posted on 2018-10-15, 13:53authored byZubair Nizamudeen, Robert Markus, Rhys Lodge, Christopher Parmenter, Mark PlattMark Platt, Lisa Chakrabarti, Virginie Sottile
Extracellular vesicles (EVs) have prevalent roles in cancer biology and regenerative medicine. Conventional techniques for characterising EVs including electron microscopy (EM), nanoparticle tracking analysis (NTA) and tuneable resistive pulse sensing (TRPS), have been reported to produce high variability in particle count (EM) and poor sensitivity in detecting EVs below 50 nm in size (NTA and TRPS), making accurate and unbiased EV analysis technically challenging. This study introduces direct stochastic optical reconstruction microscopy (d-STORM) as an efficient and reliable characterisation approach for stem cell-derived EVs. Using a photo-switchable lipid dye, d-STORM imaging enabled rapid detection of EVs down to 20–30 nm in size with higher sensitivity and lower variability compared to EM, NTA and TRPS techniques. Imaging of EV uptake by live stem cells in culture further confirmed the potential of this approach for downstream cell biology applications and for the analysis of vesicle-based cell-cell communication.
Funding
This work was supported by the Biotechnology and Biological Sciences Research Council [grant number BBSRC BB/L013827/1] and the Engineering and Physical Sciences Research Council [grant number EPSRC EP/K005138/1].
History
School
Science
Department
Chemistry
Published in
Biochimica et Biophysica Acta (BBA) - Molecular Cell Research
Volume
1865
Issue
12
Citation
NIZAMUDEEN, Z. ... et al, 2018. Rapid and accurate analysis of stem cell-derived extracellular vesicles with super resolution microscopy and live imaging. Biochimica et Biophysica Acta (BBA) - Molecular Cell Research, 1865 (12), pp.1891-1900.
This work is made available according to the conditions of the Creative Commons Attribution 4.0 International (CC BY 4.0) licence. Full details of this licence are available at: http://creativecommons.org/licenses/ by/4.0/
Acceptance date
2018-09-23
Publication date
2018-10-02
Notes
This is an Open Access Article. It is published by Elsevier under the Creative Commons Attribution 4.0 International licence (CC BY). Full details of this licence are available at: http://creativecommons.org/licenses/by/4.0/