Abstract

Objective: To explore the proteomic changes in the hypothalamus of rats treated with Mongolian medical warm acupuncture for insomnia therapy based proteomics. Method: We used an iTRAQ-based quantitative proteomic approach to identify proteins that potential molecular mechanisms involved in the treatment of insomnia by Mongolian medical warm acupuncture. Result: In total, 7477 proteins were identified, of which 36 proteins showed increased levels and 45 proteins showed decreased levels in insomnia model group (M) compared with healthy control group (C), 72 proteins showed increased levels and 44 proteins showed decreased levels from the warm acupuncture treated insomnia group (W) compared with healthy controls (C), 28 proteins showed increased levels and 17 proteins showed decreased levels from the warm acupuncture-treated insomnia group (W) compared with insomnia model group (M). Compared with healthy control groups, warm acupuncture-treated insomnia group showed obvious recovered. Bioinformatics analysis indicated that up-regulation of neuroactive ligand–receptor interaction and oxytocin signaling was the most significantly elevated regulate process of Mongolian medical warm acupuncture treatment for insomnia. Proteins showed that increased/decreased expression in the warm acupuncture-treated insomnia group included Prolargin (PRELP), NMDA receptor synaptonuclear-signaling and neuronal migration factor (NSMF), Transmembrane protein 41B (TMEM41B) and Microtubule-associated protein 1B (MAP1B) to adjust insomnia. Conclusion: A combination of findings in the present study suggest that warm acupuncture treatment is efficacious in improving sleep by regulating the protein expression process in an experimental rat model and may be of potential benefit in treating insomnia patients with the added advantage with no adverse effects.

Introduction

According to a report by the World Health Organization, about 1/3 of the world’s population suffers from sleep disorders, and the percentage in the Chinese population, which is 27%, is significantly higher than the average levels worldwide [1]. Insomnia also leads to diseases such as hypertension, low immune function and diabetes. The current understanding of clinical science on insomnia is limited, and hypnotics are primarily used for treatment. However, drug treatment is usually accompanied by many side effects, and with poor long-term efficacy [2,3].

Mongolian medical warm acupuncture therapy is a traditional Mongolian therapy that prevents and treats diseases by stimulating specific or other sites (acupoints) of human body, using special silver acupuncture needles, combined with heat stimulation. It functions by unclogging meridians, regulating blood circulation, which results in strengthening the immunity system, and preventing and/or treating diseases. Mongolian medicine annals documentation and modern clinical studies have proven the effectiveness of Mongolian medical warm acupuncture in treating insomnia, and have shown that it is safer than hypnotics as it does not possess any side effects. However, the specific mechanism warm acupuncture-treated insomnia of remains unclear [4,5].

In the post-genome era, the important role of proteins, as executors of many biological functions, has become apparent in life sciences [6]. High-throughput analysis of protein expression levels, modifications, and protein–protein interactions in organisms, tissues, and cells, can provide valuable information that can be potentially used to improve disease diagnosis and prognosis [7]. Studies of individual proteins using traditional biochemical techniques require huge workload that is almost impossible to achieve when examining the whole proteome of an organism, hence making the identification of new pathogenesis mechanisms more difficult. Therefore, in order to study the molecular mechanism of Mongolian medical warm acupuncture in the treatment of insomnia, in the present study we employed proteomics technologies as a new systems biology tool for the first time. Previous studies have shown that iTRAQ, a new quantitative comparative proteomics technique, possesses outstanding advantages when compared with research strategies based on 2D-gel electrophoresis and mass spectrometry analysis [8,9].

Using iTRAQ-based proteomics, the present study explored the proteomic changes in the hypothalamus of rats treated with Mongolian medical warm acupuncture for insomnia therapy. The animals were divided into three groups: the normal control group (C), the insomnia model group (M) and the warm acupuncture-treated insomnia group (W). Hypothalamus samples from each group were enzymatically processed and chemically labeled with distinct iTRAQ labeling agents, and proteins with differential levels in the treatment group were identified through multidimensional liquid chromatography-tandem mass spectrometry analysis. The results obtained by systems analysis, and the potential molecular mechanisms involved in the treatment of insomnia by Mongolian medical warm acupuncture are discussed.

Materials and methods

Insomnia rat model construction

We purchased 30 healthy male Sprague-Dawley rats aged 8–10 weeks and weighing 220 ± 10 g from the Department of Laboratory Animals of Peking University Health Science Center. The protocol was approved by the Laboratory Animal Welfare Committee. The animal experiments conformed the U.S. National Institutes of Health guidelines and the guidelines from Directive 2010/63/EU of the European parliament on the protection of animals used for scientific purposes.

Animal experiments were completed at the animal experiment center of Inner Mongolia medical university. All animals were maintained under controlled conditions (21–22°C; 55–65% humidity; 12-h light, 12-h dark cycle) with free access to rodent soy-free food and water. The animals were acclimated to their new circumstances for one week. Then, the animals were randomly divided into three groups (n=10/group): healthy controls (C), insomnia model group (M) and the warm acupuncture-treated insomnia group (W).

