We would like to thank the groups of Owen Davies and Nick Peake for continuing to provide material and expertise.

1. Setup of the nFCM instrument and measurements of the nFCM standards
NOTE: Three measurements are taken before beginning data acquisition for samples to validate correct alignment of the nFCM instrument and provide strong comparison between instruments. These are the concentration standard/quality control (QC), size standard, and a blank.
<ol>
	<li>Dilute the QC beads 1:100 in distilled water in an appropriate 0.6 &#181;L tube and place in loading bay.</li>
	<li>From the Sample Flow drop down menu, select Boosting to introduce the QC sample into the system for 45 s to completely replace the previous sample/cleaning solution.
	<ol>
		<li>While boosting, set the laser power to the preset template for QC beads &#34;250 nm FL QC standard&#34;, e.g., 10/40 mW for the blue laser, 20/50 mW for the red laser, with 0.2% SS decay.</li>
	</ol>
	</li>
	<li>Select the Sampling pressure from the same down menu to reduce the system pressure.</li>
	<li>Set the auto sampling pressure to 1.0 kPa to maintain a constant pressure.</li>
	<li>Initiate the 1-minute analysis by selecting Time to Record from the acquisition controls. Data will be plotted on the dot-plot showing a log scale for SS-intensity and a selected FL intensity.</li>
	<li>Insert the file name and sample dilution before saving the file.</li>
	<li>Select unload to remove the tube from the loading bay. Replace with 150 &#181;L of cleaning solution and clean for &#62;30 s by selecting Boosting before removing the cleaning solution by selecting Unload.
	<ol>
		<li>Remove any excess cleaning solution from the capillary tip using a tube containing 150 &#181;L of water.</li>
	</ol>
	</li>
	<li>Dilute the size standard beads 1:100 in water and load 100 &#181;L into the loading bay, before Boosting the sample for 45 s.</li>
	<li>Set the laser power to the preset template &#34;S16 exo 68-155 nm&#34;. This setting is for both the size standard and samples containing EVs &#60; 200 nm. For example, 15/40 mW for the blue laser, 20/50 mW for the red laser, with 0.2% SS decay.</li>
	<li>Select Sampling and proceed to recording the sample for 1 min as before.</li>
	<li>Perform the third measurement with either a water or PBS sample to create a blank measurement of your eluent, identifying false positives for removal by the software. Inputting the standard measurements is described in the following section.</li>
</ol>
2. Determining the particle concentration of an unlabeled sample and generating a PDF report
<ol>
	<li>Dilute the unlabeled EV sample in PBS to a suitable particle concentration range for nFCM analysis, 1 x 108- 5 x 108 particles/mL. Load 10-100 &#181;L of the diluted sample into the loading bay.</li>
	<li>When the particle concentration is unknown, begin with a 1:100 dilution of the EV sample. Sample concentration can be quickly approximated by the size of the laser spot on the CCD camera during boosting, or by observation of the Event Burst Trace during sampling.</li>
	<li>Boost the loaded sample for 45 s before selecting Sampling and record for 1 min, saving as previously described.</li>
	<li>To begin analyzing this data, switch from the Acquisition tab to the Analysis tab. Open the saved nfa files.</li>
	<li>To allow for accurate sample measurement, use the two standard measurements taken prior to sample measurement to set values for sample comparison as well as the blank.</li>
	<li>Create the size standard curve, for SS to diameter conversion, by first selecting the size standard file and using the set threshold tool (also known as auto-thresholding). The threshold, visible in the event burst trace, identifies the minimum signal intensity required for an event to be considered significant.</li>
	<li>With the threshold set, check the dot plot x and y parameters are SS-H or SS-A on the x axis and FITC-A on the y axis.</li>
	<li>Open the standard curve generation tool and select S16 exo 68-155 nm as the sizing template. Click on Find Peaks to identify the peak SS intensities as either a 68, 91, 113, or 155 nm diameter particle.</li>
	<li>Check whether the SS to diameter curve has been generated with an r value close to 1 before closing the window.</li>
	<li>Set the concentration standard by selecting the saved file and clicking on Count STD. Input the particle concentration of the standard.</li>
	<li>Having set the standard information, select the EV sample file and set the threshold.</li>
	<li>Select the blank file and click on Set Blank to identify the number of false positives for removal from the sample count. This should be done with the same threshold as your sample. Return to the EV sample file.</li>
	<li>Open the PDF generation tool and select Sizing and Concentration. Input the dilutions of the sample. The concentration of the sample and the size distribution of the particles are shown.</li>
</ol>
3. Sample labeling
NOTE: Two staining strategies can be used simultaneously for a comprehensive analysis of the particles in suspension. Labeling protocols often require optimization for new antibodies or sample sources.
<ol>
	<li>Dilute a portion of the EV sample to a concentration of 1.25 x 1010 particles/mL in PBS. Incubate 8 &#181;L of the diluted EV sample with 1 &#181;L of antibody and 1 &#181;L of dye for a particle concentration of 1 x 1010 particles/mL (total particles will be 1 x 108 suspended in 10 &#181;L). The incubation ratio for the antibody is 1:50 (1 &#181;L of 1:5 antibody) in this instance.
	<ol>
		<li>Use more than three different concentrations of antibody or dye during optimization, to provide data indicating the protocol allows for maximum epitope binding without over saturation of the chosen label, which may impair identification of low intensity fluorescence events. The incubation concentration for the membrane dye is 40 nM (1 &#181;L of 400 nM).</li>
	</ol>
	</li>
	<li>Mix the 10 &#181;L sample by vortexing for 5 s and incubate at RT for 30 min in the dark. 
	NOTE: Recommendations for controls are included in the discussion.</li>
	<li>Following incubation, take 1 &#181;L of the labeled sample and dilute 1:50 in PBS in a 0.6 mL tube.</li>
	<li>Load the sample into the loading bay and apply boosting pressure for 45 s. Ensure laser settings are correct and the appropriate lenses are loaded.</li>
	<li>Switch to sampling pressure and select Time to Record. Following the 1 min acquisition, name the data file and save.</li>
	<li>Unload the sample and replace with cleaning solution. Boost this for &#62;30 s before loading the next labeled sample.</li>
</ol>
4. nFCM analysis-PDF generation for subpopulation analysis
<ol>
	<li>For PDF generation, apply the same standards as previously done; only the blank measurement will be set differently.</li>
	<li>Select the sample file and set the threshold. On the dot plot, change the y-axis to show FL measurements from the green or red channel.</li>
	<li>Select the square gating tool and use left click to draw a square around the FL+ population.</li>
	<li>Open the blank measurement file and click on Set Blank before reverting to the sample file.</li>
	<li>Open the PDF generation tool as before and the size distribution, concentration, and percentage (compared to all SS+ events) are identified for the FL+ subpopulation.
	<ol>
		<li>Repeat for each subpopulation of interest identified as &#34;Total, P1, P2 etc.&#34;</li>
	</ol>
	</li>
</ol>

