scholarly journals Comprehensive Proteomic Analysis of Human Milk-derived Extracellular Vesicles Unveils a Novel Functional Proteome Distinct from Other Milk Components

2016 ◽  
Vol 15 (11) ◽  
pp. 3412-3423 ◽  
Author(s):  
Martijn J.C. van Herwijnen ◽  
Marijke I. Zonneveld ◽  
Soenita Goerdayal ◽  
Esther N.M. Nolte – 't Hoen ◽  
Johan Garssen ◽  
...  
Endocrinology ◽  
2021 ◽  
Vol 162 (4) ◽  
Author(s):  
Eric R Barros ◽  
Juan Pablo Rigalli ◽  
Alejandra Tapia-Castillo ◽  
Andrea Vecchiola ◽  
Morag J Young ◽  
...  

Abstract Context Primary aldosteronism (PA) represents 6% to 10% of all essential hypertension patients and is diagnosed using the aldosterone-to-renin ratio (ARR) and confirmatory studies. The complexity of PA diagnosis encourages the identification of novel PA biomarkers. Urinary extracellular vesicles (uEVs) are a potential source of biomarkers, considering that their cargo reflects the content of the parent cell. Objective We aimed to evaluate the proteome of uEVs from PA patients and identify potential biomarker candidates for PA. Methods Second morning spot urine was collected from healthy controls (n = 8) and PA patients (n = 7). The uEVs were isolated by ultracentrifugation and characterized. Proteomic analysis on uEVs was performed using LC-MS Orbitrap. Results Isolated uEVs carried extracellular vesicle markers, showed a round shape and sizes between 50 and 150 nm. The concentration of uEVs showed a direct correlation with urinary creatinine (r = 0.6357; P = 0.0128). The uEV size mean (167 ± 6 vs 183 ± 4nm) and mode (137 ± 7 vs 171 ± 11nm) was significantly smaller in PA patients than in control subjects, but similar in concentration. Proteomic analysis of uEVs from PA patients identified an upregulation of alpha-1-acid glycoprotein 1 (AGP1) in PA uEVs, which was confirmed using immunoblot. A receiver operating characteristic curve analysis showed an area under the curve of 0.92 (0.82 to 1; P = 0.0055). Conclusion Proteomic and further immunoblot analyses of uEVs highlights AGP1 as potential biomarker for PA.


1997 ◽  
Vol 90 (1-2) ◽  
pp. 77-84 ◽  
Author(s):  
K Iwadate ◽  
N Sakamoto ◽  
S.H Park ◽  
M Doy ◽  
H Iwase ◽  
...  

2020 ◽  
Vol 9 (1) ◽  
pp. 1757209 ◽  
Author(s):  
Dongsic Choi ◽  
Gyeongyun Go ◽  
Dae‐Kyum Kim ◽  
Jaewook Lee ◽  
Seon‐Min Park ◽  
...  

Author(s):  
Montserrat Baldan-Martin ◽  
Fernando de la Cuesta ◽  
Gloria Alvarez-Llamas ◽  
Gema Ruiz-Hurtado ◽  
Luis M. Ruilope ◽  
...  

2020 ◽  
Vol 21 (24) ◽  
pp. 9425
Author(s):  
Sebastian Sjoqvist ◽  
Kentaro Otake ◽  
Yoshihiko Hirozane

There is a lack of reliable biomarkers for disorders of the central nervous system (CNS), and diagnostics still heavily rely on symptoms that are both subjective and difficult to quantify. The cerebrospinal fluid (CSF) is a promising source of biomarkers due to its close connection to the CNS. Extracellular vesicles are actively secreted by cells, and proteomic analysis of CSF extracellular vesicles (EVs) and their molecular composition likely reflects changes in the CNS to a higher extent compared with total CSF, especially in the case of neuroinflammation, which could increase blood–brain barrier permeability and cause an influx of plasma proteins into the CSF. We used proximity extension assay for proteomic analysis due to its high sensitivity. We believe that this methodology could be useful for de novo biomarker discovery for several CNS diseases. We compared four commercially available kits for EV isolation: MagCapture and ExoIntact (based on magnetic beads), EVSecond L70 (size-exclusion chromatography), and exoEasy (membrane affinity). The isolated EVs were characterized by nanoparticle tracking analysis, ELISA (CD63, CD81 and albumin), and proximity extension assay (PEA) using two different panels, each consisting of 92 markers. The exoEasy samples did not pass the built-in quality controls and were excluded from downstream analysis. The number of detectable proteins in the ExoIntact samples was considerably higher (~150% for the cardiovascular III panel and ~320% for the cell regulation panel) compared with other groups. ExoIntact also showed the highest intersample correlation with an average Pearson’s correlation coefficient of 0.991 compared with 0.985 and 0.927 for MagCapture and EVSecond, respectively. The median coefficient of variation was 5%, 8%, and 22% for ExoIntact, MagCapture, and EVSecond, respectively. Comparing total CSF and ExoIntact samples revealed 70 differentially expressed proteins in the cardiovascular III panel and 17 in the cell regulation panel. To our knowledge, this is the first time that CSF EVs were analyzed by PEA. In conclusion, analysis of CSF EVs by PEA is feasible, and different isolation kits give distinct results, with ExoIntact showing the highest number of identified proteins with the lowest variability.


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