The efficient extraction of image data from curved tissue sheets embedded in volumetric imaging data remains a serious and unsolved problem in quantitative studies of embryogenesis. Here we present DeepProjection (DP), a trainable projection algorithm based on deep learning. This algorithm is trained on user-generated training data to locally classify the 3D stack content and rapidly and robustly predict binary masks containing the target content, e.g., tissue boundaries, while masking highly fluorescent out-of-plane artifacts. A projection of the masked 3D stack then yields background-free 2D images with undistorted fluorescence intensity values. The binary masks can further be applied to other fluorescent channels or to extract the local tissue curvature. DP is designed as a first processing step than can be followed, for example, by segmentation to track cell fate. We apply DP to follow the dynamic movements of 2D-tissue sheets during dorsal closure in Drosophila embryos and of the periderm layer in the elongating Danio embryo. DeepProjection is available as fully documented Python package.

Preparation and imaging of Drosophila embryos

Cell junctions were labeled with either DE-cadherin-GFP or DE-cadherin-mTomato (labeling Drosophila E-cadherin, which is concentrated in cell-cell junctions), both knock-in lines under control of the endogenous promoter (Huang et al., 2009). F-actin was labeled with the GFP-moesin actin binding domain, expressed under the control of the spaghetti squash promoter in the sGMCA line (Kiehart et al., 2000). All stocks were maintained at room temperature or 25°C on standard cornmeal/molasses fly food or in embryo collection cages with a grape juice agar plate and yeast paste. Embryos were collected either 2–4 hours after egg lays and aged overnight at 16°C, or from overnight egg lays at 25°C. To remove the chorion, embryos were incubated in a 50% bleach solution for 1.25 min and then rinsed extensively with deionized water. Pre-dorsal closure stage embryos were selected using a reflected-light dissecting microscope. Embryos were prepared for imaging as described previously (Kiehart et al., 1994). Images were acquired using Micro-Manager 2.0 software (Open Imaging, San Francisco, CA) to control a Zeiss Axiovert 200M microscope (Carl Zeiss, Thornwood, NY) equipped with a Yokogawa CSU-W1 spinning disk confocal head (Solamere Technology Group, Salt Lake City, UT), a Hamamatsu Orca Fusion BT camera (Hamamatsu, Japan), and a Zeiss 40X LD LCI Plan-Apochromat 1.2NA multi-immersion objective (glycerin). Due to the curvature of the embryo, we imaged multiple z planes for each embryo at each time point to view the dorsal opening. We recorded 8 z-slice stacks with 1 µm step size for single color, and 14 z-slice stacks with 0.5 µm step size for dual-color movies. Stacks were acquired every 15 s throughout the duration of closure with a 100 ms exposure per slice for GFP and a 150 ms exposure per slice for mTomato.

Zebrafish husbandry and sample preparation for live imaging

Zebrafish of the Ekkwill strain were maintained between 26 and 28.5 °C with a 14:10 hour light:dark cycle. Fish between 3-6 months were used for experiments. Transgenic krt4:lyn-EGFP fish were described previously (Lee et al., 2014). Male and female fish were set up for mating in tanks with dividers. The dividers were removed in the morning for timed mating. Embryos were collected in E3 medium and screened at 1 dpf for expression of GFP in the periderm (krt4-lynGFP). The positive embryos were transferred to a dish with E3 medium and tricaine (Sigma E10521-50G) at 0.01% concentration. The embryos were dechorionated with forceps and mounted in fluorinated ethylene propylene (FEP) tubes according to published protocols (Weber et al., 2014). The FEP tubes were coated with 3% methlycellulose and embryos were mounted in 0.1% agarose with 0.01% tricaine to immobilize them during imaging. The tube was then placed in a 60 mm culture dish with an agarose bed, held in place with 1% agarose and immersed in E3 medium. Images were acquired with LASX software on a Leica SP8 confocal microscope using an HC Fluotar L 25X/0.95NA W VISIR water-immersion objective at 0.75 or 1X zoom. Image stacks with 40-60 slices were acquired every 15 minutes with a z-step size of 2 µm. Work with zebrafish was approved by the Institutional Animal Care and Use Committee at Duke University.

The DeepProjection algorithm is available on GitHub (https://github.com/danihae/DeepProjection) and PyPI (https://pypi.org/project/deepprojection/), with documentation and a Jupyter notebook with detailed instructions.