Healthy aged male C57BL/6 mice (n = 22, aged 18 months, weights from 40.2g to 46.6 g) were purchased from SiBeiFu Experimental Animal Science and Technology Co. Ltd (Beijing, China. Permit Number: SCXK (Jing) 2016-0002). The mice were individually housed in an air-conditioned room with a temperature of 24±4℃ and 55-65% humidity, under a standard 12h-12h light-dark cycle (lights on 6 AM to 6 PM), and had free access to standard food and water. The mice were acclimatized for 1 week before the experiment. The protocol of animal experiment was approved by the Animal Care Committee of the Chinese People’s Liberation Army General Hospital (Beijing, China).
According to the protocol of our research work, all mice were euthanized before we were prepared to obtain hippocampal tissue. When those mice scheduled for obtaining the hippocampal tissue, one by one, they were put into an anesthetic introduction chamber and were anesthetized with isoflurane into a deeper level. The introduction chamber was kept clean to minimize the odor that might distress animals subsequently anesthetized. A rodent anesthesia machine were used (Model: ABM09-002, Reward, Shenzhen) and the anesthetic used was isoflurane. The concentration of the vaporizer was set at 3% and the oxygen flow rate was set at 3L/min during anesthesia. All mice were deeply anesthetized based on following signs: the slowed rising and falling of chest, no respond to toe pinch, and corneal reflex disappeared. Then, the mice were decapitated by using a guillotine in a uniformly instantaneous manner. The brain was instantly dissected on ice, and the hippocampal tissue was obtained and put into liquid nitrogen. All the mice were decapitated 24h after operation. The detailed time line of the euthanization of study animals is shown in the Supplemental Figure 1.
Mice were numbered by weight and randomly divided into two groups: Surgery and Sham, with 11 mice per group. The mice in the Surgery group were exposed to abdominal surgery under local bupivacaine anesthesia (according to the protocol from Xu et al. ), whereas those in the Sham group did not suffer from the anesthesia and surgery. At 24 hours after the surgery, three mice were randomly selected from each group and sacrificed. The hippocampus tissue was removed immediately and stored in the sterile tube (RNase Free) in liquid nitrogen.
Morris Water Maze (MWM)
The MWM test, as a hippocampal-dependent test, was applied to evaluate the spatial learning, spatial memory and cognitive flexibility for the mice . The cognitive function of remaining 8 mice in each group were assessed by the MWM experiment. The water maze was a black circular tank (120 cm in diameter and 50cm in depth) and filled with water of 22±1℃ to a depth of 35 cm. Several visual objects were installed above the pool to help mice identify the direction. The maze was divided into four quadrants, an invisible platform (10 cm in diameter) was placed 1.5 cm blew the water surface in the first quadrant (target quadrant). The whole experiment was performed under a dark and quite environment.
During the experiment, mice were released into the water facing the wall of the tank from one of the four quadrants. The mice were trained to find the hidden platform and climb onto it within 60 seconds. The animals were allowed to stay on the platform for at least 10 seconds after each trial. If the mice were unable to find the platform in 60 seconds, it was then placed on the platform for 10 second. After that, the mice were put back to the cage and the second mouse was tested on trial 1. This rotation was repeated until all animals completed trial 1. Subsequently, the process was repeated for subsequent trials until 4 trials completed per day for 5 consecutive days. At 6th day, the platform was removed, and the mice were sent to evaluate their reference memory by being released from the third quadrant. The swimming speed, platform-site crossing numbers, dwelling time in the target quadrant and the escape latency were recorded.
Total miRNAs were extracted from the hippocampal tissue (n = 3 from each group) by the miRcutemiRNA kit (TIANGEN, DP501). The nanodrop was utilized to determine the miRNA concentration of each sample according to the optical absorption at 260 nm and the gel electrophoresis was used to detect the miRNA integrity.
Microarray and Statistical Analysis
MiRNA microarray (Affymetrix miRNA 4.0) was conducted by PREMEDICAL Co. Ltd (Beijing, China). The microarray was utilized to find the aberrant expression of miRNAs from the POCD model mice to normal mice. Fluorescent signals were transformed from picture signal to digital data based on the degree of fluorescent for each probe, and then the data were saved as .DAT files by AGCC software (Affymetrix Genechip Command Console Software). The differential expression analyses were performed by using Transcriptome Analysis Console (v 4.0) and using an FDR correction for multiple testing. Considering that none of the identified miRNAs reached the threshold of adjusted significance, we chose the threshold of a nominal P value of < 0.05 for further replication.
