Quantifying extracellular vesicles (EVs) is essential for optimizing isolation workflows, developing EV-based assays, and advancing biomarker discovery. Single particle techniques such as flow cytometry and nanoparticle tracking analysis (NTA) face limitations in capital cost, throughput, and reproducibility, since they require skilled operators and extensive optimization when working from complex biofluids like serum and plasma (1-5). Western blotting can detect EV proteins but is limited by throughput, tedious sample preparation, and sensitivity. The Atlas EV ELISA offers a practical alternative: a plate-based, scalable, and highly reproducible assay for both total EV quantification and targeted surface marker detection. With high sensitivity and a wide dynamic range, the Atlas EV ELISA provides a robust and accessible solution for EV analysis.
How it works:
The Atlas EV ELISA is a one-step assay targeting the tetraspanins CD9, CD63, and CD81 on intact EVs. It runs directly on biofluids (plasma, serum, urine, CSF, cell culture supernatant) or on purified EVs (e.g. SEC fractions), using only 50 μL of sample without the need for purification or concentration. Researchers can run a few wells at a time or scale up to full 96-well plates for high-throughput studies.
The Atlas EV ELISA is available in two formats:
- Absorbance ELISA – Easy to implement on standard plate readers, offering robust performance across large cohorts and reliable tracking of EV yield and quality.
- Customizable Chemiluminescence ELISA – Provides sensitive detection with a wide dynamic range and the flexibility to target specific EV surface proteins. This format enables profiling of disease-relevant markers that conventional methods often miss.
| LOD | Dynamic range | |
| Atlas Absorbance | 9.7 e7 particles/mL | ~2 logs |
| Atlas Lumi | 1.0 e7 particles/mL | ~4 logs |
Figure 1: Atlas Absorbance and Lumi ELISAs. EV standard was serially diluted and measured with either Atlas absorbance ELISA (green) and Atlas Lumi ELISA (orange) in duplicates. Limit of Detection (LOD) and the assay’s dynamic range are presented in the table 1.
Workflow:
- Plate – Add diluted sample followed by the antibody mix directly into the wells
- Incubation – incubate the plate up to 3 hours
- Wash – Remove unbound material with wash buffer
- Signal Generation – Add substrate (TMB or chemiluminescent reagents)
- Detect – Measure absorbance or luminescence with a standard plate reader or the Atlas ELISA reader
Figure 2: Schematic illustration of the Atlas EV ELISA workflow.
Applications in EV Isolation and Characterization:
Atlas Absorbance ELISA – SEC optimization use case
Atlas absorbance ELISAs are particularly powerful for quantifying EV yield and purity following isolation by size exclusion chromatography (SEC), a method widely recommended by the MISEV guidelines. By measuring EV-specific proteins and contaminants directly, the assay allows researchers to fine-tune fraction collection and optimize workflows for downstream applications.
To demonstrate this, 0.5 mL of plasma was fractionated using Apex 4B and Apex 6B SEC columns. And the fractions were analyzed with Atlas EV ELISA and human serum albumin (HSA) ELISA. The Atlas EV ELISA showed that EVs eluted primarily in fractions 1 through 3, with higher yields observed for the Apex 6B column. In parallel, the Atlas HSA ELISA detected secreted proteins beginning in fraction 2 demonstrating lower purity than the Apex 4B. To better capture the trade-off between yield and purity, we calculated the cumulative recovery of both EVs and HSA across sequential fractions. For both column types, adding the first two fractions captured the majority of EVs while keeping secreted protein contamination low. Inclusion of the third fraction further increased EV yield but introduced some additional HSA. By contrast, collecting a fourth fraction provided little to no gain in EV recovery but caused a sharp rise in HSA levels, dramatically reducing purity. This cumulative analysis highlights how Atlas EV ELISA can guide fraction selection decisions.
Figure 3: Using the Atlas ELISAs for optimizing EV isolation.
A) A 0.5mL pooled plasma sample was fractionated with either an Apex 4B column (green) or an Apex 6B column (orange). Individual 0.5mL fractions were collected and analyzed with Atlas EV ELISA (solid lines) and Atlas HSA ELISA (dashed lines).
B) The total amount of EVs (top) and HSA (bottom) in each fraction was calculated by multiplying the concentration by the fraction volume. Cumulative levels across an increasing number of fractions for EVs (top) and HSA (bottom) were then calculated and plotted.
Comparison to single particle analysis
We also compared Atlas EV ELISA results with NTA and flow cytometry. First, we measured a commercially available EV standard (Sigma Aldrich, SAE0193) that the supplier had estimated at 5 × 10¹⁰ EV/mL when reconstituted in 100 μL of solution. Using the Atlas EV ELISA, we obtained comparable values to those reported by the manufacturer. Independent measurements by NTA and flow cytometry also produced similar concentrations (Table 2), confirming the accuracy of the assay. The flow cytometry concentration measurement was based on labeling the EVs with the same tetraspanin antibodies as the Atlas EV ELISA.
Next, we ran a comparison using a more complex samples, i.e. we isolated EVs from plasma using the Apex-6B column and analyzed pooled EV fractions with Atlas EV ELISA, NTA, and two flow-based EV systems. The Atlas EV ELISA reported concentrations consistent with those obtained by labeled flow cytometry using either the CytoFLEX Nano or NanoFCM platforms. In contrast, unlabeled NTA detected 10–20 times more particles than ELISA or labeled flow assays (Table 1), which was from the large population of lipoproteins and other non-EV nanoparticles.
| Atlas EV ELISA | CytoFlex | NanoFCM | NTA | |
| EV standard | 5.0 e10 | 2.9 e10 | 1.4 e10 | 2.9 e10 |
| Plasma EVs | 7.9 e10 | 2.7 e10 | 1.9 e10 | 5.7 e11 |
Table 2: EV characterization with Atlas EV ELISA, NTA, and single-EV flow methods.
