The Alteration of ZiBuPiYin Recipe on Proteomic Profiling of Forebrain Postsynaptic Density of db/db Mice with Diabetes-Associated Cognitive Decline

Abstract

Diabetes-associated cognitive decline (DACD) is a brain injury induced by diabetes mellitus, with cognitive impairment as the major symptom. Growing evidence has revealed that DACD is correlated with disruptions in synapses involved in cognition. Within synapses, more specifically in areas of postsynaptic density (PSD), there is a high concentration of proteins that receive and transduce synaptic information. In the present study, to identify the differentially expressed PSD proteins among DACD mice, ZiBuPiYin recipe (ZBPYR)-treated DACD mice and control mice, we applied isobaric tags for relative and absolute quantitation (iTRAQ) with LC-MS/MS technology, by which three biological replicates and three technical replicates were examined. A total of 24 and 23 differentially expressed proteins were observed in control versus DACD mice and in DACD versus ZBPYR-treated DACD mice, respectively. Notably, we found ‘Protein processing in endoplasmic reticulum’ and ‘PI3K-Akt signaling pathway’ might be impaired in DACD pathogenesis, while Growth factor receptor-bound protein 2 might be a crucial protein as a molecular target of the neuroprotective effects of ZBPYR. To our knowledge, this is the first study to provide a reference proteome map for DACD and ZBPYR-treated DACD mouse forebrain PSD to aid understanding the underlying mechanisms of DACD and ZBPYR.

Keywords

Cognitive impairments diabetes-related complications post-synaptic density proteome traditional Chinese medicine

INTRODUCTION

Epidemiological studies have reported that the global prevalence of diabetes mellitus (DM) among adults is expected to rise from 285 million persons in 2010 to an estimated 439 million in 2030 [1]. In addition to its well-known adverse effects on the peripheral nervous systems, DM also appears to negatively impact brain, increasing the risk of cognitive impairment and even dementia [2]. A growing body of studies has confirmed that both DM patients [3, 4] and DM rodent models [5, 6] exhibit impaired cognitive function compared to age-matched non-diabetic subjects or animals. This cognitive decline induced by DM is now named diabetes-associated cognitive decline (DACD), which manifests as a gradual decline of cognitivefunction [7].

Though the mechanisms responsible for DACD have not been established, several studies, including our previous study had demonstrated that DM rodent models exhibited reduced dendritic spine density [8 –10], besides impaired cognitive function. In the excitatory synapses of brain, the majority of dendritic spines encapsulate large electron-dense structures known as postsynaptic density (PSD) [11, 12]. It contains neurotransmitter receptors, scaffold proteins, cytoskeleton components, and other regulatory elements that receive and transduce synaptic information. Since PSD plays a cardinal role in synaptic regulation during learning and memory processes, a comprehensive knowledge of the protein composition of PSD will be extremely useful for understanding the mechanisms of cognitive dysfunction diseases. Continuing proteomic studies have revealed the protein components of PSD from rats [13 –17], mice [17 –21], and humans [22 –24], with numerous proteins being identified. A few studies also have examined the changes of PSD proteins in different diseases and following drug administration [25, 26]. However, there is few proteomic study of PSD in DACD, which should be important for understanding the pathogenesis of this disease.

Moreover, there is no generally accepted effective treatment for cognitive dysfunction disease currently. In addition to treat the primary disease, the main therapeutic measures are based on evidence-based medicine, mainly application of drugs that improving cognitive function, supplemented with drugs that controlling psychotic symptoms. Unfortunately, these drugs have many problems, e.g., single therapeutic targets, toxic or side effects, expensive, etc., leading to limited clinical application. Thus, exploring some effective therapies of cognitive dysfunction is very urgent. Traditional Chinese medicines are attracting increasing attention around the world because of their long historical clinical experience and reliable therapeutic efficacy for treating various diseases. The ZiBuPiYin recipe (ZBPYR) is a modification of an ancient formula used for clinical treatment of memory loss during the Qing dynasty, which was named the Zicheng Decoction recorded in the book of Bujuji written by Cheng Wu. Previous studies in our lab have demonstrated that ZBPYR can improve cognitive function in animal models of aging [27], in a rat model of intrahippocampal injection of amyloid-β peptide 1-40 [28], and in a model of DACD [29].

Therefore, in this work, we decided to explore the molecular mechanisms linking PSD proteins alteration to DACD, and whether ZBPYR improves cognitive function by affecting PSD proteins. We isolated PSD complexes from forebrains of control, DACD, and ZBPYR-treated DACD mice, and applied the multiplexed chemical labeling reagent, isobaric tags for relative and absolute quantification (iTRAQ), with LC-MS/MS analysis to examine the changes in expression levels of PSD proteins. A total of 24 proteins were differentially expressed in the comparison of control versus DACD mice. A total of 23 differentially expressed proteins were found in the comparison of DACD versus ZBPYR-treated DACD mice. Then, further Gene ontology (GO) annotations and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis of the above differentially expressed proteins were performed to explore the relationships between PSD proteins, DACD, and ZBPYR treatment. Interestingly, this iTRAQ study suggested that some potentially physiological processes involved in the pathogenesis of DACD, including ‘Protein processing in endoplasmic reticulum’, ‘Lysosome’, and ‘PI3K-Akt signaling pathway’. Besides, a noteworthy protein, Growth factor receptor-bound protein 2 (Grb2) may be both related to the development of DACD and a molecular target of the neuroprotective effects ofZBPYR.

