Precipitation‐based extracellular vesicle isolation from rat plasma co‐precipitate vesicle‐free microRNAs

Abstract

The microRNA (miRNA) cargo contained in plasma extracellular vesicles (EVs) offers a relatively little explored source of biomarkers for brain diseases that can be obtained noninvasively. Methods to isolate EVs from plasma, however, are still being developed. For EV isolation, it is important to ensure the removal of vesicle-free miRNAs, which account for approximately two-thirds of plasma miRNAs. Membrane particle precipitation-based EV isolation is an appealing method because of the simple protocol and high yield. Here, we evaluated the performance of a precipitation-based method to obtain enriched EV-specific miRNAs from a small volume of rat plasma. We performed size-exclusion chromatography (SEC) on precipitation-isolated EV pellets and whole plasma. The SEC fractions were analysed using Nanoparticle Tracking Analysis (NTA), protein and miRNA concentration assays, and droplet digital polymerase chain reaction for four miRNAs (miR-142-3p, miR-124-3p, miR-23a, miR-122). Precipitation-isolated EVs and selected SEC fractions from the plasma were also analysed with transmission electron microscopy (TEM). Precipitation-based EV isolation co-precipitated 9% to 15% of plasma proteins and 21% to 99% of vesicle-free miRNAs, depending on the individual miRNAs. In addition, the amount of miR-142-3p, found mainly in EV fractions, was decreased in the EV fractions, indicating that part of it was lost during precipitation-based isolation. Western blot and TEM revealed both protein and lipoprotein contamination in the precipitation-isolated EV-pellets. Our findings indicate that a precipitation-based method is not sufficient for purifying plasma EV-contained miRNA cargo. The particle number measured by NTA is high, but this is mostly due to the contaminating lipoproteins. Although a part of the vesicle-free miRNA is removed, vesicle-free miRNA still dominates in plasma EV pellets isolated by the precipitation-based method.

Increased expression of miR142 and miR155 in glial and immune cells after traumatic brain injury may contribute to neuroinflammation via astrocyte activation

“…Interestingly, we observed that miR-142-3p was enriched in the plasma fractions associated with EVs, rather than proteins. This is in accordance with previous studies (1,21) and it has been shown that only a minor portion of circulating miRNAs are associated with EVs, whereas a majority of circulating miRNAs could be found as bound to Argonaute2 protein (1). EVs, containing miRNAs and mRNAs, have been hypothesized to be actively released by the cells and participate in intercellular communication (25,57).…”

“…Size-exclusion chromatography (SEC) of plasma SEC analysis was performed as previously described (8,21). Briefly, plasma samples (200 µL) from four rats (two TBI, one sham and one naïve rat) were passed through sepharose CL-2B (GE Healthcare; Uppsala, Sweden) chromatography columns.…”

Y‐RNA subtype ratios in plasma extracellular vesicles are cell type‐ specific and are candidate biomarkers for inflammatory diseases

“…These different RNA carriers overlap in size and buoyant density [59], which complicates strict separation of the different particles. The different types of EV isolation methods that are currently in use vary largely in the level of contamination with LPP and RNP [22,[74][75][76]. Moreover, the currently used RNA isolation kits exhibit variable recovery efficiencies for RNAs enclosed in each of the different macromolecular complexes (EV, LPP and RNP) [22].…”

MicroRNAs in Extracellular Vesicles in Sweat Change in Response to Endurance Exercise

“…We chose to use affinity-based columns in our present study. Other EV isolation methods include ultracentrifugation, which requires high volumes of (pooled) samples, and precipitation, which does not exclude non-EV miRs from serum ( Karttunen et al, 2018 ). As the aim was to compare the serum and sweat EV-miR populations, affinity-based columns were the most promising tool for our setup ( Enderle et al, 2015 ).…”