Rats in the M and W groups use peritoneal injection of p-chlorophenylalanine (300 mg/ kg) to construct the insomnia rat model, and the dosage was adjusted with the increase in body weight. The concentrations have been described previously. In the warm acupuncture group, the rats were adaptively raised for 7 days and intraperitoneally injected with normal saline (0.l ml/kg) between 8:30 and 9:00 a.m. Each day for two consecutive days from the eight day. Starting from the 10th day. Acupuncture treatment was performed at 08:00 every morning. Stainless steel acupuncture needles (0.35 mm × 20 mm, supplied by Inner Mongolia Yuanyang Traditional Chinese and Mongolian Science and Technology Development LLC) were used. Depth of needling at each point was 5 mm. The Dinghui Acupoint, Heyi Acupoint, and Xin Acupoint of each rat were stimulated with warm acupuncture for 15 min each time (Mongolian Model MY-I electric heating needle warmers) at ∼40°C (be careful not to burn the needling site) once each day for seven consecutive days [5,10].

Sample collection

All rats were killed at the anestrus period following anesthesia under 1% sodium pentobarbital (40 mg/kg intraperitoneal injection). Collected rats hypothalamic tissue. Finally, rats were euthanized by an excessive dose of 1% sodium pentobarbital (intraperitoneal injection).

Protein preparation

The hypothalamus of all rat groups were harvested, SDT buffer was added to the sample, and then transferred into 2 ml centrifuge tubes, prefilled with appropriate amount of quartz sand and an additional 1/4 inch of ceramic bead. Following, the samples were homogenized in a MP tissue homogenizer (24×2, 6.0 M/S, 60 s, twice), ultrasonificated (80 W, 10-s ultrasound, 15-s interval, 10 cycles), and then incubated in boiling water for 15 min. After centrifugation at 14,000 g for 40 min, supernatants were filtered through a 0.22-µm filter. Protein concentrations were determined using the BCA method. The sample was stored a −80°C [11].

SDS-PAGE separation

For each sample, 20 μg of proteins were mixed with 5× loading buffer, boiled for 5 min, and then separated by 12.5% SDS-PAGE (constant current of 14 mA, 90 min). Protein bands were visualized using Coomassie Blue staining.

Filter aided sample preparation (FASP) method

For each group, 200 μg of proteins for each sample were incorporated into 30 μl SDT buffer (4% SDS, 100 mM DTT, 150 mM Tris-HCl pH 8.0). Following, the mixtures were boiled for 5 min, and then cooled down to room temperature. Next, 200 ml of UA buffer was added, mixed up, and transferred into 10 kDa ultrafiltration tubes and centrifuged at 14,000 g for 15 min, the filtrate was discarded (this step was repeated once). About 100 μl of iodoacetamide (IAA) buffer (100 mM IAA in UA) was added, then vortexed at 600 rpm for 1 min, and the mixture reacted for 30 min at room temperature, under dark conditions; then centrifuged at 14,000 g for 15 min. About 100 μl of UA buffer was added and the sample was centrifuged at 14,000 g for 15 min; the process was repeated twice. About 100 μl of 10 times diluted dissolution medium was added, and the sample was centrifuged at 14,000 g for 15 min; this step was repeated twice. Following, 40 μl of trypsin buffer (4 μg trypsin in 40 μl dissolution buffer) was added, mixed by vortexing at 600 rpm for 1 min, and then incubated at 37°C for 16–18 h. The sample column was transferred into a new collection tube, and centrifuged at 14,000 g for 15 min; then the sample was eluted by adding 40 μl of 10 times diluted dissolution buffer, followed by centrifugation at 14,000 g for 15 min. Peptides were desalinated using a C18 cartridge, and after lyophilization were re-suspended in 40 μl of dissolution buffer. Peptide concentration was estimated by measuring absorbance at OD280 [12].

iTRAQ labeling

About 100 μg peptide mixture of each sample was labeled using iTRAQ reagent according to the manufacturer’s instructions (Applied Biosystems). The experiment was carried out three times.

Peptide separation using strong cation exchange (SCX) chromatography

Labeled peptides from each group were mixed and separated using the AKTA Purifier 100. About 10 mM KH2PO4 with 25% ACN (pH 3.0) was used as buffer A, and 10 mM KH2PO4, 500 mM KCl with 25% ACN (pH 3.0) was used as buffer B. The chromatographic column was equilibrated with buffer A, and samples were loaded into the column through a sample injector with flow rate adjusted at 1 ml/min. The gradient was set as follows: linear gradient of 0–8% buffer B for 0–22 min; linear gradient of 8–52% buffer B for 22–47 min; linear gradient of 52–100% buffer B for 47–50 min; after 58 min buffer B concentration was set to 0%. During elution, the absorbance at 214 nm was recorded, and eluted solutions were collected every 1 min; totally, 30 eluted solutions were collected. After lyophilization the samples were desalinated using a C18 cartridge.

Mass spectrometry analysis

HPLC

Samples were analyzed using nano LC-MS/MS. Peptide mixtures were loaded with buffer A (0.1% formic acid) on a reversed-phase column, and then eluted under a linear gradient of buffer B (84% acetonitrile and 0.1% formic acid). The flow rate was adjusted at 300 nl/min.

