Title: Long-range mechanical signaling in biological systems
Cells can respond to signals generated by other cells that are remarkably far away. Studies from at least the 1920's showed that cells move toward each other when the distance between them is on the order of a millimeter, which is many times the cell diameter. Chemical signals generated by molecules diffusing from the cell surface would move too slowly and dissipate too fast to account for these effects, suggesting that they might be physical rather than biochemical. The non-linear elastic responses of sparsely connected networks of stiff or semiflexible filament such as those that form the extracellular matrix (ECM) and the cytoskeleton have unusual properties that suggest multiple mechanisms for long-range signaling in biological tissues. These include not only direct force transmission, but also highly non-uniform local deformations, and force-generated changes in fiber alignment and density. Defining how fibrous networks respond to cell-generated forces can help design new methods to characterize abnormal tissues and can guide development of improved biomimetic materials. more »« less
Controlling the formation of blood and lymphatic vasculatures is crucial for engineered tissues. Although the lymphatic vessels originate from embryonic blood vessels, the two retain functional and physiological differences even as they develop in the vicinity of each other. This suggests that there is a previously unknown molecular mechanism by which blood (BECs) and lymphatic endothelial cells (LECs) recognize each other and coordinate to generate distinct capillary networks.
Methods
We utilized Matrigel and fibrin assays to determine how cord-like structures (CLS) can be controlled by altering LEC and BEC identity through podoplanin (PDPN) and folliculin (FLCN) expressions. We generated BECΔFLCNand LECΔPDPN, and observed cell migration to characterize loss lymphatic and blood characteristics due to respective knockouts.
Results
We observed that LECs and BECs form distinct CLS in Matrigel and fibrin gels despite being cultured in close proximity with each other. We confirmed that the LECs and BECs do not recognize each other through paracrine signaling, as proliferation and migration of both cells were unaffected by paracrine signals. On the other hand, we foundPDPNto be the key surface protein that is responsible for LEC-BEC recognition, and LECs lackingPDPNbecame pseudo-BECs and vice versa. We also found thatFLCNmaintains BEC identity through downregulation ofPDPN.
Conclusions
Overall, these observations reveal a new molecular pathway through which LECs and BECs form distinct CLS through physical contact byPDPNwhich in turn is regulated byFLCN, which has important implications toward designing functional engineered tissues.
Yu, Xinwei; Creamer, Matthew S; Randi, Francesco; Sharma, Anuj K; Linderman, Scott W; Leifer, Andrew M(
, eLife)
Understanding the intricacies of the brain often requires spotting and tracking specific neurons over time and across different individuals. For instance, scientists may need to precisely monitor the activity of one neuron even as the brain moves and deforms; or they may want to find universal patterns by comparing signals from the same neuron across different individuals. Both tasks require matching which neuron is which in different images and amongst a constellation of cells. This is theoretically possible in certain ‘model’ animals where every single neuron is known and carefully mapped out. Still, it remains challenging: neurons move relative to one another as the animal changes posture, and the position of a cell is also slightly different between individuals. Sophisticated computer algorithms are increasingly used to tackle this problem, but they are far too slow to track neural signals as real-time experiments unfold. To address this issue, Yu et al. designed a new algorithm based on the Transformer, an artificial neural network originally used to spot relationships between words in sentences. To learn relationships between neurons, the algorithm was fed hundreds of thousands of ‘semi-synthetic’ examples of constellations of neurons. Instead of painfully collated actual experimental data, these datasets were created by a simulator based on a few simple measurements. Testing the new algorithm on the tiny worm Caenorhabditis elegans revealed that it was faster and more accurate, finding corresponding neurons in about 10ms. The work by Yu et al. demonstrates the power of using simulations rather than experimental data to train artificial networks. The resulting algorithm can be used immediately to help study how the brain of C. elegans makes decisions or controls movements. Ultimately, this research could allow brain-machine interfaces to be developed.
We exist in a physical world, and cells within biological tissues must respond appropriately to both environmental forces and forces generated within the tissue to ensure normal development and homeostasis. Cell division is required for normal tissue growth and maintenance, but both the direction and rate of cell division must be tightly controlled to avoid diseases of over‐proliferation such as cancer. Recent studies have shown that mechanical cues can cause mitotic entry and orient the mitotic spindle, suggesting that physical force could play a role in patterning tissue growth. However, to fully understand how mechanics guides cellsin vivo, it is necessary to assess the interaction of mechanical strain and cell division in a whole tissue context. In this mini‐review we first summarise the body of work linking mechanics and cell division, before looking at the advantages that theXenopusembryo can offer as a model organism for understanding: (1) the mechanical environment during embryogenesis, and (2) factors important for cell division. Finally, we introduce a novel method for applying a reproducible strain toXenopusembryonic tissue and assessing subsequent cell divisions.
