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Segmentation and tracking of adherens junctions in 3D for the analysis of epithelial tissue morphogenesis.

Cilla R, Mechery V, Hernandez de Madrid B, Del Signore S, Dotu I, Hatini V - PLoS Comput. Biol. (2015)

Bottom Line: We accentuate and detect cell outlines in a series of steps, symbolically describe the cells and their connectivity, and employ this information to track the cells.We validated the performance of the pipeline for its ability to detect vertices and cell-cell contacts, track cells, and identify mitosis and apoptosis in surface epithelia of Drosophila imaginal discs.We demonstrate the utility of the pipeline to extract key quantitative features of cell behavior with which to elucidate the dynamics and biomechanical control of epithelial tissue morphogenesis.

View Article: PubMed Central - PubMed

Affiliation: Department of Developmental, Molecular & Chemical Biology. Sackler School of Graduate Biomedical Sciences, Tufts University School of Medicine, Boston, Massachusetts, United States of America.

ABSTRACT
Epithelial morphogenesis generates the shape of tissues, organs and embryos and is fundamental for their proper function. It is a dynamic process that occurs at multiple spatial scales from macromolecular dynamics, to cell deformations, mitosis and apoptosis, to coordinated cell rearrangements that lead to global changes of tissue shape. Using time lapse imaging, it is possible to observe these events at a system level. However, to investigate morphogenetic events it is necessary to develop computational tools to extract quantitative information from the time lapse data. Toward this goal, we developed an image-based computational pipeline to preprocess, segment and track epithelial cells in 4D confocal microscopy data. The computational pipeline we developed, for the first time, detects the adherens junctions of epithelial cells in 3D, without the need to first detect cell nuclei. We accentuate and detect cell outlines in a series of steps, symbolically describe the cells and their connectivity, and employ this information to track the cells. We validated the performance of the pipeline for its ability to detect vertices and cell-cell contacts, track cells, and identify mitosis and apoptosis in surface epithelia of Drosophila imaginal discs. We demonstrate the utility of the pipeline to extract key quantitative features of cell behavior with which to elucidate the dynamics and biomechanical control of epithelial tissue morphogenesis. We have made our methods and data available as an open-source multiplatform software tool called TTT (http://github.com/morganrcu/TTT).

No MeSH data available.


Related in: MedlinePlus

Detection of mitosis and apoptosis events.In addition to cell movements, notum morphogenesis involves extensive cell delamination at the dorsal midline [30] and extensive cell proliferation required for notum expansion [7]. We therefore incorporated into the tracker algorithms to detect mitotic and apoptotic events. A) The large light green cell in the upper left region splits to produce two daughter cells marked by the same color. B) The dark brown cell in the center reduces its area until it disappears.
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pcbi.1004124.g002: Detection of mitosis and apoptosis events.In addition to cell movements, notum morphogenesis involves extensive cell delamination at the dorsal midline [30] and extensive cell proliferation required for notum expansion [7]. We therefore incorporated into the tracker algorithms to detect mitotic and apoptotic events. A) The large light green cell in the upper left region splits to produce two daughter cells marked by the same color. B) The dark brown cell in the center reduces its area until it disappears.

Mentions: Finally, the correspondence among cells in adjacent frames is resolved (Fig 1G). To this end we employ a min-cost max-flow cell tracking framework capable of detecting cellular mitosis and apoptosis events [10] (Fig 2). We consider that the detection of these events is as important as the correct association of cells among frames, although their relatively low frequency makes their detection even harder. However, understanding where and when cells proliferate and die is as important as studying how cells change their shape. Our system is able to successfully detect cellular apoptosis as the area of the dying cells tends to vanish and to detect cellular mitosis as the spatial moments of the parent cell are similar to the moment of the union of the daughter cells.


Segmentation and tracking of adherens junctions in 3D for the analysis of epithelial tissue morphogenesis.

Cilla R, Mechery V, Hernandez de Madrid B, Del Signore S, Dotu I, Hatini V - PLoS Comput. Biol. (2015)

Detection of mitosis and apoptosis events.In addition to cell movements, notum morphogenesis involves extensive cell delamination at the dorsal midline [30] and extensive cell proliferation required for notum expansion [7]. We therefore incorporated into the tracker algorithms to detect mitotic and apoptotic events. A) The large light green cell in the upper left region splits to produce two daughter cells marked by the same color. B) The dark brown cell in the center reduces its area until it disappears.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4401792&req=5

pcbi.1004124.g002: Detection of mitosis and apoptosis events.In addition to cell movements, notum morphogenesis involves extensive cell delamination at the dorsal midline [30] and extensive cell proliferation required for notum expansion [7]. We therefore incorporated into the tracker algorithms to detect mitotic and apoptotic events. A) The large light green cell in the upper left region splits to produce two daughter cells marked by the same color. B) The dark brown cell in the center reduces its area until it disappears.
Mentions: Finally, the correspondence among cells in adjacent frames is resolved (Fig 1G). To this end we employ a min-cost max-flow cell tracking framework capable of detecting cellular mitosis and apoptosis events [10] (Fig 2). We consider that the detection of these events is as important as the correct association of cells among frames, although their relatively low frequency makes their detection even harder. However, understanding where and when cells proliferate and die is as important as studying how cells change their shape. Our system is able to successfully detect cellular apoptosis as the area of the dying cells tends to vanish and to detect cellular mitosis as the spatial moments of the parent cell are similar to the moment of the union of the daughter cells.

Bottom Line: We accentuate and detect cell outlines in a series of steps, symbolically describe the cells and their connectivity, and employ this information to track the cells.We validated the performance of the pipeline for its ability to detect vertices and cell-cell contacts, track cells, and identify mitosis and apoptosis in surface epithelia of Drosophila imaginal discs.We demonstrate the utility of the pipeline to extract key quantitative features of cell behavior with which to elucidate the dynamics and biomechanical control of epithelial tissue morphogenesis.

View Article: PubMed Central - PubMed

Affiliation: Department of Developmental, Molecular & Chemical Biology. Sackler School of Graduate Biomedical Sciences, Tufts University School of Medicine, Boston, Massachusetts, United States of America.

ABSTRACT
Epithelial morphogenesis generates the shape of tissues, organs and embryos and is fundamental for their proper function. It is a dynamic process that occurs at multiple spatial scales from macromolecular dynamics, to cell deformations, mitosis and apoptosis, to coordinated cell rearrangements that lead to global changes of tissue shape. Using time lapse imaging, it is possible to observe these events at a system level. However, to investigate morphogenetic events it is necessary to develop computational tools to extract quantitative information from the time lapse data. Toward this goal, we developed an image-based computational pipeline to preprocess, segment and track epithelial cells in 4D confocal microscopy data. The computational pipeline we developed, for the first time, detects the adherens junctions of epithelial cells in 3D, without the need to first detect cell nuclei. We accentuate and detect cell outlines in a series of steps, symbolically describe the cells and their connectivity, and employ this information to track the cells. We validated the performance of the pipeline for its ability to detect vertices and cell-cell contacts, track cells, and identify mitosis and apoptosis in surface epithelia of Drosophila imaginal discs. We demonstrate the utility of the pipeline to extract key quantitative features of cell behavior with which to elucidate the dynamics and biomechanical control of epithelial tissue morphogenesis. We have made our methods and data available as an open-source multiplatform software tool called TTT (http://github.com/morganrcu/TTT).

No MeSH data available.


Related in: MedlinePlus