Open Access
Add to BibSonomy
Abstract
Lattice light-sheet microscopy (LLSM) is promising in long-term biological volumetric imaging due to its high spatiotemporal resolution and low phototoxicity. However, three-dimensional (3D) isotropic spatial resolution remains an unmet goal in LLSM because of its poorer axial resolution. Combing LLSM with fluorescence differential detection, namely LLSDM, has been proposed to improve the axial resolution of LLSM in simulation. It demonstrates the possibility of further enhancing the axial resolution in 3D volumetric imaging with LLSM by specifically discarding the off-focus photons captured using a complementary optical lattice (OL) profile generated with additional 0-π phase modulation at the objective pupil plane. The direct generation of the complementary lattice profile using the binary phase modulator conjugated to the sample plane for amplitude modulation, as used in LLSM, is also permittable. Nevertheless, the previously proposed configuration fails to provide a symmetric complementary lattice pattern along the axial axis, thus leading to the imbalanced off-focus photon suppression in the reconstructed images after subtraction [Opt. Lett. 45, 2854 (2020) [CrossRef] ]. Here, we modified the LLSDM theory which can produce an ideal complementary lattice pattern with central zero intensity and symmetrically distributed sidelobes. We also analyzed the impact of numerical aperture matching between the original and complementary lattice patterns and presented the consistency between the simulated and experimental results. As demonstrated by imaging the distribution of fluorescent beads and microtubules in fixed U2OS cells, as well as the dynamics of filopodia in live U2OS cells, LLSDM provides about 1.5 times improvement in axial resolution, and higher imaging contrast compared with traditional LLSM.
© 2022 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement
1. Introduction
Fluorescence microscopes have been widely used in the observation of the fine structure of biological samples owing to their non-invasive and sample-specific nature. The quest for higher resolution with low phototoxicity and photobleaching which enables the volumetric visualization of increasing amount of elaborate biological structures for long time further spurs the innovation in imaging techniques. Light sheet fluorescence microscopy (LSFM) is one of the most promising techniques to this end [1–6]. In LSFM, the excitation objective and detection objective are decoupled and aligned perpendicular to each other. The use of sideway illumination in LSFM provides the intrinsic capability of optical sectioning, thus helping to increase the axial resolution, enhance imaging contrast, and reduce the photobleaching and phototoxicity compared with traditional microscopies with epi-illumination [7,8].
In the early days, LSFM was developed to record the developmental process of entire embryos [9,10] and plants [11,12]. Due to its unique assets of long-term high-speed volumetric imaging, recently, LSFM has also been applied to observe the dynamic subcellular structures at the cellular level. For this aim, various efforts have been made to boost its spatial resolution [13–16]. However, in general, the axial resolution of LSFM is still worse than its lateral counterpart. The combination with structured illumination microscopy (SIM) [5] and single-molecule localization microscopy [17] in LSFM outperform in high axial resolution but at the cost of reduced imaging speed. One of the most direct methods to enhance the axial resolution of LSFM is to compress the light-sheet thickness. For example, stimulated emission depletion (STED) microscopy [7] has been introduced to reduce the thickness of the light-sheet illumination by depleting the off-focus photons, thus improving the axial resolution of LSFM [18]. Moreover, the Bessel beam was proposed to replace the Gaussian beam as the excitation beam in LSFM, benefitting from its narrower main-lobe thickness and larger imaging field of view (FOV) [4]. The off-focus background contamination caused by its concentric sidelobes can be alleviated by introducing the STED [19] principle and the confocal line detection [20] configuration, and can be further eliminated by the destructive interference when coherent Bessel beam arrays are generated with proper interval distance, as proposed in the lattice light sheet microscopy (LLSM) [5].
The thickness of the lattice light sheet is basically determined by the difference between the inner and outer numerical apertures (NAs) of the annular mask conjugated to the back focal plane (BFP) of the excitation objective. Although increasing the NA difference produces a thinner light sheet illumination profile, which provides higher axial resolution, the length that the light sheet spans is reduced, and thus it is hard to further compress the light sheet thickness while maintaining a relatively large FOV. Moreover, the axial resolution of LLSM is still diffraction limited.
Lattice light sheet difference microscopy (LLSDM) was proposed to further enhance the axial resolution of LLSM without compromise in FOV [21]. In LLSDM, a second complementary beam featuring zero intensity at the center of the light sheet is introduced to record the off-focus excited photons. By specifically discarding these additional photons with differential algorithm, the axial resolution as well as image contrast can be improved compared with LLSM. Despite similar use of the complementary beam as in STED-LSFM, fluorescence differential detection overcomes the limitation of STED microscopy, such as the requirements for specific fluorescent dyes, high laser power density, and complicated system configuration, and is easier to be applicable to any excitation wavelength [22,23]. Meanwhile, LLSDM performs imaging using the dithered mode, which achieves a faster imaging speed, compared with improving the axial resolution using the SIM mode (5 frames/reconstruction).