<ol>
	<li>Couch, Y., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+brief+history+of+nearly+EV-erything+-+The+rise+and+rise+of+extracellular+vesicles.">A brief history of nearly EV-erything - The rise and rise of extracellular vesicles.</a> Journal of Extracellular Vesicles. 10 (14), 12144 (2021).</li><li>Doyle, L. M., Wang, M. Z. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Overview+of+extracellular+vesicles,+their+origin,+composition,+purpose,+and+methods+for+exosome+isolation+and+analysis.">Overview of extracellular vesicles, their origin, composition, purpose, and methods for exosome isolation and analysis.</a> Cells. 8 (7), 727 (2019).</li><li>Grant, L. R., Milic, I., Devitt, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Apoptotic+cell-derived+extracellular+vesicles:+structure-function+relationships.">Apoptotic cell-derived extracellular vesicles: structure-function relationships.</a> Biochemical Society Transactions. 47 (2), 509-516 (2019).</li><li>Rontogianni, S., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Proteomic+profiling+of+extracellular+vesicles+allows+for+human+breast+cancer+subtyping.">Proteomic profiling of extracellular vesicles allows for human breast cancer subtyping.</a> Communications Biology. 2, 325 (2019).</li><li>Sahoo, S., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Therapeutic+and+diagnostic+translation+of+extracellular+vesicles+in+cardiovascular+diseases.">Therapeutic and diagnostic translation of extracellular vesicles in cardiovascular diseases.</a> Circulation. 143 (14), 1426-1449 (2021).</li><li>Chiang, C. -. Y., Chen, C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Toward+characterizing+extracellular+vesicles+at+a+single-particle+level.">Toward characterizing extracellular vesicles at a single-particle level.</a> Journal of Biomedical Science. 26 (1), 9 (2019).</li><li>Karimi, N., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Detailed+analysis+of+the+plasma+extracellular+vesicle+proteome+after+separation+from+lipoproteins.">Detailed analysis of the plasma extracellular vesicle proteome after separation from lipoproteins.</a> Cellular and Molecular Life Sciences. 75 (15), 2873-2886 (2018).</li><li>Akers, J. C., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Comparative+analysis+of+technologies+for+quantifying+Extracellular+Vesicles+(EVs)+in+Clinical+Cerebrospinal+Fluids+(CSF).">Comparative analysis of technologies for quantifying Extracellular Vesicles (EVs) in Clinical Cerebrospinal Fluids (CSF).</a> PLOS ONE. 11 (2), 0149866 (2016).</li><li>Bachurski, D., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Extracellular+vesicle+measurements+with+nanoparticle+tracking+analysis+-+An+accuracy+and+repeatability+comparison+between+NanoSight+NS300+and+ZetaView.">Extracellular vesicle measurements with nanoparticle tracking analysis - An accuracy and repeatability comparison between NanoSight NS300 and ZetaView.</a> Journal of Extracellular Vesicles. 8 (1), 1596016 (2019).</li><li>Vogel, R., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Measuring+particle+concentration+of+multimodal+synthetic+reference+materials+and+extracellular+vesicles+with+orthogonal+techniques:+Who+is+up+to+the+challenge.">Measuring particle concentration of multimodal synthetic reference materials and extracellular vesicles with orthogonal techniques: Who is up to the challenge.</a> Journal of Extracellular Vesicles. 10 (3), 12052 (2021).</li><li>Van Der Pol, E., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Particle+size+distribution+of+exosomes+and+microvesicles+determined+by+transmission+electron+microscopy,+flow+cytometry,+nanoparticle+tracking+analysis,+and+resistive+pulse+sensing.">Particle size distribution of exosomes and microvesicles determined by transmission electron microscopy, flow cytometry, nanoparticle tracking analysis, and resistive pulse sensing.</a> Journal of Thrombosis and Haemostasis. 12 (7), 1182-1192 (2014).</li><li>Hartjes, T. A., Mytnyk, S., Jenster, G. W., Van Steijn, V., Van Royen, M. E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Extracellular+vesicle+quantification+and+characterization:+Common+methods+and+emerging+approaches.">Extracellular vesicle quantification and characterization: Common methods and emerging approaches.</a> Bioengineering. 6 (1), 7 (2019).</li><li>Zhao, Z., Wijerathne, H., Godwin, A. K., Soper, S. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Isolation+and+analysis+methods+of+extracellular+vesicles+(EVs).">Isolation and analysis methods of extracellular vesicles (EVs).</a> Extracellular Vesicles and Circulating Nucleic Acids. 2, 80-103 (2021).</li><li>Johnsen, K. B., Gudbergsson, J. M., Andresen, T. L., Simonsen, J. B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=What+is+the+blood+concentration+of+extracellular+vesicles?+Implications+for+the+use+of+extracellular+vesicles+as+blood-borne+biomarkers+of+cancer.">What is the blood concentration of extracellular vesicles? Implications for the use of extracellular vesicles as blood-borne biomarkers of cancer.</a> Biochimica et Biophysica Acta (BBA) - Reviews on Cancer. 1871 (1), 109-116 (2019).</li><li>Zhu, S., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Light-scattering+detection+below+the+level+of+single+fluorescent+molecules+for+high-resolution+characterization+of+functional+nanoparticles.">Light-scattering detection below the level of single fluorescent molecules for high-resolution characterization of functional nanoparticles.</a> ACS Nano. 8 (10), 10998-11006 (2014).</li><li>Van Der Pol, E., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Standardization+of+extracellular+vesicle+measurements+by+flow+cytometry+through+vesicle+diameter+approximation.">Standardization of extracellular vesicle measurements by flow cytometry through vesicle diameter approximation.</a> Journal of Thrombosis and Haemostasis. 16 (6), 1236-1245 (2018).</li><li>Lucchetti, D., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Measuring+extracellular+vesicles+by+conventional+flow+cytometry:+dream+or+reality.">Measuring extracellular vesicles by conventional flow cytometry: dream or reality.</a> International Journal of Molecular Sciences. 21 (17), 6257 (2020).</li><li>Su&#225;rez, H., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+bead-assisted+flow+cytometry+method+for+the+semi-quantitative+analysis+of+Extracellular+Vesicles.">A bead-assisted flow cytometry method for the semi-quantitative analysis of Extracellular Vesicles.</a> Scientific Reports. 7 (1), 11271 (2017).</li><li>Tian, Y., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Protein+profiling+and+sizing+of+extracellular+vesicles+from+colorectal+cancer+patients+via+flow+cytometry.">Protein profiling and sizing of extracellular vesicles from colorectal cancer patients via flow cytometry.</a> ACS Nano. 12 (1), 671-680 (2018).</li><li>Silva, A. M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Quantification+of+protein+cargo+loading+into+engineered+extracellular+vesicles+at+single-vesicle+and+single-molecule+resolution.">Quantification of protein cargo loading into engineered extracellular vesicles at single-vesicle and single-molecule resolution.