Rapid magnetic isolation of extracellular vesicles via lipid-based nanoprobes

Abstract

Extracellular vesicles (EVs) can mediate intercellular communication by transferring cargo proteins and nucleic acids between cells. The pathophysiological roles and clinical value of EVs are under intense investigation, yet most studies are limited by technical challenges in the isolation of nanoscale EVs (nEVs). Here, we report a lipid-nanoprobe system that enables spontaneous labelling of nEVs for subsequent magnetic enrichment in 15 minutes, with isolation efficiency and cargo composition similar to what can be achieved by the much slower and bulkier method of ultracentrifugation. We also show that this approach allows for downstream analyses of nucleic acids and proteins, enabling the identification of EGFR and KRAS mutations following nEV isolation from the blood plasma of non-small-cell lung-cancer patients. The efficiency and versatility of the lipid-nanoprobe approach opens up opportunities in point-of-care cancer diagnostics.

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Figure 1: Schematic of the LNP system for nEV enrichment and downstream analyses.
Figure 2: Morphological characterization of the materials and optimization of the LNP system for isolation efficiency.
Figure 3: Isolated nEVs provide flexibility in downstream molecular analyses.
Figure 4: Detection of DNA mutations in nEVs isolated from plasma samples from NSCLC patients.

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Acknowledgements

S.-Y.Z. thanks the Penn State Materials Research Institute, the Huck Institute of Life Sciences, the Penn State Hershey Cancer Institute, the Penn State proteomic and mass spectrometry facilities at Hershey and University Park, the Penn State Microscopy and Cytometry Facility, and the Penn State Genomics Facility for their support. This work was partially supported by the Pennsylvania State University start-up fund and the National Cancer Institute of the National Institutes of Health under Award Number DP2CA174508. We thank the Applied Bioinformatics Center (BFX) at the New York University (NYU) School of Medicine for providing bioinformatics support and for helping with the analysis and interpretation of the data. This work used computing resources at the High Performance Computing Facility (HPCF) of the Center for Health Informatics and Bioinformatics at the NYU Langone Medical Center. We also thank the Genome Technology Center (GTC) for library preparation and sequencing. This shared resource is partially supported by the Cancer Center Support Grant, P30CA016087, at the Laura and Isaac Perlmutter Cancer Center. We would like to thank S. Hafenstein at Penn State Hershey for discussions on cryo-SEM and C. Zhang at the Dana-Farber Cancer Institute for his advice on genomic analysis.

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Contributions

Y.W. and S.-Y.Z. designed the research. Y.W. conducted experiments and analysed data. G.C. prepared the MMPs, assisted with peptide-sample preparation and performed proteomic analyses. S.-J.H. assisted with the preparation of NGS samples, the analysis of RNA NGS data, and the fluorescence imaging. M.N. prepared blood plasma. C.-D.Z. and W.-Q.L. assisted with the cell culture, nEV collection and gel electrophoresis. Y.-Q.X. performed the wound-healing assay. Z.-G.W. performed the electron microscopy. W.-L.Z. assisted with the image processing. A.S and I.A analysed NGS DNA data. X.L., S.J.R. and C.P.B. recruited patients and provided blood samples, tissue NGS data and clinical support. Y.W. and S.-Y.Z. wrote the manuscript.

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Correspondence to Si-Yang Zheng.

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The authors declare no competing financial interests.

Supplementary information

Supplementary Information

Supplementary tables, figures and references (PDF 7817 kb)

Supplementary Dataset 1

Top-1,000 expressed mRNAs (XLSX 47 kb)

Supplementary Dataset 2

Top-1,000 expressed miRNAs (XLSX 43 kb)

Supplementary Dataset 3

Cargo proteins in the nanoscale extracellular vesicles (XLSX 384 kb)

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Wan, Y., Cheng, G., Liu, X. et al. Rapid magnetic isolation of extracellular vesicles via lipid-based nanoprobes. Nat Biomed Eng 1, 0058 (2017). https://doi.org/10.1038/s41551-017-0058

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