules, CA, USA). Membranes were blocked with 5% skim milk and sequentially incubated with primary antibodies against serine/threonine-protein phosphatase 2A 65 kDa regulatory subunit A alpha isoform (PPP2R1A) (rabbit polyclonal antibody; Cell Signaling, Danvers, MA, USA), reticulon 4 (RTN4) (rabbit polyclonal antibody; Alpha Diagnostic International, San Antonio, TX, USA), vesicle-associated membrane protein 2 (VAMP-2) (rabbit polyclonal antibody; Synaptic System, Göttingen, Germany), leucine-rich glioma inactivated-1 (LGI1) (rabbit polyclonal antibody; Abcam, Cambridge, MA, USA), solute carrier family 17 (sodium-dependent inorganic phosphate cotransporter) member 7 (SLC17A7) (rabbit polyclonal antibody; Abcam), and β-actin (mouse monoclonal antibody; Sigma). Membranes were then incubated with horseradish peroxidase-conjugated secondary antibodies [anti-rabbit (Cell Signaling) and anti-mouse (Cell Signaling) IgG antibody]. Proteins were detected using an enhanced chemiluminescence

Immunohistochemistry

Brains were postfixed and cryoprotected with a 30% sucrose solution for 1 day, embedded in OCT compound (Tissue-Tek), and cut into 12 μm thick coronal sections. The sections were then incubated in 0.3% hydrogen peroxide (H2O2) in 0.1 M sodium phosphate buffer (PBS) for 30 min at room temperature (to quench endogenous peroxidase activity), immersed in blocking solution (0.1% Triton-X-100, 1% bovine serum albumin (BSA), and 5% normal goat serum in the PBS) for 1 h, incubated at 4 °C overnight with rabbit polyclonal anti-GFAP antibody (Dako, Glostrup, Denmark), washed with PBS, and incubated with biotinylated secondary antibody (Vector Laboratories, Burlingame, CA, USA) at a dilution of 1:200 for 1 h at room temperature. Sections were then rinsed three times in PBS, incubated with avidin−biotin complex reagents for 1 h at room temperature (ABC kit universal; Vector Laboratories), rinsed again three times in PBS, and treated with 3,3-diaminobenzidine tetrahydrochloride (DAB), which was used as a chromophore. Counterstaining was done using Cresyl violet. For double F



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Figure 1. Biological processes of the proteins with abundances changed by chronic partial sleep deprivation. Hypothalamic astrocyte proteins were analyzed after 7 days of sleep deprivation (20 h/day). Differentially expressed proteins in hypothalamic astrocytes were categorized using DAVID. The biological processes of proteins increased (A) and decreased (B) by sleep deprivation are shown.

ImageJ software (version 1.44, National Institutes of Health, Bethesda, MD, USA). Images were obtained from three nonoverlapping fields chosen randomly within the hypothalamus for the quantitative analysis. Percentage of RTN4/GFAP-double positive cells was determined by quantification of fluorescence intensities using ImageJ software and a colocalization plug-in, as described previously.37

immunostaining, sections were washed with PBS and immersed in blocking solution consisting of 0.1% Triton-X-100, 1% BSA, and 5% normal donkey serum in the PBS for 1 h. They were then treated with primary antibodies against GFAP (mouse monoclonal antibody; BD Biosciences, Heidelberg, Germany) and RTN4 (rabbit polyclonal antibody; Alpha Diagnostic), rinsed with PBS, and incubated with FITC-conjugated antirabbit (Jackson Immuno-Research Laboratories, PA, USA) or Cy3-conjugated anti-mouse IgG antibody (Jackson ImmunoResearch Laboratories), and examined under a fluorescence microscope. RTN4 fluorescence intensities were quantified using

Statistical Analysis

Statistical analysis was performed using SPSS, version 17.0. For determining protein ratios, IDEAL-Q provides the flexibility to calculate each ratio using only the nondegenerate peptides of G



H

a

network 5

network 4

Cell-To-Cell Signaling and Interaction, Nervous System Development and Function, Neurological Disease Cell-To-Cell Signaling and Interaction, Nervous System Development and Function, Neurological Disease Cellular Compromise, Cell Death and Survival, Neurological Disease network 3

Networks were constructed by IPA analysis from the 139 differentially expressed proteins following sleep deprivation. Proteins were named using HUGO gene nomenclature.

