Project description:Body fluids contain many populations of extracellular vesicles (EV) that differ in size, cellular origin, molecular composition, and biological activities. EV in seminal plasma are in majority originating from prostate epithelial cells, and hence are also referred to as prostasomes. Nevertheless, EV are also contributed by other accessory sex glands, as well as by the testis and epididymis. In a previous study, we isolated EV from seminal plasma of vasectomized men, thereby excluding contributions from the testis and epididymis, and identified two distinct EV populations with diameters of 50 and 100 nm, respectively. In the current study, we comprehensively analyzed the protein composition of these two EV populations using quantitative Liquid Chromatography-Mass Spectrometry (LC-MS/MS). In total 1558 proteins were identified. Of these, ≈45% was found only in the isolated 100 nm EV, 1% only in the isolated 50 nm EV, and 54% in both 100 nm and 50 nm EV. Gene ontology (GO) enrichment analysis suggest that both originate from the prostate, but with distinct biogenesis pathways. Finally, nine proteins, including KLK3, KLK2, MSMB, NEFH, PSCA, PABPC1, TGM4, ALOX15B, and ANO7, with known prostate specific expression and alternate expression levels in prostate cancer tissue were identified. These data have potential for the discovery of EV associated prostate cancer biomarkers in blood.
Project description:The observed specificity of β-thalassemia-subtype phenotypes makes new diagnostic strategies that complement current screening methods necessary to determine each subtype and facilitate therapeutic regimens for different patients. Here, we performed quantitative proteomics of plasma-derived extracellular vesicles (EVs) of β-thalassemia major (TM) patients, β-thalassemia intermedia (TI) patients, and healthy controls to explore subgroup characteristics and potential biomarkers. Plasma quantitative proteomics among the same cohorts were analyzed in parallel to compare the biomarker potential of both specimens. EV proteomics showed significantly more abnormalities in immunity and lipid metabolism in TI and TM, respectively. The differential proteomic patterns of EVs were consistent with but more striking than those of plasma. Notably, we also found EV proteins to have a superior performance for discriminating β-thalassemia subtypes. These findings allowed us to propose a diagnostic model consisting of five proteins in EVs with subtyping potential, demonstrating the ability of plasma-derived EVs for the diagnosis of β-thalassemia patients.
Project description:Breast cancer is the second cause of cancer-associated death among women and seriously endangers women's health. Therefore, early identification of breast cancer would be beneficial to women's health. At present, circular RNA (circRNA) not only exists in the extracellular vesicles (EVs) in plasma, but also presents distinct patterns under different physiological and pathological conditions. Therefore, we assume that circRNA could be used for early diagnosis of breast cancer. Here, we developed classifiers for breast cancer diagnosis that relied on 259 samples, including 144 breast cancer patients and 115 controls. In the discovery stage, we compared the genome-wide long RNA profiles of EVs in patients with breast cancer (n=14) and benign breast (n=6). To further verify its potential in early diagnosis of breast cancer, we prospectively collected plasma samples from 259 individuals before treatment, including 144 breast cancer patients and 115 controls. Finally, we developed and verified the predictive classifies based on their circRNA expression profiles of plasma EVs by using multiple machine learning models. By comparing their circRNA profiles, we found 439 circRNAs with significantly different levels between cancer patients and controls. Considering the cost and practicability of the test, we selected 20 candidate circRNAs with elevated levels and detected their levels by quantitative real-time polymerase chain reaction. In the training cohort, we found that BCExoC, a nine-circRNA combined classifier with SVM model, achieved the largest AUC of 0.83 [95% CI 0.77-0.88]. In the validation cohort, the predictive efficacy of the classifier achieved 0.80 [0.71-0.89]. Our work reveals the application prospect of circRNAs in plasma EVs as non-invasive liquid biopsies in the diagnosis and management of breast cancer.
