Tissue clearing and imaging approaches for in toto analysis of the reproductive system†

New microscopy techniques in combination with tissue clearing protocols and emerging analytical approaches have presented researchers with the tools to understand dynamic biological processes in a three-dimensional context. This paves the road for the exploration of new research questions in reproductive biology, for which previous techniques have provided only approximate resolution. These new methodologies now allow for contextualized analysis of far-larger volumes than was previously possible. Tissue optical clearing and three-dimensional imaging techniques posit the bridging of molecular mechanisms, macroscopic morphogenic development, and maintenance of reproductive function into one cohesive and comprehensive understanding of the biology of the reproductive system. In this review, we present a survey of the various tissue clearing techniques and imaging systems, as they have been applied to the developing and adult reproductive system. We provide an overview of tools available for analysis of experimental data, giving particular attention to the emergence of artificial intelligence-assisted methods and their applicability to image analysis. We conclude with an evaluation of how novel image analysis approaches that have been applied to other organ systems could be incorporated into future experimental evaluation of reproductive biology.

A β-catenin chromobody-based probe highlights endothelial maturation during vascular morphogenesis in vivo

Visualization of protein dynamics is a crucial step in understanding cellular processes. Chromobodies, fluorescently labelled single-domain antibodies, have emerged as versatile probes for live cell imaging of endogenous proteins. However, how these chromobodies behave in vivo and how accurately they monitor tissue changes remain poorly explored. Here, we generated an endothelial-specific β-catenin chromobody-derived probe and analyzed its expression pattern during cardiovascular development in zebrafish. Using high-resolution confocal imaging, we show that the chromobody signal correlates with the localization of β-catenin in the nucleus and at cell-cell junctions, and thereby can be used to assess endothelial maturation. Loss of Cadherin 5 strongly affects the localization of the chromobody at the cell membrane, confirming the cadherin-based adherens junction role of β-catenin. Furthermore, using a genetic model to block blood flow, we observed that cell junctions are compromised in most endothelial cells but not in the endocardium, highlighting the heterogeneous response of the endothelium to the lack of blood flow. Overall, our data further expand the use of chromobodies for in vivo applications and illustrate their potential to monitor tissue morphogenesis at high resolution.

OoCount: A Machine-Learning Based Approach to Mouse Ovarian Follicle Counting and Classification

The number and distribution of ovarian follicles in each growth stage provides a reliable readout of ovarian health and function. Leveraging techniques for three-dimensional (3D) imaging of ovaries in toto has the potential to uncover total, accurate ovarian follicle counts. However, because of the size and holistic nature of these images, counting oocytes is time consuming and difficult. The advent of deep-learning algorithms has allowed for the rapid development of ultra-fast, automated methods to analyze microscopy images. In recent years, these pipelines have become more user-friendly and accessible to non-specialists. We used these tools to create OoCount, a high-throughput, open-source method for automatic oocyte segmentation and classification from fluorescent 3D microscopy images of whole mouse ovaries using a deep-learning convolutional neural network (CNN) based approach. We developed a fast tissue-clearing and spinning disk confocal-based imaging protocol to obtain 3D images of whole mount perinatal and adult mouse ovaries. Fluorescently labeled oocytes from 3D images of ovaries were manually annotated in Napari to develop a machine learning training dataset. This dataset was used to retrain StarDist using a CNN within DL4MicEverywhere to automatically label all oocytes in the ovary. In a second phase, we utilize Accelerated Pixel and Object Classification, a Napari plugin, to classify labeled oocytes and sort them into growth stages. Here, we provide an end-to-end protocol for producing high-quality 3D images of the perinatal and adult mouse ovary, obtaining follicle counts and staging. We also demonstrate how to customize OoCount to fit images produced in any lab. Using OoCount, we can obtain accurate counts of oocytes in each growth stage in the perinatal and adult ovary, improving our ability to study ovarian function and fertility.

Summary sentence

This protocol introduces OoCount, a high-throughput, open-source method for automatic oocyte segmentation and classification from fluorescent 3D microscopy images of whole mouse ovaries using a machine learning-based approach.

HCR spectral imaging: 10-plex, quantitative, high-resolution RNA and protein imaging in highly autofluorescent samples

Signal amplification based on the mechanism of hybridization chain reaction (HCR) provides a unified framework for multiplex, quantitative, high-resolution imaging of RNA and protein targets in highly autofluorescent samples. With conventional bandpass imaging, multiplexing is typically limited to four or five targets owing to the difficulty in separating signals generated by fluorophores with overlapping spectra. Spectral imaging has offered the conceptual promise of higher levels of multiplexing, but it has been challenging to realize this potential in highly autofluorescent samples, including whole-mount vertebrate embryos. Here, we demonstrate robust HCR spectral imaging with linear unmixing, enabling simultaneous imaging of ten RNA and/or protein targets in whole-mount zebrafish embryos and mouse brain sections. Further, we demonstrate that the amplified and unmixed signal in each of the ten channels is quantitative, enabling accurate and precise relative quantitation of RNA and/or protein targets with subcellular resolution, and RNA absolute quantitation with single-molecule resolution, in the anatomical context of highly autofluorescent samples.

