Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2021 Nov 9:14:1355-1366.
doi: 10.2147/JAA.S330054. eCollection 2021.

Dynamic Urinary Proteome Changes in Ovalbumin-Induced Asthma Mouse Model Using Data-Independent Acquisition Proteomics

Weiwei Qin  1   2 , Ting Wang  2 , Guangwei Liu  3 , Lixin Sun  1 , Wei Han  4 , Youhe Gao  2
Affiliations

Dynamic Urinary Proteome Changes in Ovalbumin-Induced Asthma Mouse Model Using Data-Independent Acquisition Proteomics

Weiwei Qin et al. J Asthma Allergy. .

Abstract

Background: In this work, we aim to investigate dynamic urinary proteome changes during asthma development and to identify potential urinary protein biomarkers for the diagnosis of asthma.

Methods: An ovalbumin (OVA)-induced mouse model was used to mimic asthma. The urinary proteome from asthma and control mice was determined using data-independent acquisition combined with high-resolution tandem mass spectrometry.

Results: Overall, 331 proteins were identified, among which 53 were differentially expressed (26, 24, 14 and 20 on days 2, 8, 15 and 18, respectively; 1.5-fold change, adjust P<0.05). Gene Ontology annotation of the differential proteins showed that the acute-phase response, innate immune response, B cell receptor signaling pathway, and complement activation were significantly enriched. Protein-protein interaction network revealed that these differential proteins were partially biologically connected in OVA-induced asthma, as a group. On days 2 and 8, after two episodes of OVA sensitization, six differential proteins (CRAMP, ECP, HP, F2, AGP1, and CFB) were also reported to be closely associated with asthma. These proteins may hold the potential for the early screening of asthma. On days 15 and 18, after challenged with 1% OVA by inhalation, seven differential proteins (VDBP, HP, CTSE, PIGR, AAT, TRFE, and HPX) were also reported to be closely associated with asthma. Thus, these proteins hold the potential to be biomarkers for the diagnosis of asthma attack.

Conclusion: Our results indicate that the urinary proteome could reflect dynamic pathophysiological changes in asthma progression.

Keywords: OVA-induced asthma; data-independent acquisition; mice; proteome; urine.

PubMed Disclaimer

Conflict of interest statement

The authors declare that they have no competing interests.

Figures

Figure 1
Figure 1
The ELISA and flow cytometric analysis results. (A) Blood samples were collected and level of serum IgE was measured (n=6). (B) The ration of eosinophils in bronchoalveolar lavage fluid (BALF) in asthmatic mice. *p<0.001 compared to control group.
Figure 2
Figure 2
Pathological results of hematoxylin and eosin (HE) staining in the lungs of asthma and control mice. (A) The lung of normal control mice (20×). (B) The lung of normal control mice (40×). (C) The lung of asthmatic mice (20×). (D) The lung of asthmatic mice (20×).
Figure 3
Figure 3
Vein diagram of the differential urinary proteins in asthmatic mice compared with control mice.
Figure 4
Figure 4
GO analysis of the differential proteins at days 2, 8, 15 and 18 in OVA-induced mice. (A) Biological process; (B) Cellular component; (C) Molecular function.
Figure 5
Figure 5
STRING PPI network analysis of the 53 differential proteins in OVA-induced asthma mouse model. The average node degree is 3.84, average local clustering coefficient is 0.443, and PPI enrichment p-value is <1.0e-16.
See this image and copyright information in PMC

Similar articles

See all similar articles

Cited by

References

    1. Bousquet J, Humbert M. GINA 2015: the latest iteration of a magnificent journey. Eur Respir J. 2015;46(3):579–582. doi:10.1183/13993003.01084-2015 - DOI - PubMed
    1. To T, Stanojevic S, Moores G, et al. Global asthma prevalence in adults: findings from the cross-sectional world health survey. BMC Public Health. 2012;12(1):204. doi:10.1186/1471-2458-12-204 - DOI - PMC - PubMed
    1. Lai CK, Beasley R, Crane J, et al. Global variation in the prevalence and severity of asthma symptoms: phase three of the International Study of Asthma and Allergies in Childhood (ISAAC). Thorax. 2009;64(6):476–483. doi:10.1136/thx.2008.106609 - DOI - PubMed
    1. Abramson MJ, Perret JL, Dharmage SC, McDonald VM, McDonald CF. Distinguishing adult-onset asthma from COPD: a review and a new approach. Int J Chron Obstruct Pulmon Dis. 2014;9:945–962. doi:10.2147/COPD.S46761 - DOI - PMC - PubMed
    1. Moore WC, Meyers DA, Wenzel SE, et al. Identification of asthma phenotypes using cluster analysis in the severe asthma research program. Am J Respir Crit Care Med. 2010;181(4):315–323. doi:10.1164/rccm.200906-0896OC - DOI - PMC - PubMed