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. 2025 Jul 29;10(31):34659–34665. doi: 10.1021/acsomega.5c03540

The Use of dSTORM-Based Single Exosome Analysis To Study Tetraspanin Abundance in Extracellular Vesicles

Komal Abhange †, Siobhan King ‡, Nicole Peterson §, Vaibhav Sahai §, Kyle C Cuneo ∥, David M Lubman †,*
PMCID: PMC12355246  PMID: 40821521

Abstract

Serum-derived exosomes are membrane-enclosed nanovesicles secreted by cells, typically between 30 and 120 nm in diameter. Exosomes can be identified by the presence of tetraspanin protein markers including CD9, CD81, and CD63 among others. The relative amounts of these exosomal markers and their location in the exosomes are also related to their source of origin. The ability to investigate these different markers and their locations in individual and multiple exosomes was obtained using an optical imaging technique known as dSTORM (direct stochastic optical reconstruction microscopy) which can overcome the diffraction limit for detection of these nanovesicles. The use of the dSTORM imaging method has allowed us to evaluate the relative abundance of tetraspanin markers CD9, CD81, and CD63 in exosomes and the size of exosomes related to these markers. We also compared the presence of these markers in normal versus pancreatic cancer serum samples and against exosomes secreted from cell lines. We found that CD9 is generally the most abundant marker in exosomes and is found near the surface of the exosomes, although CD81 and CD63 abundance is also significant. This result is consistent with our prior DIA mass spectrometry data and may be important in future work involving analysis of exosomes as markers of disease.

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Introduction

Serum-derived exosomes are membrane-enclosed nanovesicles secreted by cells, typically between 30 and 120 nm in diameter. − These exosomes are secreted into the bloodstream by various cells and contain a distinct cargo of proteins, lipids, RNAs, and metabolites that are associated with cells from which they originate. Exosomes can be identified by the presence of tetraspanin protein markers including CD9, CD81, and CD63 among others. − The relative amount of these exosomal markers and their location in the exosomes are also related to their source of origin. This feature of exosomes may provide opportunities for their use as markers for detection of various diseases such as cancer or Alzheimer’s using a simple liquid biopsy. −

In recent work, using negative-stain TEM, it has been shown that CD9 is heavily expressed on the surface of exosomes and extracellular vesicles (EVs) isolated from patient serum. Furthermore, CD9 has been identified in previous work as a favorable prognostic marker or predictor of metastatic potential depending on the cancer type. , The CD9 marker for EVs has been used to design a CD9-based immunoaffinity column which can be used in an HPLC-based format to isolate exosomes from patient serum. The advantages of this column included efficient isolation of exosomes from serum, a rapid method where isolation could be achieved in <30 min, reusability of the column over multiple runs, and where impurities could be continuously washed away using the HPLC method.

Herein, we have explored the relative abundance and location for the tetraspanin markers CD9, CD81, and CD63 in serum-derived exosomes and exosomes secreted by cell lines obtained from a commercial source. The ability to investigate these different markers and their locations in individual and multiple exosomes was obtained using an optical imaging technique known as dSTORM (direct stochastic optical reconstruction microscopy) which can overcome the diffraction limit in imaging based on the use of blinking fluorophores. − This method depends on a “blinking” phenomenon where upon irradiation with an intense laser, only some fluorophores emit light at any given moment, i.e., stochastic blinking between an ON state and an OFF state. A sensitive camera records the ON states of the fluorophores that label a target marker in the exosome. A point-spread function (PSF) is fitted to determine the precise spatial localization. Once each blinking fluorophore is localized in the exosome membrane, the structure of the object can be reconstructed. The method can size exosomes down to at least 20 nm and can localize the number and position of the target markers based on the fluorophores.

