Title:Proteomic Analysis by 4D Label-free MS-PRM Provides Insight into the
Role and Regulatory Mechanisms of IL-25 in NK Cells
Volume: 30
Issue: 10
Author(s): Juan Feng*, Luoyao Huang, Shuaipeng Yang, Jiasheng Pan, Xiangxing Zhu and Dongsheng Tang
Affiliation:
- Guangdong Provincial Engineering and Technology Research Center for Gene Editing, School of Medicine, Foshan University, 528000, Foshan, China.
Keywords:
Proteomics, mass spectrum, PRM, IL-25, NK cells, oxidative phosphorylation, anti-inflammatory, thermogenesis.
Abstract:
Background: NK cells play an important role in immune response, immune surveillance,
and metabolism regulation. Therefore, NK cells are involved in the occurrence and development
of various diseases, such as infectious diseases, cancer, obesity, and diabetes. IL-25 is a special
member of the IL-17 family with anti-inflammatory function. IL-25 can regulate inflammatory
response and metabolism via various immune cells; however, the role and regulatory mechanism of
IL-25 in NK cells are still unclear.
Method: In this study, we investigate the role of IL-25 in NK-cell protein profile via 4D label-free
mass spectrum and validate the differential proteins via PRM analysis. In addition, GO analysis,
KEGG analysis, and other bioinformatic analysis methods are used to explore the enriched function
and signal pathway of differentially expressed proteins.
Result and Discussion: The GO and KEGG analyses suggest that IL-25 may affect the processes,
such as metabolism, thermogenesis, and oxidative phosphorylation of NK cells. There are 7 down-regulated
proteins (NCR1, GZMB, PRF1, KLRC1, NDUFA11, LAMTOR5, and IKBIP) and 1 up-regulated protein (PSMD7) in IL-25-treated NK cells versus the control group for PRM validation.
Our results indicate that IL-25 may regulate metabolism and other biological processes via
NK cells, which will be beneficial in revealing the role and regulatory mechanisms of IL-25 in NK
cells in various diseases.
Conclusion: Proteomics combined with bioinformatic analysis will help to mine more information
hidden behind mass spectrometry data and lay the foundation for finding clinical biomarkers and
mechanisms of diseases.