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Resolution doubling in light-sheet microscopy via oblique plane structured illumination

Nature Methods volume 19, pages 1419–1426 (2022)Cite this article

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Abstract

Structured illumination microscopy (SIM) doubles the spatial resolution of a fluorescence microscope without requiring high laser powers or specialized fluorophores. However, the excitation of out-of-focus fluorescence can accelerate photobleaching and phototoxicity. In contrast, light-sheet fluorescence microscopy (LSFM) largely avoids exciting out-of-focus fluorescence, thereby enabling volumetric imaging with low photobleaching and intrinsic optical sectioning. Combining SIM with LSFM would enable gentle three-dimensional (3D) imaging at doubled resolution. However, multiple orientations of the illumination pattern, which are needed for isotropic resolution doubling in SIM, are challenging to implement in a light-sheet format. Here we show that multidirectional structured illumination can be implemented in oblique plane microscopy, an LSFM technique that uses a single objective for excitation and detection, in a straightforward manner. We demonstrate isotropic lateral resolution below 150 nm, combined with lower phototoxicity compared to traditional SIM systems and volumetric acquisition speed exceeding 1 Hz.

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Fig. 1: Combination of structured illumination and light-sheet microscopy.
Fig. 2: Resolution and performance of OPSIM.
Fig. 3: Imaging of cellular samples with OPSIM.
Fig. 4: Dynamic volumetric imaging with OPSIM.

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Data availability

All data presented herein are provided under: https://zenodo.org/record/6916684

Code availability

The MATLAB scripts used in this paper are available under: https://github.com/AdvancedImagingUTSW/manuscripts/tree/main/2022-chen. The Python 2D SIM reconstruction package is available at: https://github.com/QI2lab/mcSIM and a OPSIM reconstruction example Jupyter notebook at: https://github.com/QI2lab/I2K2022-SIM. The version of the codes used here are archived on Zenodo (mcSIM reconstruction package: https://doi.org/10.5281/zenodo.6419901; OPSIM reconstruction example: https://zenodo.org/record/6916684).

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Acknowledgements

We thank the National Institutes of Health (grant nos. 1R01DK127589, 1R21HD105189, 5P30CA142543, 1RM1GM145399 and U54CA268072 to K.M.D.; MIRA R35GM125028 to D.T.B.; R35GM133522 to R.P.F.; R35GM137894 to J.R.F.; and 5R01NS117065 to C.-L.Z.). American Heart Association Graduate Student Fellowship to J.B.H. (grant no. AHA 836090). P.R. received funding from the Investissements d’Avenir French Government program managed by the French National Research Agency (grant no. ANR-16-CONV-0001) and from Excellence Initiative of Aix-Marseille University: A*MIDEX.’ The SIM code development was supported by Scialog, the Research Corporation for Science Advancement, the Frederick Gardner Cottrell Foundation (grant no. 28041) and Chan Zuckerberg Initiative (grant no. 2021-236170(5022)) to D.P.S.

Author information

Author notes

  1. Etai Sapoznik

    Present address: Genentech, San Francisco, USA

  2. These authors have contributed equally: Bingying Chen, Bo-Jui Chang.

Authors and Affiliations

  1. Lyda Hill Department of Bioinformatics, University of Texas Southwestern Medical Center, Dallas, TX, USA

    Bingying Chen, Bo-Jui Chang, Felix Zhou, Etai Sapoznik, Kevin M. Dean & Reto P. Fiolka

  2. Cecil H. and Ida Green Center for Systems Biology, University of Texas Southwestern Medical Center, Dallas, TX, USA

    Bingying Chen, Bo-Jui Chang, Felix Zhou, Kevin M. Dean & Reto P. Fiolka

  3. Department of Cell Biology, University of Texas Southwestern Medical Center, Dallas, TX, USA

    Bingying Chen, Bo-Jui Chang, Felix Zhou, Madeleine Marlar-Pavey, Jonathan R. Friedman, Kevin M. Dean & Reto P. Fiolka

