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Due to an increasing awareness of the potential hazardousness of air pollutants, new laws, rules and guidelines have recently been implemented globally. In this respect, numerous studies have addressed traffic-related exposure to particulate matter using stationary technology so far. By contrast, only few studies used the advanced technology of mobile exposure analysis. The Mobile Air Quality Study (MAQS) addresses the issue of air pollutant exposure by combining advanced high-granularity spatial-temporal analysis with vehicle-mounted, person-mounted and roadside sensors. The MAQS-platform will be used by international collaborators in order 1) to assess air pollutant exposure in relation to road structure, 2) to assess air pollutant exposure in relation to traffic density, 3) to assess air pollutant exposure in relation to weather conditions, 4) to compare exposure within vehicles between front and back seat (children) positions, and 5) to evaluate "traffic zone"- exposure in relation to non-"traffic zone"-exposure. Primarily, the MAQS-platform will focus on particulate matter. With the establishment of advanced mobile analysis tools, it is planed to extend the analysis to other pollutants including including NO2, SO2, nanoparticles, and ozone.
Planar cell polarity (PCP)–the coordinated polarisation of a whole field of cells within the plane of a tissue–relies on the interaction of three modules: a global module that couples individual cellular polarity to the tissue axis, a local module that aligns the axis of polarisation of neighbouring cells, and a readout module that directs the correct outgrowth of PCP-regulated structures such as hairs and bristles. While much is known about the molecular components that are required for PCP, the functional details of–and interactions between–the modules remain unclear. In this work, we perform a mathematical and computational analysis of two previously proposed computational models of the local module (Amonlirdviman et al., Science, 307, 2005; Le Garrec et al., Dev. Dyn., 235, 2006). Both models can reproduce wild-type and mutant phenotypes of PCP observed in the Drosophila wing under the assumption that a tissue-wide polarity cue from the global module persists throughout the development of PCP. We demonstrate that both models can also generate tissue-level PCP when provided with only a transient initial polarity cue. However, in these models such transient cues are not sufficient to ensure robustness of the resulting cellular polarisation.
The transition from local to global patterns governs the differentiation of mouse blastocysts
(2020)
During mammalian blastocyst development, inner cell mass (ICM) cells differentiate into epiblast (Epi) or primitive endoderm (PrE). These two fates are characterized by the expression of the transcription factors NANOG and GATA6, respectively. Here, we investigate the spatio-temporal distribution of NANOG and GATA6 expressing cells in the ICM of the mouse blastocysts with quantitative three-dimensional single cell-based neighbourhood analyses. We define the cell neighbourhood by local features, which include the expression levels of both fate markers expressed in each cell and its neighbours, and the number of neighbouring cells. We further include the position of a cell relative to the centre of the ICM as a global positional feature. Our analyses reveal a local three-dimensional pattern that is already present in early blastocysts: 1) Cells expressing the highest NANOG levels are surrounded by approximately nine neighbours, while 2) cells expressing GATA6 cluster according to their GATA6 levels. This local pattern evolves into a global pattern in the ICM that starts to emerge in mid blastocysts. We show that FGF/MAPK signalling is involved in the three-dimensional distribution of the cells and, using a mutant background, we further show that the GATA6 neighbourhood is regulated by NANOG. Our quantitative study suggests that the three-dimensional cell neighbourhood plays a role in Epi and PrE precursor specification. Our results highlight the importance of analysing the three-dimensional cell neighbourhood while investigating cell fate decisions during early mouse embryonic development.
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.
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.
Mechanics has an important role during morphogenesis, both in the generation of forces driving cell shape changes and in determining the effective material properties of cells and tissues. Drosophila dorsal closure has emerged as a reference model system for investigating the interplay between tissue mechanics and cellular activity. During dorsal closure, the amnioserosa generates one of the major forces that drive closure through the apical contraction of its constituent cells. We combined quantitation of live data, genetic and mechanical perturbation and cell biology, to investigate how mechanical properties and contraction rate emerge from cytoskeletal activity. We found that a decrease in Myosin phosphorylation induces a fluidization of amnioserosa cells which become more compliant. Conversely, an increase in Myosin phosphorylation and an increase in actin linear polymerization induce a solidification of cells. Contrary to expectation, these two perturbations have an opposite effect on the strain rate of cells during DC. While an increase in actin polymerization increases the contraction rate of amnioserosa cells, an increase in Myosin phosphorylation gives rise to cells that contract very slowly. The quantification of how the perturbation induced by laser ablation decays throughout the tissue revealed that the tissue in these two mutant backgrounds reacts very differently. We suggest that the differences in the strain rate of cells in situations where Myosin activity or actin polymerization is increased arise from changes in how the contractile forces are transmitted and coordinated across the tissue through ECadherin-mediated adhesion. Altogether, our results show that there is an optimal level of Myosin activity to generate efficient contraction and suggest that the architecture of the actin cytoskeleton and the dynamics of adhesion complexes are important parameters for the emergence of coordinated activity throughout the tissue.
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.
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.
A key event in cellular physiology is the decision between membrane biogenesis and fat storage. Phosphatidic acid (PA) is an important intermediate at the branch point of these pathways and is continuously monitored by the transcriptional repressor Opi1 to orchestrate lipid metabolism. In this study, we report on the mechanism of membrane recognition by Opi1 and identify an amphipathic helix (AH) for selective binding of PA over phosphatidylserine (PS). The insertion of the AH into the membrane core renders Opi1 sensitive to the lipid acyl chain composition and provides a means to adjust membrane biogenesis. By rational design of the AH, we tune the membrane-binding properties of Opi1 and control its responsiveness in vivo. Using extensive molecular dynamics simulations, we identify two PA-selective three-finger grips that tightly bind the PA phosphate headgroup while interacting less intimately with PS. This work establishes lipid headgroup selectivity as a new feature in the family of AH-containing membrane property sensors.
Background: While recent data show that crizotinib is highly effective in patients with ROS1 rearrangement, few data is available about the prognostic impact, the predictive value for different treatments, and the genetic heterogeneity of ROS1- positive patients.
Patients and methods: 1137 patients with adenocarcinoma of the lung were analyzed regarding their ROS1 status. In positive cases, next-generation sequencing (NGS) was performed. Clinical characteristics, treatments and outcome of these patients were assessed. Overall survival (OS) was compared with genetically defined subgroups of ROS1-negative patients.
Results: 19 patients of 1035 evaluable (1.8%) had ROS1-rearrangement. The median OS has not been reached. Stage IV patients with ROS1-rearrangement had the best OS of all subgroups (36.7 months, p < 0.001). 9 of 14 (64.2%) patients had at least one response to chemotherapy. Estimated mean OS for patients receiving chemotherapy and crizotinib was 5.3 years. Ten patients with ROS1-rearrangement (52.6%) harbored additional aberrations.
Conclusion: ROS1-rearangement is not only a predictive marker for response to crizotinib, but also seems to be the one of the best prognostic molecular markers in NSCLC reported so far. In stage IV patients, response to chemotherapy was remarkable high and overall survival was significantly better compared to other subgroups including EGFR-mutated and ALK-fusion-positive NSCLC.