Finally, we compared ELISA and NTA directly across SEC fractions obtained with Apex 4B and Apex 6B columns. Both assays revealed similar elution profiles, confirming that EVs elute in the early fractions. However, NTA consistently reported particle counts five- to ten-fold higher than Atlas EV ELISA. This discrepancy was especially pronounced with the Apex 6B column, which is known to co-elute small lipoproteins together with EVs. These results underscore the advantage of protein-specific quantification over particle-based approaches, demonstrating that the Atlas EV ELISA more accurately reflects true EV content rather than total particle counts.
Figure 4: Correlation between Atlas EV ELISA and NTA. Fractions 1, 2, and 3 shown in Figure 3 were analyzed using the ZetaView instrument (ParticleMetrix). NTA measurements (top) revealed an EV elution profile similar to that observed with the Atlas EV ELISA (bottom) for fractions collected using either the Apex 6B column (orange) or the Apex 4B column (green). The higher particle concentrations detected by NTA compared to ELISA can be attributed to the presence of non-EV particles, such as lipoproteins, which co-elute with EVs when using resins with smaller pore sizes (e.g., the 20 nm pores of the Apex 6B column).
Atlas Lumi ELISA with Homebrew conjugation kit for biomarker quantification
The Atlas Lumi ELISA, due to the increased sensitivity and dynamic range offered from a chemiluminescence assay, is particularly well suited for detecting tissue-specific markers on the EV surface, many of which are present at low abundance and can vary by orders of magnitude between patient samples. Using the homebrew conjugation kit, researchers can replace the standard tetraspanin capture cocktail with an antibody targeting a specific EV surface marker. As an example, we conjugated an anti-CD41 antibody and used it as a capture reagent to quantify platelet-derived EVs, which carry CD41 on their membranes. Fresh blood samples were collected, and platelets were either left unaltered or experimentally activated, a condition expected to increase the release of CD41-positive EVs. Plasma from both conditions was then fractionated using SEC, and CD41-positive EVs were quantified using the Atlas Lumi Homebrew ELISA. Due to the wide dynamic range of the chemiluminescence assay, we were able to reliably detect CD41-positive EVs in both activated and non-activated plasma samples within the same experiment, with able to reliably detect CD41-positive EVs in both activated and non-activated plasma samples within the same experiment, without the need to run multiple dilutions for each condition.
Figure 5: Colocalizing CD41 with tetraspanins on EVs using the homebrew Lumi ELISA. An anti-CD41 antibody was conjugated and used as the capture reagent in a Lumi ELISA assay. Plasma samples, with and without platelet activation, were fractionated using an Apex 4B column, and the relative levels of CD41-positive EVs were measured across fractions. The wide dynamic range of the Lumi assay enables profiling of CD41-positive EVs in both high- and low-abundance samples using the same dilution factor.
Summary – Atlas EV ELISA for scalable, reproducible EV quantification
The Atlas EV ELISA provides a robust, high-throughput, plate-based solution for quantifying extracellular vesicles (EVs) and targeted surface markers directly from biofluids or purified samples. Unlike particle-based methods such as NTA or flow cytometry, Atlas delivers specific, reproducible results with minimal sample prep, 15 minutes hands-on-time and only 50 µL input.
Atlas ELISAs from Everest Biolabs are available in two formats:
- Absorbance ELISA – Simple and reliable EV yield and purity assessment using standard plate readers.
- Chemiluminescence (Lumi) ELISA – High sensitivity, wide dynamic range, and customizable capture (Homebrew options) for profiling disease-relevant markers.
Applications include optimizing SEC fractionation, comparing EV yield vs purity, validating against NTA/flow cytometry, and detecting low-abundance, tissue-specific markers with the Lumi Homebrew kit.
What applications are you interested in using the Atlas EV ELISA for?
References:
- Théry, C., Witwer, K.W., Aikawa, E., et al. (2018). Minimal information for studies of extracellular vesicles 2018 (MISEV2018): a position statement of the ISEV and update of the MISEV2014 guidelines. Journal of Extracellular Vesicles, 7(1): 1535750.
- Welsh, J.A., Holloway, J.A., Wilkinson, J.S., & Englyst, N.A. (2017). Extracellular vesicle flow cytometry analysis and standardization. Frontiers in Cell and Developmental Biology, 5: 78.
- Welsh, J.A., van der Pol, E., Arkesteijn, G.J.A., et al. (2022). MIFlowCyt-EV: a framework for standardized reporting of extracellular vesicle flow cytometry experiments. Journal of Extracellular Vesicles, 11(2): e12182.
- Mørk, M., Handberg, A., Pedersen, S., et al. (2017). Prospects and limitations of nanoparticle tracking analysis (NTA) in extracellular vesicle research. Journal of Extracellular Vesicles, 6(1): 1305676.
- Davidson, S.M., Boulanger, C.M., & Yellon, D.M. (2023). Extracellular vesicles and cardiovascular disease: biology and translational opportunities. Cardiovascular Research, 119(5): 1132–1148.
