iTRAQ-based proteomics analysis on insomnia rats treated with Mongolian medical warm acupuncture

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.

Keywords: Traditional Mongolian medicine; iTRAQ; insomnia; proteomics; warm acupuncture.

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

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.