Quantitative proteomics identifies the core proteome of exosomes with syntenin-1 as the highest abundant protein and a putative universal biomarker.
Quantitative proteomics identifies the core proteome of exosomes with syntenin-1 as the highest abundant protein and a putative universal biomarker.
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定量蛋白质组学鉴定了外泌体的核心蛋白质组,其中syntenin-1是丰度最高的蛋白质,也是公认的通用生物标志物。
DOI:
10.1038/s41556-021-00693-y
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发表时间:
2021-06
影响因子:
21.3
通讯作者:
中科院分区:
文献类型:
--
作者:
Exosomes are extracellular vesicles derived from the endosomal compartment with potential involvement in intercellular communication. We found that frequently used biomarkers of exosomes are heterogeneous and do not exhibit universal utility across different cell types. To uncover ubiquitous and abundant proteins that can serve as biomarkers of exosomes, we employed an unbiased and quantitative proteomic approach based on Super-SILAC coupled to high-resolution mass spectrometry. In total, 1,212 proteins were consistently quantified in the proteome of exosomes irrespective of the cellular source or isolation method. A cohort of 22 proteins were universally enriched, and 15 proteins consistently depleted in the proteome of exosomes when compared to cells. Among the enriched proteins, we identified biogenesis-related, GTPases, and membrane proteins, such as CD47 and ITGB1. The cohort of depleted proteins in exosomes was predominantly composed of nuclear proteins. We identified Syntenin-1 as the highest consistently abundant protein in exosomes from distinct cellular origins, which was also present in exosomes across different species and biofluids, with potential utility as a putative universal biomarker candidate for exosomes. Our study provides a comprehensive quantitative atlas of core proteins ubiquitous to exosomes that can serve as a resource for the scientific community dedicated to the study of exosomes.
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DOI:
10.1126/science.aau6977
发表时间:
2020-02-07
期刊:
Science (New York, N.Y.)
影响因子:
--
作者:
Kalluri R;LeBleu VS
通讯作者:
LeBleu VS
影响因子:
3.7
作者:
Altadill, Tatiana;Campoy, Irene;Cheema, Amrita K.
通讯作者:
Cheema, Amrita K.
影响因子:
13.6
作者:
Gonzales, Patricia A.;Pisitkun, Trairak;Knepper, Mark A.
通讯作者:
Knepper, Mark A.
影响因子:
11.2
作者:
Hwang, Rosa F.;Moore, Todd;Logsdon, Craig D.
通讯作者:
Logsdon, Craig D.
影响因子:
4.4
作者:
Cox, Juergen;Neuhauser, Nadin;Mann, Matthias
通讯作者:
Mann, Matthias