MATERIALS AND METHODS

Ethics statement

This study has been approved by the Ethics Committee of Animal Experiments of Dalian Medical University (Permit Number: SCXK (Jun) 2007–0004). All animal experiments were conducted in accordance with the NIH Principles of Laboratory Animal Care and the institutional guidelines for the care and use of laboratory animals at Dalian Medical University.

Animals

6- to 8-week-old male C57BLKS/J-db/db mice and their age-matched non-diabetic littermate db/m mice were purchased from Nanjing Qingzilan Technology Co., Ltd. (Nanjing, Jiangsu Province, China) and housed in the specific pathogen-free animal experiment center of Dalian Medical University at 24°C ± 2°C with 65% ± 5% humidity on a 12-h light/dark cycle and were allowed to acclimatize to their environment for 1 week prior to drug administration. All db/db mice were randomly divided into two groups: diabetes group (db/db, n = 3) and diabetic mice treated with ZBPYR group (db/db/ZBPYR, n = 3). Additionally, db/m mice were used as control group (db/m, n = 3). During the whole test period, experimenters recorded body weight, food intake, and water intake daily for evaluating the health of the animals.

ZBPYR

ZBPYR was composed of 12 crude herbs: Red Ginseng (Radix Ginseng Rubra), Common Yam Rhizome (Rhizoma Dioscoreae Oppositae), Indian Buead (poria), White Peony Root (Radix Paeoniae Alba), Dan shen Root (Radix Salviae Miltiorrhizae), White Hyacinth Bean (Semen Lablab Album), Lotus Seed (Semen Nelumbinis), Grassleaf Sweetflag Rhizome (Rhizoma Acori Tatarinowii), Thinleaf Milkwort Root (Radix Palygalae), Sandalwood (Lignum Santali Albi), Tangerine Red Epicarp (Exocarpium Citri Rubrum), and Liquorice Root (Radix Glycyrrhizae).

We had done some works about the effective fractions, chemical components, and quality control of the ZBPYR in previous studies. In terms of the effective fractions, in combination with the results of polysaccharide content determination and GC-MS analysis, the active fractions of ZBPYR were presumed to be polysaccharide and volatile oil [30]. In terms of the chemical components, using ultra high performance liquid chromatography coupled with electrospray ionization quadrupole time-of-flight mass spectrometry, 155 chemical components in ZBPYR were tentatively identified. The major components were identified from Red Ginseng, Dan shen Root, White Paeony Root, liquorice root, Radix Polygalae, Tangerine Red Epicarp, Grassleaf Sweetflag Rhizome, Indian Buead, and lotus seed [31]. Moreover, fingerprint analysis and qualitative analysis were applied to ensure the quality control of the ZBPYR. HPLC fingerprint consisting of 34 common peaks was developed among 10 batches of ZBPYR, in which 7 common peaks were identified in comparison with the authentic standards and detected simultaneously. Furthermore, these seven compounds were verified by HPLC-Q-TOF-MS methods [32]. As the components of the ZBPYR are very complicated, further research is still required to precisely define the basis of this novel drug development.

Preparation and administration of ZBPYR

All 12 crude herbs were purchased from Dalian Metro Pharmaceutical Co., Ltd. (Dalian, Liaoning Province, China). The preparation and administration of ZBPYR was identical to the previous study [10]: The mixtures were soaked in 8 volumes (v/w) of distilled water for 30 min and then boiled for 90 min. The decoction was then concentrated to a final density of 3.29 g/ml and stored at 4°C. During a period of 6 weeks, ZBPYR or ultrapure water (Milli-Q Integral Water Purification System, Millipore Corporation, Billerica, MA, USA) were administered to the animals via gavage at a dose of 0.1 ml/10 g bodyweight.

Morris water maze test

The Morris water maze test was setup and operated as our previous study [10]: The test was undertaken in a circular pool (diameter 100 cm, height 50 cm, Institute of Materia Medica, Chinese Academy of Medical Sciences, Beijing, China), filled with water made opaque with milk power and maintained at 26°C ± 1°C. The experiment was performed daily for 6 days. On the 1st day, mice were permitted to swim freely in the pool for 120 s without the platform (diameter 9 cm, height 29 cm) to adapt to the new conditions. Over the following 4 days, mice underwent 4 trials per day at intervals of 60 s. On these occasions, the platform location was submerged 1 cm below the water surface and was fixed, while the starting points were changed. Each trial lasted until the animal found the platform or for a maximum observation period of 120 s. Animals that failed to find the platform within the maximum observation period were guided to the platform by the observer. On the day after the last acquisition training session, animals were tested in a single 120 s probe test without the platform. During this period, three parameters were recorded via an automatic photographic recording and analysis system (EthoVision, Noldus Information Technology b.v., Wageningen, The Netherlands): (1) the time to reach the platform (escape latency), (2) the swimming time in the target quadrant where the platform had been located during training, and (3) the number of times the animal crossed the site from which the original platform had been removed. On the 6th day, a visible-platform test was undertaken, where the platform was located 1 cm over the water surface and placed at a position different from the previous test. During this test, the experimental procedures were exactly the same as previous tests, and the escape latency and swimming distance wererecorded.

