A urinary extracellular vesicle microRNA biomarker discovery pipeline; From automated extracellular vesicle enrichment by acoustic trapping to microRNA sequencing Journal Article


Authors: Ku, A.; Ravi, N.; Yang, M.; Evander, M.; Laurell, T.; Lilja, H.; Ceder, Y.
Article Title: A urinary extracellular vesicle microRNA biomarker discovery pipeline; From automated extracellular vesicle enrichment by acoustic trapping to microRNA sequencing
Abstract: Development of a robust automated platform for enrichment of extracellular vesicles from low sample volume that matches the needs for next-generation sequencing could remove major hurdles for genomic biomarker discovery. Here, we document a protocol for urinary EVs enrichment by utilizing an automated microfluidic system, termed acoustic trap, followed by next-generation sequencing of microRNAs (miRNAs) for biomarker discovery. Specifically, we compared the sequencing output from two small RNA library preparations, NEXTFlex and CATS, using only 130 pg of input total RNA. The samples prepared using NEXTflex was found to contain larger number of unique miRNAs that was the predominant RNA species whereas rRNA was the dominant RNA species in CATS prepared samples. A strong correlation was found between the miRNA expressions of the acoustic trap technical replicate in the NEXTFlex prepared samples, as well as between the acoustic trap and ultracentrifugation enrichment methods. Together, these results demonstrate a robust and automated strategy for biomarker discovery from small volumes of urine. © 2019 Ku et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Journal Title: PLoS ONE
Volume: 14
Issue: 5
ISSN: 1932-6203
Publisher: Public Library of Science  
Date Published: 2019-05-29
Start Page: e0217507
Language: English
DOI: 10.1371/journal.pone.0217507
PUBMED: 31141544
PROVIDER: scopus
PMCID: PMC6541292
DOI/URL:
Notes: Source: Scopus
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  1. Hans Gosta Lilja
    345 Lilja