Different expression levels of exosomal miR-200a in peritoneal dialysis effluent from patients with different peritoneal transport characteristics and prediction of its biological function

doi:10.3969/j.issn.1674-8115.2021.01.007

Abstract

Abstract: Objective

·To extract and identify the exosomes in peritoneal dialysis effluent (PDE), compare the different expression levels of PDE exosomal miR-200a in patients with different peritoneal transport characteristics, predict the potential target genes of miR-200a and analyze the related biological processes.

Methods

·Twenty stable peritoneal dialysis (PD) patients were divided into two groups, i.e., H group (high/high average) and L group (low/low average) according to the values of peritoneal equilibration test (PET). Overnight PDE 500 mL from each patient was collected, concentrated, and ultracentrifuged to obtain exosomes. Transmission electron microscope (TEM), nanoparticle tracking analysis (NTA) and Western blotting were used to identify and characterize the exosomes. Exosomal miRNAs were extracted and the expression levels of PDE exosomal miR-200a in the two groups were determined by real-time quantitative PCR. The relations between exosomal miR-200a levels and PET values or ultrafiltration volume (UF) were analyzed. The target genes of miR-200a were predicted by Targetscan, miRmap and miRWalk, and DAVID was used to perform gene ontology (GO) enrichment analysis.

Results

·The exosomes extracted from concentrated PDE by ultracentrifugation exhibited a round and bilayer membrane-enveloped vesicle structure under TEM with the diameters ranging from 50-150 nm. The exosomes also expressed the particular molecular marker CD9 and CD63. The relative expression level of PDE exosomal miR-200a in L group was higher than that of H group. The expression levels were negatively correlated with PET values (r=-0.871, P=0.000) and positively correlated with 4 h UF (r=0.448, P=0.048). But there was no relationship between miR-200a and 24 h UF (r=0.355, P=0.125). Bioinformatic results showed that there were 679 target genes of miR-200a that could be predicted by all the three databases. GO analysis suggested that these genes not only participated in positive regulation of mesenchymal cells proliferation, but also focused on ion binding, especially metal cation binding.

Conclusion

·Exosomes indeed exist in PDE. The relative expression level of exosomal miR-200a is higher in the PDE from the patients with low peritoneal dialysis transport characteristics. The relative quantity of miR-200a is negatively correlated with the values of PET and positively correlated with 4 h UF. There are abundant potential target genes of miR-200a, indicating that it may affect the peritoneal transport characteristics by different biological processes.

Key words: peritoneal dialysis effluent, exosome, miR-200a, peritoneal dialysis characteristics, bioinformatics

CLC Number:

R459.5

Yan TONG, Jun-yan FANG, Hai DENG, A-hui SONG, Pu LI, Ying-li LIU. Different expression levels of exosomal miR-200a in peritoneal dialysis effluent from patients with different peritoneal transport characteristics and prediction of its biological function[J]. JOURNAL OF SHANGHAI JIAOTONG UNIVERSITY (MEDICAL SCIENCE), 2021, 41(1): 42-48.

Figures/Tables 6

Fig 1 Identification of PDE exosomes

Tab 1 Clinical characteristics of PD patients

Item	H group （n=10）	L group （n=10）	t/U value	P value
Gender （male/female）/n	4/6	5/5	-	0.999
Age/year	61.90±14.29	61.00±8.72	0.170	0.867
Dialysis time/month	34.60±20.43	50.70±23.39	1.640	0.119
PET value	0.75±0.06	0.59±0.04	6.631	0.000
eGFR/[mL·（min·1.73 m²）^-1]	2.50 （0, 5.67）	0 （0, 4.54）	44	0.660
Kt/V/（mL·min^-1）	2.41 （1.72, 2.69）	1.79 （1.75, 1.85）	36	0.315

Fig 2 Comparison of expression of PDE exosomal miR-200a between the two groups

Fig 3 Correlation analysis between PDE exosomal miR-200a and PET values, 4 h and 24 h ultrafiltration volume

Fig 4 Prediction of target genes of miR-200a and PPI modules of EMT-related target genes expressing proteins