</a> Journal of Extracellular Vesicles. 10 (10), 12130 (2021).</li><li>Dragovic, R. A., Southcombe, J. H., Tannetta, D. S., Redman, C. W. G., Sargent, I. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Multicolor+flow+cytometry+and+nanoparticle+tracking+analysis+of+extracellular+vesicles+in+the+plasma+of+normal+pregnant+and+pre-eclamptic+women.">Multicolor flow cytometry and nanoparticle tracking analysis of extracellular vesicles in the plasma of normal pregnant and pre-eclamptic women.</a> Biology of Reproduction. 89 (6), 151 (2013).</li><li>Teng, F., Fussenegger, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Shedding+light+on+extracellular+vesicle+biogenesis+and+bioengineering.">Shedding light on extracellular vesicle biogenesis and bioengineering.</a> Advanced Science. 8 (1), 2003505 (2021).</li><li>Laulagnier, K., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Mast+cell-+and+dendritic+cell-derived+exosomes+display+a+specific+lipid+composition+and+an+unusual+membrane+organization.">Mast cell- and dendritic cell-derived exosomes display a specific lipid composition and an unusual membrane organization.</a> Biochemical Journal. 380, 161-171 (2004).</li><li>Simonsen, J. B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Pitfalls+associated+with+lipophilic+fluorophore+staining+of+extracellular+vesicles+for+uptake+studies.">Pitfalls associated with lipophilic fluorophore staining of extracellular vesicles for uptake studies.</a> Journal of Extracellular Vesicles. 8 (1), 1582237 (2019).</li><li>Collot, M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=MemBright:+A+family+of+fluorescent+membrane+probes+for+advanced+cellular+imaging+and+neuroscience.">MemBright: A family of fluorescent membrane probes for advanced cellular imaging and neuroscience.</a> Cell Chemical Biology. 26 (4), 600-614 (2019).</li><li>Takov, K., Yellon, D. M., Davidson, S. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Confounding+factors+in+vesicle+uptake+studies+using+fluorescent+lipophilic+membrane+dyes.">Confounding factors in vesicle uptake studies using fluorescent lipophilic membrane dyes.</a> Journal of Extracellular Vesicles. 6 (1), 1388731 (2017).</li><li>Tian, Y., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Quality+and+efficiency+assessment+of+six+extracellular+vesicle+isolation+methods+by+nano-flow+cytometry.">Quality and efficiency assessment of six extracellular vesicle isolation methods by nano-flow cytometry.</a> Journal of Extracellular Vesicles. 9 (1), 1697028 (2020).</li><li>Mondal, A., Ashiq, K. A., Phulpagar, P., Singh, D. K., Shiras, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Effective+visualization+and+easy+tracking+of+extracellular+vesicles+in+glioma+cells.">Effective visualization and easy tracking of extracellular vesicles in glioma cells.</a> Biological Procedures Online. 21, 4 (2019).</li><li>Gelibter, S., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+impact+of+storage+on+extracellular+vesicles:+A+systematic+study.">The impact of storage on extracellular vesicles: A systematic study.</a> Journal of Extracellular Vesicles. 11 (2), 12162 (2022).</li><li>Jayachandran, M., Miller, V. M., Heit, J. A., Owen, W. G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Methodology+for+isolation,+identification+and+characterization+of+microvesicles+in+peripheral+blood.">Methodology for isolation, identification and characterization of microvesicles in peripheral blood.</a> Journal of Immunological Methods. 375 (1-2), 207-214 (2012).</li><li>Mizenko, R. R., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Tetraspanins+are+unevenly+distributed+across+single+extracellular+vesicles+and+bias+sensitivity+to+multiplexed+cancer+biomarkers.">Tetraspanins are unevenly distributed across single extracellular vesicles and bias sensitivity to multiplexed cancer biomarkers.</a> Journal of Nanobiotechnology. 19 (1), 250 (2021).</li><li>Kowal, J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Proteomic+comparison+defines+novel+markers+to+characterize+heterogeneous+populations+of+extracellular+vesicle+subtypes.">Proteomic comparison defines novel markers to characterize heterogeneous populations of extracellular vesicle subtypes.</a> Proceedings of the National Academy of Sciences of the United States of America. 113 (8), 968-977 (2016).</li><li>Laulagnier, K., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Amyloid+precursor+protein+products+concentrate+in+a+subset+of+exosomes+specifically+endocytosed+by+neurons.">Amyloid precursor protein products concentrate in a subset of exosomes specifically endocytosed by neurons.</a> Cellular and Molecular Life Sciences. 75 (4), 757-773 (2018).</li><li>Simonsen, J. B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=What+are+we+looking+at?+Extracellular+vesicles,+lipoproteins,+or+both.">What are we looking at? Extracellular vesicles, lipoproteins, or both.</a> Circulation Research. 121 (8), 920-922 (2017).</li><li>S&#243;dar, B. W., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Low-density+lipoprotein+mimics+blood+plasma-derived+exosomes+and+microvesicles+during+isolation+and+detection.">Low-density lipoprotein mimics blood plasma-derived exosomes and microvesicles during isolation and detection.</a> Scientific Reports. 6, 24316 (2016).</li><li>Brennan, K., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+comparison+of+methods+for+the+isolation+and+separation+of+extracellular+vesicles+from+protein+and+lipid+particles+in+human+serum.">A comparison of methods for the isolation and separation of extracellular vesicles from protein and lipid particles in human serum.</a> Scientific Reports. 10 (1), 103 (2020).</li><li>Welton, J. L., Webber, J. P., Botos, L. -. A., Jones, M., Clayton, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Ready-made+chromatography+columns+for+extracellular+vesicle+isolation+from+plasma.">Ready-made chromatography columns for extracellular vesicle isolation from plasma.</a> Journal of Extracellular Vesicles. 4, 27269 (2015).</li><li>Peruzzotti-Jametti, L., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Neural+stem+cells+traffic+functional+mitochondria+via+extracellular+vesicles.">Neural stem cells traffic functional mitochondria via extracellular vesicles.</a> PLOS Biology. 19 (4), 3001166 (2021).</li><li>Arab, T., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Characterization+of+extracellular+vesicles+and+synthetic+nanoparticles+with+four+orthogonal+single-particle+analysis+platforms.">Characterization of extracellular vesicles and synthetic nanoparticles with four orthogonal single-particle analysis platforms.</a> Journal of Extracellular Vesicles. 10 (6), 12079 (2021).</li><li>Th&#233;ry, C., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Minimal+information+for+studies+of+extracellular+vesicles+2018+(MISEV2018):+a+position+statement+of+the+International+Society+for+Extracellular+Vesicles+and+update+of+the+MISEV2014+guidelines.">Minimal information for studies of extracellular vesicles 2018 (MISEV2018): a position statement of the International Society for Extracellular Vesicles and update of the MISEV2014 guidelines.</a> Journal of Extracellular Vesicles. 7 (1), 1535750 (2018).</li></ol>