The use of the dSTORM imaging method has allowed us to evaluate the relative amount of tetraspanin markers CD9, CD81, and CD63 in serum-derived exosomes. Furthermore, we compared the presence of these markers in normal versus pancreatic cancer serum samples and against exosomes secreted from cell lines obtained from a commercial source. We found that CD9 is generally the most abundant marker in exosomes, especially in serum, although CD81 and CD63 are also present at significant levels. These results were compared to our previous ones based on DIA-mass spectrometry. This result may be important in future work involving isolation and analysis of exosomes as markers for various disease conditions. − ,,

Experimental Section

The general workflow for this work is shown in Figure . The initial step involves surface preparation of the assay chip, followed by capturing the exosomes on the surface. The sample needs to be fixed, blocked, and then stained by the appropriate antibodies and fluorescent tags. The experiment can be performed using either a PS capture or Tetraspanin capture mode. The exosomes can then be imaged using an ONI Nanoimaging device: Nanoimager S Mark III (Oxford Nanoimaging [ONI], Oxford UK) and analyzed using ONI CODI software.

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Experimental workflow: Exosome isolation using multiple cycles of ultracentrifugation, assay chip preparation for dSTORM imaging of exosomes using CD9, CD81, and CD63 cocktail, and ONI Nanoimager (Image Created Using BioRender).

Materials

The required components for these experiments were obtained through ONI’s EV Profiler 2 kit and include the following for PS or tetraspanin capture and profiling: the ONI assay chip and surface reagent, fixative, permeabilization buffer, staining buffer, anti-CD81-647, anti-CD63-568, anti-CD9-488, and ONI dSTORM imaging buffer.

Exosome Standards

HT29 (ab239690), PC3 (ab239689), and MCF7 (ab239691) exosome standards were purchased from Abcam (Waltham, MA), which were derived from human cancer cell lines and lyophilized. The lyophilized exosome standards, 100 μg per vial, were reconstituted with 200 μL of water to reach a concentration of 0.5 μg of EVs/μL. Exosome standards were then aliquoted and stored at −80 °C until further use. For these experiments, an equal mix of the three standards was made and denoted as “mix” in further descriptions.

Human Serum Samples

The pooled human serum, which was used as the “normal”, was purchased from Innovative Research Inc. (Novi, MI). The pooled serum was filtered through a 200 nm cartridge. After purchase, it was aliquoted and stored at −80 °C until further use to avoid freeze–thaw cycles.

The pancreatic serum samples were obtained from patients with metastatic late-stage cancer diagnoses after providing informed consent. The protocol for sample processing was the same as that utilized by the NCI EDRN, and the samples were obtained under IRB approval from the University of Michigan Hospital. The samples were stored at −80 °C and used without freeze–thaw cycles.

Extracellular Vesicle Preparation

The standard exosomes of MCF7 and the mix were diluted to a concentration of 1 × 109–11 particles/mL for this work. They were both used without further purification.

The Exosome Enrichment from serum was performed using five cycles of UC as in our prior work which has been found to provide the optimal isolation of exosomes from serum. , We used 0.5 mL of normal serum as the starting volume. Prior to UC, the serum was processed to eliminate large particle impurities, where 0.5 mL of serum was combined with an equal volume of PBS (1:1) and filtered through a 0.22 μm filter. The filtered sample was then centrifuged at 5000g for 10 min at 4 °C, and the resulting supernatant was collected. Following this, centrifugation at 10,000g for 30 min was performed, and the supernatant was collected. Next, the processed sample, along with 1 mL of PBS, was transferred to a 3 mL Open-Top Thickwall Polycarbonate tube (Beckman Coulter, Indianapolis, IN) for UC using a Beckman Optima XL-70 ultracentrifuge. Initially, the sample was subjected to UC at 100,000g for 2 h at 4 °C, followed by four cycles of UC for 1.5 h.

TEM Size Assessment

The exosome samples used in this work were assessed by TEM using negative staining in a prior work. TEM images were obtained on a JEOL 1400-plus transmission electron microscope.

