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Endogenous AJAP1 associates with the cytoskeleton and attenuates angiogenesis in endothelial cells
(2017)
The adherens junction associated protein 1 (AJAP1, aka shrew-1) is presumably a type-I transmembrane protein localizing and interacting with the E-cadherin-catenin complex. In various tumors, AJAP1 expression is reduced or lost, including hepatocellular and esophageal squamous cell carcinoma, and glial-derived tumors. The aberrant expression of AJAP1 is associated with alterations in cell migration, invasion, increased tumor growth, and tumor vascularization, suggesting AJAP1 as a putative tumor suppressor. We show that AJAP1 attenuates sprouting angiogenesis by reducing endothelial migration and invasion capacities. Further, we show for the first time that endogenous AJAP1 is associated with the microtubule cytoskeleton. This linkage is independent from cell confluency and stable during angiogenic sprouting in vitro. Our work suggests that AJAP1 is a putative negative regulator of angiogenesis, reducing cell migration and invasion by interfering with the microtubule network. Based on our results and those of other authors, we suggest AJAP1 as a novel tumor suppressor and diagnostic marker.
In three-dimensional light microscopy, the heterogeneity of the optical density in a specimen ultimately limits the achievable penetration depth and hence the three-dimensional resolution. The most direct approach to reduce aberrations, improve the contrast and achieve an optimal resolution is to minimise the impact of changes of the refractive index along an optical path. Many implementations of light sheet fluorescence microscopy operate with a large chamber filled with an aqueous immersion medium and a further inner container with the specimen embedded in a possibly entirely different non-aqueous medium. In order to minimise the impact of the latter on the optical quality of the images, we use multi-facetted cuvettes fabricated from vacuum-formed ultra-thin fluorocarbon (FEP) foils. The ultra-thin FEP-foil cuvettes have a wall thickness of about 10–12 µm. They are impermeable to liquids, but not to gases, inert, durable, mechanically stable and flexible. Importantly, the usually fragile specimen can remain in the same cuvette from seeding to fixation, clearing and observation, without the need to remove or remount it during any of these steps. We confirm the improved imaging performance of ultra-thin FEP-foil cuvettes with excellent quality images of whole organs such us mouse oocytes, of thick tissue sections from mouse brain and kidney as well as of dense pancreas and liver organoid clusters. Our ultra-thin FEP-foil cuvettes outperform many other sample-mounting techniques in terms of a full separation of the specimen from the immersion medium, compatibility with aqueous and organic clearing media, quick specimen mounting without hydrogel embedding and their applicability for multiple-view imaging and automated image segmentation. Additionally, we show that ultra-thin FEP foil cuvettes are suitable for seeding and growing organoids over a time period of at least ten days. The new cuvettes allow the fixation and staining of specimens inside the holder, preserving the delicate morphology of e.g. fragile, mono-layered three-dimensional organoids.
During gastrulation in the mouse embryo, dynamic cell movements including epiblast invagination and mesodermal layer expansion lead to the establishment of the three-layered body plan. The precise details of these movements, however, are sometimes elusive, because of the limitations in live imaging. To overcome this problem, we developed techniques to enable observation of living mouse embryos with digital scanned light sheet microscope (DSLM). The achieved deep and high time-resolution images of GFP-expressing nuclei and following 3D tracking analysis revealed the following findings: (i) Interkinetic nuclear migration (INM) occurs in the epiblast at embryonic day (E)6 and 6.5. (ii) INM-like migration occurs in the E5.5 embryo, when the epiblast is a monolayer and not yet pseudostratified. (iii) Primary driving force for INM at E6.5 is not pressure from neighboring nuclei. (iv) Mesodermal cells migrate not as a sheet but as individual cells without coordination.