Fig 5 GO enrichment analysis of miR-200a target genes

[1]	Yin LIU, Tao YANG, Yu-sai XIE, Yu-zhu WANG. Screening of key genes and pathways involved in lupus nephritis based on GEO database [J]. JOURNAL OF SHANGHAI JIAOTONG UNIVERSITY (MEDICAL SCIENCE), 2021, 41(6): 749-755.
[2]	Lu-di YANG, Gao-ming WANG, Ren-hao HU, Xiao-hua JIANG, Ran CUI. Identification of core genes in pancreatic cancer progression by bioinformatics analysis [J]. JOURNAL OF SHANGHAI JIAOTONG UNIVERSITY (MEDICAL SCIENCE), 2021, 41(5): 571-578.
[3]	Ting-wei LU, Jian-jun ZHANG, Wan-tao CHEN. Mechanisms related to regulation of natural killer cell activity by exosomes derived from malignant tumor cells [J]. JOURNAL OF SHANGHAI JIAOTONG UNIVERSITY (MEDICAL SCIENCE), 2021, 41(5): 659-664.
[4]	Qi-sheng GU, Mi-li ZHANG, Can CAO, Ji-kun LI. Association of alternative splicing and tumor immune in gastric cancer based on TCGA data set [J]. JOURNAL OF SHANGHAI JIAOTONG UNIVERSITY (MEDICAL SCIENCE), 2021, 41(4): 448-458.
[5]	Ren-yan WU, Xiao-lin GUO, Deng-li HONG, Lei CHEN. Identification of potential therapeutic target genes in pediatric acute leukemia of ambiguous lineage based on bioinformatics analysis [J]. JOURNAL OF SHANGHAI JIAOTONG UNIVERSITY (MEDICAL SCIENCE), 2021, 41(3): 320-327.
[6]	Run-ze YANG, Wen-ning XU, Huo-liang ZHENG, Sheng-dan JIANG. Effects of exosomes derived from human umbilical vein endothelial cells on apoptosis of pre-chondrogenic cells stimulated by inflammatory factors [J]. JOURNAL OF SHANGHAI JIAOTONG UNIVERSITY (MEDICAL SCIENCE), 2021, 41(2): 147-153.
[7]	Yan-ru MA, Lin-hua JI, Tian-ying TONG, Yu-qing YAN, Chao-qin SHEN, Xin-yu ZHANG, Ying-ying CAO, Jie HONG, Hao-yan CHEN. Establishment and validation of prognostic prediction model of colorectal cancer based on single-cell RNA sequencing [J]. JOURNAL OF SHANGHAI JIAOTONG UNIVERSITY (MEDICAL SCIENCE), 2021, 41(2): 159-165.
[8]	Guo-qin HU, Qin-yu LÜ, Jing ZHAO, Ming-huan ZHU, Shun-ying YU, Zheng-hui YI, Jian CHEN. Association study of non-coding variant of NOS1AP gene with schizophrenia [J]. JOURNAL OF SHANGHAI JIAOTONG UNIVERSITY (MEDICAL SCIENCE), 2021, 41(1): 29-34.
[9]	GAO Jing-ze, WU Xia. CXCL9 mRNA in ovarian tumor tissue and its relations with prognosis and characteristics of immune microenvironment [J]. , 2020, 40(4): 457-.
[10]	DING Lei, GAO Cai-xia, LIU Zhao-yuan, CHEN Lei. Evaluation of a custom transcriptome sequencing library construction reagent with a small amount of cell input [J]. , 2020, 40(4): 472-.
[11]	CHEN Si, LIU Chun-liang, ZHAO Qian, SUN Hai-peng, LIU Yun-xia. Identification of hub genes and key pathways in breast cancersurvival-based bioinformatics analysis [J]. , 2020, 40(3): 294-.
[12]	XIA Shou-bing, XU Chun-jie, JIANG Chun-hui, GU Lei, SUN Long-ci, XU Qing. Bioinformatics analysis of ulcerative colitis and its malignant complications and screening of potential therapeutic drugs [J]. , 2020, 40(3): 317-.
[13]	LIN Li, LI Hai-bo, XIA Fan, ZHOU Ji-xue, GUO Xiao-kui, ZHANG Shu-lin. Evaluation of exosome-derived miRNA-323a-3p human plasma as a potential biomarker for tuberculosis [J]. , 2020, 40(2): 171-.
[14]	ZHANG Wei-ran1, 2, LIN Xue-feng3, LI Xin2, ZHANG Hao2, WANG Meng2, SUN Wei2, HAN Xing-peng2, SUN Da-qiang1, 4. Transcriptional identification of potential biomarkers of lung adenocarcinoma [J]. JOURNAL OF SHANGHAI JIAOTONG UNIVERSITY (MEDICAL SCIENCE), 2020, 40(12): 1598-1606.
[15]	YU Meng-na1, YANG Biao2, YANG Li-zhen1. Prediction and bioinformatics analysis of hsa-miR-223-3p target genes related to diabetes mellitus [J]. JOURNAL OF SHANGHAI JIAOTONG UNIVERSITY (MEDICAL SCIENCE), 2020, 40(11): 1477-1484.