LC-MS/MS analysis

After chromatography separation, samples were analyzed on the Q-Exactive mass spectrometer. Each sample required 60 min of analysis, and radical cations were used as fragment ions; the scan range was set at 300–1800 m/z. Resolution of the primary mass spectrometry was 70,000 at 200 m/z, and the AGC target was 3e6; the primary Maximum IT was 10 ms, and the number of scan ranges was 1; dynamic exclusion was set at 40.0 s. The mass electron ratio of peptides and fractions were collected as follows: 10 fraction spectra were collected (MS2 scan) after each full scan; the MS2 activation type was HCD, and the isolation window was 2 m/z. The resolution of secondary mass spectrometry was 17,500 at 200 m/z; microscans: 1; the secondary maximum IT was 60 ms, normalized collision energy was 30eV, and underfill was 0.1%.

Data analysis

MASCOT is considered the golden standard in the proteomics qualitative analysis, thus, Mascot 2.2 was used for database searching in this study. The Uniprot protein Rattus norvegicus database (35,838 sequences) was used for search. Caramidomethylation of cysteines, iTRAQ labeling at the N-term and the lysine side chain amion groups were set as fixed modification. The oxidation of methionine and iTRAQ 4 plex(Y) were set as variable modification. The false discovery rate (FDR) for peptide was set to 1%. The minimum peptide length was set to 6. Enzyme specificity was set to be Trypsin and up to two missed cleavages per peptide were allowed. Mass tolerance for precursor ions was set to 20 ppm and for fragment ions at 0.1Da.

Gene Ontology (GO) analysis

The process of GO annotations was performed on the targeted protein clusters using Blast2GO, and was divided into four steps: sequence alignment, extraction of GO annotations, GO annotation and supplementary annotation [13]. First, the targeted protein clusters were aligned with the corresponding protein sequences in the database, using the localization sequence alignment tool NCBI BLAST+ (ncbi-blast-2.2.28+-win32.exe), and then the first 10 aligned sequences with E-value ≤ 1e-3 were saved for further analysis. Following, the GO annotations that were associated with the proteins with high similarities with the target protein clusters or with homologous proteins, which had been blasted by the Blast2GO Command Line (dataset version: go_201608.obo, www.geneontology.org), were extracted. During annotation, Blast2GO Command Line annotated the extracted GO annotations to target proteins through comprehensive examination of the sequence similarities, GO annotation resource reliabilities, and the existence of circle plots between target and aligned proteins. After annotation, to further improve the annotation efficiency, conserved motifs in EBI database that matched with target proteins were scanned using InterProScan [14], and the motif-related functional information were annotated to target protein sequences. ANNEX was used to further supplement the annotated information, and linkages between different GO types were established to improve the annotation accuracy.

KEGG pathway analysis

In the KEGG pathway database, KO (KEGG Orthology) terms were used for classification of genes and their product. Orthologous genes and their products were classified in the same pathway group, and were annotated with the same KO (or K) term. During KEGG pathway analysis of target protein clusters, first KEGG genes data were mapped, using KAAS (KEGG Automatic Annotation Server) [15], to KO terms in order to classify the target protein sequences, and then information of pathways containing these target proteins was automatically extracted according to KO classification.

Functional enrichment analysis

While conducting enrichment analysis of the GO annotations or KEGG pathway annotations of target protein clusters, Fisher’s exact test was used to compare the distribution of each GO classification or KEGG pathway between target protein clusters and total protein clusters, and for evaluating the significance of enrichment of the corresponding GO term or KEGG pathway.

Cluster analysis

Protein expression related data were analyzed using hierarchical cluster analysis. For hierarchical cluster analysis, clusters were selected and hot-plots were drafted using Cluster3.0 software (http://bonsai.hgc.jp/∼mdehoon/software/cluster/software.htm), and similarity definition was calculated using Java Treeview (http://jtreeview.sourceforge.net) with Euclidean distance and average linkage hierarchical clustering.

Results

Differentially expressed rats hypothalamus proteins among C, M and W groups were identified and analyzed in this study using LC–MS/MS. The entire experimental process is shown in Figure 1.

Experimental design for the quantitative proteomics analysis

Figure 1
Experimental design for the quantitative proteomics analysis

The experiment is divided into three groups (C, M and W). Extracted proteins were prepared via FASP and labeled with iTRAQ regents. The labeled peptides were separated by SCX chromatography and fractions were analyzed by reversed phase LC-MS/MS, all data were analyzed by bioinformatics tools from different aspects.

Figure 1
Experimental design for the quantitative proteomics analysis

The experiment is divided into three groups (C, M and W). Extracted proteins were prepared via FASP and labeled with iTRAQ regents. The labeled peptides were separated by SCX chromatography and fractions were analyzed by reversed phase LC-MS/MS, all data were analyzed by bioinformatics tools from different aspects.

