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Exosome detection via the ultrafast-isolation system: EXODUS

Nature Methods volume 18, pages 212–218 (2021)Cite this article

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Abstract

Exosomes have shown great potential in disease diagnostics and therapeutics. However, current isolation approaches are burdensome and suffer from low speed, yield and purity, limiting basic research and clinical applications. Here, we describe an efficient exosome detection method via the ultrafast-isolation system (EXODUS) that allows automated label-free purification of exosomes from varied biofluids. We obtained the ultra-efficient purification of exosomes by negative pressure oscillation and double coupled harmonic oscillator–enabled membrane vibration. Our two coupled oscillators generate dual-frequency transverse waves on the membranes, enabling EXODUS to outperform other isolation techniques in speed, purity and yield. We demonstrated EXODUS by purifying exosomes from urine samples of 113 patients and validated the practical relevance in exosomal RNA profiling with the high-resolution capability and high-throughput analysis.

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Fig. 1: The hybrid macro- and nanomechanical oscillator-based exosome isolation system: EXODUS.
Fig. 2: Mechanism and results of ultrafast purification via EXODUS with double coupled oscillators and the NPO.
Fig. 3: Characterization of EXODUS performance and comparison to other methods of exosome isolation.
Fig. 4: An example of EXODUS performance: profiling enriched pathways in bladder cancer and kidney cancer based on DEG analysis.

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Data availability

The data that support the findings of this study are available from the corresponding author upon request. The raw sequencing data are available at Genome Sequence Archive for Human with Bioproject ID PRJCA003921 and data accession number HRA000457. Source data are provided with this paper.

Code availability

The codes applied in this work are available at Zenodo47 and github website at https://github.com/sterding/EXODUS.

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Acknowledgements

We thank Tongji Hospital in the Tongji Medical College at Huazhong University of Science and Technology for providing clinical samples in this study. The work was primarily supported by research fund provided by the Zhenan Technology City Research Fund, the Zhejiang Provincial and Ministry of Health Research Fund for Medical Sciences (grant no. WKJ-ZJ-1910), the Wenzhou Medical University (grant no. 89218012) and the Wenzhou Institute, University of Chinese Academy of Sciences (grant no. WIBEZD2017006-05).

Author information

Author notes

  1. These authors contributed equally: Yuchao Chen, Qingfu Zhu.

Authors and Affiliations

  1. Eye Hospital, School of Ophthalmology and Optometry, School of Biomedical Engineering, Wenzhou Medical University, Wenzhou, Zhejiang, China

    Yuchao Chen, Qingfu Zhu, Liang Hu, Doudou Lou & Fei Liu

  2. Wenzhou Institute, University of Chinese Academy of Sciences, Wenzhou, Zhejiang, China

    Yuchao Chen, Yong Wang, Qinsi Yang & Fei Liu

  3. Department of Laboratory Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China

    Liming Cheng & Jiaoyuan Li

  4. College of Chemistry and Chemical Engineering, Xi’an University of Science and Technology, Xi’an, China

    Meng Li

  5. Department of Neurology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA

    Xianjun Dong

  6. Renal Division and Division of Engineering in Medicine, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA

    Luke P. Lee

  7. Department of Bioengineering, Department of Electrical Engineering and Computer Science, University of California at Berkeley, Berkeley, CA, USA

    Luke P. Lee

  8. Institute of Quantum Biophysics, Department of Biophysics, Sungkyunkwan University, Suwon, Korea

    Luke P. Lee

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Contributions

L.P.L. and F.L. conceived the project and designed the experiments. L.H., L.C. and J.L. organized and collected clinical samples. Y.C. designed the EXODUS device and workstation. Y.C., Q.Z. and Y.W. performed EXODUS system optimization. Y.C., Q.Z., Y.W., M.L. and Q.Y. purified and characterized urinary exosomes. L.H., D.L. and Q.Y. contributed to scanning electron microscopy and TEM analysis of exosomes. Y.W., Q.Y., Q.Z. and M.L. performed isolation method comparison, western blot analysis and NTA for urinary exosomes. Q.Z., Y.W. and Q.Y. performed EV subtype analysis. M.L., Q.Z. and Q.Y. isolated and analyzed saliva samples. M.L., Q.Z. and Q.Y. compared methods for analyzing saliva exosomes. Y.C. and Q.Z. determined the recovery rate. Y.C., Q.Z., M.L., Y.W., L.C., L.H., D.L. and X.D. contributed to data analysis and interpretation. L.C. and J.L. analyzed data related to clinical samples. Y.C. and Q.Z. wrote the manuscript. L.P.L and F.L. edited the manuscript. All experiments were conducted under the supervision of L.P.L. and F.L. All authors read and approved the final manuscript.

Corresponding authors

Correspondence to Luke P. Lee or Fei Liu.

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The authors declare no competing interests.