Chip and Sample Preparation

(see Figure ) (a) Preparation of the assay chip: The assay chip should be stored in a refrigerator but then allowed to warm to room temperature before use. The chip should be placed in a humidity chamber to prevent evaporation. 10 μL of surface reagent was applied with 15 min incubation while rocking. The chip was washed with wash buffer and 10 μL of capture reagent was applied with a 15 min incubation time while rocking. It is then washed with wash buffer again. (b) Capture and fixation: 10 μL exosome solution which should be at a concentration of 1 × 109–11 particles/mL was applied. It is then incubated for 75 min while rocking and washed with wash buffer. 20 μL of fixative was applied, followed by incubation for 10 min and then washing. (c) Staining: 10 μL of staining buffer was applied with 10 min incubation. For tetraspanin detection, Detection Antibody dilution of anti-CD9-488, anti-CD63-568, and anti-CD81-647 was prepared. 10 μL of detection antibody dilution was applied followed by incubation for 50 min with rocking and then washing. 20 μL of fixative was applied, followed by incubation for 5 min and washing again. dSTORM Imaging Buffer was prepared and 20 μL of prepared dSTORM Imaging Buffer was added to all Assay Chip lanes and seal lanes with inlet/outlet sealing stickers, followed by a 10 min incubation.

Imaging

Imaging was conducted on an ONI Nanoimager S Mark III using a 1.4 100× oil immersion objective using the CODI AutoEV software. The microscope was calibrated before the samples were imaged using a bead slide to ensure channel alignment. TIRF illumination was applied through AutoEV’s auto-TIRF function. Each label was imaged for 1,000 frames at 30 ms with the following laser powers: 640:120 mW, 561:100 mW, and 488:160 mW. A total of 3 fields of view (FOVs) were recorded per sample.

Analysis

The analysis was performed using the ONI’s CODI software with the EV profiling app. The three-color tetraspanin workflow was used for all of the samples. Here, drift correction, dSTORM filtering, and DBSCAN clustering were used to classify and quantify each extracellular vesicle (EV).

Filter Parameters

647 Channel

  • SigmaX and SigmaY: [50, 225]

  • Intensity: [200, 7500]

  • Frame Index: [50, 999]

568 Channel

  • SigmaX and SigmaY: [50, 225]

  • Intensity: [200, 7500]

  • Frame Index: [1050, 1999]

488 Channel

  • SigmaX and SigmaY: [50, 225]

  • Intensity: [200, 7500]

  • Frame Index: [2050, 2999]

Clustering Parameters

  • Method: DBSCAN

  • Epsilon (eps): 100

  • Minimum Cluster Size: 10

  • Minimum Samples: 5

  • Circularity: [0.3, 1]

  • Convex Hull Area: [700, 1,000,000]

  • Radius of Gyration: [20, 1,000,000]

  • Positivity Value: 3 (for positive cluster counting)

Results and Discussion

Figure shows the relative distribution of tetraspanin markers CD9, CD81, and CD63 for several samples obtained by the dSTORM method based on capture using PS on the ONI commercial chip. The graphs shown are color coded to show the relative number of exosomes that have the markers alone or in various combinations. In Figure a–c is the results for exosomes secreted from (a) a standard control sample of HCT116, (b) MCF7, and (c) an equal mix of MCF7/PC3/HT29 cell lines. In the case of the exosomes from the control and MCF cell line, it is shown that in nearly 50% of the exosomes, the three markers CD9, CD81, and CD63 are detected. Only a small fraction of the exosomes have CD9 markers detected alone (3% in the control and 6% in MCF). CD9 is detected in 87% of the exosomes in combination with other tetraspanin markers. The results are very similar for the exosomes from a mix of three cell lines. In this case, 40% of exosomes have all three markers, whereas CD9 alone is found in only 5% of the exosomes. CD9 is found in combination with the other markers or alone in 77% of the exosomes. Likewise, CD81 is found in 75% of the exosomes and CD63 in 72% of the exosomes in various combinations.

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Composition of CD81, CD63, and CD9 in exosome clusters for PS capture samples. (a) E1-control, (b) MCF7 exosomes, (c) Mix exosomes, and (d) normal serum exosomes.