Preparation of PSD from mouse forebrain

For preparation of PSD, the animals were anesthetized with sodium pentobarbital via intraperitoneal injection and decapitated. The PSD fraction was isolated from mice forebrains at 4°C essentially as described previously [13]: The brain structures were homogenized in ice-cold Buffer A (5 mM HEPES (pH 7.4), 1 mM MgCl₂, 0.5 mM CaCl₂, phosphatase inhibitors (1 m M NaF and 1 mM β-glycerophosphate), and protease inhibitors (Sigma) with a Teflon homogenizer (12 strokes). The resulting extract was centrifuged at low speed (1,400×g for 10 min) to collect the first supernatant (S1). The pellet (P1) was re-extracted with the homogenizer (five strokes) and centrifuged at 700×g for 10 min. The supernatant (S1’) was pooled with S1 followed by high speed centrifugation at 13,800×g for 10 min. The supernatant (S2) was removed, and the pellet (P2) was resuspended in Buffer B (0.32 M sucrose and 6 mM Tris (pH 8.0) with the same inhibitors of phosphatase and proteases) by a Teflon homogenizer (five strokes), loaded onto a discontinuous sucrose gradient (0.85/1/1.2 M in 6 mM Tris (pH 8.0)), and centrifuged at 82,500×g for 2 h. The synaptosome fraction (SynT) between 1 M and 1.2 M sucrose was collected and resuspended in Buffer B. An equal volume of Buffer C (6 mM Tris (pH 8.1) and 1% Triton X-100) was added, mixed for 15 min, and centrifuged at 32,800×g for 20 min. The resulting pellet (PSDI) was extracted again with Buffer D (6 mM Tris (pH 8.1) and 0.5% Triton X-100) for 15 min and centrifuged again at 201,800×g for 1 h to obtain a pellet (PSDII) for proteomic analysis. PSD proteins were dissolved in 50 mM Tris (pH 8.5) with 1.0% SDS at 95°C for 5 min and stored at –80°C until required. The protein concentration was determined by BCA protein assay.

Digestion of PSD samples and iTRAQ labeling

100μg of each sample was digested in parallel via a method, filter-aided sample preparation (FASP). The critical steps of the FASP method are: Each sample was loaded on an ultrafiltration filter (30 kDa cutoff, Sartorius, German), 200μl UA buffer (8 M Urea and 150 mM Tris-HCl pH 8.0) were added to the filter and centrifuged at 14000×g for 15 min, and washed again with UA buffer. Subsequently, 100μl iodoacetamide solution (50 mM iodoacetamide in UA buffer) were added to the filter. The filter unit was mixed for 1 min, followed by incubation for 30 min at room temperature in the dark and centrifuged at 14000×g for 10 min. Two wash steps with 100μl UA buffer were performed with centrifugation at 14000×g for 10 min after each wash step. Then, 100μl dissolution buffer (Applied Biosystems, Foster City, CA) was added to the filter and centrifuged at 14000×g for 10 min, and this step was repeated twice. Finally, 40μl of trypsin (Promega, Madison, WI) buffer (2μg trypsin in 40μl dissolution buffer) were added and digested at 37°C for 16–18 h. The filter unit was transferred to a new tube and centrifuged at 14000×g for 10 min. Resulting peptides were collected as a filtrate and the peptide concentration was analyzed at OD280 [33].

Subsequently, 20μg of peptides per sample was labeled with iTRAQ reagents according to the manufacturer’s instructions (iTRAQ Reagent-4plex Multiplex Kit, Applied Biosystems SCIEX, Foster City, CA). The PSD samples from db/m were labeled with reagent 114, the PSD samples from db/db were labeled with reagent 115, the PSD samples from db/db/ZBPYR were labeled with reagent 116, the REF were labeled with reagent 117. The labeling solution reaction was incubated at room temperature for 1 h prior to further analysis. Then, three independent biological experiments were performed for triplicate LC-MS/MS analyses.

EASY-nLC separation

The column was equilibrated for 20 min with 95% (v/v) solvent A (0.1% (v/v) formic acid in Milli-Q water). Peptide mixtures were first flushed into a sample column, the Thermo scientific EASY-nLC column (2 cm×100 μm 5μm-C18), then separated with a analytical column, the Thermo scientific EASY-nLC column (75 μm×100 mm 3 μm-C18) at 250 nl/min with solvent B (acetonitrile with 0.1% (v/v) formic acid, acetonitrile 84%) using a segmented gradient from 0-35% (v/v) in 100 min, from 35-100% (v/v) in 8 min and then at 100% (v/v) for 12 min.