Degeneration of neurites 13

Neurotransmission 15

Neurotransmission 15

Neurotransmission network 2

category

Cell-To-Cell Signaling and Interaction, Nervous System Development and Function, Cell Death and Survival Cell-To-Cell Signaling and Interaction, Nervous System Development and Function, Behavior

A total of 139 differentially expressed proteins were identified from 2D-LC−MS/MS analysis in the hypothalamic astrocytes of sleep-deprived rats. Protein quantification revealed that sleep deprivation increased the expression of 89 proteins and decreased the expression of 50 proteins (Table 1). Because the purity of the astrocyte preparation was >95%, a small number of non-astrocytic proteins might also be detected in the current proteomic analysis. In fact, two neuron-specific proteins (Kif5a and Snap25) were included in the list.39 Moreover, the cell isolation procedure primarily isolates the soma of the astrocytes

network 1

Effects of Sleep Deprivation on the Hypothalamic Astrocyte Proteome Profile

network ID

Table 2. List of the Differentially Expressed Proteins That Belong to the Subnetworks Constructed by IPA Analysisa

To identify hypothalamic astrocyte proteins with abundances that were changed by chronic sleep deprivation, rats were subjected to sleep deprivation for 20 h per day for 7 days (SD, n = 9), and then astrocytes were isolated from hypothalami. Nonsleep-deprived animals (NSD, n = 9), which were placed on a large platform, were used as controls. Control animals are also known to suffer from immobilization stress, social isolation, new environment, and mild starvation in the same manner as the SD animals.38 Sleep deprivation did not cause any significant change in the body weight or water or food intake in comparison with that of control animals (Supporting Information Figure 4). For each condition, hypothalamic tissues were pooled into groups of three to generate three biological replicates. Astrocytes were then isolated using a modified Percoll gradient method for each group. Hypothalamic astrocyte proteome profiles were then analyzed in triplicate by gel-assisted digestion and automated LC−MS/MS analysis (three technical replicates). The elution times of commonly identified peptides in the two biological replicates indicated a high correlation between analyses (Supporting Information Figure 5). The CVs of ratios of all astrocyte proteins under different conditions was 14%. The cutoff criteria used to define differentially expressed proteins were an adjusted p-value < 0.05 and a fold ratio difference > 1.5 (Supporting Information Table 1). The proteins identified with one or two peptides may represent low-abundance proteins. Our criteria for identification were extremely stringent, and only peptides that passed all criteria were included in the protein identification process (see Materials and Methods). While 2DLC−MS analysis resulted in the identification of 1965 peptides and 388 proteins, 1D-LC−MS analysis led to the identification of 2388 peptides and 466 proteins (Supporting Information Table 1). From the two analyses, 282 proteins were commonly detected. Proteins identified through the 2D-LC−MS analysis covered 72% of proteins identified by the 1D-LC−MS analyses (Supporting Information Table 2). The cellular localization and biological function of increased or decreased proteins identified through 2D- and 1D-LC−MS were similar (Supporting Information Figure 6).