A.L., B.P., D.A., R.L, R.T are employees of NanoFCM and their contributions to this paper were made as part of their employment.

Sample and reagent details 
Two EV isolates from separate cell lines were selected for demonstration of fluorescent labeling and subsequent nFCM analysis. Both EV sets were suspended in PBS and stored at -80 &#176;C for &#60;3 months but most other conditions were different between isolates. The C2C12 mouse myoblast cell line represents an embryonic precursor to skeletal muscle cells and were grown in 2D culture, conditioning the growth medium over 72 h before EV isolation by ultracentrifugation. SW620 is a human colon adenocarcinoma cell line and was grown in a rudimentary bioreactor, enriching media over 7 weeks, with EV isolation conducted by size exclusion chromatography (SEC) and fractions 7-9 eluted from sepharose CL-2B columns combined into a single sample.
While EVs isolated and concentrated from CCM are the easiest sample types to work with, nFCM is applicable to most EV isolates, including biofluids such as serum, plasma, urine, and CSF. These sample analyses benefit from the nFCM SS detection of all particles, allowing for corroboration with NTA, TRPS, and other particle analyses, while describing the fluorescently labeled EV subpopulations in quantitative terms as well as a proportion of the total, for an unbiased approach of multiparameter particle analysis. Analysis of low processed samples is possible too, such as unclarified urine and EV enriched CCM with the caveat of requiring low contaminate protein.
The membrane dye used here is intended to integrate into the lipid bilayer, with a lipophilic moiety for membrane loading and a hydrophilic dye for remaining in the plasma membrane25. There is currently no perfect EV labeling dye and several criteria must be considered when choosing, including specificity to EVs, suitability with fixation or permeabilization, and efficiency of EV labeling26.
Fluorescent conjugated antibody labeling of surface exposed epitopes has proven to be an effective method for identifying EV subpopulations27. A key aspect of protocol optimization is meeting, and not exceeding, the labeling saturation point to bind to all available epitopes without inhibiting detection of low fluorescence particles by allowing the surrounding buffer to be filled with fluorescent unbound antibody28. Additionally, the availability of exposed binding sites for antibody labeling is potentially influenced by several factors. Storage conditions of EVs has been shown to effect concentration and size profiles of EVs29 with observations also indicating effects on antibody labeling30. The presence of surface corona proteins, protein modifications, and impacts of isolation techniques may also have effects upon antibody labeling in some cases. Ultimately, as the utilization of fluorescent labeling becomes more prevalent for EV studies, experimental design and optimization for multiple analytical techniques will become more refined.
To increase accuracy of results, several controls can be included such as (1) PBS + dye control, to assess micelle or aggregate formation in some dyes, which can appear as SS+ particles in nFCM analysis, (2) PBS + antibody control, aggregates can occur, although often not large enough to scatter enough light for SS detection, (3) EV sample + IgG antibody control, common in flow cytometry and used to identify any non-specific binding, (4) non-EV particle sample + antibody/dye control - particularly important when needing to identify EVs in complex particle samples, controls such as purified low-density lipoprotein (LDL) particles or EV depleted/ablated samples can act as a negative control to validate selective labeling, (5) positive controls are hard to design but validation of an antibody on cells is a useful inclusion.
Presentation of tetraspanins on EVs 
The antibody and membrane labeling of this experiment demonstrates the high level of quantitative data that can be obtained in a small timeframe by nFCM analysis. Simultaneous measurement of the key physical attributes of particle diameter/concentration with the phenotypic measurements of membrane and/or protein presence leads to high level descriptions of subpopulations within particle isolation.
Importantly, varying levels of the three &#39;key&#39; EV-related tetraspanins, CD9, CD63, CD81, were identified in these two EV samples. CD9 was presented on the greatest proportion of EVs for both C2C12 derived EVs and SW620, with CD81 and CD63 being the second and least presented proteins, respectively.
Despite some similarities observed here in the tetraspanin profiles of EVs from two very different cell sources, levels of CD9, CD63, and CD81 can be very different between cell line and patient derived EVs31.
The difference in CD63 expression between the two EV samples is particularly relevant to the ongoing discussion of key identifiers of &#39;EV-ness&#39;. While presentation of CD63 in only ~8% of the SW620 EVs may be unexpected by some, CD63 has been suggested as poor identifier of the different types of EVs isolated by size or density32, and tetraspanin negative EVs have been identified, even when described as exosome-like33.
Identification of EVs within complex particle isolations 
The heterogeneity of EV tetraspanin profiles, in both cell line and patient-derived EVs, cautions against reliance on tetraspanin-based capture of EVs and highlights the future need for new EV identification methods31. EV labeling independent of specific proteins could prove to be highly beneficial to identifying EVs from similar sized non-EV particles if EV specificity can be proven to be very high. This is particularly true for biofluid EV isolates as it has been suggested that the concentration of EVs in human blood plasma is in the range of 1010 particles/mL while lipoproteins are measured at 1016 per mL14,34. Even upon EV enrichment, studies comparing particle positivity for tetraspanin markers and/or LDL marker ApoB suggest ~50-100x greater abundance of LDL in Platelet free plasma (PFP) samples compared to EV35.
The isolation technique used greatly affects the range of co-isolated non-EV particles such as very low-density lipoproteins (VLDL), intermediate-density lipoproteins (IDL), and LDL36. There are also descriptions of lipoprotein co-isolates bound to EVs which, while potentially playing an important biological role, makes achieving EV pure samples a challenging goal35.
Therefore, it could be argued that a greater focus be placed on the description of particles which make up a sample, rather than achieving isolation of a pure but limited selection of EVs. Achieving comprehensive description of particles by measuring tetraspanin abundance in bulk and particle counts separately can be insufficient to accurately determine EV concentrations, particularly from biofluid sources36,37. Identifying subpopulations in a tier-based approach, showing total particles, EVs, and EVs presenting certain proteins, as demonstrated in this experiment may provide a robust solution to nanoparticle characterization. This has been the case for projects involving EV-loading with designs for future therapeutic applications20 and identification of CD63+ EVs with luminal cargo such as mitochondria38.
nFCM within the repertoire of EV analytics 
A strength of nFCM EV analysis is the way data can corroborate and build upon the most common EV analyses and form bridges between physical and phenotypic data sets. However, this is based on accurate labeling protocols which often need to be optimized for unique labeling reagents such as dyes and antibodies. A key criterion for accurate analysis is having labeled particles suspended in a non-fluorescent buffer, which relies on either removal of excess unbound fluorophore or the refinement of protocols to not exceed epitope saturation.
Comparison studies have shown that nFCM sizing of EVs provides data in line with TRPS and cryo-TEM, techniques which are described as more accurate than NTA for EV size analysis10,39. However, as with any optical-based method, the influence of heterogeneic optical properties seen for EVs and differences between the optical properties of reference material and EVs must be acknowledged when interpreting data10.
Western blotting has been a key method for indicating EV enrichment through identification of EV markers40. But the desire to demonstrate the presence of such markers on particles has driven advances in EV-based flow cytometric analyses17. However, the necessary resolutions to provide robust data are currently best attained through dedicated instrumentation with regards to both scattered and fluorescent light19.
nFCM provides an unbiased approach of initially describing all particles irrelevant of specific markers, by use of side scatter measurement, allowing for corroboration with the most common techniques of NTA, RPS, and TEM1, while simultaneously adding phenotypic measurement similar to WB or Elisa in a quantitative manner.

What are EVs? 
Extracellular vesicles (EVs) are the collective term for a range of cell-derived membranous particles integral to many normal cellular and tissue activities. Their impact upon a wide range of scientific fields and their potential clinical relevance have driven a growth in EV research and industrial interest1. Small EV (sEV) research primarily focuses on exosomes, 40-100 nm particles that begin formation in the early endosomes before maturation and release through fusion of multi-vesicular bodies (MVB) to the plasma membrane, as well as microvesicles, which bud directly from the plasma membrane forming 80-1,000 nm particles2. A third EV population are apoptotic bodies, 50-1,500 nm particles formed during cell death meaning their relative proportion to other EVs can be greatly variable3.
Because EV characteristics may represent changes occurring in their cell/tissue of origin, there is potential for their use in diagnostics. Various &#39;omics&#39; analyses have begun to identify markers of cell origin and disease state, which may allow for non-invasive assessment of patients using EV sources such as blood plasma/serum, urine, saliva and cerebral spinal fluid (CSF)4,5. A driving force behind these EV-related innovations are new characterization techniques that overcome previous limitations.
The need for, and challenges of, single EV characterization 
Single EV characterization is becoming increasingly important for both validation and description of EV isolates, as well as elucidating key features of these nanoparticles for progression of EV-based therapies and diagnostics6. Depending on the EV source and intended use, analysis of purity, often described as a ratio of EV to non-EV particles or as EV to free protein, can require significant amounts of data from multiple analytics7.
Particle counting and sizing measurements in EV publications have previously relied heavily on Nanoparticle tracking (NTA), resistive pulse sensing (RPS), and electron microscopy (EM)2. Standard NTA and RPS lack the ability to distinguish EVs from non-EV particles and have their own caveats such as slow throughput8 and unsuitable lower limit of detection seen with NTA9,10,11.
The tetraspanins CD9, CD63, and CD81 have historically been important identifiers for the presence of EVs in EV isolations/preparations. Commonly, western blotting (WB) and dot blotting techniques are used to show the enrichment of these proteins in EV isolates compared to cell lysate12. However, the lack of quantitation to these methods and the heterogeneity of these EV markers, regarding both display within EV subpopulations and cell, tissue or patient related variation, encourages advanced analytical techniques, which unify physical and phenotypic characterization13.
Nano-flow cytometry as a comprehensive EV analysis technique 
Determining true EV concentrations requires identification of intact particles and a universal marker, particularly in complex particle isolates, with resolution capable of detecting all EVs while distinguishing them from non-EV particles14.
Nano-flow cytometry (nFCM) is a technique that allows unlabeled analysis of particles sized between 45-1,000 nm while simultaneously utilizing fluorescent labeling and detection to identify particle subpopulations. A key distinction from conventional flow cytometry is the use of equipment dedicated to nanoparticle analysis, allowing for the greatest resolution15. EV analysis, which uses conventional flow instrumentation repurposed for small particle analysis is improving, but still struggles to attain the resolution to detect and analyze &#60;100 nm EVs16,17. Bead-based flow cytometry is a further adaptation often employed for EV analysis, but this removes the possibility of single particle detection and introduces capture based biases18.
Benefitting from a lower limit of detection of ~45 nm in the side scatter (SS) channel for EV analysis, nFCM utilizes SS triggering. This can be thought of as &#39;particle first&#39; analysis as it means that events must provide a SS signal, surpassing a set threshold before analysis of the fluorescence intensity. This removes false positives such as degraded membrane and fluorophore aggregations, and focuses&#160;analysis onto intact EVs15. SS measurements are also used to size individual particles by comparison to a four-modal silica nanosphere standard19. The fluorescence measurements are taken on two further detectors allowing three simultaneous measurements for each particle to describe particle concentration, sizes and presence of markers or other targets of interest in order to identify EV subpopulations20.
In the following experiment, SS and fluorescent (FL) measurements are used to measure &#62;45 nm particles, show the subset of membrane positive EVs, and identify CD9, CD63, CD81 presentation on EV subpopulations. Both the concentration of these subpopulations and their ratio as part of the total particles measured by SS are described, as are their size profiles.

