We note that the design of the adaptive light-sheet microscope supports simultaneous acquisition of opposing views as well as more complex multi-view imaging strategies, such as orthogonal four-view imaging, which can be achieved by sequentially acquiring two sets of opposing views and physically rotating the embryo by 90 degrees in between. Due to the rotation of the point-spread function relative to the embryo, such orthogonal sets of views contain complementary frequency content that can be combined by multi-view registration and multi-view deconvolution. However, we found that the acquisition of two opposing views alone already offers good coverage of the mouse embryo at the cellular level, and we thus recommend four-view imaging only for short-term imaging of very crowded regions (e.g. migration of cells out of the primitive streak) or for investigations at the sub-cellular level, considering that this approach necessitates a two-fold increase in light exposure of the embryo.

Complementing the core adaptive imaging capabilities described above, we also introduced an optional degree of freedom in the AutoPilot framework that enables compensation for spherical aberrations in fluorescence imaging. By jointly controlling the positions of objectives and tube lenses in the detection arms with motorized stages, this degree of freedom can adapt the microscope to spatially varying spherical aberrations. In general, such variability is expected as a function of imaging depth in the embryo if the average refractive indices in the embryo and in the culturing medium differ. We observed this effect experimentally and confirmed that adaptive system correction leads to a corresponding improvement in image quality ( Figures S2 D and S2E); however, we also found that the relative impact of these corrections is considerably smaller (by a factor of ∼6) than that of the illumination and detection focus corrections discussed above. We concluded from these data that it is preferable to avoid the additional imaging time and light exposure of the specimen required for continuous spherical aberration corrections.

The advanced adaptive imaging framework described here facilitates a dynamic adaptation of the microscope configuration to local optical conditions, which serves the purpose of first optimizing and subsequently maintaining high spatial resolution across the embryo and over the time course of the experiment. As the embryo moves and/or grows, the adaptive imaging framework corrects the positions of the reference regions accordingly and adjusts their number and relative spacing to maintain adequate spatial sampling of the constantly changing optical conditions across the developing mouse embryo ( Figure 1 D; Video S1 B). To compensate for the optical heterogeneity and dramatic growth of the embryo, focal plane and light-sheet waist locations typically need to be adjusted by approximately 5 μm and 200 μm, respectively, over the course of 24 hr. Post-optimization, focal plane offsets are typically spread over a 5 μm range across the embryo in early developmental stages and over a 15 μm range during late developmental stages. Thus, adaptive imaging capabilities are critically needed to maintain high spatial resolution and the ability to track individual cells throughout development. The spatial sampling and temporal frequency of our aberration corrections are set to ensure that less than 2% of all defocus errors remain uncorrected. Thereby, the average defocus-induced mismatch between light sheets and detection focal planes is reduced to only 0.06 ± 0.04 μm, which is negligible compared to the confocal parameter of the detection optics and the size of the cellular structures imaged in the mouse embryo ( Table S1 Figures S2 B and S2C). We evaluated the quantitative impact of the adaptive imaging framework on image quality in developing mouse embryos and found that, on average, spatial resolution is increased by a factor of 3.3, signal strength by a factor of 2.1 and the cut-off radius in frequency space by 60% (measured across n = 5 different locations and developmental stages; Figure 1 F). A continuous side-by-side comparison of adaptive vs. non-adaptive imaging of post-implantation mouse development over the course of a time-lapse imaging experiment is shown in Video S1 C.

Our adaptive imaging approach comprises several crucial advances over our earlier AutoPilot system (). This latter method employed a static model of the specimen that was provided by the user and assumed a fixed, pre-defined specimen size and geometry. The user manually selected several reference locations in the specimen, at which the system monitored image quality, and the microscope then observed and reacted to optical changes only in these locations. We found this basic approach to be fundamentally ill-suited to imaging the developing post-implantation mouse embryo, which undergoes dramatic changes in size and shape and exhibits continuous movements throughout the time-lapse experiment. Both in non-adaptive light-sheet microscopy and in our original AutoPilot framework, the magnitude of detection defocus errors is on average at least as large as the depth of the focal volume of the detection objective itself (1.93 μm confocal parameter for Nikon 16x/0.8 and 1.14 μm for Zeiss 20x/1.0 objectives).

