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Journal of Integrative Neuroscience  2018, Vol. 17 Issue (2): 149-158    DOI: 10.31083/JIN-170047
Research article Previous articles | Next articles
Protein expression profiling in rat hippocampus after focal cerebral ischemia injury
Lichan He1, Rui He1, Ruihua Liang1, Yi Li1, Xiaoqiang Li1, Chuqiao Li1, Suping Zhang1, *()
1 Department of Neurology, Guangzhou Red Cross Hospital, Medical College, Jinan University, No. 396 Tongfu Zhong Road, Guangzhou 510220, China
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Abstract  

The aim in this study was to explore protein expression profiles in the rat hippocampus after induction of focal ischemia injury. Forty male Sprague Dawley rats were randomly divided into four equal groups after ischemia injury surgery: Control, Day 3, Day 7, and Day 14. Focal cortical ischemia was induced in thirty rats by photothrombosis of cortical microvessels. After surgery, the induction of ischemia was confirmed by infarct size measurement using staining by 2, 3, 5-triphenyltetrazolium chloride. To identify the differential expression of proteins between the diseased and control sides of the hippocampus, a comparative proteome analysis was performed using isobaric tags for relative or absolute quantification coupled with 2D liquid chromatography-tandem mass spectrometry analysis. 4,081 proteins were identified, 260 of which were non-redundant and showed differential expression between the three surgery groups and the control. Hierarchical cluster analysis indicated that the three surgical groups had markedly different expression patterns of these 260 proteins, including 160 upregulated and 80 downregulated proteins. A gene ontology analysis revealed 4,944 terms, among which myelin sheath and cell junction were the two most enriched items. In kyoto encyclopedia of genes and genomes database pathway analysis, ribosome was the most abundant item. A Venn diagram showing the overlap of 25 of the differentially expressed proteins quantified from the four groups and results from the kyoto encyclopedia of genes and genomes pathway analysis suggested that Epstein-Barr virus infection was the most abundant item. From the protein-protein interaction network, a total of 223 interactive proteins were predicted and used to construct a network. In conclusion, myelin sheath, cell junction, and Epstein-Barr virus infection were implicated in focal ischemia injury. Vimentin and albumin may be important proteins involved in focal ischemia injury.

Key words:  Focal ischemia injury      isobaric tags for relative or absolute quantification      gene ontology analysis      kyoto encyclopedia of genes and genomes pathway      proteomics      rat model     
Submitted:  21 June 2017      Accepted:  11 September 2017      Published:  15 May 2018     
*Corresponding Author(s):  Suping Zhang     E-mail:  supingzhang@yeah.net

Cite this article: 

Lichan He, Rui He, Ruihua Liang, Yi Li, Xiaoqiang Li, Chuqiao Li, Suping Zhang. Protein expression profiling in rat hippocampus after focal cerebral ischemia injury. Journal of Integrative Neuroscience, 2018, 17(2): 149-158.

URL: 

https://jin.imrpress.com/EN/10.31083/JIN-170047     OR     https://jin.imrpress.com/EN/Y2018/V17/I2/149

Fig. 1.  (A) A schematic diagram showing how photothrombosis induces focal ischemic injury in rats. (B) Lesion areas visualized by TTC staining. TTC staining colors: red-viable tissue, white-ischemic tissue lesions.

Fig. 2.  Hierarchical clustering of 260 differentially expressed proteins. Four main protein expression patterns were identified: the control was the protein expression atlas occurring within the first day after surgical simulation of the healthy side of the hippocampus; Day 3, 7, and 14 were the protein expression atlases occurring on the third, seventh, and fourteenth day, respectively, after surgical simulation of the diseased side of the hippocampus. Increasing red color indicates an increasing protein expression level.

Fig. 3.  Gene ontology(GO) enrichment analysis of the 260 differentially expressed proteins identified in this study.

Fig. 4.  Scatter diagram of enriched KEGG pathways of the 260 differentially expressed proteins identified in this study. Degree of enrichment was measured by Rich factor, $Q$ value, and the number of genes enriched in one pathway. The Rich factor is the ratio of the number of differential expression genes enriched in one pathway and the GO annotation number. The greater the Rich factor value, the higher the degree of enrichment. The $Q$ value is a variant of a $P$ value, for which lower values equate to significant enrichment. The $Y$-axis represents the name of pathway and the $X$-axis represents the Rich factor. The point size is the number of differentially expressed genes in one pathway, and the color of the point indicates the range of the $Q$ value.

