Protocol | Published:

Dual-view plane illumination microscopy for rapid and spatially isotropic imaging

Nature Protocols volume 9, pages 25552573 (2014) | Download Citation

Abstract

We describe the construction and use of a compact dual-view inverted selective plane illumination microscope (diSPIM) for time-lapse volumetric (4D) imaging of living samples at subcellular resolution. Our protocol enables a biologist with some prior microscopy experience to assemble a diSPIM from commercially available parts, to align optics and test system performance, to prepare samples, and to control hardware and data processing with our software. Unlike existing light sheet microscopy protocols, our method does not require the sample to be embedded in agarose; instead, samples are prepared conventionally on glass coverslips. Tissue culture cells and Caenorhabditis elegans embryos are used as examples in this protocol; successful implementation of the protocol results in isotropic resolution and acquisition speeds up to several volumes per s on these samples. Assembling and verifying diSPIM performance takes 6 d, sample preparation and data acquisition take up to 5 d and postprocessing takes 3–8 h, depending on the size of the data.

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References

  1. 1.

    , & Orthogonal-plane fluorescence optical sectioning: three-dimensional imaging of macroscopic biological specimens. J. Microsc. 170, 229–236 (1993).

  2. 2.

    , , & Thin laser light sheet microscope for microbial oceanography. Opt. Express 10, 145–154 (2002).

  3. 3.

    , , , & Optical sectioning deep inside live embryos by selective plane illumination microscopy. Science 305, 1007–1009 (2004).

  4. 4.

    , & Fast three-dimensional fluorescence imaging of activity in neural populations by objective-coupled planar illumination microscopy. Neuron 57, 661–672 (2008).

  5. 5.

    et al. Inverted selective plane illumination microscopy (iSPIM) enables coupled cell identity lineaging and neurodevelopmental imaging in Caenorhabditis elegans. Proc. Natl. Acad. Sci. USA 108, 17708–17713 (2011).

  6. 6.

    , , & Reconstruction of zebrafish early embryonic development by scanned light sheet microscopy. Science 322, 1065–1069 (2008).

  7. 7.

    , , & Quantitative high-speed imaging of entire developing embryos with simultaneous multiview light-sheet microscopy. Nat. Methods 9, 755–763 (2012).

  8. 8.

    , , , & Multiview light-sheet microscope for rapid in toto imaging. Nat. Methods 9, 730–733 (2012).

  9. 9.

    et al. Rapid three-dimensional isotropic imaging of living cells using Bessel beam plane illumination. Nat. Methods 8, 417–423 (2011).

  10. 10.

    et al. Noninvasive imaging beyond the diffraction limit of 3D dynamics in thickly fluorescent specimens. Cell 151, 1370–1385 (2012).

  11. 11.

    et al. Spatially isotropic four-dimensional imaging with dual-view plane illumination microscopy. Nat. Biotechnol. 31, 1032–1038 (2013).

  12. 12.

    , , , & Multi-view image fusion improves resolution in three-dimensional microscopy. Opt. Express 15, 8029–8042 (2007).

  13. 13.

    et al. Multiview deblurring for 3D images from light-sheet-based fluorescence microscopy. IEEE Trans Image Process. 21, 1863–1873 (2012).

  14. 14.

    et al. OpenSPIM: an open-access light-sheet microscopy platform. Nat. Methods 10, 598–599 (2013).

  15. 15.

    et al. OpenSpinMicroscopy: an open-source integrated microscopy platform. Nat. Methods 10, 599–600 (2013).

  16. 16.

    , , & Quantitative fluorescence imaging of protein diffusion and interaction in living cells. Nat. Biotechnol. 29, 835–839 (2011).

  17. 17.

    , , & 3D live fluorescence imaging of cellular dynamics using Bessel beam plane illumination microscopy. Nat. Protoc. 9, 1083–1101 (2014).

  18. 18.

    & Even fluorescence excitation by multidirectional selective plane illumination microscopy (mSPIM). Opt. Lett. 32, 2608–2610 (2007).

  19. 19.