Additional information

Peer review information Madhura Mukhopadhyay was the primary editor on this article and managed its editorial process and peer review in collaboration with the rest of the editorial team.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data

Extended Data Fig. 1 Illustration of EXODUS device.

a, A photo of the EXODUS device, with its cross-sectional illustration. Scale bar, 1 cm. b, Illustration of harmonic oscillations in the EXODUS device for minimizing fouling effect and bio-aggregates. c, The vibration motors generate acoustic streaming at different fluidic levels inside the EXODUS device. Scale bar, 1 cm.

Extended Data Fig. 2 The system design of the EXODUS workstation.

a, An image of the workstation. Scale bar, 10 cm. b, Internal view of the workstation, including (1) autosampler, (2) needle, (3) needle wash site, (4) EXODUS device window, (5) specimen tube, (6) wash buffer A, and (7) wash buffer B. Scale bar, 3 cm. c, The interface to EXODUS device via station: a device slot moves out from inside by pressing the button “Install Device” on the control panel to install EXODUS’s membrane device onto the workstation. d, The architecture of the EXODUS workstation. e, The illustration of the fluidic system in the EXODUS workstation.

Extended Data Fig. 3 Simulations of pressure, flow distribution, and vibration modes of the EXODUS device.

a, COMSOL simulation showing the pressure distribution in a cross-section view of the EXODUS device when applying a −20 kPa negative pressure (NP) from the L-outlet. The sample is injected from the top opening into the sample reservoir. b, Distribution of flow velocity on the membrane from top to bottom. The flow velocity is between 45 and 60 μm/s, with a variation below 25%. c, Simulation of different vibration modes for a clamped circular nanoporous AAO membrane at their representative vibration frequencies: 469.8 Hz (5–700 Hz), 1281.8 Hz (700–1600 Hz), 1861.8 Hz (1600–3000 Hz), 3717.8 Hz (3000–5000 Hz), 5921.8 Hz (5000–8000 Hz), and 10562 Hz (8000–11500 Hz). The integer index m refers to the azimuthal node number. The index n refers to the nth non-trivial zero of the Bessel function. The high-frequency oscillation of the membrane at 6250 Hz by piezoelectric transducer has a (0,4) vibration mode, while the low high-frequency oscillation of the membrane at 200 Hz by vibration motor has a (0,1) vibration mode. The scale ranges from no displacement (dark blue) to maximum displacement (dark red).

Extended Data Fig. 4 Characterization of EXODUS.

a, Comparison of the sample processing times of EXODUS and other methods showing their detailed procedures. For each method, the time cost was basically calculated according to its protocol. b, Size distributions and c amount of the particles obtained by EXODUS and other methods from 10 mL of urine sample aliquots. (n≥5 independent experiments). d, Isolation of exosomes from 10 mL of urine sample aliquots with 20 replications to study the reproducibility of EXODUS. Qubit™ Protein Assay Kits measured the total protein amounts of isolated samples, with an average protein amount of 4.3 μg and a CV of 9.9% over the 20 measurements. e, The concentrations and f size distributions of the particles isolated from different biofluids by EXODUS. (n = 3 independent experiments). The concentration of tear exosomes is presented as particles per centimeter tear collection paper. In c and e, data are presented as mean value ± SD. NTA profiles in b and f are constructed by the average curve (solid line) and error band (shaded area).

Source data

Extended Data Fig. 5 NTA and TEM analysis of EV subpopulations.

a, NTA profiles of EV particles with serious cut-off size ranges of 20–450, 20–100, 100–200, and 200–450 nm. b, The typical TEM images of vesicle subpopulations and the corresponding statistics of size distributions are summarized in c. (20–450 nm: n = 565 independent EVs, 20–100 nm: n = 386 independent EVs, 100–200 nm: n = 46 independent EVs, 200–450 nm: n = 31 independent EVs).

Source data

Supplementary information

Supplementary Information

Supplementary Figs. 1–17 and Notes 1–3.

Reporting Summary

Supplementary Video 1

Transverse waves observed at the top surface of liquid in PEI device.

Supplementary Video 2

Transverse waves observed in the deep of PEI device.

Supplementary Video 3

Transverse waves observed in a PMMA device.

Supplementary Table 1

Clinical information of patients

Supplementary Data

Original western blot scans.

Source data

Source Data Fig. 2

Statistical Source Data

Source Data Fig. 3

Statistical Source Data

Source Data Fig. 4

Statistical Source Data

Source Data Extended Data Fig. 4

Statistical Source Data

Source Data Extended Data Fig. 5

Statistical Source Data

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Chen, Y., Zhu, Q., Cheng, L. et al. Exosome detection via the ultrafast-isolation system: EXODUS. Nat Methods 18, 212–218 (2021). https://doi.org/10.1038/s41592-020-01034-x

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