Traditionally, mouse embryos have been grown in roller culture to ensure sufficient gas exchange and proper development (); however, such conditions are obviously incompatible with imaging, and static culture methods have been developed that support normal post-implantation growth (). We further adapted these static culture conditions for our system and ensure sufficient gas exchange by replacing the culture chamber atmosphere at a rate of at least 15 times per minute. The sample positioning stage is placed underneath the sample chamber, such that samples are mounted in a vertical position. While embryos like Drosophila and zebrafish may be mounted and held in place with agarose cylinders, the dramatic growth and sensitivity of the mouse embryo prohibits any kind of mechanical constraints. We use hollow glass capillaries filled with Matrigel as a supportive base for the embryo by gently embedding the sticky ectoplacental cone into the Matrigel, leaving the extra-embryonic and embryonic regions of the embryo above freely floating in media ( Figure 1 C). Embryos can then be placed either directly into low-volume chambers or enclosed in an ultra-thin Teflon FEP tube (25 μm wall thickness) with culture media and mounted in chambers filled with water (see sections “Transgenic mice and reporters” and “Sample preparation, embryo culture and imaging of mouse embryos” above).

For optimal mouse embryo culture conditions during imaging, we fabricated a custom incubation enclosure and sample chamber that, coupled with an Okolab Bold line environmental system, provides highly stable temperature and atmospheric control ( Figure 1 A; Figure S1 A). Embryos are cultured and imaged within this enclosure inside a sample chamber fabricated from heat or chemical-sterilization resistant materials (PEEK or Ultem). To mitigate the impact of light scattering and optical aberrations on image quality while facilitating rapid imaging of the entire embryo, the specimen is simultaneously illuminated with scanned light sheets () from two opposing directions while images are acquired with confocal slit detection, using two opposing detection objectives. Dipping objectives are used for both illumination and detection, and both sample post and objectives are enclosed by molded silicone seals ( Figure 1 B). We opted for the use of short working distance dipping optics to avoid unnecessary optical interfaces and minimize the optical path length both for light-sheet illumination and fluorescence detection, which in turn minimizes the effect of light scattering in the serum even when using an open embryo culture. The presence of four dipping objectives in one space severely restricts the available geometry for objective pairs ( Figure 1 B) and a system design based exclusively on commercial objectives would either prohibit the use of high numerical aperture detection objectives or require the use of long working distance illumination objectives. This restriction mandated the design of custom illumination objectives designed with a very small nose angle (33°), which reduce working distance to 4 mm (leaving enough space for embryo growth and sample access) and are fully compatible with detection objectives up to a numerical aperture of 1.0 ( Figure S1 E-S1H). Compared to the highest-quality, commercial illumination objectives with a long working distance, our low-profile custom design reduces light loss by a factor of 150 in a typical culturing medium containing 50% rat serum ( Figure S2 A). This performance feature and related improvements in image quality are the result of substantially reduced light scattering/absorption and aberrations due to the short illumination light path inside the medium.

In this section, we elaborate on the technical advances and design principles introduced in the light-sheet microscope described in the Results section “Adaptive multi-view light-sheet microscope for imaging mouse development”.

In total, the microscope presented here uses 77 different types of custom designed mechanical components, which are combined into 28 types of multi-part assemblies (such as the Maus Haus incubator, sample chamber, sample positioning system, etc.). To enable the replication of this instrument, we provide a complete set of technical drawings for all parts and assemblies, together with a detailed parts list, as supplemental data ( Data S1 A).

The Maus Haus environmental system and incubation chamber comprises an Okolab Bold Line heater and atmospheric control providing a mixture of air, CO 2 , N 2 , or O 2 depending on the desired concentrations. The Maus Haus incubator was custom fabricated from laser-cut acrylic panels that were designed for ease of access, sterility, temperature stability and a baffled air-exchange system to minimize vibrations. This enclosure covers the sample chamber, dipping and illumination objectives, and four-axis stage assembly. Typical light-sheet drift from ambient (21°C) to imaging temperatures (37°C) is generally around 50 μm, however the system is highly stable once it is aligned to imaging temperatures, even with repeated heating and cooling cycles.