Generally, a complementary light sheet with a hollow profile is produced by placing a 0-π step phase mask conjugated to the BFP of the excitation objective, which needs extra modifications on the optical path in the original LLSM design to create the conjugated BFP plane for the step phase mask. According to Ref. [21], however, it is possible to implement LLSDM without changing the original optical configuration in LLSM. By modifying the binary phase map on the spatial light modulator (SLM) conjugated to the sample space in LLSM mimicking the cross section of the complementary light sheet, a virtually 0-π phase modulated complementary optical lattice (COL) can be generated. Compared with a wavelength-dependent step phase mask, SLM provides more convenience during multi-color imaging since the calculated lattice pattern loaded on it can be changed freely and quickly according to the used excitation wavelength. However, due to the discontinuous modulation characteristics of the selected SLM used in LLSM, only a COL light sheet profile with asymmetric sidelobe intensity distribution will be obtained [21], which leads to imbalanced off-focus photon suppression in the reconstructed images after subtraction and may affect the reliability of intensity distribution in the final reconstructed images.
In this paper, we modified and optimized the generation process of the COL pattern with the binary phase SLM used in LLSM to produce an ideal COL pattern with symmetric sidelobe intensity distribution. This newly designed COL can be directly used to perform LLSDM without hardware modification in LLSM. We evaluated this method systematically with both numerical simulation and experiments. The results show that LLSDM with a tailored COL beam can successfully enhance the axial resolution and imaging contrast in 3D volumetric imaging. Improvement in axial resolution about 1.8 times compared with LLSM has been achieved on various samples including fluorescent beads and fixed/live mammalian cells cultured on the coverslip.
2. Principle
2.1 Principle of lattice light sheet differential detection microscopy
A simplified optical configuration of the LLSM is shown in Fig. 1(A) (for detailed system hardware information, please refer to Ref. [5]). The input laser beam is reflected by the polarization beam splitter to illuminate the SLM which is conjugated to the front focal plane (FFP) of the excitation objective. After being modulated by the binary phase map loaded on the SLM (Fig. 1(B)) and filtered by a transparent annular mask conjugated to the BFP of the excitation objective, the beam then will be focused by the excitation objective to produce the corresponding lattice pattern. With rapid dithering of the OL pattern by the x galvo mirror conjugated to the BFP of the excitation objective (not shown in the sketch), a uniform lattice light sheet illumination will be obtained.
Fig. 1. (A) Schematic diagram of the LLSM. For simplicity, the x and z galvo mirrors are not shown in the sketch. The sample moving direction (s) is indicated by the double-headed arrow. SLM: spatial light modulator; HWP: half wave plate; PBS: polarization beam splitter; L: lens; AM: annular mask; RL: relay lens; EO: excitation objective; CS: coverslip; DO: detection objective; TL: tube lens. (B) The binary phase map loaded on the SLM and the intensity distribution of the OL patterns at different locations. (C) If a physical 0-π step phase mask (indicated by the inset of the first column in Fig. 1(C)) is inserted at the BFP of the excitation objective, with the same binary phase map loaded on the SLM, a new lattice pattern with zero intensity at its center will be generated. The simulation parameters are as follows: the excitation wavelength λexc = 488 nm; the refractive index n = 1.33; the NA of the excitation objective is NAexc = 0.66; the outer and the inner NAs of the lattice pattern are NAouter = 0.55 and NAinner = 0.48. Scale bars: 5 µm.
To further compress the thickness of the light sheet to improve the axial resolution as well as image contrast, LLSDM records two images with complementary illumination profiles to reconstruct the final image, that is, an image IOL excited by the normal light sheet deriving from the dithered OL pattern, and the other image ICOL excited by the complementary light sheet featuring zero intensity at its center. Thus, the final reconstructed 3D image Ieff can be calculated as follow:
In order to obtain the aforementioned COL light sheet, a 0-π step phase mask can be inserted at the BFP of the excitation objective, which leads to a COL pattern with zero central intensity and symmetric sidelobes (Fig. 1(C)). The ideal two-dimensional (2D) electric field of the COL pattern at the sample plane of the excitation objective can be expressed as:
To minimize the negative pixels introduced in LLSDM, there are two strategies we can take into consideration: First, we can broaden the width of the OL light sheet by adjusting the OL pattern with different combination of NAs in the calculation process. By reducing the outer NA of the OL pattern (the pink profiles in Fig. 2(A), Fig. 2(D)), the thickness of the OL light sheet can be extended to match with the outer contour of the COL light sheet (indicated by the two blue profiles in Fig. 2(A)), resulting in fewer negative artifacts compared with using a larger outer NA when the same subtraction coefficient is applied (comparing the dark green profile with the yellow one in Fig. 2(B)). However, since the transmittance aperture of the annular mask is fixed, the filtering of the high-order diffraction light from the SLM is no longer complete if we further reduce the outer NA of the OL beam, leading to unwanted interference at the sample plane. Compared with the case where the NAs of the annular mask matches that of the OL pattern (Fig. 2(C)), the leaked high-order light will cause uneven distribution of the lattice (Fig. 2(D)). Worse yet, the intensity distribution of the dithered OL light sheet along the z axis can be no longer smooth, but shows a certain level of fluctuation (Fig. 2(E)). Therefore, when this strategy is used, unless the annular mask can be switched freely, the user needs to carefully adjust the outer NA of the OL pattern.
