MiRNAs in extracellular vesicles prepared from patients with multiple sclerosis
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE86863 | GEO | 2017/11/18
SECONDARY ACCESSION(S): PRJNA342953
REPOSITORIES: GEO
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Project description:Extracellular vesicles (EVs) are released by most cell types and are implicated in several biological and pathological processes, including multiple sclerosis (MS). In this study we performed RNA sequencing to analyze the diversity of microorganisms by assignment of reads using different taxa profilers. To diminish the risk of false positive biases derived from sample handling, we performed a similar analysis on EVs derived from known cultured bacterial species, as well as artificially-generated samples. Overall, we detect a range of microbial species in MS and healthy control (HC) samples, that are not detected in control samples, as well as species with differential abundance between MS and HC samples. These results reveal the relevance of putative communication of microbial species using EVs as a communication vector.
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2015-04-02 | E-GEOD-63445 | biostudies-arrayexpress
Project description:Crude extracellular vesicles (EVs) from eight healthy volunteers were separated into 6 fractions based on their densities by using the iodixanol-based density gradient centrifugation method. To determine the distribution of miRNAs among these fractions, quantities of 93 miRNAs were quantified by the TaqMan real time PCR method using the BioMark HD system (Fluidigm) equipped with 96.96 dynamic array (Fluidigm). Six samples were fractionated from a crude EVs by density gradient centrifugation. Total of 48 samples were prepared from 8 healthy volunteers. Technical replicate of 4 gave 8 x 6 x 4 x 93 = 17,856 data. As control Tris-HCl EDTA buffer (TE) was used.
2016-08-01 | E-GEOD-78763 | biostudies-arrayexpress
Project description:Transcriptional comparison of B16F10 cells with B16F10 cell-derived extracellular vesicles (EVs) to identify transcripts enriched or de-enriched in EVs compared to their donor cells.
2022-03-01 | E-MTAB-11025 | biostudies-arrayexpress
Project description:Extracellular vesicles (EVs) are membrane-enclosed nanoparticles containing specific repertoires of genetic material. In mammals, EVs can mediate the horizontal transfer of various cargos and signaling molecules, notably miRNA and mRNA species. Whether this form of intercellular communication prevails in other metazoans remains unclear. Here, we report the first parallel comparative morphologic and transcriptomic characterization of EVs from Drosophila and human cellular models. Electronic microscopy revealed that Drosophila, like human cells release exosome-like EVs with diameter ranging from 30 to 200 nm, which contain complex populations of transcripts. RNA-seq identified abundant ribosomal RNA pseudogenes and retrotransposons in human and Drosophila EVs. Vault RNAs and Y RNAs abounded in human samples, whereas small nucleolar RNAs involved in pseudouridylation were most prevalent in Drosophila EVs. Numerous mRNAs were identified, largely consisting of exonic sequences displaying full-length read coverage and enriched for translation and electronic transport chain functions. By analogy with human systems, these extensive similarities suggest that EVs could also enable RNA-mediated intercellular communication in Drosophila. We performed RNA-seq on extracellular vesicles purified from of human and Drosophila cell line cultures. S2R+ and D17 Drosophila EVs were analyzed, along with human A431 and HepG2 EVs. No ribosomal RNA depletion or polyA selection was performed on EV samples. For comparative analyses, we also analyzed total cellular RNA from Drosophila D17 and human HepG2. Ribodepletion was performed on cellular samples.
2016-06-15 | E-GEOD-76173 | biostudies-arrayexpress
Project description:Exosomes and microvesicles (i.e., extracellular vesicles; EVs) have been identified within ovarian follicular fluid, and recent evidence suggests that EVs are able to elicit profound effects on ovarian cell function. While existence of miRNA within EVs has been reported, it remains unknown if EV size and concentration as well as their cargos (i.e., proteins and RNA) change during antral follicle growth. Extracellular vesicles isolated from follicular fluid of small, medium and large bovine follicles were similar in size, while concentration of EVs decreased progressively as follicle size increased. Electron microscopy indicated a highly purified population of the lipid bilayer enclosed vesicles that were enriched in exosome biomarkers including CD81 and Alix. Small RNA sequencing identified a large number of known and novel miRNAs that changed in the EVs of different size follicles. Ingenuity Pathway Analysis (IPA) indicated that miRNA abundant in small follicle EV preparations were associated with cell proliferation pathways, while those miRNA abundant in large follicle preparations were related to inflammatory response pathways. These studies are the first to demonstrate that EVs change in their levels and makeup during antral follicle development and point to the potential for a unique vesicle-mediated cell-to-cell communication network within the ovarian follicle. Examination of small RNA population in bovine follicular fluid extracellular vesicles isolated from antral follicles
2016-02-09 | E-GEOD-74879 | biostudies-arrayexpress
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2015-05-07 | E-GEOD-59958 | biostudies-arrayexpress
Project description:Background: Renal cell carcinoma (RCC) accounts for about 2% of all cancers. Renal biopsy is the gold standard among the diagnostic tools, but it is invasive and not suitable for all patients. Therefore, new reliable and non-invasive biomarkers for ccRCC detection are required. Secretion of extracellular vesicles (EVs), containing RNA molecules that can be transferred between cells, seems to be a general characteristic of malignant transformation. Consistently, cancer-derived EVs are enriched in the blood, urine and various malignant effusions of cancer patients. Therefore, urinary samples can be a non-invasive approach for discovering diagnostic biomarkers. Methods: We enrolled 33 clear-cell RCC (ccRCC) patients and 22 healthy subjects (HS), age and sex-matched, for urine collection and extracellular vesicles isolation by differential centrifugation. Transcriptional profiles of urinary EVs from 12 patients with ccRCC and 11 HS were generated using the Illumina HumanHT-12 v4 BeadChip oligonucleotide arrays. Microarray analysis led to the identification of RNA that were then validated using RT-qPCR. Results: We showed for the first time that urinary exosomal shuttle RNA (esRNA) was significantly different in ccRCC patients compared to HS and we identified three EVs esRNA involved in the tumor biology that are potentially suitable as non-invasive biomarkers. GSTA1, CEBPA and PCBD1 RNA levels decreased in urinary EVs of patients compared to HS. After 1 month post-operation, the levels of RNA increased to reach the normal level. Conclusions: This study suggests, for the first time, the potential use of the RNA content of urinary EVs to provide a non-invasive first step to diagnose the ccRCC. Total RNA obtained from urinary extracellular vesicles isolated from ccRCC patients and healthy subjects.
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Project description:Extracellular vesicles (EVs) are nanostructures that are used as sources of biomarkers. To better understand whether EVs could be exploited as diagnostic and prognostic biomarkers in Amyotrophic Lateral Sclerosis (ALS), we analyzed plasma-derived of ALS patients and relative healthy and diseased controls. Using the nickel-based isolation, a recently published EV purification method, we unmasked peculiar features in plasma EVs of ALS patients with a potential straightforward application in a clinical setting. We report that the number of particles is increased in the plasma of ALS patients and of two mouse models of ALS while the average diameter is decreased. Proteins like HSP90 and phosphorylated TDP-43 are differentially represented in ALS patients and mice compared to the controls. In terms of disease progression, the levels of phosphorylated TDP-43 and cyclophilin A, along with the EV size distribution discriminated fast and slow progressors of the diseases suggesting a new means for patient stratification. We exploited the EV size distribution with machine learning analysis that combining different EV parameters resulted in very high prediction rates for disease diagnosis and prognosis
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