Assessing fertilized human embryos is crucial for in vitro fertilization, a task being revolutionized by artificial intelligence. Existing models used for embryo quality assessment and ploidy detection could be significantly improved by effectively utilizing time-lapse imaging to identify critical developmental time points for maximizing prediction accuracy. Addressing this, we develop and compare various embryo ploidy status prediction models across distinct embryo development stages. We present BELA, a state-of-the-art ploidy prediction model that surpasses previous image- and video-based models without necessitating input from embryologists. BELA uses multitask learning to predict quality scores that are thereafter used to predict ploidy status. By achieving an area under the receiver operating characteristic curve of 0.76 for discriminating between euploidy and aneuploidy embryos on the Weill Cornell dataset, BELA matches the performance of models trained on embryologists\' manual scores. While not a replacement for preimplantation genetic testing for aneuploidy, BELA exemplifies how such models can streamline the embryo evaluation process.

Recent advances in imaging suggested that spatial organization of hematopoietic cells in their bone marrow microenvironment (niche) regulates cell expansion, governing progression, and leukemic transformation of hematological clonal disorders. However, our ability to interrogate the niche in pre-malignant conditions has been limited, as standard murine models of these diseases rely largely on transplantation of the mutant clones into conditioned mice where the marrow microenvironment is compromised. Here, we leveraged live-animal microscopy and ultralow dose whole body or focal irradiation to capture single cells and early expansion of benign/pre-malignant clones in the functionally preserved microenvironment. 0.5 Gy whole body irradiation (WBI) allowed steady engraftment of cells beyond 30 weeks compared to non-conditioned controls. In-vivo tracking and functional analyses of the microenvironment showed no change in vessel integrity, cell viability, and HSC-supportive functions of the stromal cells, suggesting minimal inflammation after the radiation insult. The approach enabled in vivo imaging of Tet2+/- and its healthy counterpart, showing preferential localization within a shared microenvironment while forming discrete micro-niches. Notably, stationary association with the niche only occurred in a subset of cells and would not be identified without live imaging. This strategy may be broadly applied to study clonal disorders in a spatial context.

In female eutherian mammal development, X-chromosome inactivation (XCI) of one of the two X chromosomes is initiated early. Understanding the relationship between the initiation of XCI and cell fate is critical for understanding early female development and requires a system that can monitor XCI in single living cells. Traditional embryonic stem cells (ESCs) used for XCI studies often lose X chromosomes spontaneously during culture and differentiation, making accurate monitoring difficult. Additionally, most XCI assessment methods necessitate cell disruption, hindering cell fate tracking. We developed the Momiji (version 2) ESC line to address these difficulties, enabling real-time monitoring of X-chromosome activity via fluorescence. We inserted green and red fluorescent reporter genes and neomycin and puromycin resistance genes into the two X chromosomes of PGK12.1 ESCs, creating a female ESC line that retains two X chromosomes more faithfully during differentiation. Momiji (version 2) ESCs exhibit a more stable XX karyotype than other ESC lines, including the parental PGK12.1 line. This new tool offers valuable insights into the relationship between XCI and cell fate, improving our understanding of early female development.

Large-scale drug discovery and repurposing is challenging. Identifying the mechanism of action (MOA) is crucial, yet current approaches are costly and low-throughput. Here we present an approach for MOA identification by profiling changes in mitochondrial phenotypes. By temporally imaging mitochondrial morphology and membrane potential, we established a pipeline for monitoring time-resolved mitochondrial images, resulting in a dataset comprising 570,096 single-cell images of cells exposed to 1,068 United States Food and Drug Administration-approved drugs. A deep learning model named MitoReID, using a re-identification (ReID) framework and an Inflated 3D ResNet backbone, was developed. It achieved 76.32% Rank-1 and 65.92% mean average precision on the testing set and successfully identified the MOAs for six untrained drugs on the basis of mitochondrial phenotype. Furthermore, MitoReID identified cyclooxygenase-2 inhibition as the MOA of the natural compound epicatechin in tea, which was successfully validated in vitro. Our approach thus provides an automated and cost-effective alternative for target identification that could accelerate large-scale drug discovery and repurposing.

