Computational protocol: The impact of disparate isolation methods for extracellular vesicles on downstream RNA profiling

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[…] Total RNA was isolated from exosome samples using the miRNeasy Micro kit according to manufacturer's instructions (Qiagen, Valencia, CA, USA). RNA concentration was measured using a UV-Vis spectrophotometer (Nanodrop Technologies, Wilmington, DE, USA). The Experion electrophoresis system using the standard RNA chips (Bio-Rad) was used to assess RNA quality and create electropherograms. Whole genome mRNA expression profiling was performed using a custom gene expression microarray (Agilent Technologies, Amstelveen, The Netherlands). In brief, 10 ng of total RNA was labelled using the Low Input Quick Amp labelling kit (Agilent) according to the manufacturer's instructions. Cy-3-labelled cRNA was hybridized and probe intensities were analysed using an Agilent microarray scanner and Feature Extraction software. Probe intensities were background subtracted and normalized using Quantile normalization. For downstream data analysis, only probes with a normalized signal at least 2-fold above that of the negative control probe (DarkCorner) were labelled as expressed. Probes were included if expressed in all 3 replicates of 1 method. For gene-level analysis, the probe with the highest mean expression value for that gene across all samples was used. Validation of differentially expressed genes was performed via quantitative real-time polymerase chain reaction (PCR) (RT-qPCR) using PrimePCR™ assays (Bio-Rad). The 10.0-µL PCR reaction mix contained PrimePCR Assay (0.5 µL), SsoAdvanced SYBR Green Supermix (5.0 µL), cDNA (1 µL corresponding to the cDNA reverse transcribed from approximately 10 ng RNA), and nuclease-free water (4.5 µL). The 384-well plate was then run on the CFX 384 (Bio-Rad) at 95°C for 30 seconds, then 95°C for 5 seconds and 60°C for 15 seconds (for 45 cycles). PrimePCR assays that were used for qPCR are listed in Supplementary Table 1. Data were processed and normalized using qbase+2.6 software (www.biogazelle.com). Assays with too low an expression level (i.e. missing values in multiple samples) were excluded. Three reference genes (CYB5A, RCL1 and SYNGR2) were selected based on geNorm analysis including 6 candidate genes with low standard deviation across all samples in the microarray experiment.Gene set enrichment analysis was performed on mRNA lists, ranked according to mean fold change between methods using Gene Ontology biological process and KEGG pathways as gene set collections (). Alternatively, functional annotation of enriched genes was determined using the DAVID bioinformatics database (). Hierarchical clustering was performed using Manhattan distance and Ward clustering. [...] Exosome samples were suspended in reducing sample buffer (Novex® Tris-Glycine sample buffer, Invitrogen) and boiled for 2 minutes at 85°C. Samples were run on Novex® 4–20% Tris-Glycine gradient gels (Invitrogen) in denaturing SDS buffer, stained with 0.5% Coomassie Brilliant Blue (Bio-Rad) in 40% methanol and 10% acetic acid for 20 minutes, and destained in a solution composed of 40% methanol and 10% acetic acid. Gel bands were processed and analysed by liquid chromatography–mass spectrometry/mass spectrometry (LC-MS/MS) as previously described (). Raw MS/MS files were submitted to the NIH MASCOT Cluster () using MASCOT DAEMON version 2.2. Data were searched against the UNIPROT-SPROT database, updated on 20/05/08 as described (). For each peptide identification, MASCOT reports a probability-based ion score, which is defined as −10×log10(P), where P is the absolute probability that the observed match between the experimental data and the database sequence is a random event. The significance threshold for inclusion of each peptide in the output file is the individual ion score meeting or exceeding its MASCOT identity score threshold (p<0.05). Peptides with ion scores below their identity scores were rejected. MASS SIEVE was used to calculate percentage coverage for each protein identification (http://www.ncbi.nlm.nih.gov/staff/slottad/MassSieve). Peptide identifications from 1 representative experiment are shown. […]

Pipeline specifications

Software tools Mascot Server, MassSieve
Application MS-based untargeted proteomics
Diseases Neoplasms