Shrew-1, also called AJAP1, is a transmembrane protein associated with E-cadherin-mediated adherence junctions and a putative tumor suppressor. Apart from its interaction with β-catenin and involvement in E-cadherin internalization, little structure or function information exists. Here we explored shrew-1 expression during postnatal differentiation of mammary gland as a model system. Immunohistological analyses with antibodies against either the extracellular or the cytoplasmic domains of shrew-1 consistently revealed the expression of full-length shrew-1 in myoepithelial cells, but only part of it in luminal cells. While shrew-1 localization remained unaltered in myoepithelial cells, nuclear localization occurred in luminal cells during lactation. Based on these observations, we identified two unknown shrew-1 transcript variants encoding N-terminally truncated proteins. The smallest shrew-1 protein lacks the extracellular domain and is most likely the only variant present in luminal cells. RNA analyses of human tissues confirmed that the novel transcript variants of shrew-1 exist in vivo and exhibit a differential tissue expression profile. We conclude that our findings are essential for the understanding and interpretation of future functional and interactome analyses of shrew-1 variants.
Cell fate clusters in ICM organoids arise from cell fate heredity and division: a modelling approach
(2020)
During the mammalian preimplantation phase, cells undergo two subsequent cell fate decisions. During the first decision, the trophectoderm and the inner cell mass are formed. Subsequently, the inner cell mass segregates into the epiblast and the primitive endoderm. Inner cell mass organoids represent an experimental model system, mimicking the second cell fate decision. It has been shown that cells of the same fate tend to cluster stronger than expected for random cell fate decisions. Three major processes are hypothesised to contribute to the cell fate arrangements: (1) chemical signalling; (2) cell sorting; and (3) cell proliferation. In order to quantify the influence of cell proliferation on the observed cell lineage type clustering, we developed an agent-based model accounting for mechanical cell–cell interaction, i.e. adhesion and repulsion, cell division, stochastic cell fate decision and cell fate heredity. The model supports the hypothesis that initial cell fate acquisition is a stochastically driven process, taking place in the early development of inner cell mass organoids. Further, we show that the observed neighbourhood structures can emerge solely due to cell fate heredity during cell division.
Background: Due to the large amount of data produced by advanced microscopy, automated image analysis is crucial in modern biology. Most applications require reliable cell nuclei segmentation. However, in many biological specimens cell nuclei are densely packed and appear to touch one another in the images. Therefore, a major difficulty of three-dimensional cell nuclei segmentation is the decomposition of cell nuclei that apparently touch each other. Current methods are highly adapted to a certain biological specimen or a specific microscope. They do not ensure similarly accurate segmentation performance, i.e. their robustness for different datasets is not guaranteed. Hence, these methods require elaborate adjustments to each dataset.
Results: We present an advanced three-dimensional cell nuclei segmentation algorithm that is accurate and robust. Our approach combines local adaptive pre-processing with decomposition based on Lines-of-Sight (LoS) to separate apparently touching cell nuclei into approximately convex parts. We demonstrate the superior performance of our algorithm using data from different specimens recorded with different microscopes. The three-dimensional images were recorded with confocal and light sheet-based fluorescence microscopes. The specimens are an early mouse embryo and two different cellular spheroids. We compared the segmentation accuracy of our algorithm with ground truth data for the test images and results from state-of-the-art methods. The analysis shows that our method is accurate throughout all test datasets (mean F-measure: 91%) whereas the other methods each failed for at least one dataset (F-measure≤69%). Furthermore, nuclei volume measurements are improved for LoS decomposition. The state-of-the-art methods required laborious adjustments of parameter values to achieve these results. Our LoS algorithm did not require parameter value adjustments. The accurate performance was achieved with one fixed set of parameter values.
Conclusion: We developed a novel and fully automated three-dimensional cell nuclei segmentation method incorporating LoS decomposition. LoS are easily accessible features that ensure correct splitting of apparently touching cell nuclei independent of their shape, size or intensity. Our method showed superior performance compared to state-of-the-art methods, performing accurately for a variety of test images. Hence, our LoS approach can be readily applied to quantitative evaluation in drug testing, developmental and cell biology.
Background: The technical development of imaging techniques in life sciences has enabled the three-dimensional recording of living samples at increasing temporal resolutions. Dynamic 3D data sets of developing organisms allow for time-resolved quantitative analyses of morphogenetic changes in three dimensions, but require efficient and automatable analysis pipelines to tackle the resulting Terabytes of image data. Particle image velocimetry (PIV) is a robust and segmentation-free technique that is suitable for quantifying collective cellular migration on data sets with different labeling schemes. This paper presents the implementation of an efficient 3D PIV package using the Julia programming language—quickPIV. Our software is focused on optimizing CPU performance and ensuring the robustness of the PIV analyses on biological data.