Project description:The global exploration of snakebites requires the use of quantitative omics approaches to characterize snake venom as it enters into the systemic circulation. These omics approaches give insights into the venom proteome, but a further exploration is warranted to analyze the venom-reactome for the identification of snake venom biomarkers. The recent discovery of extracellular vesicles (EVs), and their critical cellular functions, has presented them as intriguing sources for biomarker discovery and disease diagnosis. Herein, we purified EV's from the snake venom (svEVs) of Crotalus atrox and C. oreganus helleri, and from plasma of BALB/c mice injected with venom from each snake using EVtrap in conjunction with quantitative mass spectrometry for the proteomic identification and quantification of svEVs and plasma biomarkers. Snake venom EVs from C. atrox and C. o. helleri were highly enriched in 5' nucleosidase, L-amino acid oxidase, and metalloproteinases. In mouse plasma EVs, a bioinformatic analysis for revealed upregulated responses involved with cytochrome P450, lipid metabolism, acute phase inflammation immune, and heat shock responses, while downregulated proteins were associated with mitochondrial electron transport, NADH, TCA, cortical cytoskeleton, reticulum stress, and oxidative reduction. Altogether, this analysis will provide direct evidence for svEVs composition and observation of the physiological changes of an envenomated organism.
Project description:tic disorders (TDs) are a series of childhood neuropsychiatric disorders characterized by invol-untary motor and/or vocal tics and commonly comorbid with several other psychopathological and/or behavioral disorders. In the present study, we aimed to identify serum small extracellular vesicles (sEVs) derived microRNAs (miRNAs) from the serum samples of children for Tic Disorders Diagnosis
Project description:BackgroundSevere acute pancreatitis (SAP) is the most common gastrointestinal disease and is associated with unpredictable seizures and high mortality rates. Despite improvements in the treatment of acute pancreatitis, the timely and accurate diagnosis of SAP remains highly challenging. Previous research has shown that extracellular vesicles (EVs) in the plasma have significant potential for the diagnosis of SAP since the pancreas can release EVs that carry pathological information into the peripheral blood in the very early stages of the disease. However, we know very little about the metabolites of EVs that might play a role in the diagnosis of SAP.MethodsHere, we performed quantitative metabolomic analyses to investigate the metabolite profiles of EVs isolated from SAP plasma. We also determined the metabolic differences of EVs when compared between healthy controls, patients with SAP, and those with mild acute pancreatitis (MAP).ResultsA total of 313 metabolites were detected, mainly including organic acids, amino acids, fatty acids, and bile acids. The results showed that the metabolic composition of EVs derived from SAP and MAP was significantly different from those derived from healthy controls and identified specific differences between EVs derived from patients with SAP and MAP. On this basis, we identified four biomarkers from plasma EVs for SAP detection, including eicosatrienoic acid (C20:3), thiamine triphosphate, 2-Acetylfuran, and cis-Citral. The area under the curve (AUC) was greater than 0.95 for both discovery (n = 30) and validation (n = 70) sets.ConclusionsOur data indicate that metabolic profiling analysis of plasma EVs and the screening of potential biomarkers are of significant potential for improving the early diagnosis and severity differentiation of acute pancreatitis.
Project description:Seminal plasma contains a variety of extracellular vesicles (EVs) that deliver RNAs including microRNAs (miRNAs) molecules. However, the roles of these EVs along with their delivered RNAs and their interactions with male infertility are not clear. Sperm-associated antigen 7 (SPAG 7) is expressed in male germ cells and plays a crucial role in several biological functions associated with sperm production and maturation. In this study, we aimed to identify the post-transcriptional regulation of SPAG7 in seminal plasma (SF-Native) and seminal plasma-derived extracellular vesicles (SF-EVs) collected from 87 men undergoing infertility treatment. Among the multiple binding sites for miRNAs within its 3'UTR of SPAG7, we identified the binding of four miRNAs (miR-15b-5p, miR-195-5p, miR-424-5p, and miR-497-5p) to the 3'UTR of SPAG7 by the dual luciferase assays. Analyzing sperm, we found reduced mRNA expression levels of SPAG7 in SF-EVs and SF-Native samples from oligoasthenozoospermic men. By contrast, two miRNAs (miR-424-5p and miR-497-5p) form the SF-Native samples, and four miRNAs (miR-195-5p, miR-424-5p, miR-497-5p, and miR-6838-5p) from the SF-EVs samples showed significantly higher expression levels in oligoasthenozoospermic men. The expression levels of miRNAs and SPAG7 were significantly correlated with basic semen parameters. These findings contribute significantly to our understanding of regulatory pathways in male fertility by showing a direct link between upregulated miRNA, notably miR-424, and downregulated SPAG7 both in seminal plasma and in plasma-derived EVs likely contributing to oligoasthenozoospermia.