Fig. 2. NA matching between OL and COL beams. (A) Simulated axial intensity profiles of the detection beam and different excitation beams. (B) Simulated axial profiles of various overall point spread functions (PSFs). The simulation parameters are as follows: n = 1.33; NAexc = 0.66; NAdet = 1.1; λexc = 488 nm; the assumed detection wavelength is λdet = 527 nm. For profiles ‘LLSD1’ and ‘LLSD2’, the corresponding NAs (NAouter-NAinner) of the OL beams are set to 0.51-0.48, and 0.55-0.48. The corresponding subtraction coefficients (0.3 or 0.7) are indicated by the number immediately following the token of ‘#’. (C)–(D) Simulation results of OL beams with NAs of 0.51-0.48 at the sample plane after being filtered by an annular mask with NAs of 0.51-0.48 (C) and 0.55-0.48 (D). (E) Simulation results of OL beams with NAs of 0.50-0.48 at the sample plane after being filtered by an annular mask with NAs of 0.55-0.48. Scale bars: 5 µm.
On the other hand, if we keep the NAs of the OL and the COL beams to be the same, we still can achieve similar results by using smaller subtraction coefficients (comparing the dash green profile with the dark green profiles in Fig. 2(B)). Empirically, α can be set between 0.3 and 0.7 according to different imaging conditions.
2.2 Principle of the generation of the complementary optical lattice for the LLSDM
To simplify the optical path configuration, it is possible to replace the phase modulation introduced by a 0-π step phase mask placed at the BFP with the modulation by the SLM conjugated to the FFP of the excitation objective, as used in the LLSM. As a result, the two beams now can be intrinsically aligned at the sample plane with improved stability. In LLSM, a binary SLM is used for its fast speed and low cost. Therefore, the calculated continuous phase map will be converted into a binary phase map with values of zero or π, depending on whether the pixel values in the continuous phase map are larger than the preset threshold [5]:
However, the binary SLM cannot recapitulate the full range of the electric field modulated with a 0-π step phase mask. Taking the square lattice as an example, which is used throughout this work, as shown in Fig. 3(A), the binary SLM phase map calculated from (3)–(5) for a lattice electric field modulated with a 0-π step phase mask presents slightly different profile for the upper and the lower halves of the map after the binarization operations, resulting in a COL pattern with sidelobes of asymmetric intensity distribution. Realizing that it is the asymmetry of the binary phase pattern that leads to the uneven illumination of the COL beam at the sample plane, we try to manipulate the binary phase map with a symmetric profile: First, the binary phase maps of the COL patterns with 0-π and π-0 step phase modulation are generated (Fig. 3(B), left). Only halves of them with the same amount of phase delay are retained to assemble the final binary phase map (Fig. 3(B), right). However, as we can see, although the intensity profile of the sidelobes is now symmetric owing to the symmetrical SLM phase map, the central intensity is no longer zero (Fig. 3(C)). This is because the phase difference between the upper and lower halves of the COL beam approaches zero, and thus the destructive interference between them cannot be efficiently realized at the sample plane. To address this problem, an additional half-period optical path difference is introduced into the calculation procedure for the second phase map (Fig. 3(D)). That is, an offset of half period (indicated by the distance between the two dash lines in Fig. 3(E)–(G)) along the axis x is introduced to shift the second half of the phase map a half-period optical path difference. Consequently, the two halves of COL beam can interfere destructively at the center, and higher modulation contrast can be preserved with ensured sidelobe symmetry.
Fig. 3. Procedure of optimizing the generation of a COL pattern. (A) An asymmetric binary SLM phase map leads to a COL pattern with sidelobes of asymmetric intensity distribution. (B) The binary SLM phase map of COL patterns with 0-π step phase mask in different orientations (left column). (C) Combining the phase map cut from (B) (indicated by the column of ‘SLM phase map cut’), the COL pattern will be generated with symmetric sidelodes but non-zero intensity distribution at its center. (D) By introducing an additional half-period (the period is defined by T = jλexc/NAinner, j > 1) optical path difference into the second half of the phase map, the COL pattern will be generated with symmetric sidelodes and zero intensity at its center as what a physical 0-π phase mask does. (E)–(G) The corresponding magnified view of the boxed region in (A), (C) and (D). The simulation parameters are as follows: λexc = 488 nm, n = 1.33, NAexc = 0.66, NAouter = 0.55, and NAinner = 0.48. Scale bars: 5 µm.