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>APC Anti-CD81 antibody (M38)</td>
			<td>abcam</td>
			<td>ab233259</td>
			<td>Anti-Human CD81 APC 
			conjugated antibody</td>
		</tr>
		<tr>
			<td>APC Anti-CD9 antibody (EM-04)</td>
			<td>Abcam</td>
			<td>ab82392</td>
			<td>Anti-mouse CD9 APC 
			conjugated antibody</td>
		</tr>
		<tr>
			<td>APC Anti-CD9 antibody (MEM-61), prediluted</td>
			<td>abcam</td>
			<td>ab82389</td>
			<td>Anti-Human CD9 APC 
			conjugated antibody</td>
		</tr>
		<tr>
			<td>APC anti-mouse CD63 antibody</td>
			<td>biolegend</td>
			<td>143905</td>
			<td>Anti-Mouse CD63 APC 
			conjugated antibody</td>
		</tr>
		<tr>
			<td>APC anti-mouse/rat CD81 antibody</td>
			<td>biolegend</td>
			<td>104909</td>
			<td>Anti-Mouse CD81 APC 
			conjugated antibody</td>
		</tr>
		<tr>
			<td>CD63 monoclonal antibody (MEM-259), APC</td>
			<td>invitrogen Via Fisherscientific</td>
			<td>A15712</td>
			<td>Anti-Human CD63 APC 
			conjugated antibody</td>
		</tr>
		<tr>
			<td>Celline AD1000 bioreactor</td>
			<td>Merck</td>
			<td>Z688037-5EA</td>
			<td></td>
		</tr>
		<tr>
			<td>Cleaning solution</td>
			<td>NanoFCM</td>
			<td>17159</td>
			<td>In house cleaning solution for nanoanalyser</td>
		</tr>
		<tr>
			<td>EVs from C2C12</td>
			<td>Gifted</td>
			<td></td>
			<td>Mouse line</td>
		</tr>
		<tr>
			<td>EVs from SW620</td>
			<td>Gifted</td>
			<td></td>
			<td>Human line</td>
		</tr>
		<tr>
			<td>Memglow - Fluorogenic Membrane Probe</td>
			<td>Cytoskeleton</td>
			<td>MG01</td>
			<td>non toxic cell membrane dye</td>
		</tr>
		<tr>
			<td>NanoAnalyzer</td>
			<td>NanoFCM</td>
			<td></td>
			<td>nano-flow cytometer for measurement of single particles</td>
		</tr>
		<tr>
			<td>PBS, pH 7.2</td>
			<td>Gibco Via Fisherscientific</td>
			<td>12549079</td>
			<td>Salt solution for dilution of samples and antibodies</td>
		</tr>
		<tr>
			<td>Snaplock Microtubes, 0.60mL</td>
			<td>Axygen Via Fisherscientific</td>
			<td>11371944</td>
			<td>Tubes required to load sample into nanoanalyser</td>
		</tr>
	</tbody>
</table>

single extracellular vesicle transmembrane protein characterization by nano-flow cytometry

Single particle characterization has become increasingly relevant for research into extracellular vesicles, progressing from bulk analysis techniques and first-generation particle analysis to comprehensive multi-parameter measurements such as nano-flow cytometry (nFCM). nFCM is a form of flow cytometry that utilizes instrumentation specifically designed for nano-particle analysis, allowing for thousands of EVs to be characterized per minute both with and without the use of staining techniques. High resolution side scatter (SS) detection allows for size and concentration to be determined for all biological particles larger than 45 nm, while simultaneous fluorescence (FL) detection identifies the presence of labeled markers and targets of interest. Labeled subpopulations can then be described in quantitative units of particles/mL or as a percentage of the total particles identified by side scatter.
Here, EVs derived from conditioned cell culture media (CCM) are labeled with both a lipid dye, to identify particles with a membrane, and antibodies specific for CD9, CD63, and CD81 as common EV markers. Measurements of comparison material, a concentration standard and a size standard of silica nanospheres, as well as labeled sample material are analyzed in a 1-minute analysis. The software is then used to measure the concentration and size distribution profile of all particles, independent of labeling, before determining the particles that are positive for each of the labels.
Simultaneous SS and FL detection can be utilized flexibly with many different EV sources and labeling targets, both external and internal, describing EV samples in a comprehensive and quantitative manner.