MS/MS analysis and quantification

The Q-Exactive (Thermo Finnigan, San Jose, CA) mass spectrometer was set to perform data acquisition in the positive ion mode, with a selected mass range of 300-1800 mass/charge (m/z). Resolving power for the Q-Exactive was set as 70000 for the MS scan and 17500 for the MS/MS scan at m/z 200. MS/MS data were acquired using the top 10 most abundant precursor ions with charge≥2 as determined from the MS scan. These were selected with an isolation window of 2 m/z and fragmented by higher energy collisional dissociation with normalized collision energies of 30 eV. The maximum ion injection times for the survey scan and the MS/MS scans were 10 and 60 ms, respectively, and the automatic gain control target values for both scan modes were set to 3e6. Dynamic exclusion for selected precursor ions was set at 40 s. Underfill ratio was defined as 0.1% on the Q-Exactive.

Raw files were processed using Mascot 2.2 and Proteome Discoverer 1.3 (Thermo). The Raw files were searched using the MASCOT engine (Matrix Science, London, UK; version 2.2) embedded into Proteome Discoverer 1.3, against Uniprot Mouse database (03-18-2013, 73952 entries). The following search parameters were set: monoisotopic mass values, fragment mass tolerance at 0.1 Da and peptide mass tolerance±20 ppm, trypsin as the enzyme and allowing up to 2 missed cleavages. Fixed modifications were defined as iTRAQ labeling and carbamidomethylation of cysteine; oxidation of methionine was specified as a variable modification. The decoy database pattern was set as reversed version of the target database. All reported data were based on 99% confidence for proteins and peptides identification as determined by false discovery rate (FDR) of no more than 1%. Protein identification was supported by at least one unique peptide identification.

The iTRAQ analysis of relative protein quantification levels across multiple samples follows. Proteome Discoverer 1.3 was used to calculate relative ratios of identified peptides among labeled samples using relative peak intensities of released iTRAQ reporter ions in each of the MS/MS spectra, while relative protein quantification among samples was based on weighted ratios of uniquely identified peptides which belonged to the specific individual protein in which sample REF was used as reference. Final ratios of protein quantification were then normalized by the median average protein quantification ratio for unequally mixed different labeled samples. This correction is based on the assumption that the expression of most proteins does not change. Thus, if samples from each experimental condition are not combined in exactly equal amounts, this normalization fixes the systematic error. Only protein identification that was inferred from the unique peptide identification in all three independent experiments was considered.

GO annotation and KEGG pathway analysis

The sequence data of the differentially expressed proteins were in batches retrieved from UniProt KB database (Release 2013_10) in FASTA format. The retrieved sequences were locally searched against SwissProt database (mouse) using the NCBI BLAST + client software (ncbi-blast-2.2.28+-win32.exe) to find homologue sequences from which the functional annotation can be transferred to the studied sequences. In this work, the top 10 blast hits with E-value less than 1e-3 for each query sequence were retrieved and loaded (Version 2.6.6) for GO mapping and annotation.

Following GO annotation, the studied proteins were blasted against KEGG GENES (mouse and rat) to retrieve their KOs and were subsequently mapped to pathways in KEGG.

Western blotting

To verify iTRAQ data, protein (20μg per PSD sample) was loaded per lane and separated on 10–15% Tris-glycine polyacrylamide gels. Electrophoresis, followed by transfer to nitrocellulose membranes and immunodetection, was performed. Nonspecific antibody binding was blocked using 5% nonfat milk for 1 h at room temperature. Immunoblot was carried out with antibodies against Casein kinase II subunit alpha (CKIIα (#ab76040, Abcam plc, Cambridge, UK) ephexin 1(#ab157593, Abcam plc, Cambridge, UK), Leukotriene A-4 hydrolase (LTA₄ H) (#ab133512, Abcam plc, Cambridge, UK), Growth factor receptor-bound protein 2 (Grb2) (#ab32111, Abcam plc, Cambridge, UK), PSD95 (#3409, Cell Signaling Technologies, Danvers, MA, USA), NMDA receptor subunit 1 (NR1, Cell Signaling Technologies, Danvers, MA, USA) and synaptophysin (Cell Signaling Technologies, Danvers, MA, USA), followed by secondary antibody (HRP conjugated anti-rabbit IgG, GE Healthcare, Buckinghamshire, UK). Blots were developed with 1 : 1 solution of Enhanced Chemiluminescence (ECL).

Statistical analysis

Statistical analysis was performed using either an ANOVA (equal variance) or a Welch’s ANOVA (unequal variance) test. Data from the Morris water maze test was analyzed using a repeated-measures analysis of variance for comparisons among trials, while an unpaired Student’s t test was used for comparisons among different groups in a given block and for the comparison of other results. The difference was considered to be statistically significant when p≤0.05.

RESULTS

Spatial learning and memory performance of db/db mice and the effect of ZBPYR

In the present study, we used db/db mice as type 2 diabetes mellitus (T2DM) animal models. It has been reported that db/db mice exhibit not only obesity, hyperglycemia, and hyperinsulinemia, but also have impaired spatial cognitive performance [5, 10]. To measure the learning and memory abilities of db/db mice in present study and the effect of ZBPYR administration, we performed the Morris water maze test.