It should be noted that the MCF7 and MCF7/PC3/HT29 mix were analyzed using mass spectrometry based on DIA-MS analysis in our prior work where over 1000 proteins were detected and where all three markers were detected in both MCF and the equal “mix”.33 CD9 was our strongest detected marker, followed by CD81. There were several other markers that were followed in this work, but CD9/CD81 markers were the strongest. CD63 was detected but at lower but significant levels compared to the other markers. This is consistent with our findings visualized by dSTORM where CD9 localizations per exosome are the highest and CD63 the lowest. This is in comparison with the work based on mass spectrometry analysis of Hoshino et al. where CD9 was found to be the most highly expressed marker, whereas CD81 was detected at much lower levels and CD63 not detected at all. However, this work was based on a different isolation and analysis method where DDA-MS was used which resulted in a much lower number of proteins detected from plasma and serum (∼270) compared to our work using DIA-MS and where it might be expected that using DDA-MS, CD63 and other markers may not be detected. Also, Saftics et al. performed work using a similar technique to that used herein but that differs in the way they achieve single-molecule localization and quantification. They also used a different isolation method for EVs. The Saftics paper shows CD9 as the major marker detected from plasma, but CD81 and CD63 were detected at lower levels. This is not consistent with our mass spectrometry data, and they did not use mass spectrometry to confirm these results.

The size distribution of the markers as a function of tetraspanin is found in Supplementary Figure S1a. The method shows that the CD81 marker is found in the smallest exosomes while CD9 is generally found in larger exosomes, although the distribution shows exosomes that are generally less than 150 nm for these commercial exosomes. The size distribution is like that found for these exosomes by TEM in prior work, where the average size was 75 nm. The dSTORM method has a distinct advantage over TEM (or mass spectrometry) where the distribution of exosome sizes based on the specific tetraspanin markers can be observed and exosome size can be observed for individual exosomes over a much larger field of view.

Figure d shows the dSTORM results for exosomes from a normal serum sample as prepared by UC. In this case, 45% of the exosomes are CD9 only and the highest number of localizations across over 4,000 clusters shows that CD9 is by far the most highly expressed. Also, the case where all three markers are present on the exosomes is only 13%, which is much lower than that of the exosomes from the cell lines which is closer to 50%. The CD9 marker is found in 87% of exosomes which is like that of the cell lines. This is shown in Figure g,h which shows a bar graph of the percentage of each marker and its combination in the exosome population, where the CD9 population is clearly the most highly expressed. The high expression of CD9 in these serum exosomes has also been shown in recent work using mass spectrometry analysis, where CD9 was the highest marker observed quantitatively. Also, in other work using negative-stain TEM, it was shown that CD9 is strongly detected in these serum exosomes and was detected near the surface of the exosomes in large numbers. The major advantage of the dSTORM method is that the distribution of these markers on the exosomes can be obtained where only a bulk number can be obtained using these other techniques. It should be noted that CD81 and CD63 are present at significant levels at 37% and 44%, respectively.

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Comparison of CD81, CD63, and CD9 composition in exosome clusters for TST v/s PS capture for (a) E1 std Tetra, (b) EV cell line mixture Tetra, (c) Normal serum Tetra, (d) E1 std PS, (e) EV cell line mix PS, and (f) Normal serum PS; (g) histogram showing relative amounts of the surface markers for Tetra capture; (h) histograms showing relative amounts of the surface markers for PS capture.

Also, Supplementary Figure S1 shows the size distribution of exosomes for each of the three markers, which is like that of the exosomes from the cell lines. The CD81 marker is found in the smallest exosomes, while CD9 is found in the larger exosomes in the distribution. The typical size of the exosomes as determined by TEM was 100–120 nm, Supplementary Figure S3.

Figure a,b shows the distribution of markers in the exosomes for the (a) mix of 3 cell lines and (b) exosomes from normal patient serum sample as obtained using tetraspanin capture (TST) on the slides. In the case of the exosomes from the cell lines, CD9 alone is only 6% while the three markers together are 39% of the exosome population, which is similar to the PS capture. This compares to the serum sample where the CD9 population as the only marker is 50% of the exosomes while the mix of three markers is only 7% of the exosome population. The CD9 marker is on 94% of the exosomes (Figure e), and the number of CD9 markers over the exosomes studied is much higher than the other markers. The population of CD63 at 32% is much lower than that of the CD9 marker. These results are roughly similar to that obtained from the PS capture where the same samples were used in both experiments and from prior work using mass spectrometry analysis. Also, note that the size distribution is similar where CD81 is on the smallest exosomes, while CD9 is on the larger exosomes (Supplementary Figure S1).