The miRNA expression profile data of replication cohort were downloaded from the Gene Expression Omnibus (GEO) database (Accession number: GSE95070; https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE95070), which were deposited by Wei et al.  from the Chaoyang Hospital. With regard to this dataset, hippocampus tissues of 10 mice (5 per group) were dissected, and the different miRNA expression levels between two groups were detected by Affymetrix miRNA 4.0 as well. Similarly, the differential expression analysis was performed by using the Transcriptome Analysis Console (v 4.0) with same parameter.
Quantitative Real-time PCR
Expression level of the most significantly aberrant miRNA, mmu-miR-190a-3p, was validated by using real-time PCR assay. Reverse transcription reaction was performed with M-MLV Reverse Transcriptase kit (Takara Code: D2639A) based on the manufacturers’ protocol. Real-time PCR was performed with SYBR Premix Ex Taq kit (Takara Code: DRR041A). The miRNA expression level was evaluated relative to the expression of U6 of the 2 -ΔΔCt. The primers for miRNA mmu-miR-190a-3p are listed in Supplemental Table 1.
Data were analyzed using GraphPad PRISM (version 6; GraphPad Prism Software, Inc. San Diego, CA, USA). Measurements of dwelling time, number of grossing, escape latency, and speed in MWM test among preoperative and postoperative mice were analyzed by using Student’s t-test. qRT-PCR data were also analyzed with Student’s t-test. A P value of < 0.05 was considered statistically significant.
The genes and miRNAs expression data of GSE73507 were acquired from GEO database (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE73507). The GSE73507 dataset was designed to gain insight into the relationship between the CAG repeat length and the Huntington disease . By excluding the expression data from other brain regions and mutant mice, we only downloaded the mRNAs and miRNAs expression data from hippocampus tissue of wild type mice for our analysis (n = 24). Because of recent progress of alignment and mapping approaches, which are capable of detecting the transcriptome profiles in a more accurate and effective way compared with former tools . The RNA and miRNA sequencing data were aligned and mapped to the GRCm38 version of mice genome using Hisat2 (v 2.1.0) and StringTie (v 1.3.4) , and the miRNA expression data by miRDeep2 (v 18.104.22.168) . A total of 16,425 mRNAs and 1,057 miRNAs were correctly mapped onto the mouse genome. Threshold for filtering out genes expressed at low levels was set to greater than 1 of the average fpkm. After the filtering process, 13,241 mRNAs and 546 miRNAs were included for WGCNA analysis.
The R package of WGCNA was used to construct the network modules of highly correlated transcripts subsets . This approach aims to find the gene pairs with similar expression patterns and highly topological overlap, and it represents a valuable tool for identifying promising target genes and understanding the pathology of complex disorders . In order to provide a comprehensive expression pattern among the mRNAs and miRNAs and detect the interaction of the transcripts, we performed our co-expression analysis by combined the mRNA and miRNA dataset together. First, we constructed a weighted network according to the gene pair correlations among all the mRNAs and miRNAs; second, by using the default parameters to assess the network interconnection, 25 specific modules were hierarchically clustered. These module sizes were from 50 to 17,500 genes. In the network we only showed a connection of the corresponding topological overlap is above a threshold of 0.05 with mmu-miR-190a-3p in the red module (n = 169). The visual gene-gene network plot was displayed by using the Cytoscape version 3.5.1 (https://www.cytoscape.org/) .
Concordance between the highly correlated mRNAs with mmu-miR-190a-3p and those not involved in the module genes were assayed by performing density plots. We compared the distribution of Pearson correlation coefficients of the 169 potential interaction targets of mmu-miR-190a-3p to a control distribution of non-predicted targets which consisted of all other mRNAs that we mapped. The mRNAs which were possibly modulated by mmu-miR-190a-3p displayed more significant negative correlation compared with the control.
ClueGO (v. 2.3.4), a plug-in software of Cytoscape, was used to decipher the pathways network and determine their biological functions for the candidate genes . The potential biological functions of each gene set were annotated using the pathway profiles of Kyoto Encyclopedia of Genes and Genomes (KEGG) .
We conducted further analysis to screen the most potential regulated genes by mmu-miR-190a-3p. We first employed the miRWalk3.0 (http://mirwalk.umm.uni-heidelberg.de/) to predict the target genes regulated by mmu-miR-190a-3p . By using a stringent standard to obtain reliable targets (Supplemental Table 2), we set the parameters for target prediction in the miRwalk3.0 as following: 1) Binding over than 0.9; 2) Energy less than -16; and 3) Accessibility less than 0.05. Second, using these predicted targets for mmu-miR-190a-3p to overlap with the WGCNA results of those highly correlated genes. Finally, we conducted a protein-protein interaction network analysis for those overlapped genes according to the STRING v 10.5 under default parameters (https://string-db.org/cgi/input.pl). By combining the gene-gene interaction result, prediction targets and the protein-protein interaction analysis, we attempted to find the high degree receivable genes regulated by mmu-miR-190a-3p.