    , , , & Confocal light sheet microscopy: micron-scale neuroanatomy of the entire mouse brain. Opt. Express 20, 20582–20598 (2012).

  20. 20.

    et al. Medical image processing, analysis, and visualization in clinical research. Proceedings of the 14th IEEE Symposium on Comput.er-Based Medical Systems (CBMS '01) 381 (2001).

  21. 21.

    Maintenance of C. elegans. in WormBook (ed. The C. elegans Research Community) 10.1895/wormbook.1.101.1 (11 February 2006).

  22. 22.

    et al. Instant super-resolution imaging in live cells and embryos via analog image processing. Nat. Methods 10, 1122–1126 (2013).

  23. 23.

    . & in Imaging in Developmental Biology: A Laboratory Manual Vol. 56 (eds. Sharpe, J. & Wong, R.) (Cold Spring Harbor Laboratory, 2010).

  24. 24.

    et al. Dual-color superresolution imaging of genetically expressed probes within individual adhesion complexes. Proc. Natl. Acad. Sci. USA 104, 20308–20313 (2007).

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Acknowledgements

We thank V. Kopuri and J. Daniels for their help with instrumentation; M. Anthony for the Solidworks drawings; A. Santella for troubleshooting registration issues with the MIPAV plug-in; and B. Mohler, A. York, H. Eden and J.-Bernard Fiche for their critical feedback on the diSPIM system. We also thank the Research Center for Minority Institutions program and the Institute of Neurobiology at the University of Puerto Rico for providing a meeting and brainstorming platform. This work was partially conducted at the Marine Biological Laboratories at Woods Hole, under a Whitman research award (to D.A.C.-R., Z.B. and H.S.). This work was supported by the Intramural Research Programs of the NIH National Institute of Biomedical Imaging and Bioengineering, the Center for Information Technology and by NIH grants U01 HD075602 and OD016474. The NIH does not endorse or recommend any commercial products, processes or services. The views and opinions of authors expressed here do not necessarily state or reflect those of the U.S. Government, and they may not be used for advertising and product endorsement purposes. Links to internet sites are only for the convenience of readers. The NIH is not responsible for the availability or the content of these external sites, nor does NIH endorse, warrant or guarantee the products, services or information described or offered at these internet sites.

Author information

Affiliations

  1. Section on High Resolution Optical Imaging, National Institute of Biomedical Imaging and Bioengineering, US National Institutes of Health (NIH), Bethesda, Maryland, USA.

    • Abhishek Kumar
    • , Yicong Wu
    • , Ryan Christensen
    • , Panagiotis Chandris
    •  & Hari Shroff
  2. Program in Cellular Neuroscience, Neurodegeneration and Repair, Department of Cell Biology, Yale University School of Medicine, New Haven, Connecticut, USA.

    • Abhishek Kumar
    •  & Daniel A Colón-Ramos
  3. Biomedical Imaging Research Services Section, Center for Information Technology, NIH, Bethesda, Maryland, USA.

    • William Gandler
    • , Evan McCreedy
    • , Alexandra Bokinsky
    •  & Matthew McAuliffe
  4. Developmental Biology Program, Sloan-Kettering Institute, New York, New York, USA.

    • Zhirong Bao
  5. Applied Scientific Instrumentation, Eugene, Oregon, USA.

    • Gary Rondeau

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Contributions

A.K., G.R., Y.W. and H.S. designed and built the optical system; A.K., G.R. and Y.W. designed the control electronics; Y.W., W.G., E.M., A.B. and M.M. designed the registration, fusion and deconvolution of the GPU-based software; A.K., Y.W., G.R., R.C., P.C. and H.S. tested the system; A.K., R.C. and P.C. performed the experiments; Z.B., D.A.C.-R. and H.S. supervised the research; and A.K., G.R., Y.W., R.C., P.C. and H.S. wrote the paper.

Competing interests

G.R. declares a competing financial interest as an employee of ASI.

Corresponding authors

Correspondence to Abhishek Kumar or Hari Shroff.

Integrated supplementary information

Supplementary information

PDF files

  1. 1.

    Supplementary Text and Figures

    Supplementary Notes 1–3 and Supplementary Tables 1–4

  2. 2.