  4. Aix-Marseille University, CNRS, Centrale Marseille, I2M, Turing Centre for Living Systems, Marseille, France

    Philippe Roudot

  5. Department of Cell and Developmental Biology, Vanderbilt Medical Center, University of Vanderbilt, Nashville, TN, USA

    James B. Hayes & Dylan T. Burnette

  6. Center for Biological Physics and Department of Physics, Arizona State University, Tempe, AZ, USA

    Peter T. Brown & Douglas P. Shepherd

  7. Department of Molecular Biology, University of Texas Southwestern Medical Center, Dallas, TX, USA

    Chih-Wei Zeng & Chun-Li Zhang

  8. Department of Cell Biology, Harvard Medical School, Boston, MA, USA

    Talley Lambert

  9. Department of Systems Biology, Harvard Medical School, Boston, MA, USA

    Talley Lambert

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Contributions

R.P.F. conceived the idea of OPSIM and the image rotator. B.C. mathematically described the image rotator. B.J.C. performed numerical simulations and practical experiments. B.C., B.J.C. and R.P.F. designed an experimentally tractable image rotator. B.C. built the image rotator. R.P.F. built the microscope. R.P.F. T.L. and B.J.C. acquired experimental data. R.P.F., P.T.B., B.J.C. and B.C. performed data processing. P.R. and F.Z. wrote the fine registration algorithm. R.P.F., B.J.C., P.T.B. and D.P.S. wrote the SIM reconstruction software. M.M.-P., J.B.H., J.R.F., E.S., K.M.D., D.T.B., C.-W.Z. and C.-L.Z. provided biological samples. E.S. and J.B.H. performed imaging with the SoRA and iSIM system, respectively.

Corresponding author

Correspondence to Reto P. Fiolka.

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Competing interests

R.P.F., B.C. and B.J.C. have filed a patent application (United States Patent and Trademark Office application number 63/253,047) for the image rotator and applications to microscopy. All other authors declare no competing interests.

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Nature Methods thanks Ingo Gregor, Thomas Huser and Lin Shao for their contribution to the peer review of this work. Primary Handling Editor: Rita Strack, in collaboration with the Nature Methods team. Peer reviewer reports are available.

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Extended data

Extended Data Fig. 1 Conceptual setup for structured illumination with three illumination directions.

a Rendering of a potential setup for multi-directional LSFM-SIM, consisting of three illumination objectives, angled at 120 degrees to each other, and one detection objective. b Bottom view of the objective assembly.

Extended Data Fig. 2 Schematic illustration of the oblique plane structured illumination sheet.

a: Electric field (blue stripe) in the pupil of the primary objective in an OPM system. The offset in the negative kx direction of the electric field (that is the blue stripe is not centered in the pupil) causes the light-sheet to be tilted in sample space. Middle: x-z view of the oblique light-sheet intensity distribution as it emerges from the objective. Right: y-z view of the light-sheet intensity distribution. b The electric field in the pupil has been shifted to the left (in the minus ky direction). As a result, in the y-z view, the light-sheet is angled and propagates diagonally (in a positive y direction). c The electric field in the pupil has been shifted to the right (positive ky direction). As a result, in the y-z view, the light-sheet is angled and propagates diagonally (in a negative y direction). d Coherent superposition of the electric fields in B-C results in a 1D interference pattern along the y direction as seen in the y-z view. Importantly, even though the individual light-sheets are angled (as viewed in an y-z plane), the beam waist of each sheet remains parallel to the focal plane of the primary objective. The dotted lines in A-D indicate the limits of the beam waist. In other words, the beam waists are not rotated in an y-z view, but rather form a parallelogram. Please see also Extended Data Fig. 4a-d on how the two light-sheets are aligned in the OPSIM setup.

Extended Data Fig. 3 CAD model of the Image rotator.

Rendering of the image rotator unit (left) and a top, side and frontal view (right). The main components are two galvo mirrors and three static mirrors. Two folding mirrors bring the in and output beam (blue arrows) on a common optical axis.

Extended Data Fig. 4 Setup for Oblique Plane Structured Illumination Microscopy.

a Schematic drawing of the setup. The illumination unit creates to interfering light-sheets (blue), which can be phase stepped by a piezo actuator. They are coupled into the OPSIM microscope with a dichroic mirror. The image rotator module rotates the light-sheets by three discrete steps. The returning fluorescence light (green) is de-rotated by the image rotator to align with the alignment of the tertiary objective. b Rendering of the image rotator module. Two galvanometric mirrors are used to select three beam paths, each of which imparts a different amount of image rotation. c, d Optical path for light-sheet illumination, showing only one tip-tilt mirror of the Michelson interferometer. For clarity, the beam splitter, motorized mirror, dichroic mirror and galvo mirror, as well as the corresponding reflections, have been left out. C Tilting the mirror around the y-axis changes the tilt angle of the light-sheet in the x-z plane and translates the laser beam in the pupil plane along the kx axis. D Titling the mirror around the x-axis tilts the light-sheet in the y-z plane and translates the laser beam in the pupil plane along the ky axis. With these degrees of freedom, both light-sheets can be aligned as shown in Extended Data Fig. 2.

