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Nanoscale imaging using differential expansion microscopy

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Abstract

Expensive and time-consuming approaches of immunoelectron microscopy of biopsy tissues continues to serve as the gold-standard for diagnostic pathology. The recent development of the new approach of expansion microscopy (ExM) capable of fourfold lateral expansion of biological specimens for their morphological examination at approximately 70 nm lateral resolution using ordinary diffraction limited optical microscopy, is a major advancement in cellular imaging. Here we report (1) an optimized fixation protocol for retention of cellular morphology while obtaining optimal expansion, (2) an ExM procedure for up to eightfold lateral and over 500-fold volumetric expansion, (3) demonstrate that ExM is anisotropic or differential between tissues, cellular organelles and domains within organelles themselves, and (4) apply image analysis and machine learning (ML) approaches to precisely assess differentially expanded cellular structures. We refer to this enhanced ExM approach combined with ML as differential expansion microscopy (DiExM), applicable to profiling biological specimens at the nanometer scale. DiExM holds great promise for the precise, rapid and inexpensive diagnosis of disease from pathological specimen slides.

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Acknowledgements

Work presented in this article was supported in part by the National Science Foundation Grants EB00303, CBET1066661 (BPJ).

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Author notes

  1. Sebastian P. Pernal, Asiri Liyanaarachchi and Domenico L. Gatti contributed equally to the study.

Authors and Affiliations

  1. Department of Physiology, Wayne State University School of Medicine, 540 E. Canfield, 5245, 5215 Scott Hall, Detroit, MI, 48201, USA

    Sebastian P. Pernal, Asiri Liyanaarachchi, Brent Formosa, Rishika Pulvender, Eric R. Kuhn, Rafael Ramos, Akshata R. Naik, Kathleen George & Bhanu P. Jena

  2. NanoBioScience Institute, Wayne State University, Detroit, MI, 48201, USA

    Sebastian P. Pernal, Domenico L. Gatti, Rishika Pulvender, Rafael Ramos, Suzan Arslanturk & Bhanu P. Jena

  3. Center for Molecular Medicine and Genetics, Wayne State University, Detroit, MI, 48201, USA

    Rishika Pulvender & Bhanu P. Jena

  4. Biochemistry, Microbiology and Immunology, School of Medicine, Wayne State University, Detroit, MI, 48201, USA

    Domenico L. Gatti

  5. Department of Computer Science, College of Engineering, Wayne State University, Detroit, MI, 48201, USA

    Suzan Arslanturk

  6. Department of Pathology and Laboratory Medicine, Microscopy Imaging Center, University of Vermont College of Medicine, Burlington, VT, 05405, USA

    Douglas J. Taatjes

Authors
  1. Sebastian P. Pernal
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  2. Asiri Liyanaarachchi
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  9. Kathleen George
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  11. Douglas J. Taatjes
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  12. Bhanu P. Jena
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Contributions

BPJ developed the idea. BPJ, SPP, AL and DLG designed experiments for the study. BPJ and DLG wrote the manuscript. SPP, AL, BF, ERK, RR and KG performed the expansion studies. ARN performed the human primary skeletal muscle cell cultures. DLG, SA and BPJ participated in the machine learning (ML) aspects of the study and DLG performed all ML studies. DJT performed electron microscopy. RP helped SPP, AL and BF in expansion experiments and in the manual morphometric analysis of the images. All authors participated in discussions and proofreading of the manuscript.

Corresponding author

Correspondence to Bhanu P. Jena.

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Conflict of interest

BPJ, SPP, AL, DLG, BF and SA have filed for patent protection on a subset of the technologies described in the manuscript. BPJ has helped co-found a company (QPathology) to help develop an automated high-throughput screening device for disease detection and to disseminate such device and the associated neural network platforms to the community.

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Electronic supplementary material

Below is the link to the electronic supplementary material.

418_2020_1869_MOESM1_ESM.docx

Supplementary Material: Supplementary material containing figures S1-S3; the Video/Audio Tutorial, and the Matlab script to determine the probability distribution of linear expansion ratios, are provided on line. (DOCX 1711 kb)

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Pernal, S.P., Liyanaarachchi, A., Gatti, D.L. et al. Nanoscale imaging using differential expansion microscopy. Histochem Cell Biol 153, 469–480 (2020). https://doi.org/10.1007/s00418-020-01869-7

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  • DOI: https://doi.org/10.1007/s00418-020-01869-7

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