symbols

Experimental Design of Proteomic Analysis

21

major functions

RESULTS AND DISCUSSION

25

IPA network score

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AKAP5, AMPH, ANXA1, AP2A1, AP2B1, ARC, CALB2, CNTN1, CTNNB1, DKK1, DPYSL5, DYNLL1, EGR1, FGF12, FN1, FUS, FYN, GNAO1, GNB4, GRIN1, HSP90B1, HSPA5, IL6, IQGAP1, MAP2K1, MAPT, PAK1, PRKAR2B, RARA, RTN4, SLC18A2, SLC6A3, SNCA, TGFB1, TUBA1A ACOT7, ADAM22, APP, ATP1A2, ATP1B3, ATP6 V0D1, CACNA1A, CACNA1E, CFL1, DLG2, DLG4, FYN, GRIA2, HDAC4, IGF1, KCNA2, LGI1, LRP1, MAPT, Mbp, PDE2A, PLAT, PLP1, PPP3CA, PRNP, PSEN1, SEPT11, SFXN3, SLC17A7, SLC25A5, SPTBN1, TUBA1A, UBA52, VAMP2, VDAC2 ADORA2A, AMPH, ATP2B1, ATP2B2, BIN1, CACNA1A, CACNA1B, CACNA1E, CAMK2A, CDK5, CDK5R1, COX6A1, DLST, DRD1, Eef1a1, FUS, GNA11, GNAQ, GPI, GRIA2, GRIN1, HAP1, HTT, KIF5A, KLC1, NDUFS3, NEFM, PPIB, PURB, SLC6A3, SNCA, SYN1, SYN2, SYNJ1 ADORA2A, AHCYL1, AKR1A1, AP2S1, APP, ARC, ATP5L, CACNA1A, CACNA1B, CACNA1E, CAMK2A, CLASP2, DNAJC5, DPP6, ESR2, FMR1, GAP43, GRIA2, GRIN1, GSK3B, HSPA12A, ITPR1, JUN, PAK1, PI4KA, PPP2R1A, PPP3CA, PRKACA, PURA, SNAP25, SNCA, SYN1, SYN2, VAMP2, VCL ACTA1, ADORA2A, ANXA2, APP, ATP6 V0A1, ATP6 V1A, BCL2, CACNA1B, CANX, DLG4, DPYSL3, EGFR, EIF2AK2, FOS, GDI2, GFAP, GSK3B, HSP90AA1, HTT, JUN, LRP1, MAP3K12, MAPT, MT-CO2, NEFL, NR4A2, PLAT, PPP3CA, PSEN1, QDPR, SERPINE1, SOD1, STAT3, TGFBR2

proteins or by using all detected peptides. It was found that the degeneracies of peptide/protein identifications were based on database search results. IDEAL-Q also provides an option to eliminate outlier peptide ratios of a protein using Dixon’s Q-test. For western blot analysis, Tukey’s HSD test was used as a posthoc test when significance was detected at the p < 0.05 level (mean ± SEM). Effects of SD on body weight and water/food intake were analyzed by one-way ANOVA followed by Bonferroni’s posthoc test.

Long-term potentiation

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Figure 2. Literature-based functional clustering of differentially expressed proteins using Ingenuity Pathway Analysis. Relevant networks were constructed from the 139 sleep deprivation-modulated proteins using Ingenuity Pathway knowledge criteria. Five subnetworks emerged from the 89 increased and 50 decreased proteins (A). These five subnetworks were combined into three large networks, namely, long-term potentiation, neurotransmission, and degeneration of neuritis (B). Increased proteins are shown in red, and decreased proteins, in green.

and not the astrocytic processes. Thus, the astrocytic proteome would be enriched in the proteins present in the cell body. In addition, during the isolation procedures, vesicular proteins might have been depleted. The isolation of astrocytes through a

gradient was done under calcium- and magnesium-free conditions to minimize the release of glial proteins. However, the cell isolation process, gel digestion, and dynamic exclusion might have affected peptide quantification. When differentially I



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Figure 3. Sleep deprivation-induced astrogliosis in the hypothalamic region. After chronic partial sleep deprivation, animals were sacrificed, and brain sections were immunostained with anti-GFAP antibody. GFAP-positive hypertrophic astrocytes were detected in the VLPO, LH, and TMN regions of the hypothalamus after sleep deprivation (SD) or sleep deprivation and recovery (SD + R). Counterstaining was conducted using Cresyl violet. Scale bar = 100 μm. NSD, nonsleep deprivation; SD, sleep deprivation; SD + R, sleep deprivation followed by sleep recovery. Additional animals (n = 3 for each group) were used for the histological analyses. The results shown are one representative of three independent experiments.