LC–MS/MS

The results indicated that a total of 7477 corresponding proteins (Supplementary Table S1) and fold change of differentially expressed proteins among C, W and M groups were determined based on the intergroup ratio in iTRAQ reports. Proteins that conformed to the following screening criteria were deemed as differentially expressed: expression fold change > 1.2 (up- or down-regulation) and P-value<0.05, while the protein difference multiple <0.8 and P<0.05 are the difference significant proteins. Comparisons between M/C, W/C and W/M groups were carried out, with altogether 81 (including 36 up- and 45 down-regulated), 116 (72 up- and 44 down-regulated) and 45 (28 up- and 17 down-regulated) differentially expressed proteins identified, respectively (Supplementary Table S2).

Optimized screening criteria, for those proteins where in differences could be seen between W/M and W/C groups, with no difference being seen M/C groups, or those differences showing opposite variation trend. The identified proteins were further screened to yield a total of 45 optimized differentially expressed proteins (Table 1).

Table 1
Optimized differentially expressed proteins between groups
Protein IDProteinFold changeP-value
A0A096MK16 Protein Arap2 (Fragment) 1.236180578 0.000882046 
F1M1E4 Protein Pnkd 1.203434233 0.002100419 
B1H223 Down syndrome critical region gene 3 1.221180934 0.002523703 
P02680 Fibrinogen gamma chain 1.233337549 0.002750139 
P14480 Fibrinogen beta chain 1.205154782 0.006176793 
Q6IFW6 Keratin, type I cytoskeletal 10 1.586636239 0.006670983 
A8IRI3 Glucocorticoid receptor 1.374519231 0.007279957 
A0A0G2KAQ8 Peroxisomal membrane protein 2 1.253174259 0.007771405 
Q62649 Neuronatin 1.224901775 0.012138775 
A0A0G2JWX4 Keratin, type II cytoskeletal 2 epidermal 1.56566129 0.012393709 
A0A0G2K4U7 Protein Mtus2 1.232703408 0.01391488 
D4A1U8 Protein RGD1311744 1.277139639 0.014144665 
P24090 Alpha-2-HS-glycoprotein 1.296358037 0.01441777 
F1LYI7 Protein Tmem256 1.207978689 0.015866603 
D3ZA53 Protein Pnmal1 1.421893598 0.016281749 
Q9EQP5 Prolargin 1.273012448 0.017232379 
M0RA79 Protein LOC691828 1.273971816 0.019054036 
Q95571 RT1.A(U) alpha chain (Fragment) 1.266842428 0.019175113 
M0R6Y8 Phosphoglycerate kinase 1.22539767 0.024665028 
Q9ESM0 Inositol hexakisphosphate kinase 1 1.274174463 0.025457038 
D4AAJ2 NMDA receptor synaptonuclear-signaling and neuronal migration factor 1.227341863 0.029753527 
O08562 Sodium channel protein type 9 subunit alpha 1.421454082 0.034185457 
Q5FVN2 Transmembrane protein 41B 1.32306624 0.036331955 
D4A8N1 Protein Dpm1 1.253915809 0.036970623 
O88752 Epsilon 1 globin 1.533583884 0.040836379 
D4A4T6 Protein Rint1 1.307495336 0.042824768 
P17209 Myosin light chain 4 1.254133152 0.048826237 
D3ZBP4 Protein-methionine sulfoxide oxidase MICAL1 1.220699776 0.049482287 
O55145 Fractalkine 0.821730332 0.002073597 
D3ZC82 Protein Nufip2 0.780885927 0.003504731 
D3ZIC4 Protein phosphatase 1 regulatory subunit 0.797201943 0.006803938 
Q3KR51 HMP19 protein, isoform CRA_a 0.813904866 0.009560059 
P58405 Striatin-3 0.811684263 0.015950492 
Q4KLX9 Protein Ccdc163 0.716197358 0.016416855 
D3ZWP8 Protein Lrrc58 0.756999583 0.017218939 
Q5UAJ6 Cytochrome c oxidase subunit 2 0.735583341 0.021848769 
A0A0G2K7Z3 Acyl-coenzyme A thioesterase 1 0.824303275 0.024433777 
P15205 Microtubule-associated protein 1B 0.47872137 0.02960253 
F1LW77 Protein Rab33b 0.811272188 0.032017895 
A0A0G2JW88 Microtubule-associated protein 0.82499354 0.033513215 
F1LWM1 Protein Ssh1 0.765742084 0.037036806 
Q6AXT8 Splicing factor 3A subunit 2 0.790258668 0.045489055 
A0A140UHW6 Protein Trmt1 0.792470864 0.046071567 
A1L1L5 Ccnk protein 0.819841333 0.046441222 
A0A0G2K1W9 Lactate dehydrogenase D, isoform CRA_d 0.679338388 0.048325937 
Protein IDProteinFold changeP-value
A0A096MK16 Protein Arap2 (Fragment) 1.236180578 0.000882046 
F1M1E4 Protein Pnkd 1.203434233 0.002100419 
B1H223 Down syndrome critical region gene 3 1.221180934 0.002523703 
P02680 Fibrinogen gamma chain 1.233337549 0.002750139 
P14480 Fibrinogen beta chain 1.205154782 0.006176793 
Q6IFW6 Keratin, type I cytoskeletal 10 1.586636239 0.006670983 
A8IRI3 Glucocorticoid receptor 1.374519231 0.007279957 
A0A0G2KAQ8 Peroxisomal membrane protein 2 1.253174259 0.007771405 
Q62649 Neuronatin 1.224901775 0.012138775 
A0A0G2JWX4 Keratin, type II cytoskeletal 2 epidermal 1.56566129 0.012393709 
A0A0G2K4U7 Protein Mtus2 1.232703408 0.01391488 
D4A1U8 Protein RGD1311744 1.277139639 0.014144665 
P24090 Alpha-2-HS-glycoprotein 1.296358037 0.01441777 
F1LYI7 Protein Tmem256 1.207978689 0.015866603 
D3ZA53 Protein Pnmal1 1.421893598 0.016281749 
Q9EQP5 Prolargin 1.273012448 0.017232379 
M0RA79 Protein LOC691828 1.273971816 0.019054036 
Q95571 RT1.A(U) alpha chain (Fragment) 1.266842428 0.019175113 
M0R6Y8 Phosphoglycerate kinase 1.22539767 0.024665028 
Q9ESM0 Inositol hexakisphosphate kinase 1 1.274174463 0.025457038 
D4AAJ2 NMDA receptor synaptonuclear-signaling and neuronal migration factor 1.227341863 0.029753527 
O08562 Sodium channel protein type 9 subunit alpha 1.421454082 0.034185457 
Q5FVN2 Transmembrane protein 41B 1.32306624 0.036331955 
D4A8N1 Protein Dpm1 1.253915809 0.036970623 
O88752 Epsilon 1 globin 1.533583884 0.040836379 
D4A4T6 Protein Rint1 1.307495336 0.042824768 
P17209 Myosin light chain 4 1.254133152 0.048826237 
D3ZBP4 Protein-methionine sulfoxide oxidase MICAL1 1.220699776 0.049482287 
O55145 Fractalkine 0.821730332 0.002073597 
D3ZC82 Protein Nufip2 0.780885927 0.003504731 
D3ZIC4 Protein phosphatase 1 regulatory subunit 0.797201943 0.006803938 
Q3KR51 HMP19 protein, isoform CRA_a 0.813904866 0.009560059 
P58405 Striatin-3 0.811684263 0.015950492 
Q4KLX9 Protein Ccdc163 0.716197358 0.016416855 
D3ZWP8 Protein Lrrc58 0.756999583 0.017218939 
Q5UAJ6 Cytochrome c oxidase subunit 2 0.735583341 0.021848769 
A0A0G2K7Z3 Acyl-coenzyme A thioesterase 1 0.824303275 0.024433777 
P15205 Microtubule-associated protein 1B 0.47872137 0.02960253 
F1LW77 Protein Rab33b 0.811272188 0.032017895 
A0A0G2JW88 Microtubule-associated protein 0.82499354 0.033513215 
F1LWM1 Protein Ssh1 0.765742084 0.037036806 
Q6AXT8 Splicing factor 3A subunit 2 0.790258668 0.045489055 
A0A140UHW6 Protein Trmt1 0.792470864 0.046071567 
A1L1L5 Ccnk protein 0.819841333 0.046441222 
A0A0G2K1W9 Lactate dehydrogenase D, isoform CRA_d 0.679338388 0.048325937 