3. Methods
3.1 Image rendering
The binary SLM phase maps of OL patterns with NAs of 0.55-0.48 and 0.51-0.48, and COL pattern with NAs of 0.55-0.48 are pre-calculated and loaded onto the SLM before imaging. The OL pattern with NAs of 0.55-0.48 provides an approximate FOV of 22 µm along the axis of excitation objective, defined by the full width at half maximum (FWHM) of the light sheet profile. The rapid dithering of the x galvo allows the lattice pattern to form a uniform light sheet to excite the sample within the camera exposure time. At every z plane, the different patterns will excite the sample sequentially. The sample will be scanned across the fixed light sheet along the s axis (indicated by the double arrow in Fig. 1) with a piezo-tube stage (PZT) for 3D volumetric imaging.
The obtained 3D image stacks were then pre-processed by self-written MATLAB codes according to Eq. (1). Due to the complexity of the images of biological samples, with a fixed subtraction coefficient, it is inevitable to introduce negative distortions in some positions of the images. Therefore, different subtraction coefficients were tried for various types of imaging conditions. After performing intensity difference and resetting the negative value to zero, by comparing images with different subtraction coefficients, we empirically picked the appropriate one which contained less negative distortion and more useful information for the subsequent image rendering procedure. That is, the reconstructed 3D image stacks were then sent to the LLSpy package [25] to perform de-skewing and deconvolution with the experimental LLSM PSF or LLSDM PSFs with corresponding subtraction coefficient with 10 iterations to further enhance the image resolution. For better visualization, the deconvolved image stacks were further depth-coded by custom MATLAB codes.
3.2 Sample preparation
3.2.1 Immunofluorescence staining
Human osteosarcoma cells U2OS were cultured in McCoy's 5A Media (Thermo Fisher Scientific, Inc.) supplemented with 10% fetal bovine serum (FBS; Thermo Fisher Scientific, Inc.) in a humidified incubator at 37°C with 5% CO2. The U2OS cells were seeded in 5-mm-diameter coverslips and cultured overnight. The following day, cells were first washed with phosphate-buffered saline (PBS; Thermo Fisher Scientific, Inc.) and then fixed with 4% paraformaldehyde for 13 min at 37 °C in an incubator. The fixed cells were rinsed thrice with PBS and blocked with a blocking buffer containing 0.2% Triton-X 100 and 5% goat serum for 1 hour. Alpha and beta Tubulin antibody (WA31679510 and TG2597441, Invitrogen), and Goat anti-Mouse IgG (H + L) Cross-Adsorbed Secondary Antibody, Alexa Fluor Plus 488 (TF266577, Invitrogen) were diluted at 1:200 in the blocking buffer. The cells were incubated with primary antibody overnight at 4 °C. Three washes with PBS, in which two washes for 3 min, and the last wash for 15 min. After incubating the secondary antibody for 1 hour at room temperature under light-protected conditions. The sample was rinsed thrice with PBS and imaged with the microscope.
3.2.2 Stable transfection
Human embryonic kidney cells HEK-293 T in the logarithmic phase were cultured in DMEM (2362192, Thermo Fisher Scientific, Inc.) supplemented with 10% FBS. Start packing virus particles after reaching approximately 80% confluence. The PLVX-Lifeact-mEGFP, psPAX2 and pmD2.G were transfected into the cells using Lipofectamine 3000 (Invitrogen) according to the manufacturer’s instructions. After 72 hours of transfection, the virus supernatant was collected. The virus was first filtered through a 0.45-µm filter membrane and centrifuged at 25 000 r/min for 2 hours at 4 °C to obtain the virus precipitate.
The U2OS cells were grown overnight in 6-well plates and infected with the virus when they grew to a 30% confluence rate. A mixture of virus particles and DMEM medium and addition of Polybrene at a final concentration of 8 ug/mL to infect cells in 6-well plates. After 24 hours of infection, 1–2 µg/mL puromycin was added for screening and untransfected cells were removed. After 24 hours, the stably transfected cells were seeded in the 5-mm-diameter coverslip. After 12 hours of growth, the imaging was performed in an environment of DMEM with no phenol red (8120180, Thermo Fisher Scientific, Inc.) at 37°C with 5% CO2.
