Project description:In this study we used transgenic mouse model to comapre two isolation techniques INTACT and FANS for the isolation of activated neuronal nuclei. Comparison is perfomed on multiple levels like isolation efficiency, membrane integrity, transcriptional and epigenetic state using RNA-seq and ATAC-seq
Project description:Background & aims: MicroRNAs (miRNAs) encapsulated in EVs are potential diagnostic and prognostic biomarkers. However, discrepancies on miRNA patterns and their validation are still frequent due to differences in sample origin, EVs isolation, miRNA extraction and sequencing methods. Selecting appropriate EVs isolation methods is therefore a critical step for miRNA-based biomarker discovery. The aim of the present study is to find the most suitable EVs isolation method for miRNAs sequencing adequate for clinical application. Material & Methods EVs were isolated by Size Exclusion Chromatography (SEC), iodixanol gradients (GRAD) and the combination of both (SEC+GRAD), using the same plasma sample, in triplicate isolation assays. Isolated EVs were characterized and RNA was extracted. Three different protocols for miRNA library preparation were compared (NEBNext, NEXTFlex and SMARTer smRNA-seq) and miRNAs encapsulated on EVs were sequenced using NextSeq 500 system (Illumina). Finally, the yield, abundance and diversity of miRNAs using the three different EVs isolation protocols were analyzed and compared between them. Results The majority of lipoproteins, total cholesterol and plasma proteins were removed from the EVs-containing fractions by using SEC, GRAD, and SEC+GRAD. SEC method recovered a larger amount of EVs followed by GRAD and SEC+GRAD, while GRAD and SEC+GRAD yielded the purest vesicles. NEBNext was the library preparation kit that showed the highest reproducibility among replicas, higher number of reads corresponding to miRNAs and more different miRNAs, followed by NEXTFlex and SMARTer smRNA-seq. GRAD method showed the highest reproducibility among replicas, a higher number of reads corresponding to miRNAs and more different miRNAs, followed by SEC and SEC+GRAD methods. Conclusions These results render the GRAD method to isolate EVs as one of the most appropriate to detect miRNAs from Evs.