The proteins above have shown differences between W/M and W/C groups groups.

Cluster analysis

First, cluster analysis was conducted (Figure 2). Hierarchical clustering results were expressed as a tree heat map, with red representing up-regulation and green indicating down-regulation. As determined through horizontal comparison, samples could be classified into three categories: C1-C3, M1-M3and W1-W3. Such vertical comparison indicated that proteins could be classified into two categories with opposite directional variation, which displayed the expression patterns of differentially expressed proteins in three groups, demonstrating the rationality of the selected differentially expressed proteins. The cluster analysis process thus supported that the differentially expressed proteins screened out in this experiment were reasonable and accurate.

Cluster analysis of differential level proteins between (A) M versus C, (B) W versus C and (C) W versus M

Figure 2
Cluster analysis of differential level proteins between (A) M versus C, (B) W versus C and (C) W versus M

Colors indicate the differential protein levels, which increase successively from green to dark red. Increased levels of proteins are indicated in red, and decreased levels are marked in green.

Figure 2
Cluster analysis of differential level proteins between (A) M versus C, (B) W versus C and (C) W versus M

Colors indicate the differential protein levels, which increase successively from green to dark red. Increased levels of proteins are indicated in red, and decreased levels are marked in green.

GO functional annotation and analysis

As shown in Figure 3A, in the model group, the proteins with differential levels, as compared with the control groups, were enriched in the biological processes of growth regulation, signal transduction and hormone regulation. Molecular function enrichment was observed in molecular signal transduction, transcription factor activation, protein binding and catalytic reactions. The cellular compositions of the altered proteins were mainly membrane supramolecular complexes and intermembrane macromolecular complexes, which participate in the cell division and intercellular connection (Supplementary Table S3).

GO analyses of protein functions in (A) M versus C, (B) W versus C and (C) W versus M

Figure 3
GO analyses of protein functions in (A) M versus C, (B) W versus C and (C) W versus M

Gene ontology annotation. The differentially expressed proteins are mainly annotated as protein binding, cell, and single organism process in terms of molecular function, cell composition, and biological process, respectively.