Accurate staging of chick embryonic tissues via deep learning of salient features

Recent work shows that the developmental potential of progenitor cells in the HH10 chick brain changes rapidly, accompanied by subtle changes in morphology. This demands increased temporal resolution for studies of the brain at this stage, necessitating precise and unbiased staging. Here, we investigated whether we could train a deep convolutional neural network to sub-stage HH10 chick brains using a small dataset of 151 expertly labelled images. By augmenting our images with biologically informed transformations and data-driven preprocessing steps, we successfully trained a classifier to sub-stage HH10 brains to 87.1% test accuracy. To determine whether our classifier could be generally applied, we re-trained it using images (269) of randomised control and experimental chick wings, and obtained similarly high test accuracy (86.1%). Saliency analyses revealed that biologically relevant features are used for classification. Our strategy enables training of image classifiers for various applications in developmental biology with limited microscopy data.

HCR spectral imaging: 10-plex, quantitative, high-resolution RNA and protein imaging in highly autofluorescent samples

Signal amplification based on the mechanism of hybridization chain reaction (HCR) provides a unified framework for multiplex, quantitative, high-resolution imaging of RNA and protein targets in highly autofluorescent samples. With conventional bandpass imaging, multiplexing is typically limited to four or five targets due to the difficulty in separating signals generated by fluorophores with overlapping spectra. Spectral imaging has offered the conceptual promise of higher levels of multiplexing, but it has been challenging to realize this potential in highly autofluorescent samples including whole-mount vertebrate embryos. Here, we demonstrate robust HCR spectral imaging with linear unmixing, enabling simultaneous imaging of 10 RNA and/or protein targets in whole-mount zebrafish embryos and mouse brain sections. Further, we demonstrate that the amplified and unmixed signal in each of 10 channels is quantitative, enabling accurate and precise relative quantitation of RNA and/or protein targets with subcellular resolution, and RNA absolute quantitation with single-molecule resolution, in the anatomical context of highly autofluorescent samples.

SUMMARY

Spectral imaging with signal amplification based on the mechanism of hybridization chain reaction enables robust 10-plex, quantitative, high-resolution imaging of RNA and protein targets in whole-mount vertebrate embryos and brain sections.

Automatic detector synchronization for long-term imaging using confocal light-sheet microscopy

Light sheet fluorescence microscopy (LSFM) is an important tool in developmental biology. In this microscopy technique confocal line detection is often used to improve image contrast. To this end, the image of the illuminating scanned focused laser beam must be mapped onto a line detector. This is not trivial for long-term observations, since the spatial position of the laser beam and therefore its image on the detector may drift. The problem is aggravated in two-photon excitation LSFM, since pulsed laser light sources exhibit a lower laser beam pointing stability than continuous wave lasers. Here, we present a procedure for automatic synchronization between the excitation laser and detector, which does not require any additional hardware components and can therefore easily be integrated into existing systems. Since the recorded images are affected by noise, a specific, noise-tolerant focus metric was developed for calculating the relative displacement, which also allows for autofocusing in the detection direction. Furthermore, we developed an image analysis approach to determine a possible tilt of the excitation laser, which is executed in parallel to the autofocusing and enables the measurement of three solid angles. This allows to automatically correct for the tilting during a measurement. We demonstrated our approach by the observation of the migration of oligodendrocyte precursor cells in two-day-old fluorescent Tg(olig2:eGFP) reporter zebrafish larvae over a time span of more than 20 hours.

An adaptive microscope for the imaging of biological surfaces

Scanning fluorescence microscopes are now able to image large biological samples at high spatial and temporal resolution. This comes at the expense of an increased light dose which is detrimental to fluorophore stability and cell physiology. To highly reduce the light dose, we designed an adaptive scanning fluorescence microscope with a scanning scheme optimized for the unsupervised imaging of cell sheets, which underly the shape of many embryos and organs. The surface of the tissue is first delineated from the acquisition of a very small subset (~0.1%) of sample space, using a robust estimation strategy. Two alternative scanning strategies are then proposed to image the tissue with an improved photon budget, without loss in resolution. The first strategy consists in scanning only a thin shell around the estimated surface of interest, allowing high reduction of light dose when the tissue is curved. The second strategy applies when structures of interest lie at the cell periphery (e.g. adherens junctions). An iterative approach is then used to propagate scanning along cell contours. We demonstrate the benefit of our approach imaging live epithelia from Drosophila melanogaster. On the examples shown, both approaches yield more than a 20-fold reduction in light dose -and up to more than 80-fold- compared to a full scan of the volume. These smart-scanning strategies can be easily implemented on most scanning fluorescent imaging modality. The dramatic reduction in light exposure of the sample should allow prolonged imaging of the live processes under investigation.

