Throughout the lifetime of living systems, tissue homeostasis and renewal constantly take place to confront challenging conditions, both internally, such as cell aging, and externally, such as infections, so that health can be maintained. Such processes require a tight balance between cell proliferation and differentiation. When homeostasis is disturbed, diseases like cancer can develop. Therefore, understanding the regulation of tissue homeostasis is a key question in biology. However, directly monitoring the dynamics of proliferation and differentiation in live animals remains extremely challenging. Common methods, such as immunostaining and single-cell RNA sequencing, require killing the animal and fixing the cells. Therefore, they can merely provide information in a single time frame. As a result, lineage tracing techniques are introduced, where cells are labeled with a heritable marker that can be detected in progeny after a certain period by fluorescence microscopy or sequencing. Nevertheless, they only produce lineage dynamics indirectly.@en

Organoids have emerged as powerful model systems to study organ development and regeneration at the cellular level. Recently developed microscopy techniques that track individual cells through space and time hold great promise to elucidate the organizational principles of organs and organoids. Applied extensively in the past decade to embryo development and 2D cell cultures, cell tracking can reveal the cellular lineage trees, proliferation rates, and their spatial distributions, while fluorescent markers indicate differentiation events and other cellular processes. Here, we review a number of recent studies that exemplify the power of this approach, and illustrate its potential to organoid research. We will discuss promising future routes, and the key technical challenges that need to be overcome to apply cell tracking techniques to organoid biology.

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Time-lapse microscopy is routinely used to follow cells within organoids, allowing direct study of division and differentiation patterns. There is an increasing interest in cell tracking in organoids, which makes it possible to study their growth and homeostasis at the singlecell level. As tracking these cells by hand is prohibitively time consuming, automation using a computer program is required. Unfortunately, organoids have a high cell density and fast cell movement, which makes automated cell tracking difficult. In this work, a semi-automated cell tracker has been developed. To detect the nuclei, we use a machine learning approach based on a convolutional neural network. To form cell trajectories, we link detections at different time points together using a min-cost flow solver. The tracker raises warnings for situations with likely errors. Rapid changes in nucleus volume and position are reported for manual review, as well as cases where nuclei divide, appear and disappear. When the warning system is adjusted such that virtually error-free lineage trees can be obtained, still less than 2% of all detected nuclei positions are marked for manual analysis. This provides an enormous speed boost over manual cell tracking, while still providing tracking data of the same quality as manual tracking.

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Although the physical properties of chromosomes, including their morphology, mechanics, and dynamics are crucial for their biological function, many basic questions remain unresolved. Here we directly image the circular chromosome in live E. coli with a broadened cell shape. We find that it exhibits a torus topology with, on average, a lower-density origin of replication and an ultrathin flexible string of DNA at the terminus of replication. At the single-cell level, the torus is strikingly heterogeneous, with blob-like Mbp-size domains that undergo major dynamic rearrangements, splitting and merging at a minute timescale. Our data show a domain organization underlying the chromosome structure of E. coli, where MatP proteins induce site-specific persistent domain boundaries at Ori/Ter, while transcription regulators HU and Fis induce weaker transient domain boundaries throughout the genome. These findings provide an architectural basis for the understanding of the dynamic spatial organization of bacterial genomes in live cells.

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Although the spatiotemporal structure of the genome is crucial to its biological function, many basic questions remain unanswered on the morphology and segregation of chromosomes. Here, we experimentally show in Escherichia coli that spatial confinement plays a dominant role in determining both the chromosome size and position. In non-dividing cells with lengths increased to 10 times normal, single chromosomes are observed to expand > 4-fold in size. Chromosomes show pronounced internal dynamics but exhibit a robust positioning where single nucleoids reside robustly at mid-cell, whereas two nucleoids self-organize at 1/4 and 3/4 positions. The cell-size-dependent expansion of the nucleoid is only modestly influenced by deletions of nucleoid-associated proteins, whereas osmotic manipulation experiments reveal a prominent role of molecular crowding. Molecular dynamics simulations with model chromosomes and crowders recapitulate the observed phenomena and highlight the role of entropic effects caused by confinement and molecular crowding in the spatial organization of the chromosome. Imaging chromosomes in E. coli within a broad length range, Wu et al. observe that chromosome size and position strongly depend on cell size. They provide evidence that this arises from a confinement-modulated entropic repulsion between chromosome and cytosolic crowders, highlighting the importance of confinement effects in cellular organization.

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