Project description:Seminal plasma is a complex mixture of secretions from various glands in the male genital tract. Compared to sperm cells, it contains important proteins that are both directly and indirectly associated with sperm motility. Here, we constructed quantitative proteomes of human seminal plasma from three normozoospermic and asthenozoospermic individuals. A total of 524 proteins were identified, and 366 of them were found to be quantified in all six samples. We first investigated the absolute expression features of these proteins and found that the variations of protein identification among different samples and other published datasets were mainly due to some lowly expressed proteins. By integration of various proteomic datasets and bioinformatics databases, we comprehensively annotated the biological functions, physiological originations, and disease associations of these proteins. We found that our dataset could benefit the studies of both male infertility and other male diseases. Finally, based on the relative expression values determined by chemical labeling, we identified a total of 29 differentially expressed proteins, which could be used as candidate targets for studying the molecular bases of sperm motility or developing precise diagnostic biomarkers of asthenozoospermia. We further successfully verified the expression trends of four representative proteins by Western blotting. Compared to a previous dataset based on label-free quantification, our results showed that most of the important proteins could be identified in the sample collected only once for each individual, providing the bases for personalized examination of seminal plasma proteins in clinic.
Project description:Extracellular vesicles (EVs) are submicron, membrane-enclosed particles that are released from cells in various pathophysiological states. The molecular cargo of these vesicles is considered to reflect the composition of the cell of origin, and the EV proteome is therefore a potential source of biomarkers for various diseases. Our aim was to determine whether EVs isolated from plasma provide additional diagnostic value or improved pathophysiological understanding compared to plasma alone in the context of myocardial infarction (MI). A panel of proximity extension assays (n = 92) was employed to analyze EV lysates and plasma from patients with MI (n = 60) and healthy controls (n = 22). After adjustment for multiple comparisons, a total of 11 dysregulated proteins were identified in EVs of MI patients compared to the controls (q < 0.01). Three of these proteins: chymotrypsin C (CTRC), proto-oncogene tyrosine-protein kinase SRC (SRC) and C-C motif chemokine ligand 17 (CCL17) were unaltered in the corresponding plasma samples. As biomarkers for MI, rudimentary to no evidence exists for these proteins. In a separate group of patients with varying degrees of coronary artery disease, the decrease in EV-associated (but not plasma-related) SRC levels was confirmed by ELISA. Confirmation of the presence of SRC on EVs of different sizes and cellular origins was performed with ELISA, flow cytometry and nanoparticle tracking analysis. In conclusion, the data revealed that despite a similarity in the EV and plasma proteomes, analysis of isolated EVs does indeed provide additional diagnostic information that cannot be obtained from plasma alone.
Project description:BackgroundThere is a lack of biomarkers for distinguishing non-obstructive azoospermia (NOA) patients with successful sperm retrieval (Sp+) from those with failed sperm retrieval (Sp-). This study aimed to determine the potential of extracellular vesicles tRNA-derived small RNA (tsRNA) as a novel non-invasive biomarker for successful sperm retrieval by microdissection testicular sperm extraction (mTESE).MethodsThe study included 18 patients with NOA with successful sperm retrieval (Sp+) and 23 patients with NOA with failed sperm retrieval (Sp-), 15 obstructive azoospermia (OA) patients, 5 idiopathic oligospermia (IO) patients, and 12 healthy people. Seminal plasma extracellular vesicles tsRNA levels were used in a two-stage case-control study (screened by tsRNA sequencing on Illumina NextSeq instrument and validated by qRT-PCR). The bioinformatic analysis was performed to determine the role of tsRNA in the pathogenesis of non-obstructive azoospermia.ResultsTwo tsRNAs (tRF-Val-AAC-010: AUC = 0.96, specificity = 80%, sensitivity = 95%; tRF-Pro-AGG-003: AUC = 0.96, specificity = 87%, sensitivity = 95%) were found to have high predictive accuracy for distinguishing the origin of azoospermia. In addition, the extracellular vesicles tRF-Val-AAC-010 resulted in high predictive ability (AUC = 0.89, sensitivity = 72%, specificity = 91%, P < 0.0001) in predicting the presence of sperm in non-obstructive azoospermia undergoing mTESE. Finally, bioinformatic analysis revealed that tRF-Val-AAC-010 were involved in spermatogenesis.ConclusionsThis study identified that the extracellular vesicles tRF-Val-AAC-010 and tRF-Pro-AGG-003 are biomarkers for the diagnosis of non-obstructive azoospermia, and that tRF-Val-AAC-010 as a potential non-invasive biomarker for predicting the presence of sperm in non-obstructive azoospermia testicular tissue.