Compared with db/m mice, db/db mice had significantly longer escape latencies on the 3rd, 4th, and 5th days in the training trials. Then, the escape latencies of db/db/ZBPRY mice were shorter than that of db/db mice on the 4th and 5th days in the training trials (Fig. 1A). As shown in Fig. 1B, in the probe test, db/db mice had difficulty in finding the original platform position when compared with db/m mice, and db/db/ZBPRY mice spent less time in locating the original platform position than db/db mice. For the swimming time in the target quadrant where the platform had been located during training tests, the duration of db/db mice were significantly shorter than those of db/m mice, but db/db/ZBPYR mice spent much more time in the target quadrant than db/db mice (Fig. 1C). The number of times the db/db mice crossed the original platform location was much fewer than that of db/m mice, and was increased in db/db/ZBPYR mice, although there was a significant difference between db/m and db/db/ZBPYR mice (Fig. 1D). In the visible platform version of the Morris water maze test, which is not hippocampus-dependent, there was no significant difference among the groups in terms of escape latency and swimming distance (Fig. 1E, F).

These above data suggested that in the present study, the untreated T2DM db/db mice had relatively poor spatial cognitive ability, indicating that they developed DACD. After 6 weeks of ZBPYR administration, the spatial learning and memory performance of db/db/ZBPYR mice was improved.

Protein distribution and purification of PSD samples

In order to observe the distribution of the PSD protein from different animal forebrains, the proteins (20μg per PSD sample) were separated by SDS-PAGE on 12.5% Criterion gels. Electrophoresis conditions: constant current 14 mA, electrophoresis time 90 min. After electrophoresis the proteins were visualized by Coomassie blue staining (Fig. 2A). Although there were some subtle differences in band intensities, the overall pattern of major bands looked highly similar among the PSDs from different animals, and was likely the same as that identified by others [13, 17].

The purification of PSD was evaluated by observing the levels of some selected proteins in the PSD fraction as compared to the parent fractions. Equal amounts of P2, synaptosome (synT), and PSD fractions were run on SDS gels, electroblotted onto nitrocellulose membranes, and immunostained with antibodies against PSD95, NR1, and synaptophysin (SynPhy), respectively. PSD95 is a major scaffolding protein in the PSD fraction and is considered to be a PSD marker, which was enriched in the pellet P2 and synT, and significantly more in the PSD fraction. NR1 is an excitatory glutamate receptor and is a well-established PSD protein in the PSD fraction, so it was enriched in all three fractions. As expected, SynPhy, a component of synaptic vesicles, was enriched in the P2 and synT fractions, but was reduced drastically in the PSD fraction, indicating effective elimination of some presynaptic components (Fig. 2B).

Three independent iTRAQ experiments were performed as shown in Fig. 2C, and every experiment with three biological replicates to gather reliable quantitative information. To identify and compare the relative amounts of proteins in the PSD fractions, we prepared a pooled sample, which was made of identical quality protein mixtures from different groups and served as a REF sample. The PSD preparation of each group was digested with trypsin, and the resulting peptides were labeled with one of the four versions of the stable isotope iTRAQ reagent to allow for comparison of relative abundance levels.

Protein identification of mice forebrain PSDs

From the three iTRAQ experiments, a total of 23,060 unique peptides with 99% confidence matching 3154 proteins (≥1 peptide) were identified in the forebrain PSD fractions from db/m, db/db, and db/db/ZBPYR groups. In fact, about 40.9% of the total identified proteins were obtained by single peptide. For more reliable unique protein identification, we used the criteria as follow: (1) proteins must be observed in all three biological replicates, (2) proteins must contain at least two unique peptides, (3) manually remove the proteins like keratins or fibrinogens (common MS/MS contaminants) or tRNA ligases. Finally, a total of 1,863 unique proteins were identified in the three iTRAQ experiments from all three biological replicates (Supplementary Table 1).

GO is now widely used to describe the function of genes and gene products in a standardized format [34]. In order to better understand the identified proteins, GO annotation was performed. The identified proteins were categorized according to GO functional annotation, including cellular components, molecular functions, and biological processes. The distribution of these identified proteins is shown in Fig. 3A, and their functions and processes are shown in Fig. 3B and C. The most prevalent cellular components were located in the cytoplasm (26.36%) and membrane (20.17%). The most common molecular function was protein binding (26.40%), and another major functional category was catalytic activity (22.24%). The most frequently encountered biological processes were metabolic process (20.07%), regulation of biological process (13.13%), response to stimulus (10.75%), and transport (10.30%).

Identification of differentially expressed PSD proteins

To reveal the proteins that were significantly differentially expressed, we applied stringent criteria as follow: (1) proteins must be observed in all three biological replicates, (2) proteins must contain at least two unique peptides, (3) a fold change of > 1.20 or < 0.83 would be the meaningful cutoff representing significant differences, (4) statistical analysis was conducted between two groups, and the relative quantification p-values must be below 0.05, (5) FDR was calculated as implemented to assess whether differences had occurred by chance or could be deemed significant [35], and changes in protein expression are considered to be significant when the FDR is <0.05.

