Distinct mechanisms of microRNA sorting into cancer cell-derived extracellular vesicle subtypes
Abstract
Extracellular vesicles (EVs) encompass a variety of vesicles secreted into the extracellular space. EVs have been implicated in promoting tumor metastasis, but the molecular composition of tumor-derived EV sub-types and the mechanisms by which molecules are sorted into EVs remain mostly unknown. We report the separation of two small EV sub-populations from a metastatic breast cancer cell line, with biochemical features consistent with different sub-cellular origins. These EV sub-types use different mechanisms of miRNA sorting (selective and non-selective), suggesting that sorting occurs via fundamentally distinct processes, possibly dependent on EV origin. Using biochemical and genetic tools, we identified the Lupus La protein as mediating sorting of selectively packaged miRNAs. We found that two motifs embedded in miR-122 are responsible for high-affinity binding to Lupus La and sorting into vesicles formed in a cell-free reaction. Thus, tumor cells can simultaneously deploy multiple EV species using distinct sorting mechanisms that may enable diverse functions in normal and cancer biology.
Data availability
RNA sequencing data have been deposited in SRA under accession code PRJNA532890.
Article and author information
Author details
Funding
Howard Hughes Medical Institute
- Randy Schekman
National Institutes of Health (R01 GM37949)
- Alan M Lambowitz
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Reviewing Editor
- Suzanne R Pfeffer, Stanford University School of Medicine, United States
Version history
- Received: April 9, 2019
- Accepted: August 21, 2019
- Accepted Manuscript published: August 22, 2019 (version 1)
- Version of Record published: September 5, 2019 (version 2)
- Version of Record updated: October 14, 2019 (version 3)
Copyright
© 2019, Temoche-Diaz et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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