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RI-SEC-seq: Comprehensive Profiling of Nonvesicular Extracellular RNAs with Different Stabilities

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BIO-PROTOCOL
卷 11, 期 4, 页码 -

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BIO-PROTOCOL
DOI: 10.21769/BioProtoc.3918

关键词

exRNA; RNA biomarker; Intercellular communication; Next generation sequencing; Exosomes; Liquid biopsies; Differential stability; Extracellular ribosomes

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资金

  1. Agencia Nacional de Investigacion e Innovacion (ANII, Uruguay) [FCE_3_2018_1_148745]
  2. Comision Sectorial de Investigacion Cientifica (CSIC-UdelaR, Uruguay) [MIA_PAS2019_2_99]
  3. National Institutes of Health, USA [NIH Common Fund, through the Office of Strategic Coordination/Office of the NIH Director] [UG3CA241694]

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Exosomes and other extracellular vesicles are important for transporting RNAs, but a significant portion of extracellular RNAs do not co-purify with vesicles, leading to a biased non-vesicular exRNA profile. A new method using size-exclusion chromatography has allowed for the identification and study of extracellular ribosomes and tRNAs, offering a dynamic view of the extracellular RNAome that can impact biomarker discovery.
Exosomes and other extracellular vesicles (EVs) are considered the main vehicles transporting RNAs in extracellular samples, including human bodily fluids. However, a major proportion of extracellular RNAs (exRNAs) do not copurify with EVs and remain in ultracentrifugation supernatants of cell-conditioned medium or blood serum. We have observed that nonvesicular exRNA profiles are highly biased toward those RNAs with intrinsic resistance to extracellular ribonucleases. These highly resistant exRNAs are interesting from a biomarker point of view, but are not representative of the actual bulk of RNAs released to the extracellular space. In order to understand exRNA dynamics and capture both stable and unstable RNAs, we developed a method based on size-exclusion chromatography (SEC) fractionation of RNase inhibitor (RI)-treated cell-conditioned medium (RI-SEC-seq). This method has allowed us to identify and study extracellular ribosomes and tRNAs, and offers a dynamical view of the extracellular RNAome which can impact biomarker discovery in the near future.

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