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.

Switching Homes: How Cancer Moves to Bone

“…This also holds true for high invasive MDA-MB-231 vs. low invasive MCF7 cell lines [238,239]. Although in general terms, inter-patient variability seems to be in line with that of other biomarkers [240], a biomarker-based pilot study to assess normal levels of EV-shuttled factors is crucial for most biomarkers (e.g., miRNAs), since the field is new, and normality ranges, biological variability and technical variability are still not established [241,242]. However, the fact that these are communication devices for cells, opens many possibilities in the drug delivery field.…”

Extracellular Vesicles in Immune System Regulation and Type 1 Diabetes: Cell-to-Cell Communication Mediators, Disease Biomarkers, and Promising Therapeutic Tools

“…Importantly, exosomes also contain different species of RNAs that can be transferred to recipient cells (56)(57)(58)(59)(60)(61)(62). Among these, microRNAs (miRNAs), small non-coding RNAs approximately 19 to 24 nts in length, have generated a particular interest in the scientific community for their regulatory function.…”

Stumbling on elusive cargo: how isomiRs challenge microRNA detection and quantification, the case of extracellular vesicles

“…Therefore, a careful bioinformatic analysis is required to figure out whether the lack of robustness can be explained given the abundance of specific isomiRs in each case. A concern that escapes the scope of this text is the ligation and amplification biases that may occur during library construction, and the type of normalization that limits sRNA-seq profiling (for review on this matter, see references [ 2 , 5 , 20 , 25 , 28 , 29 , 62 – 64 ]). Poor reproducibility across platforms is the result of a complex blend of several factors, originated by the intrinsic mechanisms by which each platform detects microRNAs.…”

“…Lower quantities might be used for library construction, but the quality tests and concentration measurements must be skipped. Additionally, higher PCR amplification cycles are required during library construction, but it is known this originates acute amplification biases [ 5 , 64 , 69 ].…”