Original Article Simple and Fast SEC-Based Protocol to Isolate Human Plasma-Derived Extracellular Vesicles for Transcriptional Research Laetitia S. Gaspar, 1,2,3,7 Magda M. Santana, 1,2,7 Carina Henriques, 1,2,6 Maria M. Pinto, 1,2,5 Teresa M. Ribeiro-Rodrigues, 2,4 Henrique Girão, 2,4 Rui Jorge Nobre, 1,2,3,6 and Luís Pereira de Almeida 1,2,5,6 1 Center for Neuroscience and Cell Biology (CNC), University of Coimbra, 3004-504 Coimbra, Portugal; 2 Center for Innovation in Biomedicine and Biotechnology (CIBB), University of Coimbra, Coimbra, Portugal; 3 Institute for Interdisciplinary Research (IIIUC), University of Coimbra, 3030-789 Coimbra, Portugal; 4 Coimbra Institute for Clinical and Biomedical Research (iCBR), Faculty of Medicine, University of Coimbra, 3000-548 Coimbra, Portugal; 5 Faculty of Pharmacy, University of Coimbra, 3000-548 Coimbra, Portugal; 6 ViraVector, University of Coimbra, 3004-504 Coimbra, Portugal Extracellular vesicles (EVs) are membranous structures that protect RNAs from damage when circulating in complex bio- logical fluids, such as plasma. RNAs are extremely specific to health and disease, being powerful tools for diagnosis, treat- ment response monitoring, and development of new therapeu- tic strategies for several diseases. In this context, EVs are poten- tial sources of disease biomarkers and promising delivery vehicles. However, standardized and reproducible EV isolation protocols easy to implement in clinical practice are missing. Here, a size exclusion chromatography-based protocol for EV-isolation from human plasma was optimized. We propose a workflow to isolate EVs for transcriptional research that al- lows concomitant analysis of particle number and size, total protein, and quantification of a major plasma contaminant. This protocol yields 7.54  10 9 ± 1.22  10 8 particles, quanti- fied by nanoparticle tracking analysis, with a mean size of 115.7 ± 11.12 nm and a mode size of 83.13 ± 4.72 nm, in a ratio of 1.19  10 10 ± 7.38  10 9 particles/mg of protein, determined by Micro Bicinchoninic Acid (BCA) Protein Assay, and 3.09 ± 0.7 ng RNA, assessed by fluorescence-based RNA-quantitation, from only 900 mL of plasma. The protocol is fast and easy to implement and has potential for application in biomarkers research, therapeutic strategies development, and clinical practice. INTRODUCTION Extracellular vesicles (EVs) have emerged as promising shields of dis- ease-specific or therapeutic RNAs. 1–4 EVs comprise a heterogeneous population of membranous structures that are naturally released from all cell types into the extracellular space. These structures carry a variety of molecules that reflect the biomolecular composition of the tissue and cells of origin. 2,5,6 Thus, EVs have emerged as promising disease biomarkers. 7 Moreover, EVs from healthy cells can elicit bene- ficial effects in disease-associated recipient cells, being increasingly identified as promising cell-free therapeutic agents. 8 Advanced techno- logical strategies are also being developed to load specific therapeutic RNAs into EVs, as these structures are more stable, efficiently protect nucleic acids from environmental damage, and have reduced immuno- genicity when compared to other nano-based drug delivery systems. 2 Efforts performed in the field have been focused on isolating these vesicles from plasma and serum as these body fluids are abundant, easily accessible, and routinely collected through minimally invasive procedures. 9,10 However, the use of blood-derived EVs in a clinical context depends on the capacity to isolate these structures from con- taminants in sufficient yields and in a reproducible, cost-effective, and simple manner. 11–15 Among the different techniques available so far, size exclusion chromatography (SEC) holds great promise for EV- based translational research as this method can be easily adapted to most research and clinical laboratories. 16,17 SEC separates molecules, based on their size, by filtration through a resin-packed column. 16–19 This technique allows isolation of homo- geneous EV populations, removes major biofluid components, avoids EV aggregation, and preserves their functional characteristics. 20–23 When compared to other methods, SEC is user-friendly, less time- consuming, has a relatively low cost, and requires a small amount of starting material. 16,17 Indeed, SEC has been successfully used for small scale analysis of EVs from clinical samples. 24 Its performance is determined by multiple variables, such as column stacking, resin pore size, or sample volume/collected volume ratio. 17,19 The use of commercial columns avoids column preparation and allows faster protocols in quality-controlled and consistent conditions, decreasing the method variability. 25 SEC is also easily automated by using acces- sible equipment, reducing hands-on time and user influence, and improving consistency and reproducibility. 16 Received 15 February 2020; accepted 8 July 2020; https://doi.org/10.1016/j.omtm.2020.07.012. 7 These authors contributed equally to this work. Correspondence: Luís Pereira de Almeida, Center for Neuroscience and Cell Biology (CNC), University of Coimbra, 3004-504 Coimbra, Portugal. E-mail: luispa@cnc.uc.pt Molecular Therapy: Methods & Clinical Development Vol. 18 September 2020 ª 2020 723 This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).