Figure 3
GO analyses of protein functions in (A) M versus C, (B) W versus C and (C) W versus M

Gene ontology annotation. The differentially expressed proteins are mainly annotated as protein binding, cell, and single organism process in terms of molecular function, cell composition, and biological process, respectively.

As shown in Figure 3B, in the warm acupuncture-treated group, when compared with the control groups, the proteins with altered levels were enriched in the GO biological processes of growth regulation, metabolism process, movement regulation and behavioral regulation. GO molecular function enrichment of differential level proteins was observed in catalytic activity activation, signal transduction activation, antioxidant activity activation, transcription factor activation, protein binding and molecular function regulation. The GO cellular composition of the altered proteins was enriched in intercellular connection of intermembrane, neural synapse and extracellular domains, and the synaptic regulation (Supplementary Table S4).

As shown in Figure 3C, in the warm acupuncture treated group, when compared with the model groups, the proteins with altered levels were enriched in the GO biological processes of signal transduction, regeneration, regulation, growth, immunological reaction and metabolism process; molecular function GO enrichment was observed in nerve conduction electrical carrier activation, antioxidant activity activation, catalytic activation and intermembrane transduction activation. The GO cellular composition of the altered proteins was enriched in cell membrane, synapse, intermembrane tissue, supramolecular complex and intermembrane space, participation in cell junctions (Supplementary Table S5).

KEGG pathway analysis

As shown in Figure 4A, in the model group, proteins with differential levels, as compared with the control groups, were enriched in the KEGG pathways of tight junctions, atherosclerosis, endocytosis, choline metabolism in cancer, inflammatory mediator regulation of TRP channels, insulin resistance, insulin signal transduction, ribosome, herpes simplex infection, hippocampal signaling, RNA transportation, glycerol phospholipid metabolism, glycerolipid metabolism, complement and coagulation cascades, protein processing in endoplasmic reticulum, synaptic vesicle recycling, chemical carcinogenesis, influenza A and MAPK signaling (Supplementary Table S6).

KEGG analyses of protein functions in in (A) M versus C, (B) W versus C, (C) W versus M

Figure 4
KEGG analyses of protein functions in in (A) M versus C, (B) W versus C, (C) W versus M
Figure 4
KEGG analyses of protein functions in in (A) M versus C, (B) W versus C, (C) W versus M

As shown in Figure 4B, in the warm acupuncture-treated group, when compared with the control groups, proteins with differential levels were enriched in the KEGG pathways of ribosome, RNA transportation, chemical carcinogenesis, protein processing in endoplasmic reticulum, 5-hydroxytryptamine synapse, adhering junctions, inflammatory mediator regulation of TRP channels, platinum resistance, influenza A, Hippo signaling, glycolysis, apelin signaling, mTOR signaling, olfactory transduction, of vascular smooth muscle contraction, insulin resistance, protein binding, Rapl signaling and central carbon metabolism in cancer (Supplementary Table S7).

As shown in Figure 4C, in the warm acupuncture-treated group, when compared with the model groups, the proteins with differential levels were enriched in the KEGG pathways of cardiac muscle contraction, endocytosis, platelet activation, actin cytoskeleton regulation, complement and coagulation cascades, apelin signaling, oxytocin signaling, amino acid biosynthesis, autophagy, axon singling, Alzheimer disease, non-alcoholic fatty liver disease (NAFLD), cytokine–cytokine receptor interaction, spliceosome, chemokine signaling, TNF-α signaling, neuroactive ligand–receptor interaction, phagocytosis, oxidative phosphorylation and autoimmune thyroid disease (Supplementary Table S8).

Protein expression change

As shown in Figure 5, compared with the protein expression change between the three groups, the warm acupuncture-treated group protein expression verge on control group suggests that warm acupuncture treatment is efficacious in improving sleep by regulating the protein expression process in an experimental rat model.

Three groups protein expression change, the warm acupuncture-treated group protein expression verge on control group

Figure 5
Three groups protein expression change, the warm acupuncture-treated group protein expression verge on control group

(A) up-regulate protein recovery condition and (B) down-regulate protein recovery condition.

Figure 5
Three groups protein expression change, the warm acupuncture-treated group protein expression verge on control group

(A) up-regulate protein recovery condition and (B) down-regulate protein recovery condition.

Enrichment nerve related proteins with differential levels in the warm acupuncture-treated group

In our study, integration of the three groups of clusters analysis, revealed GO and KEGG pathway enrichment for four nerve–related proteins with differential levels in the warm acupuncture treated group, as compared with the model groups. These proteins were Prolargin (PRELP), NMDA receptor synaptonuclear-signaling and neuronal migration factor (NSMF), Transmembrane protein 41B (TMEM41B) and Microtubule-associated protein 1B (MAP1B) (shown in Table 2). These results provided new clues and theoretical basis for the further studies on the treatment mechanism of Mongolian medical warm acupuncture. Moreover, these four proteins were found to be closely related to neuroregulation or insomnia treatment. Among them, prolactin protein prolactin (prelp), which has been shown to be closely related to insomnia treatment, is the focus of our future research.