The light-sheet microscope we designed for live imaging of post-implantation mouse development ( Figure S1 A, Data S1 A) consists of four main components: 1) Two bi-lateral scanned light-sheet illumination arms, 2) two wide-field fluorescent detection arms, 3) the environmental controls and Maus Haus incubation chamber and 4) the microscope control infrastructure. The illumination arms comprise an Omicron SOLE-6 multi-laser system with 488 nm, 515 nm, 561 nm, 594 nm, 642 nm, and 685 nm wavelengths with two exit ports and one QiOptiq kineFlex single-mode fiber for each illumination arm, each of which are connected to fiber-to-free-space collimators. The light path then travels through a filter wheel (96A351, driven by a MAC 6000 controller, Ludl) and shutter (Uniblitz LS6 with VMM-D3 three channel shutter driver), two relay lenses (49361-INK, Edmund Optics), one on either side of a dual-axis XY galvanometer scanning system (6125LH and RH from Cambridge Technology with dual-axis driver), before entering a second, identical XY galvanometer scanning system and then through an f-theta lens (S4LFT4375, Sill Optics), illumination tube lens (49361-INK, Edmund Optics) and a custom designed water-dipping 6.4× illumination objective (manufactured by Special Optics, model no. 54-12.5-31, see Figure S1 E-S1H). Illumination objectives are mounted on 800 μm travel PIHera linear piezo stages (P-628.1CD and E-665 LVPZT-Amplifier/Servo controller, Physik Instrumente) coupled to custom made adjustable bases. Dipping objectives enter a custom fabricated heat and chemical sterilization resistant sample chamber made from black PEEK or Ultem and are held in place by custom molded silicone seals (Albright Technologies) to prevent leaks. Additionally, the sample chamber was designed with moats and overflow drains to protect sensitive electronics in the case of leaks or spills. The sample is held in place underneath the objectives by a custom stainless-steel sample holder, which is connected to a post on the stage assembly by a strong magnet. To ensure proper rotation this holder-to-post connection is guided by a combination of ball-bearings on the holder set into grooves notched out of the post. The stage assembly itself is comprised of three linear translation stages for XYZ positioning, and one rotation stage which is directly coupled to the sample post (M-116.DG and M111.2.DG with PI C-809.40 motion controller, Physik Instrumente). The fluorescent detection arms are comprised of water dipping objectives (either Nikon CFI LWD 16×/0.8W or Carl Zeiss Plan-Apochromat 20×/1.0W) mounted on 250 μm travel PIHera linear piezo stages (P-622.1CD and E-665 LVPZT-Amplifier/Servo controller, Physik Instrumente) coupled to custom adjustable bases. Following the light path, each detection arm furthermore consists of a detection filter wheel with internal shutter (96A354 with MAC 6000 modular controller, Ludl), a detection tube lens (either Nikon ITL200 or Carl Zeiss 425308-000-000) mounted on a 1500 μm linear travel piezo stage (PI-629.1CD with E-665 LVPZT-Amplifier/Servo controller, Physik Instrumente), and an sCMOS camera (Orca Flash 4.0 v2, Hamamatsu).

Image acquisition and the control of all microscope components is facilitated via a distributed system consisting of a computer workstation (for data acquisition and user interface) and a National Instruments PXI-8110 embedded controller (for real-time control of microscope components) inside of a PXI-1042Q chassis containing a PXI-7350 motion controller for the stage assembly, a PXI-8432/2 RS232 interface connected to the filter wheel controllers, and two PXI-6733 input/output modules integrated with two BNC-2110 connector blocks, which output analog and digital waveforms controlling individual microscope components and monitor camera states. The microscope control computer itself is directly connected to the two Orca Flash 4.0 v2 cameras by way of FireBird CameraLink frame grabbers (Active Silicon) and is based on a Colfax SX6750 workstation base platform with dual Intel Xenon E5-2687W CPUs, 256 GB of RAM, and an Intel RS2WG160 RAID controller with 12 TB of SSD storage, running Windows 7 Professional 64-bit. Custom control software is written in LabVIEW (National Instruments) and Java to operate the microscope, execute the adaptive imaging workflow and run the online specimen tracking module. The adaptive imaging control framework is based on the AutoPilot automated control system (), which was extended in several ways to facilitate long-term live imaging of post-implantation mouse embryos at high spatiotemporal resolution. New functionality in the extended AutoPilot system includes (1) continuous measurement and stabilization of 3D position of the specimen, (2) continuous measurement of specimen size and adaptation of the imaging volume to dynamic size changes, (3) use of a dynamic geometrical model of the specimen for mapping optical properties and determining the corresponding optimal microscope parameters across the specimen volume, including the adaptive placement of reference planes and their position correction through integration with the online specimen tracking module, and (4) the design of a new hardware- and software-based AutoPilot degree of freedom for adaptive correction for spherical aberrations (enabled by the use of motorized tube lenses). The algorithms underlying modules (1)-(3), which were essential to enable the in toto imaging and image quality reported in this study ( Videos S1 B and S1C), are described in more detail in the next section.