Results: QuickPIV is three times faster than the Python implementation hosted in openPIV, both in 2D and 3D. Our software is also faster than the fastest 2D PIV package in openPIV, written in C++. The accuracy evaluation of our software on synthetic data agrees with the expected accuracies described in the literature. Additionally, by applying quickPIV to three data sets of the embryogenesis of Tribolium castaneum, we obtained vector fields that recapitulate the migration movements of gastrulation, both in nuclear and actin-labeled embryos. We show normalized squared error cross-correlation to be especially accurate in detecting translations in non-segmentable biological image data.
Conclusions: The presented software addresses the need for a fast and open-source 3D PIV package in biological research. Currently, quickPIV offers efficient 2D and 3D PIV analyses featuring zero-normalized and normalized squared error cross-correlations, sub-pixel/voxel approximation, and multi-pass. Post-processing options include filtering and averaging of the resulting vector fields, extraction of velocity, divergence and collectiveness maps, simulation of pseudo-trajectories, and unit conversion. In addition, our software includes functions to visualize the 3D vector fields in Paraview.
Three-dimensional multicellular aggregates such as spheroids provide reliable in vitro substitutes for tissues. Quantitative characterization of spheroids at the cellular level is fundamental. We present the first pipeline that provides three-dimensional, high-quality images of intact spheroids at cellular resolution and a comprehensive image analysis that completes traditional image segmentation by algorithms from other fields. The pipeline combines light sheet-based fluorescence microscopy of optically cleared spheroids with automated nuclei segmentation (F score: 0.88) and concepts from graph analysis and computational topology. Incorporating cell graphs and alpha shapes provided more than 30 features of individual nuclei, the cellular neighborhood and the spheroid morphology. The application of our pipeline to a set of breast carcinoma spheroids revealed two concentric layers of different cell density for more than 30,000 cells. The thickness of the outer cell layer depends on a spheroid’s size and varies between 50% and 75% of its radius. In differently-sized spheroids, we detected patches of different cell densities ranging from 5 × 105 to 1 × 106 cells/mm3. Since cell density affects cell behavior in tissues, structural heterogeneities need to be incorporated into existing models. Our image analysis pipeline provides a multiscale approach to obtain the relevant data for a system-level understanding of tissue architecture.
"Mehr Licht!" – so lauteten, glaubt man seinem Arzt Carl Vogel, die letzten Worte des größten deutschen Dichters und Denkers Johann Wolfgang Goethe. Aus der Sicht der Fluoreszenzmikroskopie ist das kein guter Grundsatz. Die Kernidee der Lichtscheiben-Fluoreszenzmikroskopie (LSFM) liegt in der Macht der dunklen Seite. Anders gesagt: Sie folgt dem Prinzip, dass weniger manchmal viel mehr sein kann. Die schonende Beleuchtung empfindlicher Proben bei der LSFM birgt großes Potenzial für die moderne Zell- und Entwicklungsbiologie.
Spheroids resemble features of tissues and serve as model systems to study cell–cell and cell–ECM interactions in non-adhesive three-dimensional environments. Although it is generally accepted that mature spheroids resemble tissue properties very well, no studies relate different phases in the spheroid formation processes that contribute to tissue integrity. Tissue integrity involves the cellular processes adhesion formation, adhesion reinforcement, rearrangement as well as proliferation. They maintain the structure and function of tissues and, upon dysregulation, contribute to malignancy. We investigated spheroid formation dynamics in cell lines of different metastatic potential. We dissected spheroid formation into phases of aggregation, compaction and growth to identify the respective contributions of E-cadherin, actin, microtubules and FAK. E-cadherin, actin and microtubules drive the first two phases. Microtubules and FAK are involved in the proliferation phase. FAK activity correlates with the metastatic potential of the cells. A robust computational model based on a very large number of experiments reveals the temporal resolution of cell adhesion. Our results provide novel hypotheses to unveil the general mechanisms that contribute to tissue integrity.