4. Result and discussion
4.1 Comparison of LLSM and LLSDM
By synchronizing the motion of the detection objective (Nikon, CFI Apo LWD 25XW, 1.1NA) and z galvo mirror conjugated to the BFP of the excitation objective (Special Optics, 54-10-7@488-910 nm, 0.66NA) which refocuses the light sheet correspondingly, the 3D PSFs excited by the dithered OL light sheet and COL light sheet will be recorded, when the three binary phase maps are loaded onto the SLM sequentially (Fig. 4). Fluorescent beads (1437608, Life technologies) of 100-nm diameter were excited by a 488-nm laser with an exposure time of 10 ms per plane. Compared to the OL light sheet with NAs of 0.55-0.48, the axial width of the OL light sheet with NAs of 0.51-0.48 is broadened to achieve the beam size matching with the COL counterpart, and the final reconstructed bead image (Fig. 4(D)) achieves better axial resolution (∼482 nm) (defined by FWHM) than the former (∼663 nm, Fig. 4(A)). On the other hand, when the OL light sheet with NAs of 0.55-0.48 is used, with the subtraction coefficient from 0.3 to 0.5, the reconstructed axial resolution can be enhanced by ∼1.3 to ∼1.5 times, reaching ∼496 nm and ∼428 nm, which are closer to the experimental lateral resolution (∼306 nm defined by FWHM). Note that using larger subtraction coefficients allows for higher axial resolution (Fig. 4(H)), but will also introduces more negative artifacts (Fig. 4(I)), risking more information loss.
Fig. 4. Experimental comparison of 100-nm fluorescent beads in different imaging modalities. (A) The xz maximum-intensity projection (MIP) with normalized intensity of a bead excited by the OL light sheet with the outer NA and inner NA of 0.55-0.48. (B) The xz MIP with normalized intensity of the same bead excited by the COL light sheet with NAs of 0.55-0.48. (C) The xz MIP with normalized intensity of the same bead excited by the OL light sheet with NAs of 0.51-0.48. For (A)–(C), all of the excitation beams of 488 nm are filtered by a fixed annular mask with NAs of 0.55-0.48. (D)The final effective xz MIP of the bead reconstructed by (B) and (C) with a subtraction coefficient of 0.5. (E)–(F) The final effective xz MIP of the same bead reconstructed by (A) and (B) with a subtraction coefficient of 0.3 (E) and 0.5 (F). Scale bars: 1 µm. (G) The corresponding axial profiles of beads in (A)–(F). Except for the profile of (B) is fitted with the second-order Gaussian function, all the other profiles are fitted with the first-order Gaussian function. (H) The FWHM of the beads decreases as the subtraction coefficient increases. (I) The ratio of the minimum value to the maximum value of the subtracted image increase as the subtraction coefficient increases.
4.2 Cells imaging with LLSDM
The fixed U2OS cell sample was incubated in PBS solution and imaged at room temperature. The collar ring position of the detection objective correcting the spherical aberration resulting from refraction index mismatch was optimized correspondingly. The cell sample was scanned across the fixed dithered light sheet in a step size of 350 nm (and thus the step size along the detection objective is ∼184 nm) by the sample PZT with 10-ms exposure time per plane to complete the 3D volumetric imaging. Since the optical axis of the detection objective is not perpendicular to the coverslip, though at the expense of axial resolution, the reconstructed images were de-skewed and rotated for better visualization of the cell morphology.
The MIP microtubule images in Fig. 5 are color-coded as a function of depth. Through the entire cell depth, the xz and yz cross-section images show a better axial resolution than the LLSM image with modest subtraction coefficients of 0.3 and 0.5 (Figs. 4(C)–(D), (E)–(F)). Remarkably, the LLSDM image shows not only the thinner microtubule diameter but also higher image contrast (Fig. 4(F)). Larger subtraction coefficients typically provide better axial resolution and higher imaging contrast (comparing LLSD2#0.3 with LLSD2#0.5). When using the same COL pattern with NAs of 0.55-0.48 and the same subtraction coefficient of 0.5, the reconstructed image combined with the OL pattern of larger outer NA provides a higher improvement in axial resolution (comparing LLSD1#0.5 with LLSD2#0.5). Gaussian fitting the line profiles in Fig. 4(F) shows that the size of the microtubules along the axial axis is reduced from ∼1.06 µm (for ‘LLS’) to ∼0.82 µm (for ‘LLSD2#0.3’), ∼0.77 µm (for ‘LLSD1#0.5’), and ∼0.58 µm (for ‘LLSD2#0.5’), indicating that LLSDM can improve the axial resolution by 1.28–1.82 times. Note that the improvement along the axial direction also benefits the contrast in the xy projection for dense samples (Figs. 5B, E).
Fig. 5. Imaging results of microtubules of a fixed U2OS cell. The image stacks are de-skewed and rotated so that the coverslip is oriented horizontally. (A) The xy MIP of a U2OS cell imaged with LLSDM with a subtraction coefficient of 0.5. Scale bar: 10 µm. (B) Magnified view of the boxed region in (A). For comparison, the original image (denoted by ‘LLS’), the LLSDM image excited by the OL pattern with NAs of 0.51-0.48 (denoted by ‘LLSD1’), and the LLSDM images excited by the OL pattern with NAs of 0.55-0.48 (denoted by ‘LLSD2’) are displayed sequentially. Different subtraction coefficients are applied and indicated by the number after ‘#’. Scale bars: 2 µm. (C) The yz slices are oriented perpendicular to the sample scan axis (s axis, indicated in Fig. 2), indicated by the dash line C in (A). Scale bar: 10 µm. (D) The xz slices are oriented perpendicular to the sample scan axis, indicated by the dash line D in (A). Scale bar: 10 µm. (E)–(G) The corresponding line profiles indicated by the dash lines in (B)–(D).