According to the above criteria, in the comparison of db/m and db/db mice, we observed 24 proteins that showed significant differences, of which the expression of 9 proteins increased and 15 decreased (Table 1). We also compared the changes in relative protein abundance of the PSDs following chronic treatment with ZBPYR. 23 proteins were found to have significant changes with 10 proteins upregulated and 13 proteins downregulated (Table 2).

Eight proteins were significantly altered by both DACD presence and ZBPYR treatment (Table 3). Among the eight proteins, the expression of four proteins increased in db/db mice when compared to db/m mice: CKIIα, ephexin 1, SCY1-like protein 2, and protein FAM210A. After ZBPYR treatment, the levels of the above four proteins were downregulated. The expression of four remaining proteins decreased in db/db mice when compared to db/m mice: LTA₄ H, ATP-binding cassette sub-family B member 9, NADH dehydrogenase (ubiquinone) complex I assembly factor 6, and Grb2. All these four proteins were upregulated upon ZBPYR treatment.

Bioinformatics analysis of the differentially expressed proteins

To further understand the functions of the differentially expressed proteins identified in db/m versus db/db mice and in db/db versus ZBPYR-treated db/db mice, we respectively assigned GO categories and KEGG pathways for the differentially expressed proteins.

In the comparison of db/m and db/db mice, cellular component of GO analysis revealed that the highest proportion of differentially expressed proteins was located in the cell part. Proteins located in the protein complex and the membrane-bounded organelle were the next two largest groups (Fig. 4A). Analysis based on the molecular functions of GO analysis revealed that the majority of the differentially expressed PSD proteins in db/m versus db/db mice were associated with two major functions, one is binding, including protein binding, ion binding, organic cyclic compound binding, and heterocyclic compound binding, another is catalyst activity, including transferase activity, hydrolase activity, and transmembrane transporter activity (Fig. 4B). In addition, the biological process of GO analysis revealed that the differentially expressed PSD proteins in db/m versus db/db mice mainly involved in cellular process, single-organism process, biological regulation, metabolic process, and response to stimulus (Fig. 4C).

To investigate the effect of ZBPYR on the PSD molecular progress of DACD, we also analyzed the differentially expressed PSD proteins in db/db versus db/db/ZBPYR mice by GO categories. And they showed similar results with the differentially expressed PSD proteins in db/m versus db/db mice regard to cellular components, biological processes, and molecular functions (Fig. 4).

KEGG is a knowledge base for systematic analysis of gene functions, linking genomic information with higher order functional information that is stored in the PATHWAY database [36]. A complete KEGG analysis of the differentially expressed proteins identified in db/m versus db/db mice and in db/db versus db/db/ZBPYR mice, with their assigned proteins and the number of proteins identified in each pathway, was respectively provided in Supplementary Tables 2 and 3. Highlights from the two tables are presented in Table 4, showing the list of KEGG pathways with at least two differentially expressed proteins.

24 differentially expressed proteins identified in db/m versus db/db mice were mainly involved in three KEGG pathways, including ‘Protein processing in endoplasmic reticulum’, ‘Lysosome’, and ‘PI3K-Akt signaling pathway’. Moreover, among these three pathways, the differentially expressed proteins involved in ‘Protein processing in endoplasmic reticulum’ and ‘PI3K-Akt signaling pathway’ were decreased in abundance in db/db mice. This finding suggested that ‘Protein processing in endoplasmic reticulum’ and ‘PI3K-Akt signaling pathway’ might be impaired in DACD pathogenesis.

23 differentially expressed proteins identified in db/db versus db/db/ZBPYR mice were mainly involved in four KEGG pathways: ‘Arachidonic acid metabolism’, ‘MAPK signaling pathway’, ‘Ras signaling pathway’, and ‘Proteoglycans in cancer’. Interestingly, the KEGG pathway analysis showed that a particular difference exists between db/m versus db/db mice and db/db versus db/db/ZBPYR mice. We thought this difference likely due to the great amount and complexity of the molecular functions of differentially expressed proteins.

Validation of selected differentially expressed protein by western blotting

To verify the quantitative results of the iTRAQ-LC/MS/MS experiments, western blotting experiments were performed on four selected differentially expressed proteins: CKIIα ephexin 1, LTA₄ H, and Grb2, with the same nine PSD fraction samples (n = 3/each group). We found significantly increased levels of CKIIα and ephexin 1 in the PSD fractions of db/db as compared with those of db/m (Fig. 5A, B), and significantly decreased levels in the PSD fractions of db/db/ZBPYR. Moreover, we observed that LTA₄ H and Grb2 expression was decreased sharply in db/db when compared to db/m, and that ZBPYR treatment enhanced the proteins’ expression (Fig. 5C, D). As β-actin levels showed no changes among the groups, consistent with the iTRAQ-based LC-MS/MS analysis data, it was used as a loading control.