    Supplementary Figure 1

    Diagnostics for assessing excitation input to diSPIM.

  3. 3.

    Supplementary Figure 2

    Offset and aligned SPIM beams as viewed in the bottom camera.

  4. 4.

    Supplementary Figure 3

    'Pencil' and epi beams as viewed in SPIM camera.

  5. 5.

    Supplementary Figure 4

    Fine adjustment of light sheets, as viewed in the bottom camera.

  6. 6.

    Supplementary Figure 5

    Epifluorescence, SPIM, and overlapped beams as viewed in arm A camera.

  7. 7.

    Supplementary Figure 6

    Misalignment in diSPIM components diagnosed through arm A camera.

  8. 8.

    Supplementary Figure 7

    Synchronizing the light sheet and collection objective when performing volumetric imaging.

  9. 9.

    Supplementary Figure 8

    Example showing the effect of varying the Z-Galvo conversion factor.

  10. 10.

    Supplementary Figure 9

    Examples showing partial and full coverage of an embryo in plane and volume.

  11. 11.

    Supplementary Figure 10

    Maximum intensity projections of nuclei in C. elegans embryos, corresponding to arm A and arm B views.

Videos

  1. 1.

    Volumetric time series of C. elegans embryo (strain BV24) expressing GFP-histones.

    C. elegans strain BV24 (ltIs44 [pie-1p-mCherry::PH(PLC1delta1) + unc-119(+)]; zuIs178 [(his-72 1kb::HIS-72::GFP); unc-119(+)] V embryo expressing a GFP-histone fusion protein was imaged for 14 hours, demonstrating long-term imaging capabilities of the diSPIM system. Individual frames of the movie were normalized using the 'enhance contrast' command in ImageJ to maintain a similar brightness level throughout the movie. Volumes were sampled every minute, using 45 planes/volume/view and 1 μm inter-plane spacing. Data were derived from arm A and arm B; the presented data has been deconvolved after registration. See also Fig. 3.

  2. 2.

    Volumetric time series of human lung fibroblast cell expressing GFP tagged H-Ras.

    DiSPIM image sequence of a cultured human lung fibroblast cell, expressing GFP-tagged H-Ras, and demonstrating dynamic cellular movements. The image stack was converted to 8-bit format in ImageJ, and the 'Hot Red' LUT was applied to it. Volumes were sampled every 5 seconds, at 120 planes/volume/view and 0.5 μm inter-plane spacing. Data were derived from arm A and arm B; the presented data has been deconvolved after registration. See also Fig. 4.

  3. 3.

    Examples of a partially and a fully captured embryo in volumetric imaging.

    Examples of a volume where the C. elegans embryo is not completely captured by the z-stack (left images) and where the embryo is completely captured (right images). The volume was sampled at 44 planes/volume and 1 μm inter-plane spacing. The presented data were derived from arm A. See also Supplementary Fig. 9.

  4. 4.

    Volumetric images of an embryo collected from arms A and B.

    Data derived from arm A (left) and arm B (right) of a C. elegans embryo. The volume was sampled at 40 planes/volume and 1 μm inter-plane spacing. See also Supplementary Fig. 10.

Zip files

  1. 1.

    Supplementary Data 1

    Processed (16 bit) C. elegans embryo data using joint deconvolution showing an example of a successful and failed registration. Images of an embryo after registering the images from arm A and B and processing them using joint deconvolution (10 iterations were used in this dataset), showing the effects of successful (left) and failed (right) registration. In the failed registration case, some cells appear displaced or artificially divided (see also Supplementary Note 1 SF1).

  2. 2.

    Supplementary Data 2

    Bead (16 bit) data when the light sheet is synchronized with, lagging, or leading the collection objective: A fluorescent bead layer was imaged in arm A. The volume was sampled at 45 planes/volume and 1 μm inter-plane spacing. synch.tif, demonstrates optimal synchronization between light sheet and the collection objective. For examples that illustrate the effects of light sheet lagging or leading the objective, see lagging.tif, or leading.tif. See also Supplementary Figure 7.

  3. 3.