Adaptive volume expansion, placement of reference planes and specimen tracking

In order to assess specimen movements as well as dynamic changes in specimen size and shape, the microscope control framework continuously computes and analyzes maximum-intensity projections of the imaging volume along multiple axes and in real time. The procedures described below are executed independently for each specimen view recorded by the microscope.

To facilitate specimen tracking and volume expansion along the imaging axis ( z -axis), the imaging volume is projected onto the z -axis, producing the intensity profile I ( z ) , which is subjected to the following automated procedure after each volume acquisition:

1) The minimum and maximum intensity values, I z , m i n and I z , m a x , of the z -axis intensity profile I ( z ) are computed. From these values, a threshold t = I z , m i n + l ⋅ ( I z , m a x − I z , m i n ) is computed, using the adaptive threshold level l ∈ [ 0 , 1 ] ( l = 0.1 for the experiments reported here). Using the z-axis intensity profile and threshold t , the z locations z f , 1 and z f , 2 along the profile are determined at the point in which the profile’s intensity values cross this threshold first ( z f , 1 , rising edge of transition from background to foreground) and last ( z f , 2 , falling edge of transition from foreground to background), respectively.

2) The locations z r , i along the z axis of the current set of n r reference planes used for adaptive imaging are compared to z f , 1 and z f , 2 to determine the distance d r , 1 between the first reference plane ( z r , 1 , lowest value of z ) and z f , 1 and the distance d r , 2 between the last reference plane ( z r , n , highest value of z ) and z f , 2 . If this is the first time point of the time-lapse recording, the distances d r , 1 and d r , 2 are stored for use as reference values at later time points ( d r , 1 , ref and d r , 2 , ref ).

3) The distances d b , 1 and d b , 2 between the foreground/background transition coordinates z f , 1 and z f , 2 and the boundaries z b , 1 and z b , 2 of the current imaging volume along the z -axis are determined. These distances d b , 1 = z f , 1 − z b , 1 and d b , 2 = z b , 2 − z f , 2 represent the size of the background margin at each end of the imaging volume and are subsequently normalized to the size of the imaging volume: f b , 1 = d b , 1 / ( z b , 2 − z b , 1 ) and f b , 2 = d b , 2 / ( z b , 2 − z b , 1 ) . If this is the first time point of the time-lapse recording, these fractions f b , 1 and f b , 2 are stored for use as reference values at later time points ( f b , 1 , ref and f b , 2 , ref ). Irrespective of the initial configuration of the imaging volume, however, the control framework will not allow these fractions to fall below 0.05, to prevent loss of data in the event of rapid changes in specimen location or size. The only exception to this rule is the exhaustion of the physical z -range supported by the stage system of the microscope. In this latter scenario, the control software will suspend all attempts at adjusting the respective end of the specimen but will still try to keep the other end intact.

4) The current location of the center of the specimen along the z -axis is determined as z c = ∑ i z i ⋅ I ( z i ) / ∑ i I ( z i ) , where z i is the location of the image plane i in the imaging volume. If this is the first time point of the time-lapse recording, the location z center is stored for use as a reference value at later time points ( z c , ref ) .

5) The new size of the imaging volume is computed, and, if deemed appropriate, new image planes are added on either side of the current imaging volume. This decision is made by comparing the current values f b , 1 and f b , 2 to the respective stored reference values. If f b , 1 is smaller than f b , 1 , ref , then the size of the imaging volume is expanded by adding new image planes before the first plane to increase the background margin to f b , 1 , ref . Likewise, if f b , 2 is smaller than f b , 2 , ref , then the size of the imaging volume is expanded by adding new image planes after the last plane to increase the background margin to f b , 2 , ref .