Table 2
Enrichment nerve-related proteins
Gene symbolProtein nameFunctionFold-change
PRELP Prolargin Generation of neurons. Electrical activity and intracellular signal transduction in hypothalamic neurons 1.27 
NSMF NMDA receptor synaptonuclear-signaling and neuronal migration factor Positive regulation of neuron migration. Regulation of neuronal synaptic plasticity 1.23 
TMEM41B Transmembrane protein 41B Integral to membrane. nervous system development 1.32 
MAP1B Microtubule-associated protein 1B Microtubule cytoskeleton organization. Nervous system development 0.48 
Gene symbolProtein nameFunctionFold-change
PRELP Prolargin Generation of neurons. Electrical activity and intracellular signal transduction in hypothalamic neurons 1.27 
NSMF NMDA receptor synaptonuclear-signaling and neuronal migration factor Positive regulation of neuron migration. Regulation of neuronal synaptic plasticity 1.23 
TMEM41B Transmembrane protein 41B Integral to membrane. nervous system development 1.32 
MAP1B Microtubule-associated protein 1B Microtubule cytoskeleton organization. Nervous system development 0.48 

Proteins that showed increased levels in serum from gastric cancer patients is shown in red and those that showed decreased levels are shown in green.

Discussion

Insomnia is a subjective experience of sleep and is characterized by a difficulty in falling and/or staying asleep. This condition can result in insufficient sleep quantity to meet an individual’s normal physiological needs, and affects normal life activities [16]. Insomnia is the most common sleep disorder and is associated with high rates of morbidity [17]. However, drug treatment is usually accompanied by many side effects, and with poor long-term efficacy. Long-term administration of hypnotics has been reported to cause problems such as addiction and tolerance, which all together make drug treatment not an ideal therapeutic regimen. Therefore, finding a safe and effective way to treat insomnia will be the focus of future research [18].

Mongolian medical warm acupuncture is one of the most commonly used methods for treatment of insomnia in Mongolian medicine. Mongolian medical warm acupuncture therapy is a traditional Mongolian therapy that prevents and treats diseases by stimulating specific or other sites (acupoints) of the human body, using special silver acupuncture needles, combined with heat stimulation [19,20]. Through integration of the acupuncture and warm effects, and specific responses to acupoint stimulation, Mongolian medical warm acupuncture can treat diseases by regulating multiple aspects of function various body parts, which involves multi-pathway mechanisms and the function of the blood circulatory system, the nervous system and the immune system [21,22].

It functions by unclogging meridians, regulating blood circulation, which results in strengthening the immunity system, and preventing and/or treating diseases [5]. Mongolian medicine annals documentation and modern clinical studies have proven the effectiveness of Mongolian medical warm acupuncture in treating insomnia, and have shown that it is safer than hypnotics as it does not possess any side effects. Thus, treatment of insomnia using Mongolian medical warm acupuncture has been widely accepted by the patients due to its advantages such as high efficiency, safety, no side effects, simplicity and no drug dependence [5,10].

In the present study, the effects of warm acupuncture treat with insomnia rat hypothalamus proteome were investigated, and the data obtained were integrated with related biological information in an attempt to reveal the molecular mechanisms involved in Mongolian medical warm acupuncture for insomnia therapy.

The recent advances in proteomics technologies have provided useful tools for studying the mechanisms of insomnia, which can contribute to the development of insomnia treatments that can be potential applied in clinical practice [23]. In insomnia studies, proteomics has been mainly used to identify physiopathologic mechanisms associated with insomnia and its developing process; however, there is no information on the proteome changes in response to Mongolian medical warm acupuncture. In the present study, iTRAQ-based proteomics analysis was performed to study the proteome changes associated with the application of Mongolian medical warm acupuncture in insomnia treatment. The underlying molecular mechanisms were also investigated by integrating the functional information of the identified proteins, which can potentially provide new or improved treatment strategies in clinical practice.

The experimental insomnia animal model and the quality control were labeled by different iTRAQ labeling reagents in order to detect meaningful changes in proteins, and further bioinformatics analysis was performed to obtain the related biological function of the identified proteins [24].

Gene Ontology (GO) function annotation is a standard function classification system, it provides a set of dynamically updated standardized vocabulary, and describes the characteristics of genes and gene products from three aspects: biological process, molecular function and cellular component [25]. In the present study, we observed GO enrichment in the biological processes of signal transduction, regeneration, regulation, growth, immunological reaction and metabolism process in the warm acupuncture-treated groups [26]. This indicated that warm acupuncture treatment of insomnia involves regulation of nerve signal transduction, growth, and regeneration in rats. We also found GO function enrichment in immune responses, suggesting that Mongolian medical warm acupuncture treated insomnia through up-regulation of immunologic response mechanisms. Furthermore, enrichment was observed in the GO molecular function annotations of nerve conduction electrical carrier activation, antioxidant activity activation, catalytic activation and intermembrane transduction activation, implying that during Mongolian medical warm acupuncture treatment of insomnia rats, nerve signal transduction was stimulated, inter membrane transduction was activated, and the electrical signal conduction was up-regulated. Cellular composition GO analysis revealed enrichment of cell membrane, synapse, intermembrane tissue, supramolecular complex, intermembrane space, and cell junctions, which further indicated differential expression of proteins located in cell membrane and intermembrane space, during Mongolian medical warm acupuncture treatment of insomnia rats. Additionally, enrichment was observed in cell membranes, cell membrane receptor proteins and complicated mesh frame structures composed of signaling polysaccharide macromolecules, which are vital for neurotransmission and signal conduction; thus, cell membrane proteins play vital roles in Mongolian medical warm acupuncture treatment of insomnia. These results also suggested that extracellular matrix proteins are implicated in the initiation and progression of insomnia.

