A guide to light-sheet fluorescence microscopy for multiscale imaging

Journal name:
Nature Methods
Year published:
Published online


The impact of light-sheet fluorescence microscopy (LSFM) is visible in fields as diverse as developmental and cell biology, anatomical science, biophysics and neuroscience. Although adoption among biologists has been steady, LSFM has not displaced more traditional imaging methods despite its often-superior performance. One reason for this is that the field has largely conformed to a do-it-yourself ethic, although the challenges of big image data cannot be overstated. With the most powerful implementations of LSFM available to only a few groups worldwide, the scope of this technique is unnecessarily limited. Here we elucidate the key developments and define a simple set of underlying principles governing LSFM. In doing so, we aim to clarify the decisions to be made for those who wish to develop and use bespoke light-sheet systems and to assist in identifying the best approaches to apply this powerful technique to myriad biological questions.

At a glance


  1. Light-sheet fluorescence microscopy.
    Figure 1: Light-sheet fluorescence microscopy.

    (a) The archetypal light-sheet microscope: paired, orthogonal optical paths provide plane-wise illumination (blue) and wide-field fluorescence detection (green). (b) Optical sectioning by selective illumination of a single plane.

  2. Parallelization of light-sheet generation.
    Figure 2: Parallelization of light-sheet generation.

    (a) SPIM illuminates and captures fluorescence from the entire FOV simultaneously, whereas mSPIM reduces striped artifacts by pivoting the light sheet about its center. DSLM produces a virtual light sheet by time-sharing the beam, with fluorescence arising only from the illuminated strip at any given time. (b) To maintain identical SNRs, DSLM requires higher peak intensities (Ipeak) as the FOV size increases (along the scanning axis) relative to the light-sheet thickness, ωls.

  3. Spatial resolution in light-sheet fluorescence microscopy.
    Figure 3: Spatial resolution in light-sheet fluorescence microscopy.

    (a) Interplay between light-sheet thickness (ωls) and length (zls). (b) Overlap of illumination (blue) and detection (green) PSFs yields the system PSF. (c) Influence of the detection NA on the system PSF, displayed as a summed projection orthogonal to the illumination and detection axes. The color scale defines the normalized intensity of the system PSF.

  4. Reflected light-sheet geometries.
    Figure 4: Reflected light-sheet geometries.

    (a) RLSM—the light sheet is launched from an opposing objective. (b) soSPIM—the light sheet is launched from the detection objective.

  5. Gaussian and Bessel beams for light-sheet generation.
    Figure 5: Gaussian and Bessel beams for light-sheet generation.

    (a,b) Gaussian (a) and Bessel (b) beams produce a light sheet with equivalent length (~6 μm; λill = 488 nm; refractive index, nimm = 1.33) despite the disparity in NA. Only a single NA is necessary to define the Gaussian beam, whereas the Bessel beam features two corresponding values that define the inner and outer NA of the annular spectrum of the beam. Although the Bessel beam features a much smaller central beam lobe only, ~11% of the total Bessel beam irradiance is contained therein, and only ~30% is contained within the Gaussian beam waist105. The color scale shows the normalized intensity of each of the beams. Scale bars, 1 μm.

  6. Axially swept light-sheet geometries.
    Figure 6: Axially swept light-sheet geometries.

    (a,b) 2D virtual light-sheet production (axially swept or laterally scanned) using ultrasonic (tunable acoustic gradient; TAG) lenses by one-photon excitation with confocal line detection (CLD) to remove undesired signal (a) or two-photon excitation to suppress undesired signal (b). (c) 1D virtual light-sheet production (axially swept) with CLD to remove undesired signal or with sequential acquisition of images at different beam waist positions and subsequent image stitching.

  7. Light-sheet penetration.
    Figure 7: Light-sheet penetration.

    Spreading of the beam illustrates the degree of scattering in tissue, and the color opacity illustrates the potential signal evolved. (a) The hypothetical unscattered beam is shown for comparison. (b) With one-photon excitation, scattering in tissue is severe; however, the signal per unit volume decays linearly as the beam spreads. (c) With two-photon excitation, scattering is reduced; however, the signal decays quadratically as the beam spreads.

  8. Multiview imaging.
    Figure 8: Multiview imaging.

    (a) Improved axial resolution can be achieved by reconstructing images taken from different angles either achieved by sample rotation (two, three or four lenses) or by using all of the lenses for illumination and detection (4*). (b) Optical coverage arises from the overlap of efficiently illuminated and detected quadrants. The (minimum) number of imaging angles to provide full optical coverage and improved axial resolution is given for each case.

  9. Ultrafast volumetric imaging.
    Figure 9: Ultrafast volumetric imaging.

    (a) Generic scheme for ultrafast light sheet-based volumetric imaging. The light sheet is scanned through an extended DOF. In the case of ETL-SPIM, an extended DOF is produced temporally by a defocusing electrically tunable lens. (b) Wavefront coding uses a cubic phase mask to produce a static, artificially extended DOF. (c) SPED exploits spherical aberration, which results from focusing through a stratified refractive medium to statically extend the DOF (n1 and n2 indicate the refractive index in the first or second immersion medium, respectively). (d) OPM–SCAPE uses a tilted illumination and detection scheme alongside image rotation optics for single-objective ultrafast volume imaging.

  10. Hyperspectral light-sheet microscopy.
    Figure 10: Hyperspectral light-sheet microscopy.

    A single line in a multiply labeled sample is illuminated, and the resulting fluorescence is dispersed across the camera chip, encoding spatial (x) and spectral (λ) information. The spectrum at each spatial location (x) is subsequently unmixed to give the contribution from each fluorophore.


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  1. Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany.

    • Rory M Power &
    • Jan Huisken
  2. Department of Medical Engineering, Morgridge Institute for Research, Madison, Wisconsin, USA.

    • Rory M Power &
    • Jan Huisken
  3. Department of Biomedical Engineering, University of Wisconsin, Madison, Wisconsin, USA.

    • Rory M Power &
    • Jan Huisken

Competing financial interests

J.H. is a co-inventor on patent US 20060033987 and an inventor on patent US 20110115895, which are related to light-sheet microscopy.

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