Brief Communication | Published:

Nanobody immunostaining for correlated light and electron microscopy with preservation of ultrastructure

Nature Methodsvolume 15pages10291032 (2018) | Download Citation

Abstract

Morphological and molecular characteristics determine the function of biological tissues. Attempts to combine immunofluorescence and electron microscopy invariably compromise the quality of the ultrastructure of tissue sections. We developed NATIVE, a correlated light and electron microscopy approach that preserves ultrastructure while showing the locations of multiple molecular moieties, even deep within tissues. This technique allowed the large-scale 3D reconstruction of a volume of mouse hippocampal CA3 tissue at nanometer resolution.

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Data availability

The authors declare that the main data supporting the findings of this study within the article and its Supplementary Information files are available. The high-resolution EM, low-resolution EM and aligned LM image stacks can be downloaded from https://software.rc.fas.harvard.edu/lichtman/temp/NATIVE.

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

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Acknowledgements

We thank S.-H. Sheu for helpful discussions of the tissue staining protocols and K. Swee (BioMed X Innovation Center, Heidelberg, Germany) and V. Verschoor (Boston Children’s Hospital, Boston, MA, USA) for providing the Ly-6C/G-specific nanobody. This research is supported by grants D16PC00002, GG008784, P50 MH094271, and U19 NS104653-01 to J.L.; R01AI087879 to H.P.; and F32CA220990 to T.F.

Author information

Author notes

  1. These authors contributed equally: Tao Fang and Xiaotang Lu.

Affiliations

  1. Program of Cellular and Molecular Medicine, Boston Children’s Hospital, Boston, MA, USA

    • Tao Fang
    •  & Hidde Ploegh
  2. Department of Molecular and Cellular Biology and The Center for Brain Science, Harvard University, Cambridge, MA, USA

    • Xiaotang Lu
    • , Daniel Berger
    • , Christina Gmeiner
    • , Richard Schalek
    •  & Jeff Lichtman
  3. Department of Biology, Massachusetts Institute of Technology, Cambridge, MA, USA

    • Julia Cho

Authors

  1. Search for Tao Fang in:

  2. Search for Xiaotang Lu in:

  3. Search for Daniel Berger in:

  4. Search for Christina Gmeiner in:

  5. Search for Julia Cho in:

  6. Search for Richard Schalek in:

  7. Search for Hidde Ploegh in:

  8. Search for Jeff Lichtman in:

Contributions

X.L. and T.F. conceived, designed and implemented NATIVE with contributions from all authors. R.S. assisted in collecting serial sections, EM imaging and aligning EM images. D.B. provided the tracing tool and performed EM-LM alignment and 3D rendering. C.G. led segmentation efforts with contributions from X.L., T.F. and J.C. J.L. and H.P. supervised the work. All authors contributed to data analysis. All authors contributed to writing of the manuscript.

Competing interests

A provisional patent application has been filed.

Corresponding authors

Correspondence to Hidde Ploegh or Jeff Lichtman.

Integrated supplementary information

  1. Supplementary Figure 1 Raw fluorescent Z-stack images.

    The corresponding video (Supplementary Video 1) shows nanobody-labeled GFAP (astrocyte marker) in red, CD11b (microglia marker) in yellow, Ly-6C/6G (endothelial cell marker for capillaries) in green, and cell nuclei labeled by Hoechst in blue

  2. Supplementary Figure 2 3D view of part of the LM image data.

    The corresponding video (Supplementary Video 2) shows nanobody-labeled GFAP (astrocyte marker) in red, CD11b (microglia marker) in yellow, Ly-6C/6G (endothelial cell marker for capillaries) in green, and cell nuclei labeled by Hoechst 33342 in white. A prominent microglia with its branches can be seen in the center of the video. This is a screen capture from the VAST 3D viewer

  3. Supplementary Figure 3 LM image data overlaid on top of the low-resolution EM data after affine LM–EM alignment.

    The corresponding video (Supplementary Video 3) demonstrates the alignment precision reached by a single linear (3D affine) transformation across an example section of the dataset and how to use LM to assist cell-type identification in EM data. This is a screen capture from the VAST 2D view

  4. Supplementary Figure 4 High-resolution electron microscopy images demonstrate excellent preservation of ultrastructure across the whole imaged tissue block.