function, neurological disease (score 15); network 5, cellular compromise, cell death and survival, neurological disease (score 13) (Table 2). These overlapping networks are closely related and can be combined into three large networks, that is, long-term potentiation, neurotransmission, and degeneration of neurites (Figure 2, Supporting Information Figure 7, and Supporting Information Table 3). Disease/disorder function-oriented IPA analysis revealed that the differentially expressed astrocytic proteins are associated with neurological disease (Supporting Information Table 4). We also performed pathway enrichment analysis using the online biological classification tool DAVID. A total of 12 KEGG pathways with p-values less than 0.05 were related to brain metabolism and dysfunction, suggesting relevance in neurological disease (Supporting Information Table 5). Therefore, we postulate that SD may increase susceptibility to neurological disease by altering astrocytic activity. To determine whether these functional networks were relevant to altered astrocyte activity, three different regions of the hypothalamus were examined by GFAP immunohistochemistry (Figure 3). In the VLPO, LH, and tuberomammillary nucleus (TMN), the number of reactive astrocytes was markedly increased by sleep deprivation and decreased by sleep recovery. Sleep recovery was given for 7 days by placing the animals in home cages after chronic sleep deprivation. These findings suggest that sleep deprivation may evoke astrocyte activation and alter their neuron−glia communication activities in the hypothalamus, which could be related to increased susceptibility to neurological disease. Because the hypothalamus is the pivotal region with respect to a variety of endocrine, autonomic, and behavioral functions, such as temperature regulation, control of food and water intake, fatigue, sleep, and circadian cycles,23,40 aberrant glial activation or neuron−glial communication in the hypothalamus may have pathological consequences.

expressed proteins were categorized based on biological processes using the DAVID bioinformatics tool, increased proteins were found to be mainly associated with the generation of precursor metabolites and energy (18.97%), regulation of neurotransmitter levels (12.07%), translational elongation (10.34%), regulation of hydrolase activity (10.34%), protein folding (8.62%), protein complex biogenesis (6.90%), regulation of defense response to virus by virus (5.17%), monosaccharide metabolic process (3.45%), carboxylic acid catabolic process (3.45%), cation transport (3.45%), response to inorganic substance (3.45%), regulation of cell size (3.45%), behavior (1.72%), ATP biosynthetic process (1.72%), cell−cell signaling (1.72%), ion transport (1.72%), and regulation of apoptosis (1.72%). On the other hand, decreased proteins were associated with nitrogen compound biosynthetic process (27.78%), differentiation (13.89%), oxygen transport (8.33%), cell−cell signaling (8.33%), protein heterooligomerization (5%), cell cycle process (5%), protein folding (5%), purine nucleotide metabolic process (3%), protein oligomerization (3%), protein complex assembly (3%), microtubule-based process (3%), apoptosis (3%), cell proliferation (3%), and phosphate metabolic process (3%) (Figure 1). Accordingly, sleep deprivation appears to influence both inter- and intracellular events associated with hypothalamic astrocytes. Pathway and Network Analyses of Differentially Expressed Proteins

Differentially expressed proteins were subjected to network analysis using IPA to identify relevant interaction networks. Five high-scoring molecular networks (based on p-values) emerged: network 1, cell-to-cell signaling and interaction, nervous system development and function, cell death and survival (score 25); network 2, cell-to-cell signaling and interaction, nervous system development and function, behavior (score 21); network 3, cellto-cell signaling and interaction, nervous system development and function, neurological disease (score 15); network 4, cell-tocell signaling and interaction, nervous system development and J



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Figure 4. Validation of the changes in the expression of representative proteins. Western blot analysis was performed to validate alterations in the selected protein levels as determined by LC−MS/MS analysis. After chronic partial sleep deprivation, total proteins were extracted from hypothalamic astrocytes and subjected to western blot analysis (A). NSD, nonsleep deprivation; SD, sleep deprivation. Densitometric analyses of the representative proteins were performed after normalization to β-actin levels. The results shown (blot) are the representative of the three experiments. Data in the graphs are mean ± SEM (n = 3). Additional animals (n = 3 for each group), separate from those used for the proteomic analyses, were used for western blot analysis. Significant differences are indicated as *p < 0.05. SD-induced protein changes as determined by 2D-LC−MS and western blotting were compared (B). Correlation analysis between the two sets of results produced an R2 value of 0.905 (C).