In organisms, proteins function through coordinated interactions with different proteins in order to accomplish a series of biochemical functions [27–29]. Thus, pathway analysis is the most direct and essential method to systematically and comprehensively understand the cellular biological processes involved in the pathogenesis of diseases, and the mechanism of function of medicines [30]. KEGG pathways analysis showed that warm acupuncture treatment groups enriched in oxytocin signaling, amino acid biosynthesis, autophagy, axon singling, cytokine–cytokine receptor interaction, spliceosome, chemokine signaling, TNF-α signaling and neuroactive ligand–receptor interaction. We speculate that the nerve transduction related mechanism was attributed to the coupling of the oxytocin signaling pathway, the neuroactive ligand–receptor interaction and oxidative phosphorylation. Down-regulation of oxytocin protein has been reported to correlate with depression, insomnia and neural regulation. To sum up, KEGG pathway enrichment identified pathways and signaling proteins important for target selections in future studies.

In the present study, integration of the three groups of Cluster analysis, revealed GO and KEGG pathway enrichment for four nerve related proteins with differential levels in the warm acupuncture treated group were PRELP, NSMF, TMEM41B and MAP1B.

PRELP (Prolargin) related to neural regulation, decreased prolactin is associated with depression and insomnia [31]. Prolactin can regulated tuberoinfundibular dopamine neuron discharge pattern, neuronal excitability [32,33]. In the present study, the expression of prolactin increased under warm acupuncture, which is one of the ways to alleviate insomnia. NSMF (NMDA receptor synaptonuclear-signaling and neuronal migration factor) positive regulation of neuron migration and regulation of neuronal synaptic plasticity [34] is crucial for synaptic plasticity and memory, brain-derived neurotrophic factor increases the motility of a particular NMDA /GABA - responsive subset of neural progenitor cells. It is related to the regulation of memory and nerve development [35,36]. Treatment with warm acupuncture can repair neurodevelopmental that is one of the ways to alleviate insomnia. TMEM41B (Transmembrane protein 41B) regulated nervous system development and related to the formation of synapses [37,38]. MAP1B (Microtubule-associated protein 1B) is required for shaping the neural tube, regulated axonal growth and neuronal migration in the central nervous system, and it is highly expressed in nerve injury. Decreased expression after warm acupuncture therapy is one of the manifestations of nerve injury healing [39,40]. These results provided new clues and theoretical basis for the further studies on the treatment mechanism of Mongolian medical warm acupuncture.

Conclusions

The iTRAQ-based proteomic data analyses presented here elucidate variations of the proteomics involved in the treatment of insomnia by Mongolian medical warm acupuncture. They also increase our understanding of the molecular mechanisms involved in these processes. Distinct protein played an important role in the treatment of insomnia by Mongolian medical warm acupuncture. KEGG and GO analyses enrichment for four nerve–related proteins with differential levels in the warm acupuncture treated group were Prolargin, NMDA receptor synaptonuclear-signaling and neuronal migration factor, transmembrane protein 41B and Microtubule-associated protein 1B to adjust insomnia. It may through regulatory mechanisms of neuronal function on insomnia. It also reveals the potential molecular mechanisms associated with the treatment of insomnia by Mongolian medical warm acupuncture.

Competing Interests

The authors declare that there are no competing interests associated with the manuscript.

Funding

This work was supported by Mongolian medicine collaborative innovation project [grant number MYYXT201501] and the National Natural Science Foundation of China [grant number 81660468].

Author Contribution

Gula A and Xiulan Su: Propose the research plan and organize the implementation; Yanan Xu and Xian Li: Writing text; Xiulan Su: To write the outline, organize the implementation, review; Manduriwa: Animal feeding and treatment, animal behavior observation and detection.

Acknowledgements

We’d like to show our great appreciation to Shanghai Applied Protein Technology Co, Ltd. for technical support of proteomics.

Abbreviations

     
  • MAP1B

    microtubule-associated protein 1B

  •  
  • NAFLD

    non-alcoholic fatty liver disease

  •  
  • NSMF

    neuronal migration factor

  •  
  • PRELP

    prolargin

  •  
  • TMEM41B

    transmembrane protein 41B

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Author notes

*

These authors contributed equally to this work.

This is an open access article published by Portland Press Limited on behalf of the Biochemical Society and distributed under the Creative Commons Attribution License 4.0 (CC BY).

Supplementary data