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Simple and fast SEC-Based protocol to isolate human plasma-Derived extracellular vesicles for transcriptional research

  • Laetitia S. Gaspar
  • , Magda M. Santana
  • , Carina Henriques
  • , Maria M. Pinto
  • , Teresa M. Ribeiro-Rodrigues
  • , Henrique Girão
  • , Rui Jorge Nobre
  • , Luís Pereira de Almeida*
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

36 Citations (Scopus)

Abstract

Extracellular vesicles (EVs) are membranous structures that protect RNAs from damage when circulating in complex biological fluids, such as plasma. RNAs are extremely specific to health and disease, being powerful tools for diagnosis, treatment response monitoring, and development of new therapeutic strategies for several diseases. In this context, EVs are potential 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 allows concomitant analysis of particle number and size, total protein, and quantification of a major plasma contaminant. This protocol yields 7.54 × 109 ± 1.22 × 108 particles, quantified 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 × 1010 ± 7.38 × 109 particles/μg 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 μL of plasma. The protocol is fast and easy to implement and has potential for application in biomarkers research, therapeutic strategies development, and clinical practice.
Original languageEnglish
Pages (from-to)723-737
Number of pages15
JournalMolecular Therapy - Methods and Clinical Development
Volume18
DOIs
Publication statusPublished - 11 Sept 2020
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • Biomarkers
  • Clinical research
  • Extracellular vesicles
  • Plasma
  • Size exclusion chromatography
  • Therapy
  • Transcriptional research

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