Extended Data Fig. 5 Workflow for data preprocessing, part 1.

Prior to SIM processing, the data is pre-processed: Each raw stack is de-skewed and rotated into the coverslip (x-y-z) reference frame as it is schematically shown in A-D and on biological data from E-F. a To scan a volume, the light-sheet and detection focal plane (blue line) are scanned along the coverslip. x-z is the coordinate system of the primary objective, with z along its optical axis. x’-z’ is the coordinate frame of the light-sheet and the tilted detection focal plane. b The images from a scan are assembled into a stack. As the scan direction is not along the z’ axis, the resulting stack is skewed (that is each plane has a desired displacement in z’, but also an unwanted one in x’). c De-skewing results in a proper x’-z’ stack. d The data is rotated into a x-z reference frame. Empty data, introduced by the de-skewing, above the cell and below the coverslip is discarded. e, f: maximum intensity projections of an U2OS cell labeled for MIC60 at different stages of the pre-processing.

Extended Data Fig. 6 Workflow for data preprocessing, part 2.

a-f After de-skewing and rotating the data into an x-y-z coordinate frame of the primary objective/coverslip, the data volumes for the first (A, Direction 0) and the third (C, Direction 2) are rotated by plus and minus 60 degrees around the z- axis to share the same orientation as the second direction (B, Direction 1). g The rotated data sets for Direction 0 and Direction 1 are then registered to Direction 1, which have been color coded here for clarity. Inset shows a magnified version of the red boxed region.

Extended Data Fig. 7 Cardiomyocyte labeled with Phalloidin and Actinin.

a Phalloidin labeled channel of the cell shown in Fig. 3c as imaged by OPSIM. b Alpha-Actinin 2, labeled with Alexa 561, as imaged by OPSIM. Scale bar: 10 microns.

Extended Data Fig. 8 Spinal cord slice imaged with a Confocal microscope.

Single plane of neurofilament (NF200, green) and myelin (PLP, magenta) in a 20 micron thick spinal cord slice, as imaged with a Confocal microscope.

Extended Data Fig. 9 Spinal cord slices imaged with a Nikon SoRa spinning disk.

Single plane of neurofilament (NF200, green) and myelin (PLP, magenta) in a 20 micron thick spinal cord slice, as imaged with a SoRa spinning disk.

Extended Data Fig. 10 Excitation intensity in the primary pupil in Oblique Plane Structured Illumination Microscopy.

Schematic drawing of the pupil of the primary objective (numerical aperture: 1.35) in OPSIM, and the location of the two thin stripes (blue) that create the structured, oblique light-sheet. For a tilt angle of 45 degrees, a light-sheet NA of ~0.12, an NA for structured illumination of 0.82 results. Experimentally, the highest excitation NA we have achieved was 0.79, before running into beam clipping or vignetting effects. For conventional SIM, the highest NA that can be used for pattern generation equals to the NA of the primary objective, which illustrates the tradeoff that needs to be done for the tilted structured light-sheet.

Supplementary information

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Supplementary Note 1, Figs. 1–6 and Tables 1 and 2.

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Supplementary Video 1

Supplementary Video 1 Clathrin-coated vesicle dynamics. An ARPE-19 cell, labeled for AP2-eGFP, imaged by OPSIM over 40 timepoints at a volumetric acquisition rate of 0.86 Hz (1.16 s acquisition time for a full OPSIM data set for one timepoint). The left side shows a maximum intensity projection of the whole field of view, and magnified versions of the boxed regions are shown on the right.

Supplementary Video 2

Supplementary Video 2 Mitochondria dynamics. An U2OS cell, labeled for GFP-OMP25, imaged by OPSIM over 38 timepoints at a volumetric acquisition rate of 1.2 Hz (0.82 s acquisition time for a full OPSIM data set for one timepoint). Left shows a maximum intensity projection of the whole field of view, color coded for height. On the right, magnified versions of the boxed regions on the left are shown. White arrows point at protruding and retracting mitochondria.

Supplementary Video 3

Supplementary Video 3 Clathrin-coated vesicle dynamics. An ARPE-19 cell, labeled for eGFP AP2, imaged by OPSIM over 38 timepoints at a volumetric acquisition rate of 1.4 Hz (0.7 s acquisition time for a full OPSIM data set for one timepoint). The video is displayed as a maximum intensity projection.

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Chen, B., Chang, BJ., Roudot, P. et al. Resolution doubling in light-sheet microscopy via oblique plane structured illumination. Nat Methods 19, 1419–1426 (2022). https://doi.org/10.1038/s41592-022-01635-8

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