China Animal Husbandry and Veterinary Medicine ›› 2025, Vol. 52 ›› Issue (5): 1955-1965.doi: 10.16431/j.cnki.1671-7236.2025.05.002

• Biotechnology • Previous Articles    

The Blood Proteomics Study and Bioinformatics Analysis of Mucus-Excreting Giant Pandas

XIA Maohua, LI Xiangxiang, LIU Jinpeng, GUO Xinxin, XU Haihong, LIU Yanhui, DAI Chunkuo, LI Xi, WANG Yunsheng   

  1. Beijing Zoo, Beijing Key Laboratory of Captive Wildlife Technologies, Beijing 100044, China
  • Received:2024-09-11 Published:2025-04-27

Abstract: 【Objective】 The proteomic characteristics of serum in captive giant pandas during mucus-excreting and non-mucus-excreting periods were investigated to elucidate the molecular mechanisms underlying mucus excretion and provide scientific support for the health management of captive giant pandas.【Method】 Eight captive giant pandas were selected for this study,with one blood sample collected from each panda during both the mucus-excreting period and the non-mucus-excreting period.The samples were then divided into the mucus-excreting period group (NY) and the non-mucus-excreting period group (Con).Blood was collected from the mucus-excreting group within 2 h after mucus excretion,while for the non-excreting group,blood collection occurred at least 30 days after the last mucus-excreting period.After blood proteins were extracted and digested,the resulting peptides were desalted and quantified.Data-independent acquisition (DIA) was used for liquid chromatography-mass spectrometry (LC-MS/MS) analysis,and the data were processed using SpectronautTM software.Data analysis was conducted on the Majorbio Cloud Platform,with criteria for screening differentially expressed proteins set at P<0.05 and a FoldChange (FC)>1.2 or<0.8.These proteins were further analyzed through clustering,GO functional enrichment analysis,metabolic pathway enrichment analysis,and protein interaction analysis with bioinformatics databases.Protein data were validated by parallel reaction monitoring (PRM),with peptide quantification values normalized according to reference peptides.Statistical significance was set at P<0.05,and DIA results were compared with PRM validation outcomes.【Result】 A total of 273 proteins were identified in the blood samples of giant pandas,with 258 proteins shared between groups,12 proteins unique to the mucus-excreting period,and 3 proteins unique to the non-mucus-excreting period.Analysis of differential protein expression revealed 25 differentially expressed proteins between the mucus-excreting and non-mucus-excreting groups,including 7 up-regulated proteins and 18 down-regulated proteins.The differentially expressed proteins were found to be primarily involved in biological processes such as cell growth,immune response and inflammatory response,with significant enrichment observed in the Rap1,Estrogen,phosphatidylinositol 3-kinase-protein kinase B (PI3K-Akt),and Relaxin signaling pathways.Through protein interaction analysis,A0A7N5KNP1(FBLN5),D2GWB9(THBS1),D2HUL0(SERPIND1) and D2HHD2(ITGA2) were identified as key proteins,showing significant changes during the mucus-excreting period.【Conclusion】 Twenty-five differentially expressed proteins were identified in the serum of giant pandas during mucus excretion compared to the non-mucus-excreting period.These proteins were primarily enriched in the PI3K-Akt,Rap1,Estrogen and Relaxin signaling pathways,with core proteins A0A7N5KNP1(FBLN5),D2GWB9(THBS1),D2HUL0(SERPIND1) and D2HHD2(ITGA2) found to play important roles in the mucus excretion phenomenon in giant pandas.

Key words: giant panda; serum proteome; mucus-excreting; data-independent acquisition (DIA); parallel reaction monitoring

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