To further demonstrate that LLSDM enables long-term volumetric imaging of live cells with higher axial resolution and contrast, we investigated the dynamics of actin cytoskeleton in live U2OS cells, which are critical for the cellular morphology development and migration [26]. Totally 100 volumes with 5-ms exposure time for each OL and COL pattern illumination were recorded at a constant 30-s interval to visualize the dynamics of filopodia on the apical surface of a live U2OS cell. Despite additional excitation patterns needed for LLSDM reconstruction, we observed no obvious photobleaching effect during the whole recording process (see Visualization 1). We reconstructed the final LLSDM images with subtraction coefficients of 0.5 and 0.7 when using the OL patterns with NAs of 0.55-0.48 and 0.51-0.48. The capability of resolving the curved arcs of the slimmer filaments at the dorsal membrane in LLSDM indicates better axial resolution compared with the LLSM image (Fig. 6(B)). The high speed and axial resolution afforded by LLSDM enable direct visualization of various types of filament movement, such as waving (the yellow arrows, Fig. 6(C)), inward (the magenta arrow, Fig. 6(C)) and outward (the cyan arrows, Fig. 6(C)) extension as well as an inward retraction (the green arrows, Fig. 6(C)).
Fig. 6. (A) Side view of the volumetric rendering of the filopodia dynamics on the dorsal surface of a U2OS cell expressing mEmerald-Lifeact by LLSDM. The NAs of the OL pattern are 0.55-0.48 and a subtraction coefficient of 0.5 is used (denoted by ‘LLSD2#0.5’). Scale bar: 5 µm. (B) Magnified view of the box region in (A). For comparison, the same magnified region of the original LLSM image (denoted by ‘LLS’), the LLSDM image subtracted from the OL pattern with NAs of 0.51-0.48 and subtraction coefficient of 0.7 (denoted by ‘LLSD1#0.7’) are also presented. Scale bars: 2 µm. (C) The xz side view images of reconstructed LLSD2#0.5 showing filopodia dynamics at three time points (see Visualization 1). Scale bars: 5 µm.
5. Discussion and conclusion
In this work, we investigated the method to achieve higher axial resolution and better image contrast for 3D volumetric imaging by LLSDM. LLSDM enhances the axial resolution by specifically discarding the off-focus photons with differential algorithm during the post-processing stage. The FOV covered by the light sheet illumination can be preserved and nearly isotropic spatial resolution can be obtained with a modest compromised imaging speed.
LLSDM has advantages regarding the light sheet thickness and imaging speed. Since the axial resolution in LSFM mainly depends on the light sheet thickness, a thinner light sheet profile provides better optical sectioning capability and higher axial resolution. However, it is difficult to compress the light sheet thickness while maintaining a large FOV simultaneously. Note that increasing the radius of the annular ring/beam is beneficial to obtain a thinner light sheet (or better axial resolution) but with shorter propagation length [27]. For example, similar axial resolution of about 401 nm can theoretically be obtained in LLSM with NAs of 0.66-0.38, assuming that λexc = 488 nm, c = 0.22, and λdet = 527 nm, NAdet = 1.1. However, the high axial resolution is obtained at the expense of FOV which is greatly reduced to only about 4.6 µm (FWHM). The introduction of the STED principle confines the excitation thickness by depleting the photons at the outer edge of the beam at the sample plane. Premature photobleaching and phototoxicity can be introduced due to the exposure of the complementary depletion beam with high laser power densities. Therefore, discarding the off-focus photons by differential subtraction with mild addition of photodamage to the sample, the proposed LLSDM provides an alternative since the complementary beam has no requirement of high laser power. On the other hand, compared with LLSM using SIM algorithm, LLSDM outperforms in imaging speed with fewer images acquired for image reconstruction, less computational complexity and less photobleaching.
Currently, there are two limitations associated with the implementation of this method. Compared with LLSM using the dithering mode, the imaging speed will be decreased by half along with the doubled amount of data needed for processing. On the other hand, the choice of the subtraction coefficient will affect the resolution and image contrast of the reconstructed images. For samples with enough sparsity, we may consider using larger subtraction for higher axial resolution and contrast. Whereas for specimens with high density, modest subtraction coefficients are preferred to prevent introducing too many negative artifacts, as shown both in the simulation (Fig. 2(B)) and experimental results (Fig. 4). In the volumetric imaging experiment for live samples, we recommend using the OL pattern with larger outer NA and smaller subtraction coefficient to reconstruct the LLSDM image, which can further circumvent the premature photobleaching problem benefitting from the more confined illumination area.