Tetraspanin presentation on SW620 derived EVs and C2C12 derived EVs 
Modern analysis of the abundance of key tetraspanins CD9, CD63, and CD81 on EVs from a variety of sources has highlighted the extreme variability of their presence, both in bulk analyses and when analyzing their presentation on EV subpopulations21. This is likely related to the availability of different biogenesis pathways such as the ESCRT-dependent and independent pathways22.
CD9 was presented on the greatest percentage of C2C12 EVs at ~50%, with CD63 presentation on only ~30%, in Figure 1. When labeling was performed with all three anti-tetraspanins in one incubation, ~70% of particles were shown to present at least one of the EV markers. Repeat measurements showed lowest standard deviation for the CD9/63/81 labeling of C2C12 EVs at ~3.8%, while this was ~8.1% for the CD81 labeled C2C12 EVs.
SW620 derived EVs showed a different tetraspanin profile, with a much greater difference between the most presented CD9 at ~40% and the least presented CD63 at ~7%. Similar to the C2C12 EVs, CD9 was present on the majority of the tetraspanin positive population, as the CD9/63/81 combined labeling identified ~42% of particles as having at least one of the three markers.
The majority of C2C12 derived particles, the total SS+ population, ranged in size from 45-120 nm, with a median ~65 nm diameter. The size profiles for each of the single tetraspanin labeled EV-subpopulations, shown in Figure 1, are similar to each other, showing a larger median size of ~75-85 nm and fewer &#60;65 nm EVs compared to the total particle population.
SW620 derived particles ranged between 45-160 nm with a median size of ~65 nm, showing a skewed distribution. The tetraspanin labeled EVs show a more normal distribution and larger median diameter between 90-110 nm, with similar distributions between individual tetraspanin positive subpopulations.
While the most and least presented tetraspanins are the same for these two cell lines, their proportional representation differ greatly and there is an interesting difference between the potential co-presentation of tetraspanins observable from the difference in CD9 positivity and the CD9/63/81 positivity.
Combining EV membrane labeling with antibody labeling 
The bilayer membrane of EVs provides a more generic labeling target, which may allow distinction from similar sized non-EV particles such as protein aggregates and some forms of LDL with lipid monolayers23. The specificity of this type of labeling must be validated as some common membrane dyes used in EV research have been shown to bind to non-EV particles as well24.
Membrane labeling repeatedly showed ~80% positivity of C2C12 derived EVs and SW620 EVs. The SS intensity (SS-H) shows good correlation with FITC intensity on the dot plots of both C2C12 and SW620 results shown in Figure 2. This is expected as the SS intensity is relative to the particle size and hence the membrane surface area.
The majority of antibody labeled EVs were also positive for the membrane labeling showing double positive percentages (FITC+ &#38; APC+) very similar to the tetraspanin positive percentages. FITC vs APC dot plots show slight correlation between membrane and tetraspanin labeling with CD63 labeling seeming to show the weakest correlation to membrane labeling. Few events were detected that were positive for antibody labeling but negative for membrane labeling.
Reproducibility, dual labeling efficiency, and alternative data outputs 
An important consideration in designing nFCM experiments is fluorophore or label interactivity. Figure 3a shows that repeating the antibody labeling with and without additional membrane labeling leads to very similar % positivity measurements. In particular, the SW620 labeling shows very little variation between the two measurement sets. This shows limited interference between the dye and antibody binding and also highlights good reproducibility when repeating EV labeling.
Intensity measurements, both side scatter and fluorescence, can be exported to excel for each individual particle measured. From this we can generate mean fluorescence intensity (MFI) measurements to provide comparative approximations of the abundance of our labeled target. MFI for the fluorescent populations of C2C12 derived EVs suggest slightly lower presentation of CD63 and CD81 with MFI measurements of ~550 and ~600, respectively, compared to the ~850 MFI seen for CD9+ EVs. The units of measurement for MFI in this instance are FL-A and are not standardized against a fluorescent calibration. The use of all three antibodies does not elicit a much greater fluorescence than just CD9 labeling. This is very different to the SW620 MFI measurements, which suggest that using a cocktail of all three antibodies provides a greater fluorescence signal for labeled EVs, than the use of any individual antibody label.
The size distribution histograms produced by the NanoFCM software can also be exported into excel allowing for triplicate data sets to be overlayed. The size distributions profiles of Figure 3 are similar to those of Figure 1 but include error bars. Median EV size of the tetraspanin positive subpopulations in C2C12 derived EVs show a median around 70 nm, slightly larger than the 60 nm average of the total particle populations. SW620 EVs positive for tetraspanin markers are larger, showing peaks at ~100 nm.
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/64020/64020fig01.jpg" /> 
Figure 1: CD9, CD63, CD81 positive EV subpopulations identified by antibody labeling. (A) Bar chart showing percentage of labeled EVs compared to total particles observed by SS for C2C12 derived EVs. (B) Bar chart showing percentage of labeled EVs compared to total particles observed by SS for SW620 derived EVs. (C) Representative size distribution profiles for C2C12 derived EVs. Each histogram is taken from the PDFs generated for the first measurement of triplicate datasets. (D) Representative size distribution profiles for SW620 derived EVs. Each histogram is taken from the PDFs generated for the first measurement of triplicate datasets. Error bars represent standard deviation of triplicate measurements of the same labeled samples. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/64020/64020fig01large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/64020/64020fig02.jpg" /> 
Figure 2: Membrane labeling and antibody labeling of CD9, CD63, CD81 presenting EV subpopulations. (A) Bar chart showing Membrane+ %, tetraspanin+ % and double+ % for C2C12 EVs. (B) Bar chart showing Membrane+ %, tetraspanin+ % and double+ % for SW620 EVs. (C) Representative SS vs FITC dot plots showing gating for the Membrane positive population. (D) Representative FITC vs APC dot plots showing gating for double positive population of EVs from C2C12. (E) Representative FITC vs APC dot plots showing gating for double positive population of EVs from SW620. Error bars represent standard deviation of triplicate measurements of the same labeled samples. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/64020/64020fig02large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 3" class="xfigimg" src="/files/ftp_upload/64020/64020fig03.jpg" /> 
Figure 3: Assessing variation in repeat measurements. (A) Bar charts showing antibody labeling % positivity with and without additional membrane labeling. (B) Mean fluorescence intensity measurements for gated EV subsets. (C) Averaged size distribution histograms for triplicate data sets for C2C12 EVs. (D) Averaged size distribution histograms for triplicate data sets for SW620 EVs. Error bars represent standard deviation of triplicate measurements of the same labeled samples. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/64020/64020fig03large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>

Watch this Scientific Journal Video about Single Extracellular Vesicle Transmembrane Protein Characterization by Nano-Flow Cytometry at JoVE.com

Single Extracellular Vesicle Transmembrane Protein Characterization by Nano-Flow Cytometry

The latest generation of EV characterization tools are capable of single EV analysis across multiple parameters simultaneously. Nano-flow cytometry measures all biological particles larger than 45 nm without labeling and identifies specific characteristics of subpopulations by a variety of fluorescent labeling techniques.

Single particle characterization has become increasingly relevant for research into extracellular vesicles, progressing from bulk analysis techniques and ...

single-extracellular-vesicle-transmembrane-protein-characterization

Nanyang Technological University

Research

JoVE Journal

Biology

4.5K Views.  NanoFCM Co., Ltd. The latest generation of EV characterization tools are capable of single EV analysis across multiple parameters simultaneously. Nano-flow cytometry measures all biological particles larger than 45 nm without labeling and identifies specific characteristics of subpopulations by a variety of fluorescent labeling techniques.

Video: Single Extracellular Vesicle Transmembrane Protein Characterization by Nano-Flow Cytometry

IP-FCM:  Immunoprecipitation Detected by Flow Cytometry

Immunoprecipitation detected by flow cytometry (IP-FCM) is an efficient method for detecting and quantifying protein-protein interactions. The basic principle extends that of sandwich ELISA, wherein the captured primary analyte can be detected together with other molecules physically associated within multiprotein complexes. The procedure involves covalent coupling of polystyrene latex microbeads with immunoprecipitating monoclonal antibodies (mAb) specific for a protein of interest, incubating these beads with cell lysates, probing captured protein complexes with fluorochrome-conjugated probes, and analyzing bead-associated fluorescence by flow cytometry. IP-FCM is extremely sensitive, allows analysis of proteins in their native (non-denatured) state, and is amenable to either semi-quantitative or quantitative analysis. As additional advantages, IP-FCM requires no genetic engineering or specialized equipment, other than a flow cytometer, and it can be readily adapted for high-throughput applications.

The IP-FCM method is presented, which allows a sensitive, robust, biochemical assessment of native protein-protein interactions, without requiring genetic engineering or large sample sizes.

Immunoprecipitation detected by flow cytometry (IP-FCM) is an efficient method for detecting and quantifying protein-protein interactions. The basic ...

