Glycyrrhizic Acid against Mycoplasma gallisepticum -Induced Inflammation and Apoptosis Through Suppressing the MAPK Pathway in Chickens.
Yingjie WangLulu WangRonglong LuoYingfei SunMengyun ZouTengfei WangQiao GuoXiuli PengPublished in: Journal of agricultural and food chemistry (2022)
Mycoplasma gallisepticum (MG) is the primary pathogen of chronic respiratory diseases (CRDs) in chickens. In poultry production, antibiotics are mostly used to prevent and control MG infection, but the drug resistance and residue problems caused by them cannot be ignored. Glycyrrhizic acid (GA) is derived from licorice, a herb traditionally used to treat various respiratory diseases. Our study results showed that GA significantly inhibited the mRNA and protein expression of pMGA1.2 and GapA in vitro and in vivo. Furthermore, the network pharmacology study revealed that GA most probably resisted MG infection through the MAPK signaling pathway. Our results demonstrated that GA inhibited MG-induced expression of MMP2/MMP9 and inflammatory factors through the p38 and JUN signaling pathways, but not the ERK pathway in vitro. Besides, histopathological sections showed that GA treatment obviously attenuated tracheal and lung damage caused by MG invasion. In conclusion, GA can inhibit MG-triggered inflammation and apoptosis by suppressing the expression of MMP2/MMP9 through the JNK and p38 pathways and inhibit the expression of virulence genes to resist MG. Our results suggest that GA might serve as one of the antibiotic alternatives to prevent MG infection.
Keyphrases
- pet ct
- signaling pathway
- oxidative stress
- pi k akt
- poor prognosis
- diabetic rats
- induced apoptosis
- cell migration
- cell cycle arrest
- cell death
- epithelial mesenchymal transition
- mental health
- endoplasmic reticulum stress
- pseudomonas aeruginosa
- escherichia coli
- staphylococcus aureus
- respiratory tract
- gene expression
- long non coding rna
- cell proliferation
- cystic fibrosis
- dna methylation
- candida albicans
- single cell
- endothelial cells
- bioinformatics analysis