Validation of the Changes in Expression of Representative Proteins

SLC17A7 protein expression was increased by sleep deprivation in the hypothalamus but not in the cortex or cerebellum (Supporting Information Figure 8). These results indicate that LC−MS/MS data for several disease-related proteins are consistent with the individual validation results. Moreover, the characteristic changes shown by these proteins following sleep deprivation appear to be specific to the hypothalamus. Because the hypothalamus plays a central role in the homeostatic control of sleep, we investigated the proteome profile of hypothalamic astrocytes after sleep deprivation. Astrocyte-focused proteomic analysis results indicated that

Differentially expressed proteins with a high relevance in the context of gliotransmission and neurological disease from 2Dand 1D-LC−MS data were selected for validation by western blot analysis (Figure 4A,B). Western blot analysis of these hypothalamic astrocyte proteins revealed a linear correlation between western blot data and 2D-LC−MS/MS data without an appreciable qualitative change in the expression pattern (Figure 4C). We also measured the levels of one of the differentially expressed proteins in the hypothalamus and other brain areas. K



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Figure 5. Immunohistochemical detection of RTN4 in the hypothalamus. Immunofluorescence analysis of sleep-deprived animal brains (n = 3) revealed the increase of RTN4 (green) in the TMN after sleep deprivation and their partial colocalization (yellow) with GFAP-positive astrocytes (red). Nuclei were stained with DAPI (blue) (A). Scale bar = 100 μm. Results are one representative of three independent experiments. Fluorescence intensities of RTN4 staining were increased in the TMN after SD (B). Quantification of RTN4 fluorescence intensity was carried out by determining the percent colocalization of RTN4- and GFAP-positive astrocytes (C). Results are mean ± SEM (n = 3). *p < 0.05, NSD vs SD in the same TMN region.

astrocytic proteins of altered abundance after sleep deprivation are mainly associated with astrocytic activation, gliotransmission, and neurological disease. We focused on the astrocytic proteins that may influence neuronal functions. Under sleep-deprived conditions, these astrocytic proteins may be responsible for altered neuron−glia interaction, thereby modulating neuronal functions. It is hoped that current findings may shed light on the molecular and cellular mechanisms underlying physiological and pathological consequences of chronic sleep deprivation. Leucine-rich glioma inactivated-1 (LGI-1) is a metastasis suppressor in glioma cells and a regulator of synaptic transmission in neurons.41 Previous studies have demonstrated that in neurological disorders LGI-1 has crucial functions, which include the formation of anti-epileptogenic complex.42 For example, mutation of LGI-1 was found to be responsible for autosomal dominant lateral temporal lobe epilepsy,42c,43 and its deficiency was found to induce spontaneous seizure and hippocampal pathologies, including astrocyte hyperactivity.43a These previous reports led us to speculate that a reduction of LGI-1 protein may be implicated in glial proliferation and activation during sleep deprivation. RTN4 (also known as neurite outgrowth inhibitor; NogoA) was initially found to be an inhibitor of neurite outgrowth in the CNS.44 Although previously thought to be mainly expressed in oligodendrocytes or neuronal cells,45 we observed an increase of RTN4 in hypertrophic astrocytes of the TMN (Figure 5). Consistently, in a previous report, the transient expression of RTN4 was observed in reactive astrocytes in the hippocampus after a knife lesion and in nonreactive astrocytes of the cerebellum.46 This report demonstrates that RTN4 induces astrocyte activation and facilitates their participation in the constructions of cytoskeletal elements, adhesion molecules, and extracellular matrix proteins after a lesion. Therefore, the increased astrocytic RTN4 in sleep-deprived animals may be closely related with the adverse effects of sleep loss.

Our data indicate that the expression of PPP2R1A and VAMP2 was increased by sleep deprivation. While a decrease of PPP2R1A was previously associated with an increased phosphorylation of tau and impaired dephosphorylation of vimentin in an Alzheimer’s disease (AD) model,47 astrocytic enzyme activity of PPP2R1A was significantly increased in an AD model, implying that an increase of PPP2R1A in astrocytes may promote their migration and morphological change.48 Our proteomic analysis showed an association between sleep deprivation and the active molecular transport functions of astrocytes, such as endocytosis, exocytosis, ion transport, ATP synthesis and transport, and glutamate transport. In particular, the expression of SLC17A7 (vesicular glutamate transporter 1, VGLUT-1) and VAMP-2 was significantly increased in the hypothalamic astrocytes of sleep-deprived animals. The higher astrocytic expression of these proteins may be related to intracellular Ca2+ elevation in astrocytes and to the extracellular accumulation of glutamate and ATP. Recently, it was suggested that chronic sleep deprivation might be associated with synaptic potentiation via the increase of glutamate receptors, and this potentiation might also increase neuron susceptibility to neurotoxic insults.49 Prolonged high ATP consumption and the accumulation of adenosine may evoke hypothalamic dysfunctions, such as obesity,50 anorexia,29,51 impotence,52 reduced immunity,53 and impaired neurological performance and behavior.54 The data imply that SD may be associated with long-term impairment of neurological function.