DISCUSSION

Abundant evidence indicates that DM is a significant risk factor of cognitive dysfunctions [2 , 38], and DACD is therefore attracting increasing attention, but its pathogenesis is still unclear. In this study, we adopted proteomic analysis on forebrain PSD samples to identify protein expression differences in animals with DACD and also assessed the effects of ZBPYR on DACD. We used db/db mice, a model of spontaneous T2DM [39], asexperimental animals, since our previous research [10] and other studies [40-43] have confirmed that db/db mice develop impaired spatial cognitive ability. As expected, by performing the Morris water maze test in this study, we confirmed again that db/db mice exhibited significant spatial cognitive impairments compared with the age-matched db/m mice, which are non-diabetic animals. In summary, db/db mice are a promising animal model for studying DACD.

A number of previous studies have analyzed proteins in the PSD fraction obtained from rodent forebrain [13, 14], cerebral cortex [15], whole brain [17], cerebellum [14, 18], and hippocampus [18 , 26,44], primary neuronal cultures [16], and even the human neocortex [22, 23] and anterior cingulate cortex [24], using different proteomics techniques such as one-dimensional gel electrophoresis [13, 17], 2-DE [45, 46], label-free [23], ICAT- [14 , 44] or iTRAQ-labeled technology [18] combined with MALDI-TOF/TOF mass spectrometry or LC-MS/MS. However, almost all of the previous studies have focused on the profiles of PSD from normal physiological conditions animals, and only a few have focused on the effects of drug administration on PSD proteomes. In addition, to the best of our knowledge, there was only one proteomics report for DACD status, which was produced by our laboratory. In that research, we reported alterations in the hippocampal protein profile of DACD rats and ZBPYR-treated DACD rats using DIGE-based MALDI-TOF/TOF mass spectrometry. In fact, the proteomic technique used in that study had limitations, resulting in membrane proteins and extremely low-abundance proteins not being identified.

So based on the above background, in this work, in terms of technology application, we selected a more sophisticated proteomics approach, iTRAQ-based LC-MS/MS, to reveal protein changes. In terms of research subject, unlike the hippocampus and cortex, we isolated PSD fractions from mice forebrains, since the PSD fraction is the pivotal micro-domain of the postsynaptic membrane specialized for signaling and plasticity, and plays an important role in cognitive function. In addition, we prepared three replicates of the PSD samples from each group, which were made for triplicate iTRAQ analysis, to improve the opportunities for identification and statistical analysis of the data [47]. Therefore, in this study, we not only aimed at the protein composition of the forebrain PSD complex from DACD animals, but also examined how this proteomic network is affected by chronic treatment with ZBPYR.

Compared with all above studies, the merits of this work could be summed up into three aspects, including the more sophisticated proteomic technique, the more precise subjects— PSD fractions from forebrain, and the animal model, which is much closer to the pathogenesis of DACD in human. In fact,compared with the previous results of all above studies, our present proteomic analysis exist both advantages and defects. On the advantage hand, we identified much more forebrain PSD proteins than that had been identified previously [13, 14]. A large number of previously identified PSD proteins, as well as novel groups of proteins, were detected. For examples, the eight proteins significantly altered by both DACD presence and ZBPYR treatment (Table 3) are interesting candidates for being involved in synaptic function. However, if we want to exactly know what their physiological functions are, we should continue further supporting experiments to affirm these proteins, which are whether truly components of the PSD. On the defect hand, we failed to identify several proteins that had been shown to be present in the PSD, including some AMPA receptor complex, nNOS, PKA, EphB receptor, etc. Since the purification of PSD and the procedure of LC-MS/MS were typically sophisticated, a substantial portion of AMPA receptors might be extracted from the PSD by Triton X-100, or some proteins might have been missed by mass spectrometry, or even the tryptic peptides used in the LC-MS/MS might be incompatible with PSD proteins.

In total, 3,154 proteins were identified in the experiment, with 1,863 unique proteins identified in three individual iTRAQ experiments from all three biological replicates according to the criteria. GO analysis were performed to further study the identified proteins. The results revealed that most of the identified proteins were located in the cytoplasm and membrane (Fig. 3A), attributable to the molecular functions of protein binding and catalytic activity (Fig. 3B), suggesting that the preparation of the PSD in this study was successful, with the GO annotations of the identified proteins being consistent with the position and physiological functions of the PSD. In addition, GO analysis also revealed that most of the identified proteins were involved in metabolic process (Fig. 3C), indicating that in addition to participating in nerve physiological and pathological processes, PSD proteins might play an important role in metabolism.

