Correlating cell behavior with tissue topology in embryonic epithelia

• Published in: PloS one Vol. 6; no. 4; p. e18081
• Main Authors: Sandersius, Sebastian A, Chuai, Manli, Weijer, Cornelis J, Newman, Timothy J
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 29.04.2011; Public Library of Science (PLoS)
• Subjects: Algorithms; Analysis; Animals; Biology; Cell adhesion & migration; Cell division; Cell Movement; Cell Proliferation; Chemical reactions; Chick Embryo; Chickens; Computer Simulation; Correlation; Developmental biology; Drosophila; Embryonic development; Epithelium - metabolism; Female; Gastrula - cytology; Insects; Life sciences; Markov Chains; Markov processes; Models, Statistical; Morphology; Physics; Plate tectonics; Primitive streak; Primitive Streak - physiology; Rheology; Spatial distribution; Statistical analysis; Statistics; Tissues; Topology; Xenopus; United States > US; Arizona
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0018081

Measurements on embryonic epithelial tissues in a diverse range of organisms have shown that the statistics of cell neighbor numbers are universal in tissues where cell proliferation is the primary cell activity. Highly simplified non-spatial models of proliferation are claimed to accurately reproduce these statistics. Using a systematic critical analysis, we show that non-spatial models are not capable of robustly describing the universal statistics observed in proliferating epithelia, indicating strong spatial correlations between cells. Furthermore we show that spatial simulations using the Subcellular Element Model are able to robustly reproduce the universal histogram. In addition these simulations are able to unify ostensibly divergent experimental data in the literature. We also analyze cell neighbor statistics in early stages of chick embryo development in which cell behaviors other than proliferation are important. We find from experimental observation that cell neighbor statistics in the primitive streak region, where cell motility and ingression are also important, show a much broader distribution. A non-spatial Markov process model provides excellent agreement with this broader histogram indicating that cells in the primitive streak may have significantly weaker spatial correlations. These findings show that cell neighbor statistics provide a potentially useful signature of collective cell behavior.