In summary, we proposed LLSDM to provide a 1.5× improvement in the axial resolution compared to LLSM in dithering mode for imaging with mildly enhanced contrast. As a methodology of resolution and contrast enhancement, the proposed method can also bring benefits to other light-sheet-based imaging systems without compromised FOV.
Funding
National Natural Science Foundation of China (62125504, 61827825, 61735017 31901059); Major Program of the Natural Science Foundation of Zhejiang Province (LD21F050002); Key Research and Development Program of Zhejiang Province (2020C01116); Zhejiang Lab (2020MC0AE01); Zhejiang Provincial Ten Thousand Plan for Young Top Talents (2020R52001); Fundamental Research Funds for the Central Universities (2021QNA5004); the Open Project Program of Wuhan National Laboratory for Optoelectronics (2021WNLOKF007).
Acknowledgments
We would like to thank Lu Yang (Zhejiang University), and Xin Luo (Zhejiang University) for supplying the samples used in the research. We are grateful to Dr. Fenghua Shi (Anhui Normal University) for constructive comments. The control software of the microscope and the post-processing codes are licensed by Howard Hughes Medical Institute, Janelia Research Campus. We thank Dr. Talley Lambert for creating and maintaining the software package LLSpy for lattice light sheet data processing.
Disclosures
The authors declare no conflicts of interest.
Data availability
Data underlying the results presented in this paper are not publicly available at this time but may be obtained from the authors upon reasonable request.
References
1. J. Huisken, J. Swoger, F. Del Bene, J. Wittbrodt, and E. H. K. K. Stelzer, “Optical Sectioning Deep Inside Live Embryos by Selective Plane Illumination Microscopy,” Science 305(5686), 1007–1009 (2004). [CrossRef]
2. P. J. Keller, A. D. Schmidt, J. Wittbrodt, and E. H. K. Stelzer, “Reconstruction of zebrafish early embryonic development by scanned light sheet microscopy,” Science 322(5904), 1065–1069 (2008). [CrossRef]
3. Y. Wu, A. Ghitani, R. Christensen, A. Santella, Z. Du, G. Rondeau, Z. Bao, D. Colón-Ramos, and H. Shroff, “Inverted selective plane illumination microscopy (iSPIM) enables coupled cell identity lineaging and neurodevelopmental imaging in Caenorhabditis elegans,” Proc. Natl. Acad. Sci. U. S. A. 108(43), 17708–17713 (2011). [CrossRef]
4. T. A. Planchon, L. Gao, D. E. Milkie, M. W. Davidson, J. A. Galbraith, C. G. Galbraith, and E. Betzig, “Rapid three-dimensional isotropic imaging of living cells using Bessel beam plane illumination,” Nat. Methods 8(5), 417–423 (2011). [CrossRef]
5. B. C. Chen, W. R. Legant, K. Wang, L. Shao, D. E. Milkie, M. W. Davidson, C. Janetopoulos, X. S. Wu, J. A. Hammer, Z. Liu, B. P. English, Y. Mimori-Kiyosue, D. P. Romero, A. T. Ritter, J. Lippincott-Schwartz, L. Fritz-Laylin, R. D. Mullins, D. M. Mitchell, J. N. Bembenek, A. C. Reymann, R. Böhme, S. W. Grill, J. T. Wang, G. Seydoux, U. S. Tulu, D. P. Kiehart, and E. Betzig, “Lattice light-sheet microscopy: Imaging molecules to embryos at high spatiotemporal resolution,” Science 346(6208), 1 (2014). [CrossRef]
6. U. Krzic, S. Gunther, T. E. Saunders, S. J. Streichan, and L. Hufnagel, “Multiview light-sheet microscope for rapid in toto imaging,” Nat. Methods 9(7), 730–733 (2012). [CrossRef]
7. W, Hell S and J. Wichmann, “Breaking the diffraction resolution limit by stimulated emission: stimulated-emission-depletion fluorescence microscopy,” Opt. Lett. 19(11), 780–782 (1994). [CrossRef]
8. M. G. L. L. Gustafsson, “Surpassing the lateral resolution limit by a factor of two using structured illumination microscopy,” J. Microsc. 198(2), 82–87 (2000). [CrossRef]
9. W. C. Lemon, S. R. Pulver, B. Höckendorf, K. McDole, K. Branson, J. Freeman, and P. J. Keller, “Whole-central nervous system functional imaging in larval Drosophila,” Nat. Commun. 6(1), 7924 (2015). [CrossRef]
