Determining the impact of cell mixing on signaling during development
Cell movement and intercellular signaling occur simultaneously to organize morphogenesis during embryonic development. Cell movement can cause relative positional changes between neighboring cells. When intercellular signals are local such cell mixing may affect signaling, changing the flow of infor...
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| Acceso en línea: | http://hdl.handle.net/20.500.12110/paper_00121592_v59_n5_p351_Uriu |
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todo:paper_00121592_v59_n5_p351_Uriu2023-10-03T14:10:16Z Determining the impact of cell mixing on signaling during development Uriu, K. Morelli, L.G. cell movement coupled oscillators Delta-Notch signal mean squared displacement synchronization cell culture cell mixing cell motion cell tracking embryo development nonhuman oscillator quantitative analysis Review signal transduction theoretical study zebra fish animal biological rhythm embryo development human physiology signal transduction theoretical model Animals Biological Clocks Embryonic Development Humans Models, Theoretical Signal Transduction Cell movement and intercellular signaling occur simultaneously to organize morphogenesis during embryonic development. Cell movement can cause relative positional changes between neighboring cells. When intercellular signals are local such cell mixing may affect signaling, changing the flow of information in developing tissues. Little is known about the effect of cell mixing on intercellular signaling in collective cellular behaviors and methods to quantify its impact are lacking. Here we discuss how to determine the impact of cell mixing on cell signaling drawing an example from vertebrate embryogenesis: the segmentation clock, a collective rhythm of interacting genetic oscillators. We argue that comparing cell mixing and signaling timescales is key to determining the influence of mixing. A signaling timescale can be estimated by combining theoretical models with cell signaling perturbation experiments. A mixing timescale can be obtained by analysis of cell trajectories from live imaging. After comparing cell movement analyses in different experimental settings, we highlight challenges in quantifying cell mixing from embryonic timelapse experiments, especially a reference frame problem due to embryonic motions and shape changes. We propose statistical observables characterizing cell mixing that do not depend on the choice of reference frames. Finally, we consider situations in which both cell mixing and signaling involve multiple timescales, precluding a direct comparison between single characteristic timescales. In such situations, physical models based on observables of cell mixing and signaling can simulate the flow of information in tissues and reveal the impact of observed cell mixing on signaling. © 2017 Japanese Society of Developmental Biologists JOUR info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by/2.5/ar http://hdl.handle.net/20.500.12110/paper_00121592_v59_n5_p351_Uriu |
| institution |
Universidad de Buenos Aires |
| institution_str |
I-28 |
| repository_str |
R-134 |
| collection |
Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) |
| topic |
cell movement coupled oscillators Delta-Notch signal mean squared displacement synchronization cell culture cell mixing cell motion cell tracking embryo development nonhuman oscillator quantitative analysis Review signal transduction theoretical study zebra fish animal biological rhythm embryo development human physiology signal transduction theoretical model Animals Biological Clocks Embryonic Development Humans Models, Theoretical Signal Transduction |
| spellingShingle |
cell movement coupled oscillators Delta-Notch signal mean squared displacement synchronization cell culture cell mixing cell motion cell tracking embryo development nonhuman oscillator quantitative analysis Review signal transduction theoretical study zebra fish animal biological rhythm embryo development human physiology signal transduction theoretical model Animals Biological Clocks Embryonic Development Humans Models, Theoretical Signal Transduction Uriu, K. Morelli, L.G. Determining the impact of cell mixing on signaling during development |
| topic_facet |
cell movement coupled oscillators Delta-Notch signal mean squared displacement synchronization cell culture cell mixing cell motion cell tracking embryo development nonhuman oscillator quantitative analysis Review signal transduction theoretical study zebra fish animal biological rhythm embryo development human physiology signal transduction theoretical model Animals Biological Clocks Embryonic Development Humans Models, Theoretical Signal Transduction |
| description |
Cell movement and intercellular signaling occur simultaneously to organize morphogenesis during embryonic development. Cell movement can cause relative positional changes between neighboring cells. When intercellular signals are local such cell mixing may affect signaling, changing the flow of information in developing tissues. Little is known about the effect of cell mixing on intercellular signaling in collective cellular behaviors and methods to quantify its impact are lacking. Here we discuss how to determine the impact of cell mixing on cell signaling drawing an example from vertebrate embryogenesis: the segmentation clock, a collective rhythm of interacting genetic oscillators. We argue that comparing cell mixing and signaling timescales is key to determining the influence of mixing. A signaling timescale can be estimated by combining theoretical models with cell signaling perturbation experiments. A mixing timescale can be obtained by analysis of cell trajectories from live imaging. After comparing cell movement analyses in different experimental settings, we highlight challenges in quantifying cell mixing from embryonic timelapse experiments, especially a reference frame problem due to embryonic motions and shape changes. We propose statistical observables characterizing cell mixing that do not depend on the choice of reference frames. Finally, we consider situations in which both cell mixing and signaling involve multiple timescales, precluding a direct comparison between single characteristic timescales. In such situations, physical models based on observables of cell mixing and signaling can simulate the flow of information in tissues and reveal the impact of observed cell mixing on signaling. © 2017 Japanese Society of Developmental Biologists |
| format |
JOUR |
| author |
Uriu, K. Morelli, L.G. |
| author_facet |
Uriu, K. Morelli, L.G. |
| author_sort |
Uriu, K. |
| title |
Determining the impact of cell mixing on signaling during development |
| title_short |
Determining the impact of cell mixing on signaling during development |
| title_full |
Determining the impact of cell mixing on signaling during development |
| title_fullStr |
Determining the impact of cell mixing on signaling during development |
| title_full_unstemmed |
Determining the impact of cell mixing on signaling during development |
| title_sort |
determining the impact of cell mixing on signaling during development |
| url |
http://hdl.handle.net/20.500.12110/paper_00121592_v59_n5_p351_Uriu |
| work_keys_str_mv |
AT uriuk determiningtheimpactofcellmixingonsignalingduringdevelopment AT morellilg determiningtheimpactofcellmixingonsignalingduringdevelopment |
| _version_ |
1782030462182490112 |