期刊
JOURNAL OF PROTEOME RESEARCH
卷 19, 期 9, 页码 3644-3651出版社
AMER CHEMICAL SOC
DOI: 10.1021/acs.jproteome.0c00138
关键词
tear; extracellular vesicles; MALDI-TOF-MS; dry eye syndrome
资金
- National Natural Science Foundation of China [81771984, 31741036, 21904098]
- Zhejiang Provincial and Ministry of Health Research Fund for Medical Sciences [WKJ-ZJ-1707, WKJ-ZJ-1910]
- Wenzhou Institute of Biomaterials and Engineering [WIBEZD2017006-05]
- Leading Science and Technology Innovation Talent of Zhejiang Provincial Ten Thousand Talent Project [2017R52050]
- Wenzhou Medical University [89218012, 89219012]
The tear is a biological fluid that has the diagnostic potential for ocular diseases. Extracellular vesicles (EVs), widly detected in various biofluids including tears, are nanoparticles released by living cells and considered as promising detection sources for noninvasive liquid biopsy. Understanding the roles of tears and tear-EVs in ocular diseases such as dry eye can facilitate the studies of clinical diagnosis, which usually entails detecting such liquid objects with a rapid and effective method. In this study, we used a mass spectrometry-based strategy to analyze peptidome/proteome profiles of tears and EVs for rapid dry eye diagnosis. Nanosized EVs were isolated from tears of both healthy control (HC) individuals and dry eye syndrome (DES) patients, and the tear compositions were further analyzed by tracking their fingerprints with matrix-assisted laser desorption ionization/time-of-flight mass spectrometry. The fingerprints of tear-EVs could be observed in a dose-dependent manner and tears, allowing for comparison of the discriminant peaks between tears and EVs. By analyzing these peaks, the fingerprints of both tear and tear-EVs were showed to have the capability of distinguishing patients with DES from HC donors and providing an efficient way for screening potential DES biomarkers. The proposed tear and EV fingerprinting approach is expected to be a potential tool in the rapid diagnosis of ocular diseases and in-depth research on pathogenesis. Data are available via ProteomeXchange with identifier PXD020217.
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