10. R. K. Chhetri, F. Amat, Y. Wan, B. Höckendorf, W. C. Lemon, and P. J. Keller, “Whole-animal functional and developmental imaging with isotropic spatial resolution,” Nat. Methods 12(12), 1171–1178 (2015). [CrossRef]
11. M. Lucas, K. Kenobi, D. Von Wangenheim, U. Voß, K. Swarup, I. De Smet, D. Van Damme, T. Lawrence, B. Péret, E. Moscardi, D. Barbeau, C. Godin, D. Salt, S. Guyomarc’h, E. H. K. Stelzer, A. Maizel, L. Laplaze, and M. J. Bennett, “Lateral root morphogenesis is dependent on the mechanical properties of the overlaying tissues,” Proc. Natl. Acad. Sci. U. S. A. 110(13), 5229–5234 (2013). [CrossRef]
12. D. Von Wangenheim, J. Fangerau, A. Schmitz, R. S. Smith, H. Leitte, E. H. K. Stelzer, and A. Maizel, “Rules and self-organizing properties of post-embryonic plant organ cell division patterns,” Curr. Biol. 26(4), 439–449 (2016). [CrossRef]
13. L. Gao, L. Shao, C. D. Higgins, J. S. Poulton, M. Peifer, M. W. Davidson, X. Wu, B. Goldstein, and E. Betzig, “Noninvasive imaging beyond the diffraction limit of 3D dynamics in thickly fluorescent specimens,” Cell 151(6), 1370–1385 (2012). [CrossRef]
14. W. R. Legant, L. Shao, J. B. Grimm, T. A. Brown, D. E. Milkie, B. B. Avants, L. D. Lavis, and E. Betzig, “High-density three-dimensional localization microscopy across large volumes,” Nat. Methods 13(4), 359–365 (2016). [CrossRef]
15. D. N. Düring, M. D. Rocha, F. Dittrich, M. Gahr, and R. H. R. Hahnloser, “Expansion Light Sheet Microscopy Resolves Subcellular Structures in Large Portions of the Songbird Brain,” Front. Neuroanat. 13, 1 (2019). [CrossRef]
16. B. Cao, S. Coelho, J. Li, G. Wang, and A. Pertsinidis, “Volumetric interferometric lattice light-sheet imaging,” Nat. Biotechnol. 39(11), 1385–1393 (2021). [CrossRef]
17. C. H. Lu, W. C. Tang, Y. T. Liu, S. W. Chang, F. C. M. Wu, C. Y. Chen, Y. C. Tsai, S. M. Yang, C. W. Kuo, Y. Okada, Y. K. Hwu, P. Chen, and B. C. Chen, “Lightsheet localization microscopy enables fast, large-scale, and three-dimensional super-resolution imaging,” Commun. Biol. 2(1), 1–10 (2019). [CrossRef]
18. J. M. Hernández, A. Buisson, I. Wang, and J.-C. Vial, “Improved optical slicing by stimulated emission depletion light sheet microscopy,” Biomed. Opt. Express 11(2), 660 (2020). [CrossRef]
19. C. Gohn-Kreuz and A. Rohrbach, “Light needles in scattering media using self-reconstructing beams and the STED principle,” Optica 4(9), 1134 (2017). [CrossRef]
20. F. O. Fahrbach and A. Rohrbach, “Propagation stability of self-reconstructing Bessel beams enables contrast-enhanced imaging in thick media,” Nat. Commun. 3(1), 632 (2012). [CrossRef]
21. C. Zhang, Y. Chen, W. Liu, C. Kuang, Z. Zhang, X. Hao, and X. Liu, “Isotropic three-dimensional imaging with lattice light-sheet difference microscopy,” Opt. Lett. 45(10), 2854 (2020). [CrossRef]
22. C. Liu, X. Yu, C. Bai, X. Li, Y. Zhou, S. Yan, J. Min, D. Dan, R. Li, S. Gu, and B. Yao, “Axial resolution enhancement for planar Airy beam light-sheet microscopy via the complementary beam subtraction method,” Appl. Opt. 60(32), 10239 (2021). [CrossRef]
23. C. Liu, C. Bai, X. Yu, S. Yan, Y. Zhou, X. Li, J. Min, Y. Yang, D. Dan, and B. Yao, “Extended field of view of light-sheet fluorescence microscopy by scanning multiple focus-shifted Gaussian beam arrays,” Opt. Express 29(4), 6158 (2021). [CrossRef]
24. C. J. Mann, L. Yu, C.-M. Lo, and M. K. Kim, “High-resolution quantitative phase-contrast microscopy by digital holography,” Opt. Express 13(22), 8693 (2005). [CrossRef]
25. T. Lambert, L. Shao, and H. Volker, “tlambert03/LLSpy: v0.4.8,” (2019).
26. T. Svitkina, “The actin cytoskeleton and actin-based motility,” Cold Spring Harb. Perspect. Biol. 10(1), a018267 (2018). [CrossRef]
27. B.-J. Chang, K. M. Dean, and R. Fiolka, “Systematic and quantitative comparison of lattice and Gaussian light-sheets,” Opt. Express 28(18), 27052 (2020). [CrossRef]