    Supplementary Data 3

    Bead (16 bit) data acquired by keeping the light sheet stationary and scanning the collection objective. In this example, the light sheet was kept fixed and the collection objective was scanned through the bead layer. The volume was sampled at 99 planes/volume and 0.5 μm inter-plane spacing. This figure shows how best to pick the objective piezo offset. See also step 79.

  4. 4.

    Supplementary Data 4

    Bead (16 bit) data showing the effect of a non-optimal Z-galvo conversion factor. Fluorescent bead data showing the effect of a poor choice of Z-galvo conversion factor, lower by 0.002 V from the optimal value (compare to Supplementary Data 2 (synch.tif)). The lightsheet is ahead of the collection objective initially and lags behind towards the end of the acquisition. The resulting maximum intensity projection shows focused beads only in the middle of the stack, and blurry beads on both ends (see Supplementary Fig. 8.). The volume was sampled at 45 planes/volume and 1 μm inter-plane spacing.

  5. 5.

    Supplementary Data 5

    Bead dataset showing the resolution expected in unregistered/undeconvolved images from individual SPIM arms, and in a registered, deconvolved volume. Images include: (SPIMA.tif) Bead (16 bit) data acquired by SPIMA: Raw data of a fluorescent bead layer, collected in arm A. The volume was sampled at 70 planes/volume and 0.5 μm inter-plane spacing. Also see Fig. 3. (SPIMB.tif) Bead (16 bit) data acquired by SPIMB: Raw data of a fluorescent bead layer, collected in arm B. The volume was sampled at 70 planes/volume and 0.5 μm inter-plane spacing. Also see Fig. 2. The sample is identical to that in Supplementary Data 5 (SPIMA.tif). (deconv.tif) Processed (16 bit) bead data using joint deconvolution: The bead data in Supplementary Data 5 (SPIMA.tif and SPIMB.tif), after registering the datasets and processing them using joint deconvolution (15 iterations were used in this dataset). Also see Fig. 2.

  6. 6.

    Supplementary Data 6

    Bead data (16 bit) acquired by scanning the light sheet and keeping the collection objective fixed at a single plane. An example of data used for measuring the light sheet thickness. The volume was sampled at 99 planes/volume and 0.5 μm inter-plane spacing. See also Fig. 2 and step 95.

  7. 7.

    Supplementary Data 7

    C. elegans embryo dataset, showing the resolution expected in unregistered/undeconvolved images from individual SPIM arms, and in a registered, deconvolved volume. Images include: (SPIMA.tif) Raw (16 bit) data of a C. elegans embryo from arm A: The volume was sampled at 40 planes/volume and 1 μm inter-plane spacing. (SPIMB.tif) Raw (16 bit) data of a C. elegans embryo from arm B: The volume was sampled at 40 planes/volume and 1 μm inter-plane spacing. (deconv.tif) Processed (16 bit) C. elegans embryo data using joint deconvolution: Images of embryo in Supplementary Data 7 (SPIMA.tif and SPIMB.tif) after registering the images and processing them using joint deconvolution (10 iterations were used in this dataset).

  8. 8.

    Supplementary Data 8

    Fibroblast dataset, showing the resolution expected in unregistered/undeconvolved images from individual SPIM arms, and in a registered, deconvolved volume. Images include: (SPIMA.tif) Raw (16 bit) data of a cell from arm A: An image sequence of a cultured human lung fibroblast cell acquired in arm A, expressing GFP-tagged H-Ras. The volume was sampled at 120 planes/volume/view and 0.5 μm inter-plane spacing. (SPIMB.tif) Raw (16 bit) data of a cell from arm B: An acquired image sequence of a cultured human lung fibroblast cell from arm B, expressing GFP-tagged H-Ras. The volume was sampled at 120 planes/volume/view and 0.5 μm inter-plane spacing. (deconv.tif) Processed (16 bit) data of cell using joint deconvolution: Images of a cultured human lung fibroblast cell (SPIMA.tif and SPIMB.tif) after registering the images and processing them using joint deconvolution (10 iterations were used in this dataset).

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https://doi.org/10.1038/nprot.2014.172

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