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CONCLUDING REMARKS In our proteomic study, molecular categorization and functional network analysis suggest that alterations in the expression of hypothalamic astrocyte proteins caused by sleep deprivation may be related to the dysregulation of gliotransmission and lead to increased susceptibility to neurological disease. However, because sleep deprivation causes many issues related to brain L



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(2) Berger, R. J.; Phillips, N. H. Energy conservation and sleep. Behav. Brain Res. 1995, 69, 65−73. (3) Everson, C. A. Sustained sleep deprivation impairs host defense. Am. J. Physiol. 1993, 265, R1148−R1154. (4) Swift, E. J., Jr. The effect of sealants on dental caries: a review. J. Am. Dent. Assoc. 1988, 116, 700−704. (5) Dang-Vu, T. T.; Desseilles, M.; Peigneux, P.; Maquet, P. A role for sleep in brain plasticity. Pediatr. Rehabil. 2006, 9, 98−118. (6) Alhola, P.; Polo-Kantola, P. Sleep deprivation: Impact on cognitive performance. Neuropsychiatr. Dis. Treat. 2007, 3, 553−567. (7) Belenky, G.; Wesensten, N. J.; Thorne, D. R.; Thomas, M. L.; Sing, H. C.; Redmond, D. P.; Russo, M. B.; Balkin, T. J. Patterns of performance degradation and restoration during sleep restriction and subsequent recovery: a sleep dose-response study. J. Sleep Res. 2003, 12, 1−12. (8) Lo, J. C.; Groeger, J. A.; Santhi, N.; Arbon, E. L.; Lazar, A. S.; Hasan, S.; von Schantz, M.; Archer, S. N.; Dijk, D. J. Effects of partial and acute total sleep deprivation on performance across cognitive domains, individuals and circadian phase. PLoS One 2012, 7, e45987. (9) Spiegel, K.; Tasali, E.; Penev, P.; Van Cauter, E. Sleep curtailment in healthy young men is associated with decreased leptin levels, elevated ghrelin levels, and increased hunger and appetite. Ann. Int. Med. 2004, 141, 846−850. (10) Gottlieb, D. J.; Punjabi, N. M.; Newman, A. B.; Resnick, H. E.; Redline, S.; Baldwin, C. M.; Nieto, F. J. Association of sleep time with diabetes mellitus and impaired glucose tolerance. Arch. Int. Med. 2005, 165, 863−867. (11) Liu, Y.; Tanaka, H. Overtime work, insufficient sleep, and risk of non-fatal acute myocardial infarction in Japanese men. Occup. Environ. Med. 2002, 59, 447−551. (12) Strine, T. W.; Chapman, D. P. Associations of frequent sleep insufficiency with health-related quality of life and health behaviors. Sleep Med. 2005, 6, 23−27. (13) Baldwin, D. C., Jr.; Daugherty, S. R. Sleep deprivation and fatigue in residency training: results of a national survey of first- and second-year residents. Sleep 2004, 27, 217−223. (14) Pilcher, J. J.; Huffcutt, A. I. Effects of sleep deprivation on performance: a meta-analysis. Sleep 1996, 19, 318−326. (15) Patel, S. R.; Ayas, N. T.; Malhotra, M. R.; White, D. P.; Schernhammer, E. S.; Speizer, F. E.; Stampfer, M. J.; Hu, F. B. A prospective study of sleep duration and mortality risk in women. Sleep 2004, 27, 440−444. (16) Gallopin, T.; Luppi, P. H.; Cauli, B.; Urade, Y.; Rossier, J.; Hayaishi, O.; Lambolez, B.; Fort, P. The endogenous somnogen adenosine excites a subset of sleep-promoting neurons via A2A receptors in the ventrolateral preoptic nucleus. Neuroscience 2005, 134, 1377−1390. (17) Lee, M. G.; Hassani, O. K.; Jones, B. E. Discharge of identified orexin/hypocretin neurons across the sleep−waking cycle. J. Neurosci. 2005, 25, 6716−6720. (18) Huang, Z. L.; Urade, Y.; Hayaishi, O. The role of adenosine in the regulation of sleep. Curr. Top. Med. Chem. 2011, 11, 1047−1057. (19) (a) Nadjar, A.; Blutstein, T.; Aubert, A.; Laye, S.; Haydon, P. G. Astrocyte-derived adenosine modulates increased sleep pressure during inflammatory response. Glia 2013, 61, 724−731. (b) Blutstein, T.; Haydon, P. G. The importance of astrocyte-derived purines in the modulation of sleep. Glia 2013, 61, 129−139. (c) Halassa, M. M.; Florian, C.; Fellin, T.; Munoz, J. R.; Lee, S. Y.; Abel, T.; Haydon, P. G.; Frank, M. G. Astrocytic modulation of sleep homeostasis and cognitive consequences of sleep loss. Neuron 2009, 61, 213−219. (d) Scammell, T. E.; Gerashchenko, D. Y.; Mochizuki, T.; McCarthy, M. T.; Estabrooke, I. V.; Sears, C. A.; Saper, C. B.; Urade, Y.; Hayaishi, O. An adenosine A2a agonist increases sleep and induces Fos in ventrolateral preoptic neurons. Neuroscience 2001, 107, 653−663. (20) Simard, M.; Nedergaard, M. The neurobiology of glia in the context of water and ion homeostasis. Neuroscience 2004, 129, 877−896. (21) Brown, A. M.; Ransom, B. R. Astrocyte glycogen and brain energy metabolism. Glia 2007, 55, 1263−1271.

