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Assessment of methods for serum extracellular vesicle small RNA sequencing to support biomarker development.

ABSTRACT: Extracellular vesicles (EVs) have great potential as a source for clinically relevant biomarkers since they can be readily isolated from biofluids and carry microRNA (miRNA), mRNA, and proteins that can reflect disease status. However, the biological and technical variability of EV content is unknown making comparisons between healthy subjects and patients difficult to interpret. In this study, we sought to establish a laboratory and bioinformatics analysis pipeline to analyse the small RNA content within EVs from patient serum that could serve as biomarkers and to assess the biological and technical variability of EV RNA content in healthy individuals. We sequenced EV small RNA from multiple individuals (biological replicates) and sequenced multiple replicates per individual (technical replicates) using the Illumina Truseq protocol. We observed that the replicates of samples clustered by subject indicating that the biological variability (~95%) was greater than the technical variability (~0.50%). We observed that ~30% of the sequencing reads were miRNAs. We evaluated the technical parameters of sequencing by spiking the EV RNA preparation with a mix of synthetic small RNA and demonstrated a disconnect between input concentration of the spike-in RNA and sequencing read frequencies indicating that bias was introduced during library preparation. To determine whether there are differences between library preparation platforms, we compared the Truseq with the Nextflex protocol that had been designed to reduce bias in library preparation. While both methods were technically robust, the Nextflex protocol reduced the bias and exhibited a linear range across input concentrations of the synthetic spike-ins. Altogether, our results indicate that technical variability is much smaller than biological variability supporting the use of EV small RNAs as potential biomarkers. Our findings also indicate that the choice of library preparation method leads to artificial differences in the datasets generated invalidating the comparability of sequencing data across library preparation platforms.

SUBMITTER: Srinivasan S

PROVIDER: S-EPMC6844434 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Project description:Small extracellular vesicles (EVs) are 50-200 nm sized mediators in intercellular communication that reflect both physiological and pathophysiological changes of their parental cells. Thus, EVs hold great potential for biomarker detection. However, reliable purification methods for the downstream screening of the microRNA (miRNA) cargo carried within urinary EVs by small RNA sequencing have yet to be established. To address this knowledge gap, RNA extracted from human urinary EVs obtained by five different urinary EV purification methods (spin column chromatography, immunoaffinity, membrane affinity, precipitation and ultracentrifugation combined with density gradient) was analyzed by small RNA sequencing. Urinary EVs were further characterized by nanoparticle tracking analysis, Western blot analysis and transmission electron microscopy. Comprehensive EV characterization established significant method-dependent differences in size and concentration as well as variances in protein composition of isolated vesicles. Even though all purification methods captured enough total RNA to allow small RNA sequencing, method-dependent differences were also observed with respect to library sizes, mapping distributions, number of miRNA reads and diversity of transcripts. Whereas EVs obtained by immunoaffinity yielded the purest subset of small EVs, highly comparable with results attained by ultracentrifugation combined with density gradient, precipitation and membrane affinity, sample purification by spin column chromatography indicated a tendency to isolate different subtypes of small EVs, which might also carry a distinct subset of miRNAs. Based on our results, different EV purification methods seem to preferentially isolate different subtypes of EVs with varying efficiencies. As a consequence, sequencing experiments and resulting miRNA profiles were also affected. Hence, the selection of a specific EV isolation method has to satisfy the respective research question and should be well considered. In strict adherence with the MISEV (minimal information for studies of extracellular vesicles) guidelines, the importance of a combined evaluation of biophysical and proteomic EV characteristics alongside transcriptomic results was clearly demonstrated in this present study.

Project description:Atherosclerosis can occur throughout the arterial vascular system and lead to various diseases. Early diagnosis of atherosclerotic processes and of individual disease patterns would be more likely to be successful if targeted therapies were available. For this, it is important to find reliable biomarkers that are easily accessible and with little inconvenience for patients. There are many cell culture, animal model or tissue studies that found biomarkers at the microRNA (miRNA) and mRNA level describing atherosclerotic processes. However, little is known about their potential as circulating and liquid biopsy markers in patients. In this study, we examined serum-derived miRNA - profiles from 129 patients and 28 volunteers to identify potential biomarkers. The patients had four different atherosclerotic manifestations: abdominal aneurysm (n = 35), coronary heart disease (n = 34), carotid artery stenosis (n = 24) and peripheral arterial disease (n = 36). The samples were processed with an extracellular vesicle enrichment protocol, total-RNA extraction and small RNA-sequencing were performed. A differential expression analysis was performed bioinformatically to find potentially regulated miRNA biomarkers. Resulting miRNA candidates served as a starting point for an overrepresentation analysis in which relevant target mRNAs were identified. The Gene Ontology database revealed relevant biological functions in relation to atherosclerotic processes. In patients, expression of specific miRNAs changed significantly compared to healthy volunteers; 27 differentially expressed miRNAs were identified. We were able to detect a group-specific miRNA fingerprint: miR-122-5p, miR-2110 and miR-483-5p for abdominal aortic aneurysm, miR-370-3p and miR-409-3p for coronary heart disease, miR-335-3p, miR-381-3p, miR493-5p and miR654-3p for carotid artery stenosis, miR-199a-5p, miR-215-5p, miR-3168, miR-582-3p and miR-769-5p for peripheral arterial disease. The results of the study show that some of the identified miRNAs have already been associated with atherosclerosis in previous studies. Overrepresentation analysis on this data detected biological processes that are clearly relevant for atherosclerosis, its development and progression showing the potential of these miRNAs as biomarker candidates. In a next step, the relevance of these findings on the mRNA level is to be investigated and substantiated.

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Assessment of methods for serum extracellular vesicle small RNA sequencing to support biomarker development.

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