At first, embryos are made up of identical cells. Then, as the embryo develops, these cells specialize into different types, such as heart and brain cells. Chemical signals sent and received by the cells are key to forming the right type of cell at the right time and place. The cellular machinery that produces and interprets these signals is exceedingly complex and difficult to understand. In the 1950s, Conrad Waddington presented an alternative way of thinking about how an unspecialized cell progresses to one of many different fates. He suggested visualizing the developing cell as a ball rolling along a hilly landscape. As the ball travels, obstacles in its way guide it along particular paths. Eventually the ball comes to rest in a valley, with each valley in the landscape representing a different cell fate. Although this “landscape model” is an appealing metaphor for how signaling events guide cell specialization, it was not clear whether it could be put to productive use. The egg-laying organ in the worm species Caenorhabditis elegans is called the vulva, and is often studied by researchers who want to learn more about how organs develop. The vulva develops from a small number of identical cells that adopt one of three possible cell fates. Two chemical signals, called epidermal growth factor (EGF) and Notch, control this specialization process. Corson and Siggia have now constructed a simple landscape model that can reproduce the normal arrangement of cell types in the vulva. When adjusted to describe the effect of genetic mutations that affect either EGF or Notch, the model could predict the outcome of mutations that affect both signals at once. The twists and turns of cell paths in the landscape could also account for several non-intuitive cell fate outcomes that had been assumed to result from subtle regulation of EGF and Notch signals. Landscape models should be easy to apply to other developing tissues and organs. By providing an intuitive picture of how signals shape cellular decisions, the models could help researchers to learn how to control cell and tissue development. This could lead to new treatments to repair or replace failing organs, making regenerative medicine a reality.
Cell elongation along the division axis, or mitotic elongation, mediates proper segregation of chromosomes and other intracellular materials, and is required for completion of cell division. In three‐dimensionally confining extracellular matrices, such as dense collagen gels, dividing cells must generate space to allow mitotic elongation to occur. In principle, cells can generate space for mitotic elongation during cell spreading, prior to mitosis, or via extracellular force generation or matrix degradation during mitosis. However, the processes by which cells drive mitotic elongation in collagen‐rich extracellular matrices remains unclear. Here, it is shown that single cancer cells generate substantial pushing forces on the surrounding collagen extracellular matrix to drive cell division in confining collagen gels and allow mitotic elongation to proceed. Neither cell spreading, prior to mitosis, nor matrix degradation, during spreading or mitotic elongation, are found to be required for mitotic elongation. Mechanistically, laser ablation studies, pharmacological inhibition studies, and computational modeling establish that pushing forces generated during mitosis in collagen gels arise from a combination of interpolar spindle elongation and cytokinetic ring contraction. These results reveal a fundamental mechanism mediating cell division in confining extracellular matrices, providing insight into how tumor cells are able to proliferate in dense collagen‐rich tissues.
Alisafaei, Farid, Chen, Xingyu, Leahy, Thomas, Janmey, Paul A., and Shenoy, Vivek B. Long-range mechanical signaling in biological systems. Retrieved from https://par.nsf.gov/biblio/10275613. Soft Matter 17.2 Web. doi:10.1039/D0SM01442G.
@article{osti_10275613,
place = {Country unknown/Code not available},
title = {Long-range mechanical signaling in biological systems},
url = {https://par.nsf.gov/biblio/10275613},
DOI = {10.1039/D0SM01442G},
abstractNote = {Cells can respond to signals generated by other cells that are remarkably far away. Studies from at least the 1920's showed that cells move toward each other when the distance between them is on the order of a millimeter, which is many times the cell diameter. Chemical signals generated by molecules diffusing from the cell surface would move too slowly and dissipate too fast to account for these effects, suggesting that they might be physical rather than biochemical. The non-linear elastic responses of sparsely connected networks of stiff or semiflexible filament such as those that form the extracellular matrix (ECM) and the cytoskeleton have unusual properties that suggest multiple mechanisms for long-range signaling in biological tissues. These include not only direct force transmission, but also highly non-uniform local deformations, and force-generated changes in fiber alignment and density. Defining how fibrous networks respond to cell-generated forces can help design new methods to characterize abnormal tissues and can guide development of improved biomimetic materials.},
journal = {Soft Matter},
volume = {17},
number = {2},
author = {Alisafaei, Farid and Chen, Xingyu and Leahy, Thomas and Janmey, Paul A. and Shenoy, Vivek B.},
editor = {null}
}
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