energetics/metabolism, which may be reflected in every cell in the body, further studies are necessary to better understand the effects of sleep deprivation on brain astrocytes. Nevertheless, we believe that the present study enhances the understanding of the role played by astrocytes in the physiological and pathological consequences associated with sleep deprivation.

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ASSOCIATED CONTENT

S Supporting Information *

1D-LC−ESI−MS/MS analysis method; Figure S1: experimental design; Figure S2: determination of astrocyte purity after Percoll gradient isolation; Figure S3: annotated MS/MS spectrum of single quantified peptides in the quantitative comparison of the NSD and SD group; Figure S4: effects of sleep deprivation on body weights and water/food intake; Figure S5: performance of LC analysis; Figure S6: comparison of subcellular localizations and molecular functions of the differentially expressed proteins following SD based on 2D- and 1D−LC−MS; Figure S7: functional networks of differentially expressed proteins after sleep deprivation; Figure S8: 2D-LC−MS data validation in different regions of brain; Table S1: detailed identification information on all peptides and proteins based on triplicate runs of 2D- and 1D-LC−MS samples; Table S2: fold changes of differentially expressed proteins common in 2D- and 1D-LC− MS results; Table S3: biological function and disease analysis of each network by Ingenuity Pathway Analysis (IPA); Table S4: biological function and disease analysis of the five subnetworks by Ingenuity Pathway Analysis (IPA); and Table S5: enriched KEGG pathways of differently expressed proteins after sleep deprivation. This material is available free of charge via the Internet at http://pubs.acs.org.

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AUTHOR INFORMATION

Corresponding Author

*Tel.: +82-53-420-4835. Fax: +82-53-256-1566. E-mail: ksuk@ knu.ac.kr. Author Contributions ⊥

These authors contributed equally to this work.

Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS This work was supported by a National Research Foundation of Korea (NRF) grant funded by the Korean government (MSIP) (grant nos. 2008-0062282 and 2012R1A2A2A02046812).

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ABBREVIATIONS SD, sleep deprivation; NSD, nonsleep deprivation; LC−ESI− MS/MS, liquid chromatography−electrospray ionization/multistage mass spectrometry; IPA, ingenuity pathways analysis; DAVID, database for annotation, visualization and integrated discovery; VLPO, ventrolateral preoptic nucleus; LH, lateral hypothalamic area; TMN, tuberomammillary nucleus; REM, rapid eye movement; FACS, fluorescence activated cell sorting; BCA, bicinchoninic acid; TFA, trifluoroacetic acid; ACN, acetonitrile

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REFERENCES

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