Transmembrane Domain Oligomerization Propensity determined by ToxR Assay

The oversimplified view of protein transmembrane domains as merely anchors in phospholipid bilayers has long since been disproven. In many cases membrane-spanning proteins have evolved highly sophisticated mechanisms of action.1-3 One way in which membrane proteins can modulate their structures and functions is by direct and specific contact of hydrophobic helices, forming structured transmembrane oligomers.4,5 Much recent work has focused on the distribution of amino acids preferentially found in the membrane environment in comparison to aqueous solution and the different intermolecular forces that drive protein association.6,7 Nevertheless, studies of molecular recognition at the transmembrane domain of proteins still lags behind those of water-soluble regions. A major hurdle remains: despite the remarkable specificity and affinity that transmembrane oligomerization can achieve,8 direct measurement of their association is challenging. Traditional methodologies applied to the study of integral membrane protein function can be hampered by the inherent insolubility of the sequences under examination. Biophysical insights gained from studying synthetic peptides representing transmembrane domains can provide useful structural insight. However, the biological relevance of the detergent micellar or liposome systems used in these studies to mimic cellular membranes is often questioned; do peptides adopt a native-like structure under these conditions and does their functional behaviour truly reflect the mode of action within a native membrane? In order to study the interactions of transmembrane sequences in natural phospholipid bilayers, the Langosch lab developed ToxR transcriptional reporter assays.9 The transmembrane domain of interest is expressed as a chimeric protein with maltose binding protein for location to the periplasm and ToxR to provide a report of the level of oligomerization (Figure 1).
In the last decade, several other groups (e.g. Engelman, DeGrado, Shai) further optimized and applied this ToxR reporter assay.10-13 The various ToxR assays have become a gold standard to test protein-protein interactions in cell membranes. We herein demonstrate a typical experimental operation conducted in our laboratory that primarily follows protocols developed by Langosch. This generally applicable method is useful for the analysis of transmembrane domain self-association in E. coli, where &#946;-galactosidase production is used to assess the TMD oligomerization propensity. Upon TMD-induced dimerization, ToxR binds to the ctx promoter causing up-regulation of the LacZ gene for &#946;-galactosidase. A colorimetric readout is obtained by addition of ONPG to lyzed cells. Hydrolytic cleavage of ONPG by &#946;-galactosidase results in the production of the light absorbing species o-nitrophenolate (ONP) (Figure 2).

An efficient procedure to assess the oligomerization propensity of single-pass transmembrane domains (TMDs) is described. Chimeric proteins consisting of the TMD fused to ToxR are expressed in an E. coli reporter strain. TMD-induced oligomerization causes dimerization of ToxR, activation of transcription and production of the reporter protein, -galactosidase.

The oversimplified view of protein transmembrane domains as merely anchors in phospholipid bilayers has long since been disproven.  In many cases ...

Purification of the Cystic Fibrosis Transmembrane Conductance Regulator Protein Expressed in Saccharomyces cerevisiae

Defects in the cystic fibrosis transmembrane conductance regulator (CFTR) protein cause cystic fibrosis (CF), an autosomal recessive disease that currently limits the average life expectancy of sufferers to &#60;40 years of age. The development of novel drug molecules to restore the activity of CFTR is an important goal in the treatment CF, and the isolation of functionally active CFTR is a useful step towards achieving this goal.
We describe two methods for the purification of CFTR from a eukaryotic heterologous expression system, S. cerevisiae. Like prokaryotic systems, S. cerevisiae can be rapidly grown in the lab at low cost, but can also traffic and posttranslationally modify large membrane proteins. The selection of detergents for solubilization and purification is a critical step in the purification of any membrane protein. Having screened for the solubility of CFTR in several detergents, we have chosen two contrasting detergents for use in the purification that allow the final CFTR preparation to be tailored to the subsequently planned experiments.
In this method, we provide comparison of the purification of CFTR in dodecyl-&#946;-D-maltoside (DDM) and 1-tetradecanoyl-sn-glycero-3-phospho-(1&#39;-rac-glycerol) (LPG-14). Protein purified in DDM by this method shows ATPase activity in functional assays. Protein purified in LPG-14 shows high purity and yield, can be employed to study post-translational modifications, and can be used for structural methods such as small-angle X-ray scattering and electron microscopy. However it displays significantly lower ATPase activity.

Purification of the Cystic Fibrosis Transmembrane Conductance Regulator Protein Expressed in Saccharomyces cerevisiae

Heterologous expression and purification of the cystic fibrosis transmembrane conductance regulator (CFTR) are significant challenges and limiting factors in the development of drug therapies for cystic fibrosis. This protocol describes two methods for the isolation of milligram quantities of CFTR suitable for functional and structural studies.&#160;

Defects in the cystic fibrosis transmembrane conductance regulator (CFTR) protein cause cystic fibrosis (CF), an autosomal recessive disease that ...

Characterization of G Protein-coupled Receptors by a Fluorescence-based Calcium Mobilization Assay

For more than 20 years, reverse pharmacology has been the preeminent strategy to discover the activating ligands of orphan G protein-coupled receptors (GPCRs). The onset of a reverse pharmacology assay is the cloning and subsequent transfection of a GPCR of interest in a cellular expression system. The heterologous expressed receptor is then challenged with a compound library of candidate ligands to identify the receptor-activating ligand(s). Receptor activation can be assessed by measuring changes in concentration of second messenger reporter molecules, like calcium or cAMP. The fluorescence-based calcium mobilization assay described here is a frequently used medium-throughput reverse pharmacology assay. The orphan GPCR is transiently expressed in human embryonic kidney 293T (HEK293T) cells and a promiscuous G&#945;16 construct is co-transfected. Following ligand binding, activation of the G&#945;16 subunit induces the release of calcium from the endoplasmic reticulum. Prior to ligand screening, the receptor-expressing cells are loaded with a fluorescent calcium indicator, Fluo-4 acetoxymethyl. The fluorescent signal of Fluo-4 is negligible in cells under resting conditions, but can be amplified more than a 100-fold upon the interaction with calcium ions that are released after receptor activation. The described technique does not require the time-consuming establishment of stably transfected cell lines in which the transfected genetic material is integrated into the host cell genome. Instead, a transient transfection, generating temporary expression of the target gene, is sufficient to perform the screening assay. The setup allows medium-throughput screening of hundreds of compounds. Co-transfection of the promiscuous G&#945;16, which couples to most GPCRs, allows the intracellular signaling pathway to be redirected towards the release of calcium, regardless of the native signaling pathway in endogenous settings. The HEK293T cells are easy to handle and have proven their efficacy throughout the years in receptor deorphanization assays. However, optimization of the assay for specific receptors may remain necessary.

The here described fluorescence-based calcium mobilization assay is a medium-throughput reverse pharmacology screening system for the identification of functionally activating ligand(s) of orphan G protein-coupled receptors (GPCRs).

For more than 20 years, reverse pharmacology has been the preeminent strategy to discover the activating ligands of orphan G protein-coupled receptors ...

High Efficiency Differentiation of Human Pluripotent Stem Cells to Cardiomyocytes and Characterization by Flow Cytometry

There is an urgent need to develop approaches for repairing the damaged heart, discovering new therapeutic drugs that do not have toxic effects on the heart, and improving strategies to accurately model heart disease. The potential of exploiting human induced pluripotent stem cell (hiPSC) technology to generate cardiac muscle &#8220;in a dish&#8221; for these applications continues to generate high enthusiasm. In recent years, the ability to efficiently generate cardiomyogenic cells from human pluripotent stem cells (hPSCs) has greatly improved, offering us new opportunities to model very early stages of human cardiac development not otherwise accessible. In contrast to many previous methods, the cardiomyocyte differentiation protocol described here does not require cell aggregation or the addition of Activin A or BMP4 and robustly generates cultures of cells that are highly positive for cardiac troponin I and T (TNNI3, TNNT2), iroquois-class homeodomain protein IRX-4 (IRX4), myosin regulatory light chain 2, ventricular/cardiac muscle isoform (MLC2v) and myosin regulatory light chain 2, atrial isoform (MLC2a) by day 10 across all human embryonic stem cell (hESC) and hiPSC lines tested to date. Cells can be passaged and maintained for more than 90 days in culture. The strategy is technically simple to implement and cost-effective. Characterization of cardiomyocytes derived from pluripotent cells often includes the analysis of reference markers, both at the mRNA and protein level. For protein analysis, flow cytometry is a powerful analytical tool for assessing quality of cells in culture and determining subpopulation homogeneity. However, technical variation in sample preparation can significantly affect quality of flow cytometry data. Thus, standardization of staining protocols should facilitate comparisons among various differentiation strategies. Accordingly, optimized staining protocols for the analysis of IRX4, MLC2v, MLC2a, TNNI3, and TNNT2 by flow cytometry are described.

