In-depth characterization of EVs can be challenging, requiring multiple instruments to describe individual parameters. Measuring these key criteria in a single technique like Nano-Flow Cytometry describes multiple EVs subpopulations simultaneously. So each EV is measured individually identifying particles larger than 14 nanometers in diameter label-free before determining their fluorescence.
This makes for a robust data set by removing false positives. Nano-Flow Cytometry can be applied to EVs from a variety of sources, including those enriched from plasma, CSF, and culture medium. This technique is also used for the analysis of viruses, lipid nanoparticles, and nanomaterials.
It's important to get the labeling protocol optimized. This maximizes any fluorescence associated with a particle compared to any residual fluorescence left in the buffer. To begin, turn the instrument on, load Nano-Flow Profession and select Start Up from the Sheath Flow dropdown menu, load water into the loading bay, and select Boosting from the Sheath Flow dropdown menu.
Dilute the QC beads one to 100 in distilled water in a 0.6 microliter tube, and place it in the loading bay to introduce the sample into the system. Then boost the sample for 45 seconds as demonstrated earlier to completely replace the previous sample, water, or cleaning solution. While boosting, set the laser power to the preset template for QC beads to 250 nanometers FL QC standard.
Later, to reduce the system pressure, select the sampling pressure from the same dropdown menu and set the auto-sampling pressure to one kilo pascal to maintain a constant pressure. Then initiate the one-minute analysis by selecting Time To Record from the acquisition controls. Data will be plotted on the dot plot showing a log scale for side scatter intensity, and a selected fluorescence intensity.
Before saving the file, insert the file name and sample dilution. Next, select unload to remove the tube from the loading bay. Replace the QC beads with 150 microliters of cleaning solution and clean for more than 30 seconds by selecting Boosting.
Using a tube containing 150 microliters of water, remove any excess cleaning solution from the capillary tip by dipping the tip in water. Then dilute the size standard beads one to 100 in water and load 100 microliters into the loading bay. Now, set the laser power to the preset template, S16 EXO 68 to 155 nanometers.
This setting is for both the size standard and samples containing EVs smaller than 200 nanometers. Select sampling and proceed to record the sample for one minute. Perform the third measurement with either a water or PBS sample to create a blank measurement devaluent, identifying false positives for removal by the software.
Dilute the unlabeled EV samples in PBS to a suitable particle concentration range of one times 10 to the eighth to five times 10 to the eighth particles per milliliter for nFCM analysis. And load 10 to 100 microliters of the diluted sample into the loading bay. If the particle concentration is unknown, begin with a one to 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. Once the loaded sample is boosted for 45 seconds, record for one minute and save the file as demonstrated earlier. After recording, begin analyzing this data, switching from the Acquisition tab to the Analysis tab and opening the saved NFA files.
For accurate sample measurement, use the two standard measurements taken prior to sampling measurement to set values for sample comparison as well as the blank. Create the size standard curve for side scatter to diameter conversion by selecting the size standard file and using the set threshold tool. The threshold, visible in the event burst trace, identifies the minimum signal intensity required for an event to be considered significant.
With the threshold set, check the dot plot parameters, SS-H or SS-A on the X-axis and FITC-A on the Y axis. Open the Standard Curve Generation tool and select S16 EXO 68 to 155 nanometers as the sizing template. Click on Find Peaks to identify the peak side scatter intensities as either 68, 91, 113, or 155 nanometer diameter particles.
Before closing the window, check whether the side scattered to diameter curve has been generated with an R value close to one. Set the concentration standard. Select the saved file, click on count standard and input the particle concentration of the standard.
Set the standard information. Select the EV sample file and set the threshold. Select the blank file and click on set blank to identify the number of false positives for removal from the sample count.
Once the PDF Generation Tool is opened, check sizing, concentration, and the dilutions of the sample. Then show the concentration of the sample and the size distribution of the particles. After labeling the EV samples as described in the manuscript, take one microliter of the labeled sample and dilute one to 50 in PBS in a 0.6 milliliter tube.
Load the sample into the loading bay and apply boosting pressure for 45 seconds. Also, ensure correct laser settings and the appropriate lenses are loaded. Now, switch to sampling pressure and select the time to record.
Following the one minute acquisition, name the data file and save. Unload the sample, replace it with a cleaning solution, and boost the cleaning solution for more than 30 seconds before loading the next labeled sample as demonstrated previously. For PDF generation, apply the same standards as previously demonstrated.
Only the blank measurement will be set differently. Select the sample file and set the threshold. Select the gating tool and use the left click to draw a line separating the fluorescence positive population.
Set the names and colors for representation. Set the blank file and click on set blank to identify the number of false positives for removal from each different population. Open the PDF Generation Tool and identify the size distribution, concentration, and percentage of the fluorescence positive subpopulation.
On the dot plot, change the Y-axis to show fluorescence measurements from the green or red channel. Set the blank and generate the PDF as demonstrated previously. On the dot plot, set the X-axis to FITC and Y axis to APC.
Utilize the quadrant tool to identify double fluorescent positive populations. Set names and colors to be representative, then open the PDF file and select the fluorescent subpopulations. C2C12 derived EVs showed approximately 50%CD9, 30%CD63 presentation, and 70%population presented at least one of the three EV markers.
The size profiles for single tetraspanin-labeled EV subpopulations showed a larger median size of approximately 75 to 85 nanometers and fewer less than 65 nanometer EVs compared to the total particle population. SW620-derived EVs showed approximately 40%CD9, 7%CD63 presentation, and 42%of particles as having at least one of the three markers. The SW620-derived, tetraspanin-labeled EVs showed a more normal distribution and larger median diameter between 90 to 110 nanometers with similar distributions between individual tetraspanin positive subpopulations.
Membrane labeling repeatedly showed 80%positivity of C2C12 and SW620-derived EVs. The side scatter intensity correlated with FITC intensity on the dot plots of both C2C12 and SW620. The double positive percentages are very similar to the tetraspanin positive percentages.
And CD63 labeling seems to show the weakest correlation to membrane labeling. The percentage positivity measurements were similar between the antibody labeling with and without additional membrane labeling. Mean fluorescence intensity for the fluorescent populations of C2C12-derived EVs suggested a lower presentation of CD63 and CD81 as compared to CD9 EVs, while SW620 showed that using all three antibodies provides a greater fluorescence signal than any individual antibody label In this protocol, common EV markers have been fluorescently labeled, but many of the antibody targets can be chosen to show the EV origin, the EV function, or the disease state.