Multimodal high-resolution embryonic imaging with light sheet fluorescence microscopy and optical coherence tomography

A high-resolution imaging system combining optical coherence tomography (OCT) and light sheet fluorescence microscopy (LSFM) was developed. LSFM confined the excitation to only the focal plane, removing the out of plane fluorescence. This enabled imaging a murine embryo with higher speed and specificity than traditional fluorescence microscopy. OCT gives information about the structure of the embryo from the same plane illuminated by LSFM. The co-planar OCT and LSFM instrument was capable of performing co-registered functional and structural imaging of mouse embryos simultaneously.

Cytoskeletal control of early mammalian development

The cytoskeleton - comprising actin filaments, microtubules and intermediate filaments - serves instructive roles in regulating cell function and behaviour during development. However, a key challenge in cell and developmental biology is to dissect how these different structures function and interact in vivo to build complex tissues, with the ultimate aim to understand these processes in a mammalian organism. The preimplantation mouse embryo has emerged as a primary model system for tackling this challenge. Not only does the mouse embryo share many morphological similarities with the human embryo during its initial stages of life, it also permits the combination of genetic manipulations with live-imaging approaches to study cytoskeletal dynamics directly within an intact embryonic system. These advantages have led to the discovery of novel cytoskeletal structures and mechanisms controlling lineage specification, cell-cell communication and the establishment of the first forms of tissue architecture during development. Here we highlight the diverse organization and functions of each of the three cytoskeletal filaments during the key events that shape the early mammalian embryo, and discuss how they work together to perform key developmental tasks, including cell fate specification and morphogenesis of the blastocyst. Collectively, these findings are unveiling a new picture of how cells in the early embryo dynamically remodel their cytoskeleton with unique spatial and temporal precision to drive developmental processes in the rapidly changing in vivo environment.

Fluorescent proteins for in vivo imaging, where's the biliverdin?

Noninvasive fluorescent imaging requires far-red and near-infrared fluorescent proteins for deeper imaging. Near-infrared light penetrates biological tissue with blood vessels due to low absorbance, scattering, and reflection of light and has a greater signal-to-noise due to less autofluorescence. Far-red and near-infrared fluorescent proteins absorb light >600 nm to expand the color palette for imaging multiple biosensors and noninvasive in vivo imaging. The ideal fluorescent proteins are bright, photobleach minimally, express well in the desired cells, do not oligomerize, and generate or incorporate exogenous fluorophores efficiently. Coral-derived red fluorescent proteins require oxygen for fluorophore formation and release two hydrogen peroxide molecules. New fluorescent proteins based on phytochrome and phycobiliproteins use biliverdin IXα as fluorophores, do not require oxygen for maturation to image anaerobic organisms and tumor core, and do not generate hydrogen peroxide. The small Ultra-Red Fluorescent Protein (smURFP) was evolved from a cyanobacterial phycobiliprotein to covalently attach biliverdin as an exogenous fluorophore. The small Ultra-Red Fluorescent Protein is biophysically as bright as the enhanced green fluorescent protein, is exceptionally photostable, used for biosensor development, and visible in living mice. Novel applications of smURFP include in vitro protein diagnostics with attomolar (10-18 M) sensitivity, encapsulation in viral particles, and fluorescent protein nanoparticles. However, the availability of biliverdin limits the fluorescence of biliverdin-attaching fluorescent proteins; hence, extra biliverdin is needed to enhance brightness. New methods for improved biliverdin bioavailability are necessary to develop improved bright far-red and near-infrared fluorescent proteins for noninvasive imaging in vivo.

A versatile, multi-laser twin-microscope system for light-sheet imaging

Light-sheet microscopy offers faster imaging and reduced phototoxicity in comparison to conventional point-scanning microscopy, making it a preferred technique for imaging biological dynamics for durations of hours or days. Such extended imaging sessions pose a challenge, as it reduces the number of specimens that can be imaged in a given day. Here, we present a versatile light-sheet imaging instrument that combines two independently controlled microscope-twins, built so that they can share an ultrafast near-infrared laser and a bank of continuous-wave visible lasers, increasing the throughput and decreasing the cost. To permit a wide variety of specimens to be imaged, each microscope-twin provides flexible imaging parameters, including (i) operation in one-photon and/or two-photon excitation modes, (ii) delivery of one to three light-sheets via a trio of orthogonal excitation arms, (iii) sub-micron to micron imaging resolution, (iv) multicolor compatibility, and (v) upright (with provision for inverted) detection geometry. We offer a detailed description of the twin-microscope design to aid instrument builders who wish to construct and use similar systems. We demonstrate the instrument's versatility for biological investigation by performing fast imaging of the beating heart in an intact zebrafish embryo, deep imaging of thick patient-derived tumor organoids, and gentle whole-brain imaging of neural activity in behaving larval zebrafish.