The article describes the detailed methodology to efficiently differentiate human pluripotent stem cells into cardiomyocytes by selectively modulating the Wnt pathway, followed by flow cytometry analysis of reference markers to assess homogeneity and identity of the population.

There is an urgent need to develop approaches for repairing the damaged heart, discovering new therapeutic drugs that do not have toxic effects on the ...

Techniques for the Analysis of Extracellular Vesicles Using Flow Cytometry

Extracellular Vesicles (EVs) are small, membrane-derived vesicles found in bodily fluids that are highly involved in cell-cell communication and help regulate a diverse range of biological processes. Analysis of EVs using flow cytometry (FCM) has been notoriously difficult due to their small size and lack of discrete populations positive for markers of interest. Methods for EV analysis, while considerably improved over the last decade, are still a work in progress. Unfortunately, there is no one-size-fits-all protocol, and several aspects must be considered when determining the most appropriate method to use. Presented here are several different techniques for processing EVs and two protocols for analyzing EVs using either individual detection or a bead-based approach. The methods described here will assist with eliminating the antibody aggregates commonly found in commercial preparations, increasing signal&#8211;to-noise ratio, and setting gates in a rational fashion that minimizes detection of background fluorescence. The first protocol uses an individual detection method that is especially well suited for analyzing a high volume of clinical samples, while the second protocol uses a bead-based approach to capture and detect smaller EVs and exosomes.

Many different methods exist for the measurement of extracellular vesicles (EVs) using flow cytometry (FCM). Several aspects should be considered when determining the most appropriate method to use. Two protocols for measuring EVs are presented, using either individual detection or a bead-based approach.

Extracellular Vesicles (EVs) are small, membrane-derived vesicles found in bodily fluids that are highly involved in cell-cell communication and help ...

Detecting and Characterizing Protein Self-Assembly In Vivo by Flow Cytometry

Protein self-assembly governs protein function and compartmentalizes cellular processes in space and time. Current methods to study it suffer from low-sensitivity, indirect read-outs, limited throughput, and/or population-level rather than single-cell resolution. We designed a flow cytometry-based single methodology that addresses all of these limitations: Distributed Amphifluoric FRET or DAmFRET. DAmFRET detects and quantifies protein self-assemblies by sensitized emission FRET in vivo, enables deployment across model systems-from yeast to human cells-and achieves sensitive, single-cell, high-throughput read-outs irrespective of protein localization or solubility.

This article describes a FRET-based flow cytometry protocol to quantify protein self-assembly in both S. cerevisiae and HEK293T cells.

Protein self-assembly governs protein function and compartmentalizes cellular processes in space and time. Current methods to study it suffer from ...

Quantification of Cellular Densities and Antigenic Properties using Magnetic Levitation

The described method was developed based on the principles of magnetic levitation, which separates cells and particles based on their density and magnetic properties. Density is a cell type identifying property, directly related to its metabolic rate, differentiation, and activation status. Magnetic levitation allows a one-step approach to successfully separate, image and characterize circulating blood cells, and to detect anemia, sickle cell disease, and circulating tumor cells based on density and magnetic properties. This approach is also amenable to detecting soluble antigens present in a solution by using sets of low- and high-density beads coated with capture and detection antibodies, respectively. If the antigen is present in solution, it will bridge the two sets&#160;of beads, generating a new bead-bead complex, which will levitate in between the rows of antibody-coated beads. Increased concentration of the target antigen in solution will generate a larger number of bead-bead complexes when compared to lower concentrations of antigen, thus allowing for quantitative measurements of the target antigen. Magnetic levitation is advantageous to other methods due to its decreased sample preparation time and lack of dependance on classical readout methods. The image generated is easily captured and analyzed using a standard microscope or mobile device, such as a smartphone or a tablet.

This paper describes a magnetic levitation-based method that can specifically detect the presence of antigens, either soluble or membrane-bound, by quantifying changes in the levitation height of capture beads with fixed densities.

The described method was developed based on the principles of magnetic levitation, which separates cells and particles based on their density and magnetic ...

Extracellular Vesicle Uptake Assay via Confocal Microscope Imaging Analysis

There is a need for practical assays to visualize and quantify the cells' extracellular vesicle (EV) uptake. EV uptake plays a role in intercellular communication in various research fields; cancer biology, neuroscience, and drug delivery. Many EV uptake assays have been reported in the literature; however, there is a lack of practical, detailed experimental methodology. EV uptake can be assessed by fluorescently labeling EVs to detect their location within cells. Distinguishing between internalized EVs in cells and the superficial EVs on cells is difficult, yet critical, to accurately determine the EV uptake. Therefore, an assay that efficiently quantifies EV uptake through three-dimensional (3D) fluorescence confocal microscopy is proposed in this work. Fluorescently labeled EVs were prepared using a nano-filtration-based microfluidic device, visualized by 3D confocal microscopy, and then analyzed through advanced image-processing software. The protocol provides a robust methodology for analyzing EVs on a cellular level and a practical approach for efficient analysis.

Extracellular Vesicle Uptake Assay via Confocal Microscope Imaging Analysis

Extracellular vesicles (EVs) contribute to cellular biology and intercellular communications. There is a need for practical assays to visualize and quantify EVs uptake by the cells. The current protocol proposes the EV uptake assay by utilizing three-dimensional fluorescence imaging via confocal microscopy, following EV isolation by a nano-filtration-based microfluidic device.

There is a need for practical assays to visualize and quantify the cells' extracellular vesicle (EV) uptake. EV uptake plays a role in intercellular ...

Isolation and Characterization of Cyanobacterial Extracellular Vesicles

Cyanobacteria are a diverse group of photosynthetic, Gram-negative bacteria that play critical roles in global ecosystems and serve as essential biotechnology models. Recent work has demonstrated that both marine and freshwater cyanobacteria produce extracellular vesicles -&#160;small membrane-bound structures released from the outer surface of the microbes. While vesicles likely contribute to diverse biological processes, their specific functional roles in cyanobacterial biology remain largely unknown. To encourage and advance research in this area, a detailed protocol is presented for isolating, concentrating, and purifying cyanobacterial extracellular vesicles. The current work discusses methodologies that have successfully isolated vesicles from large cultures of Prochlorococcus, Synechococcus, and Synechocystis. Methods for quantifying and characterizing vesicle samples from these strains are presented. Approaches for isolating vesicles from aquatic field samples are also described. Finally, typical challenges encountered with cyanobacterial vesicle purification, methodological considerations for different downstream applications, and the trade-offs between approaches are also discussed.

The present protocol providesdetailed descriptions for isolation, concentration,and characterization of extracellular vesicles from cyanobacterial cultures. Approaches for purifying vesicles from cultures at different scales, trade-offs among methodologies, and considerations for working with field samples are also discussed.

Single Extracellular Vesicle Transmembrane Protein Characterization by Nano-Flow Cytometry

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Chapters in this video

IP-FCM: Immunoprecipitation Detected by Flow Cytometry

Transmembrane Domain Oligomerization Propensity determined by ToxR Assay

Purification of the Cystic Fibrosis Transmembrane Conductance Regulator Protein Expressed in Saccharomyces cerevisiae

Characterization of G Protein-coupled Receptors by a Fluorescence-based Calcium Mobilization Assay

High Efficiency Differentiation of Human Pluripotent Stem Cells to Cardiomyocytes and Characterization by Flow Cytometry

Techniques for the Analysis of Extracellular Vesicles Using Flow Cytometry

Detecting and Characterizing Protein Self-Assembly In Vivo by Flow Cytometry

Quantification of Cellular Densities and Antigenic Properties using Magnetic Levitation

Extracellular Vesicle Uptake Assay via Confocal Microscope Imaging Analysis

Isolation and Characterization of Cyanobacterial Extracellular Vesicles