Refine
Document Type
- Article (3)
Language
- English (3)
Has Fulltext
- yes (3)
Is part of the Bibliography
- no (3)
Keywords
- BMP signaling (1)
- Blastocysts (1)
- Cell differentiation (1)
- Cytokines (1)
- Embryos (1)
- Endotoxins (1)
- Immune receptor signaling (1)
- Inflammation (1)
- Macrophages (1)
- Mathematical models (1)
Institute
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.
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.
Self-extracellular RNA (eRNA), released from stressed or injured cells upon various pathological situations such as ischemia-reperfusion-injury, has been shown to act as an alarmin by inducing procoagulatory and proinflammatory responses. In particular, M1-polarization of macrophages by eRNA resulted in the expression and release of a variety of cytokines, including tumor necrosis factor (TNF)-α or interleukin-6 (IL-6). The present study now investigates in which way self-eRNA may influence the response of macrophages towards various Toll-like receptor (TLR)-agonists. Isolated agonists of TLR2 (Pam2CSK4), TLR3 (PolyIC), TLR4 (LPS), or TLR7 (R848) induced the release of TNF-α in a concentration-dependent manner in murine macrophages, differentiated from bone marrow-derived stem cells by mouse colony stimulating factor. Here, the presence of eRNA shifted the dose-response curve for Pam2CSK4 (Pam) considerably to the left, indicating that eRNA synergistically enhanced the cytokine liberation from macrophages even at very low Pam-levels. The synergistic activation of TLR2 by eRNA/Pam was duplicated by other TLR2-agonists such as FSL-1 or Pam3CSK4. In contrast, for TLR4-agonists such as LPS a synergistic effect of eRNA was much weaker, and was not existent for TLR3-, or TLR7-agonists. The synergistic eRNA/Pam action was dependent on the NFκB-signaling pathway as well as on p38MAP- and MEK1/ERK-kinases and was prevented by predigestion of eRNA with RNase1 or by antibodies against TLR2. Thus, the presence of self-eRNA as alarming molecule sensitizes innate immune responses towards pathogen-associated molecular patterns (PAMPs) in a synergistic way and may thereby contribute to the differentiated outcome of inflammatory responses.