Fig. 5.  Venn diagrams of differentially expressed proteins detected in the four different groups of this study. The overlap represents 25 differentially expressed proteins common to the four different groups.

Table 1  Significantly common differential expressed proteins in comparison of three different groups to control group
Full Name Protein Control Day 3 Day 7 Day 14 Diff
vimentin Vim 1 1.6888018 1.8868765 1.1111086 Up
albumin Alb 1 1.9026365 1.5283766 1.8301984 Up
inositol polyphosphate-4-phosphatase type I A Inpp4a 1 1.6200069 1.6290152 1.5800826 Up
Immunoglobulin Superfamily Member 1 Igsf1 1 2.3230176 1.8921153 1.7076355 Up
Annexin A2 Anxa2 1 2.2720585 2.044857 2.3424204 Up
Keratin 42 Krt42 1 0.3280528 0.2928025 0.383155 Down
adhesion G protein-coupled receptor B2 Bai2 1 2.2532386 2.0167047 2.1554665 Up
Keratin 10 Krt10 1 0.4665165 0.4376957 0.4944855 Down
heat shock protein family B (small) member 1 Hspb1 1 2.8599699 3.0146699 1.7950201 Up
Janus kinase and microtubule interacting protein 3 Jakmip3 1 1.6155215 1.825131 2.0279192 Up
keratin 1 Krt1 1 0.5069798 0.4425769 0.5083873 Down
Superantigen Speg 1 3.5801003 2.7894874 3.4058149 Up
Uridine phosphorylase 1 Upp1 1 3.988925 3.988925 3.988925 Up
BSD domain-containing 1 Bsdc1 1 2.4016067 2.4016067 2.5175142 Up
protein kinase AMP-activated non-catalytic subunit gamma 1 Prkag1 1 3.1601653 3.5112872 3.2670759 Up
potassium calcium-activated channel subfamily M regulatory beta subunit 4 Kcnmb4 1 2.964934 3.1601653 3.0908423 Up
Eukaryotic translation initiation factor 4E nuclear import factor 1 Eif4enif1 1 3.5015653 3.7217987 3.6200258 Up
ATP-binding cassette sub-family F member 1 Abcf1 1 3.8264326 3.742494 3.8370565 Up
Molecule interacting with casL-like 1 Micall1 1 3.6200258 3.8477098 3.8264326 Up
nudix hydrolase 5 Nudt5 1 2.421666 1.571345 2.2973966 Up
ATPase secretory pathway Ca2+ transporting 1 Atp2c1 1 2.2783665 2.1140359 2.044857 Up
GAR1 ribonucleoprotein Gar1 1 2.247 2.0279192 2.102346 Up
exportin for tRNA Xpot 1 2.3817139 1.9399239 2.2657676 Up
general transcription factor IIF subunit 1 Gtf2f1 1 2.2783665 1.9507109 1.760518 Up
kinase non-catalytic C-lobe domain containing 1 Kndc1 1 2.179504 2.1140359 2.2099291 Up
Fig. 6.  GO enrichment analysis of 25 differentially expressed proteins identified in this study.

Fig. 7.  Scatter diagram of enriched KEGG pathways of 25 differentially expressed proteins identified in this study. The degree of enrichment was measured by Rich factor, $Q$ value, and the number of genes enriched in one pathway. The Rich factor is the ratio of the number of differentially expressed genes enriched in one pathway and the GO annotation number. The greater the value of the Rich factor, the higher the degree of enrichment. The $Q$ value is a variant of a $P$ value, for which lower values equate to significant enrichment. The $Y$-axis represents the name of pathway and the $X$-axis represents the Rich factor. The point size is the number of differentially expressed genes in one pathway, and the color of the point indicates the range of the $Q$ value.

Fig. 8.  A protein-protein interaction network of differentially expressed proteins. The circular nodes indicate differentially expressed proteins. Arrowed nodes stand for essential proteins predicted by STRING.

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