Article

MDCK Cystogenesis Driven by Cell Stabilization within Computational Analogues

University of California San Diego, United States of America
PLoS Computational Biology (Impact Factor: 4.83). 04/2011; 7(4):e1002030. DOI: 10.1371/journal.pcbi.1002030
Source: PubMed

ABSTRACT The study of epithelial morphogenesis is fundamental to increasing our understanding of organ function and disease. Great progress has been made through study of culture systems such as Madin-Darby canine kidney (MDCK) cells, but many aspects of even simple morphogenesis remain unclear. For example, are specific cell actions tightly coupled to the characteristics of the cell's environment or are they more often cell state dependent? How does the single lumen, single cell layer cyst consistently emerge from a variety of cell actions? To improve insight, we instantiated in silico analogues that used hypothesized cell behavior mechanisms to mimic MDCK cystogenesis. We tested them through in vitro experimentation and quantitative validation. We observed novel growth patterns, including a cell behavior shift that began around day five of growth. We created agent-oriented analogues that used the cellular Potts model along with an Iterative Refinement protocol. Following several refinements, we achieved a degree of validation for two separate mechanisms. Both survived falsification and achieved prespecified measures of similarity to cell culture properties. In silico components and mechanisms mapped to in vitro counterparts. In silico, the axis of cell division significantly affects lumen number without changing cell number or cyst size. Reducing the amount of in silico luminal cell death had limited effect on cystogenesis. Simulations provide an observable theory for cystogenesis based on hypothesized, cell-level operating principles.

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Available from: Jesse A Engelberg, Aug 12, 2015
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    • "For example, CELL DIVI- SION was implemented in an agent-based manner so CELLS had access to information about the points contained within them, thus it was straightforward to randomize or invert the axis of CELL DIVISION. In order to validate the quantitative results of ISMA-M and ISMA-C, similarity measures were developed for cell number, lumen and cyst size, mean cell area, and the ratio of cellular to cyst area [2]. Similarity Measure 1 (SM1) measured the percentage of in silico simulations at a given day that were within ± 25% of the mean in vitro value at that day, "
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