Amoeboid cell motility is fundamental for a multitude of biological processes such as embryogenesis, immune responses, wound healing, and cancer metastasis. It is characterized by specific cell shape changes: the extension and retraction of membrane protrusions, known as pseudopodia. A common approach to investigate the mechanisms underlying this type of cell motility is to study phenotypic differences in the locomotion of mutant cell lines. To characterize such differences, methods are required to quantify the contour dynamics of migrating cells. AmoePy is a Python-based software package that provides tools for cell segmentation, contour detection as well as analyzing and simulating contour dynamics. First, a digital representation of the cell contour as a chain of nodes is extracted from each frame of a time-lapse microscopy recording of a moving cell. Then, the dynamics of these nodes-referred to as virtual markers-are tracked as the cell contour evolves over time. From these data, various quantities can be calculated that characterize the contour dynamics, such as the displacement of the virtual markers or the local stretching rate of the marker chain. Their dynamics is typically visualized in space-time plots, the so-called kymographs, where the temporal evolution is displayed for the different locations along the cell contour. Using AmoePy, you can straightforwardly create kymograph plots and videos from stacks of experimental bright-field or fluorescent images of motile cells. A hands-on guide on how to install and use AmoePy is provided in this chapter.

Immune responses rely on efficient and coordinated migration of immune cells to the site of infection or injury. To reach the site of immunological threat often requires long-range navigation of immune cells through complex tissue and vascular networks. Chemotaxis, cell migration steered by gradients of cell-attractive chemicals that bind sensory receptors, is central to this response. Chemoattractant receptors mostly belong to the G-protein-coupled receptor (GPCR) family, but the way attractant-receptor signaling directs cell migration is not fully understood. Direct-viewing chemotaxis chambers combined with time-lapse microscopy give a powerful tool to study the dynamic details of cells\' responses to different attractant landscapes. Here, we describe the application of one such chamber (the Dunn chamber) to study bone marrow-derived macrophage chemotaxis to gradients of complement C5a.

The cell intrinsic mechanisms directing peripheral nerve regeneration have remained largely understudied, thus limiting our understanding of these processes and constraining the advancement of novel clinical therapeutics. The use of primary adult rat dorsal root ganglion (DRG) neurons cultured in vitro is well established. Despite this, these cells can be challenging to culture and have so far not been amenable to robust transfection or live-cell imaging. The ability to transfect these cells with fluorescent plasmid constructs to label subcellular structures, combined with high resolution time-lapse imaging has the potential to provide invaluable insight into how peripheral neurons coordinate their regenerative response, and which specific cellular structures are involved in this process. Here we describe a protocol that facilitates transfection and subsequent live-imaging of adult rat DRG neurons.

Actin flow refers to the motion of the F-actin cytoskeleton and has been observed in many different cell types, especially in motile cells including neuronal growth cones. The direction of the actin flow is generally retrograde from the periphery toward the center of the cell. Actin flow can be harnessed for forward movement of the cell through substrate-cytoskeletal coupling; thus, a key function of actin flow is in cell locomotion. In this chapter, we illustrate three different methods of quantifying retrograde F-actin flow in growth cones derived from cultured Aplysia bag cell neurons. These methods include tracking the movement of surface marker beads as well as kymograph analysis of time-lapse sequences acquired by differential interference contrast (DIC) imaging or fluorescent speckle microscopy (FSM). Due to their large size, Aplysia neuronal growth cones are uniquely suited for these methods; however, they can also be applied to any other growth cones with clear F-actin-rich peripheral domains.

The study of microtubules arrangements and dynamics during axon outgrowth and pathfinding has gained scientific interest during the last decade, and numerous technical resources for its visualization and analysis have been implemented. In this chapter, we describe the cell culture protocols of embryonic cortical and retinal neurons, the methods for transfecting them with fluorescent reporters of microtubule polymerization, and the procedures for time-lapse imaging and quantification in order to study microtubule dynamics during axon morphogenesis.

The use of time-lapse live imaging enables us to track the dynamic changes in neurites during their formation. Ex vivo live imaging with acute brain slices provides a more physiological environment than cultured cells. To accomplish this, a certain method of labeling is necessary to visualize and identify neurite morphology. To understand the dynamics of neurite structure at early stages of neurite formation, we describe in this chapter ex vivo live imaging using a confocal microscope at P0 in combination with in utero electroporation (IUE).