The differentially expressed PSD proteins might help us further understand the pathogenesis of DACD and the mechanism of ZBPYR effectiveness, so we are strict with the selection of differentially expressed PSD proteins. Some researchers thought that t-test or fold change alone might overestimate the number of differentially regulated proteins, because they both do not take into account the effect of multiple testing [35]. So in our study, we had developed a rigorouscriterion for screening the differentially expressed PSD proteins. We not only applied t-test and fold change at the same time, but also calculated FDR as implemented. By quantitative comparison and consecutive bioinformatics analysis, we finally obtained several noteworthy findings. First, we observed 24 differentially expressed proteins between normal and DACD animals (db/m versus db/db mice). This result suggested that DACD is indeed related to the abundance of some PSD proteins, and perhaps these quantitative changes led to the occurrence of DACD. Second, we found 23 proteins that were differentially regulated in ZBPYR-treated animals (db/db versus db/db/ZBPYR mice). This result implied that ZBPYR probably enhanced the learning and memory abilities of db/db mice through improving the expressions of some PSD proteins. Third, the GO annotation of these differentially expressed proteins indicated that the above two datasets showed similar cellular components, molecular functions, and biological processes (Fig 4A–C). And the GO analysis provided an overview of the cellular roles of the differentially expressed proteins under DACD and ZBPYR treatment, which allowed us to categorize them according to their functions. Finally, the differentially expressed proteins in the above two datasets were respectively subjected to query against the KEGG pathway database, and the results highlighted a number of pathways that play possible roles in the pathogenesis of DACD and the mechanism of ZBPYR. Here, we focused on several pathways in which we were interested.

First of all, our data indicated that two proteins were involved in ‘protein processing in endoplasmic reticulum’ (Table 4), and all these proteins were downregulated in db/db mice (db/m versus db/db). The endoplasmic reticulum (ER) plays a vital role in protein synthesis, protein folding, and calcium homeostasis. Abnormalities of these processes in several different pathological states create a condition defined as ER stress that leads to activation of a complex signaling network termed the unfolded protein response (UPR). Accumulating evidence has confirmed ER stress [48 –50] and UPR [51, 52] as molecular mechanisms of cognitive impairment, including aging, Alzheimer’s disease, and DACD. Our proteomics data is partly consistent with this mechanism, suggesting that decreased protein expression of ‘protein processing in endoplasmic reticulum’ might contribute to DACD.

Next, we found two proteins were involved in ‘PI3K-Akt signaling pathway’ (Table 4), and these two proteins were also downregulated in db/db mice (db/m versus db/db). The PI3K-Akt signaling pathway is an important pathway implicated in the proliferation, survival, and glucose transport of cells in the CNS. And a number of neuroendocrine factors exert neuroprotective effects via this pathway, e.g., brain–derived neurotrophic factor [53], hormone (GH)/insulin-like growth factor-I [54], and glucagon-like peptide-1 [55]. Previous studies have revealed that the PI3K-Akt signaling pathway plays a pivotal role in cognition and synaptic plasticity [56]. Our results support this earlier work and imply that alternated protein expression of the PI3K-Akt signaling pathway is probably a common phenomenon observed in animals with cognitive dysfunction.

Finally, our results also showed that there were two differentially expressed proteins that participate in ‘arachidonic acid metabolism’, and both proteins were upregulated in db/db/ZBPYR mice (db/db versus db/db/ZBPYR). Arachidonic acid metabolism is closely associated with inflammation and the production of inflammatory mediators. Since the pathological processes of many diseases are related to inflammation, including DM and cognitive impairment, we have reasons to believe that arachidonic acid metabolism might be involved in the development of DACD. The present results show that ZBPYR improved DACD, possibly through influencing the arachidonic acid pathway.

Notably, we are interested in a novel protein, namely Grb2, for DACD. Grb2 is an important intracellular adapter protein and plays an important role as a bridge in the signal transduction pathway. As a key molecule of PI3K-Akt signaling pathway, the inhibition of Grb2 leads to the levels of Akt and phospho-Akt protein significantly reduced, thereby blocking the downstream signaling pathways, and starting the pathology process. The results of our present proteomic analysis and western blotting experiments confirmed that Grb2 level decreased in the DACD animal, and ZBPYR treatment could improve its level, implying that Grb2 might be a crucial protein both as a pathological mark of DACD and a molecular target of the neuroprotective effects of ZBPYR.

Conclusions

In the present study, we identified differentially expressed proteins that were related to the DACD condition and/or ZBPYR treatment. The database of differentially expressed proteins altered by DACD should be useful for further functional studies related to DACD, learning and memory, and cognitive function. We thought ‘Protein processing in endoplasmic reticulum’ and ‘PI3K-Akt signaling pathway’ might be impaired in DACD pathogenesis. The database of differentially expressed proteins altered by ZBPYR could be important for further exploring the potential intervention targets of ZBPYR. We supported that ZBPYR improved DACD possibly through influencing the ‘arachidonic acid pathway’. We also suggested that Grb2 might be a crucial protein for DACD and ZBPYR. Further studies are required to investigate the exact role of these differentially expressed proteins and the pathways they participate in, since this information is important in the development of potential therapeutic targets for DACD and in understanding the underlying action of ZBPYR.

Footnotes

ACKNOWLEDGMENTS

This work was financially supported by The Key Project of National Natural Science Foundation, China (No. 81230084) and the Specialized Research Fund for the Doctoral Program of Higher Education, China (No. 20132105130001). We also thank Shanghai applied protein technology Co. Ltd. for the technology support.

Authors’ disclosures available online ().

Appendix

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