CHINESE JOURNAL OF PARASITOLOGY AND PARASITIC DISEASES ›› 2024, Vol. 42 ›› Issue (3): 295-302.doi: 10.12140/j.issn.1000-7423.2024.03.003

• ORIGINAL ARTICLES • Previous Articles     Next Articles

MicroRNA differential expression profiles and their diagnostic value in the sheep infected with Echinococcus granulosus

WU Yixuan1(), GUO Xiaola2, CHEN Yixia1,*()   

  1. 1 Life Science and Engineering College of Northwest Minzu University, Lanzhou 730030, Gansu, China
    2 National Key Laboratory of Animal Disease Prevention and Control, Lanzhou Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Gansu Provincial Key Laboratory of Animal Parasitic Diseases, Lanzhou 730046, China
  • Received:2024-02-01 Revised:2024-04-30 Online:2024-06-30 Published:2024-07-16
  • Supported by:
    National Natural Science Foundation of China(32260874);State Key Laboratory of Sheep Genetic Improvement and Healthy Production(MYSKLKF202003)

Abstract:

Objective To screen the miRNAs differential expression profiles in the serum from the sheep infected with Echinococcus granulosus and evaluate their potential values in the diagnosis of echinococcosis. Methods 10 sheep were divided into an infection group (5) and a control group (5). The E. granulosus infected-group was given 2 000 eggs per sheep by gavage, and the control group of sheep was given saline. Sixty days after infection, peripheral blood was collected from both groups, and total serum RNA was extracted. Small RNA high-throughput sequencing was used to identify and screen differentially expressed miRNAs. Five differentially expressed miRNAs were validated by real-time quantitative PCR (qRT-PCR). MedCale software was used to draw receiver operating characteristic (ROC) curves, calculate the area under the curve (AUC), and select miRNAs with potential diagnostic values (AUC ≥ 0.7). qRT-PCR was used to detect the relative transcription levels of miRNAs with potential diagnostic values in 15 serum samples of sheep infected with E. granulosus, and the AUC, sensitivity, and specificity were calculated.Target genes of the differentially expressed miRNAs were predicted using miRanda and RNA hybrid software, and gene ontology (GO) enrichment analysis and Kyoto encyclopedia of genes and genomes (KEGG) pathway enrichment analysis were conducted. Results Sequencing results identified a total of 26 differentially expressed miRNAs, including 21 upregulated and 5 downregulated. The qRT-PCR results showed that the relative expression levels of five relatively abundant differentially expressed miRNAs in infection group, including oar-miR-191, oar-let-7a, oar-miR-150, oar-miR-26a, and oar-miR-21, were 2.22 ± 0.31, 2.12 ± 0.24, 2.42 ± 0.35, 2.09 ± 0.15, and 3.23 ± 0.83, respectively, which were higher than the control group (1.00 ± 0.11). There was a statistically significant difference in the relative expression levels of oar-miR-191, oar-let-7a, oar-miR-150, and oar-miR-26a compared to the control group (t = 3.960, 4.766, 4.096, 9.126; all P < 0.05). ROC curve analysis revealed that the AUC of oar-let-7a, oar-miR-26a, and oar-miR-21 were all less than 0.7. the AUC of oar-miR-191 was 0.858, with a 95% confidence interval (95% CI) of 0.719-0.997 (P < 0.05), indicating its high diagnostic value, with a sensitivity of 71.43% and specificity of 85.71%. The AUC of oar-miR-150 was 0.738, with a 95% CI of 0.550-0.926 (P < 0.05), indicating its diagnostic significance, with a sensitivity of 53.33% and specificity of 86.67%. The results of the GO significance enrichment analysis showed that miRNA target genes with transcriptional levels increased by more than twice were mainly related to stress response, cell surface molecules, protein binding, and other functions. The KEGG pathway enrichment analysis results indicate that miRNA target genes with at least a two-fold increase in transcription levels are mainly enriched in key signalling pathways such as inflammation response, autophagy, and apoptosis. Conclusion The oar-miR-191 and oar-miR-150 screened in this study have good sensitivity and specificity in the diagnosis of E. granulosus infection, suggesting their potential as a biomarker for the diagnosis of echinococcosis.

Key words: Echinococcus granulosus, MicroRNA, Serum, High-throughput sequencing, ROC curve

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