Identification and characterization of microRNAs, especially gga-miR-181b-5p, in chicken macrophages associated with avian pathogenic E. coli infection

ABSTRACT

Avian pathogenic E. coli (APEC) is a common pathogen in the poultry industry, which can cause substantial economic losses. Recently, emerging evidence showed that miRNAs were involved in various viral and bacterial infections. To elucidate the role of miRNAs in chicken macrophages in response to APEC infection, we attempted to investigate the miRNAs expression pattern upon APEC infection via miRNA-seq, and to identify the molecular mechanism of the important miRNAs by using RT-qPCR, western blotting, dual-luciferase reporter assay, and CCK-8. The results showed that a total of 80 differentially expressed (DE) miRNAs were identified in comparison of APEC vs. wild-type group, which corresponded to 724 target genes. Moreover, the target genes of the identified DE miRNAs were mainly significantly enriched in the MAPK signalling pathway, autophagy-bird, mTOR signalling pathway, ErbB signalling pathway, Wnt signalling pathway, and TGF-beta signalling pathway. Remarkably, gga-miR-181b-5p is able to participate in host immune and inflammatory responses against APEC infection via targeting of TGFBR1 to modulate the activation of TGF-beta signalling pathway. Collectively, this study provides a perspective of miRNA expression patterns in chicken macrophages upon APEC infection. These findings provide insight into miRNAs against APEC infection, and gga-miR-181b-5p might be a potential target for treating APEC infection.

KEYWORDS:

• Macrophage
• chicken
• avian pathogenic E. coli
• gga-miR-181b-5p
• TGFBR1
• miRNA

Disclosure statement

No potential conflict of interest was reported by the authors.

Data availability statement

All data generated or analysed for this study are included in this article and its supplementary files. The raw sequence reads were deposited into NCBI SRA database under accession no. PRJNA840858.

Additional information

Funding

This research was funded by the National Natural Science Foundation of China [grant number 31802053]; Natural Science Foundation of Jiangsu Province [grant number BK20180907]; China Postdoctoral Science Foundation [grant number 2019M661950]; Jiangsu Postdoctoral Science Research Foundation [grant number 137070510]; Graduate Student Research and Practice Innovation Program of Jiangsu Province China [grant number SJCX22_1796].