Figure a–f shows the dSTORM analysis of exosome markers obtained from a pancreatic cancer serum sample. Figure a represents the exosome standard obtained by using Tetra capture for comparison, where CD9, CD81, and CD63 and combinations thereof are detected. Figure b,c shows a comparison of analysis of exosomes from a metastatic pancreatic serum sample versus a normal sample for TST capture, respectively. Figure d shows the exosome standard results obtained using PS capture. Figure e,f shows a comparison of the results from a pancreatic cancer serum sample versus a normal sample using PS capture. As in the case of the normal serum, where CD9 alone is typically detected in 45–50% of the exosomes, CD9 is also the dominant marker detected in the pancreatic exosomes, where it was detected as the single marker in 43–50% of the exosomes. CD9 was also observed as the dominant marker with the CD9 marker combined with other markers, where it was detected in 87–94% of the exosomes in normal serum as compared to 88–93% for the pancreatic samples. Also, the results obtained between the TST and PS methods were similar in terms of the distribution of exosome surface markers detected. In addition, the size distributions between normal and cancer samples were similar, where the CD81 exosomes were generally on the smaller side of the size distribution, whereas the CD9 exosomes were on the larger side of the distribution.

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Composition of CD81, CD63, and CD9 in exosome clusters for (a) E1 Tetra std, (b) pancreatic cancer serum Tetra, (c) normal serum Tetra, (d) E1 PS std, (e) pancreatic cancer serum PS, and (f) normal serum PS capture.

Conclusions

We used the dSTORM single exosome method to study the distribution of tetraspanin markers on exosomes from serum and cell lines. The major advantage of this method is that one can study the distribution of markers based on individual exosomes and can also study the size distribution relative to these markers, as opposed to prior work using mass spectrometry to characterize these samples. We used dSTORM imaging for exosomes from normal and pancreatic serum samples as prepared by UC and found that the CD9 marker alone had the highest number of localizations and that CD9 was the most highly expressed of the tetraspanins monitored. This was found to be the case for both the use of TST and PS capture. The CD9 marker was found to be present on nearly 90% of all exosomes using both capture methods, although both CD81 and CD63 were detected at significant levels. This result contrasts with that of the exosomes from cell lines, where CD9 alone may only be on 5% of the exosomes. Also, the case where all three markers are present on the exosomes is only 13% for normal serum, which is much lower than that of the exosomes from the cell lines, which is closer to 50%. It was also found that in terms of the size distribution, the smallest exosomes were CD81 positive, whereas the CD9 marker was generally on the larger exosomes.

Supplementary Material

ao5c03540_si_001.pdf (617.9KB, pdf)

Acknowledgments

We would like to thank Alex Kukreja, PhD, and Regan Moore, Ph.D. Field Application ScientistsOxford Nanoimaging for help acquiring and interpreting some of the data.

The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acsomega.5c03540.

  • Size distribution of EV samples using PS capture vs TST capture; E1-control, MCF7 EVs, Mix EVs, and normal serum EVs; single exosome cluster visualization using CODI along with the specific markers from the CD cocktail; presence of CD81 visualized in pink, CD63 in yellow, and CD9 in cyan; size and morphology characterization of exosomes using TEM; and pancreatic serum sample where the exosomes have been isolated using multiple cycles of ultracentrifugation (PDF)

⊥.

K.A. and S.K. contributed equally. The manuscript was written through contributions of all authors. All authors have given approval to the final version of the manuscript.

This work was funded by the National Cancer Institute under grant 1R01 CA258240 (DML) and under Award Number P30 CA046592.

The pancreatic cancer sample in this work was archived and deidentified. It was originally obtained by Kyle C. Cuneo, M.D., and Vaibhav Sahai, MBBS, under IRB approval with consent from the University of Michigan Hospital.

The authors declare no competing financial interest.

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