6) The current specimen drift z Δ along the z -axis is measured as the distance between z c and z c , ref .

7) The current average spacing s between reference planes used for adaptive imaging is computed, and the need for placement of new reference planes or repositioning of existing reference planes is evaluated as follows:

7a) If the current number of reference planes n r is smaller than the maximum allowed number of reference planes n m a x , the control framework determines whether the distance between the first reference plane located at z r , 1 (respectively, last reference plane located at z r , n ) and the location of the background/foreground boundary z f , 1 (respectively, z f , 2 ) exceeds d b , 1 + s (respectively, d b , 2 + s ). If so, then a new reference plane is added at the location z r , 1 − s (respectively, z r , n + s ). If conditions are met, it is possible that new reference planes are added on both ends of the imaging volume in this step.

7b) If the current number of reference planes n r is equal to or larger than the maximum allowed number of reference planes n m a x , the control framework shifts all reference planes such that the distance between the first reference plane and the volume boundary z b , 1 becomes equal to d r , 1 , ref , the distance between the last reference plane and the volume boundary z b , 2 becomes equal to d r , 2 , ref , and the ratio of distances between any two pairs of reference planes remains unchanged (i.e. the spatial arrangement of reference planes is uniformly rescaled to adapt to the new size of the imaging volume).

7c) The z -coordinates of all image planes and reference planes in the imaging volume are corrected to compensate for the specimen drift z Δ .

To facilitate specimen tracking along the axes perpendicular to the imaging axis ( x - and y -axis), the imaging volume is projected onto the x - y -plane, producing the maximum-intensity image I x , y . We implemented and evaluated several different algorithms for converting the information encoded in I x , y into an estimated movement vector of the specimen: center-of-mass global (COM global), center-of-mass filtered (COM filtered), foreground centered (FG centered), foreground negative edge (FG –edge), foreground positive edge (FG +edge), and orthogonal edge tracking modes.

The COM global algorithm first performs a background subtraction of I x , y and then determines the x - and y -coordinates of the fluorescence center-of-mass. The center-of-mass determined at the first time point serves as a reference position and the specimen is moved after each volume acquisition to compensate for the displacement between the current center-of-mass and this reference position. This is the primary mode of specimen tracking along the x - and y -dimensions used in the mouse live imaging experiments presented in this study.

All other algorithms are incorporated into the imaging workflow via the same automated procedure after each volume acquisition:

1) The image I x , y is background corrected, thresholded according to a manually set threshold level and filtered to retain only 8-connected foreground objects with a minimum pixel count of c min (set to 5,000 when imaging mouse embryos).

2) If the largest connected object is at least three times larger than the second-largest object, all other foreground objects are deleted; otherwise, they are kept. The former situation is typically encountered when an embryo expressing ubiquitous fluorescent labels is surrounded by auto-fluorescent background objects. The latter situation is typically encountered when using sparse fluorescent markers that “fragment” the foreground occupied by the embryo upon thresholding.

3) For FG –edge and FG +edge tracking modes, if more than one connected foreground object remains that meets the criteria defined in step (2), the object closest to the designated edge (see below) is selected as the reference object for further analysis. For FG center and COM filtered tracking modes, if more than one connected foreground object remains, only the largest object is kept for further analysis.

4) The final computation performed with the remaining foreground object(s) is then specific to each mode:

4a) COM filtered: x - and y -coordinates of the fluorescence center-of-mass of the image region in I x , y corresponding to the largest foreground object are determined. Coordinates at the first time point serve as a reference and drift correction is performed by compensating for the displacement between the current COM coordinates and reference COM coordinates.

4b) FG centered: the geometrical center of the largest foreground object is computed and is kept centered within the field-of-view.

4c) FG –edge: the – x or – y boundary of the reference object selected in step (3) is kept at a constant distance from the edge of the field-of-view.

4d) FG +edge: the + x or + y boundary of the reference object selected in step (3) is kept at a constant distance from the edge of the field-of-view.