    (a) Section #1 (0 µm, surface of the block). (b) Section #200 (10 µm deep). (c) Section #400 (20 µm deep). (d) Section #600 (30 µm deep). (e) Section #800 (40 µm deep). This experiment was performed twice independently, with the same results obtained each time

  5. Supplementary Figure 5 High-resolution electron micrograph of a sample stained by NATIVE.

    This experiment was performed twice independently, with the same results obtained each time

  6. Supplementary Figure 6 High-resolution electron micrograph of a sample stained by a traditional protocol including 0.1% (v/v) Triton.

    This experiment was performed twice independently, with the same results obtained each time

  7. Supplementary Figure 7 Multi-angle view of the 3D-EM reconstructed ROI.

    This 3D-EM reconstruction contains an astrocyte, a microglial cell and a branch of capillary

  8. Supplementary Figure 8 Electron microscopy images showing possible synapse elimination in the adjacent region of Fig. 3d.

    This experiment was performed twice independently, with the same results obtained each time

  9. Supplementary Figure 9 High-resolution electron microscopy confirms the presence of GFAP bundles as an EM marker for astrocytes.

    Bundles are highlighted by arrowheads. This experiment was performed twice independently, with the same results obtained each time

  10. Supplementary Figure 10 LM reconstruction of GFAP (red) wrapping around a nucleus (blue).

    The detailed structure was further confirmed by 3D-EM reconstruction, as shown in the corresponding videos

  11. Supplementary Figure 11 3D-EM reconstruction of GFAP around a nucleus.

    In the figure, GFAP is shown as a belt-like structure, and the nucleus is shown in blue

Supplementary information

  1. Supplementary Text and Figures

    Supplementary Figures 1–11

  2. Reporting Summary

  3. Supplementary Protocol

    NATIVE Protocol

  4. Supplementary Video 1

    Raw fluorescent Z-stack images. The video shows nanobody-labeled GFAP (astrocyte marker) in red, CD11b (microglia marker) in yellow, Ly-6C/6G (endothelial cell marker for capillaries) in green, and cell nuclei labeled by Hoechst in blue

  5. Supplementary Video 2

    3D view of part of the LM image data. The video shows nanobody-labeled GFAP (astrocyte marker) in red, CD11b (microglia marker) in yellow, Ly-6C/6G (endothelial cell marker for capillaries) in green, and cell nuclei labeled by Hoechst 33342 in white. A prominent microglia with its branches can be seen in the center of the video

  6. Supplementary Video 3

    LM image data overlaid on top of the low-resolution EM data after affine LM-EM alignment. The video demonstrates the alignment precision reached by a single linear (3D affine) transformation across an example section of the dataset and how to use LM to assist cell-type identification in EM data

  7. Supplementary Video 4

    Multi-angle view of the 3D-EM reconstructed ROI. The 3D-EM reconstruction contains an astrocyte, a microglial cell and a branch of capillary

  8. Supplementary Video 5

    LM reconstruction of GFAP wrapping around a nucleus. The video shows a 3D-LM reconstruction of GFAP (red) wrapping around a nucleus in an astrocyte, which was further confirmed by 3D-EM reconstruction

  9. Supplementary Video 6

    EM reconstruction of GFAP wrapping around a nucleus. The video shows a 3D-EM reconstruction of GFAP (shown as belt-like structure) around a nucleus (blue)

  10. Supplementary Software 1

    “scanvastcolorfile.m”: helper script to import metadata from VAST into Matlab

  11. Supplementary Software 2

    “project_lm_to_em_dapi.m”: Matlab script to compute a 3D affine transformation based on a set of corresponding-point pairs and to transform a 3D LM image volume to a 3D target EM image volume based on the computes transform

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DOI

https://doi.org/10.1038/s41592-018-0177-x