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      Cell Patterns Emerge from Coupled Chemical and Physical Fields with Cell Proliferation Dynamics: The Arabidopsis thaliana Root as a Study System

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          Abstract

          A central issue in developmental biology is to uncover the mechanisms by which stem cells maintain their capacity to regenerate, yet at the same time produce daughter cells that differentiate and attain their ultimate fate as a functional part of a tissue or an organ. In this paper we propose that, during development, cells within growing organs obtain positional information from a macroscopic physical field that is produced in space while cells are proliferating. This dynamical interaction triggers and responds to chemical and genetic processes that are specific to each biological system. We chose the root apical meristem of Arabidopsis thaliana to develop our dynamical model because this system is well studied at the molecular, genetic and cellular levels and has the key traits of multicellular stem-cell niches. We built a dynamical model that couples fundamental molecular mechanisms of the cell cycle to a tension physical field and to auxin dynamics, both of which are known to play a role in root development. We perform extensive numerical calculations that allow for quantitative comparison with experimental measurements that consider the cellular patterns at the root tip. Our model recovers, as an emergent pattern, the transition from proliferative to transition and elongation domains, characteristic of stem-cell niches in multicellular organisms. In addition, we successfully predict altered cellular patterns that are expected under various applied auxin treatments or modified physical growth conditions. Our modeling platform may be extended to explicitly consider gene regulatory networks or to treat other developmental systems.

          Author Summary

          The emergence of tumors results from altered cell differentiation and proliferation during organ and tissue development. Understanding how such altered or normal patterns are established is still a challenge. Molecular genetic approaches to understanding pattern formation have searched for key central genetic controllers. However, biological patterns emerge as a consequence of coupled complex genetic and non-genetic sub-systems operating at various spatial and temporal scales and levels of organization. We present a two-dimensional model and simulation benchmark that considers the integrated dynamics of physical and chemical fields that result from cell proliferation. We aim at understanding how the cellular patterns of stem-cell niches emerge. In these, organizer cells with very low rates of proliferation are surrounded by stem cells with slightly higher proliferation rates that transit to a domain of active proliferation and then of elongation and differentiation. We quantified such cellular patterns in the Arabidopsis thaliana root to test our theoretical propositions. The results of our simulations closely mimic observed root cellular patterns, thus providing a proof of principle that coupled physical fields and chemical processes under active cell proliferation give rise to stem-cell patterns. Our framework may be extended to other developmental systems and to consider gene regulatory networks.

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          Author and article information

          Contributors
          Role: Editor
          Journal
          PLoS Comput Biol
          PLoS Comput. Biol
          plos
          ploscomp
          PLoS Computational Biology
          Public Library of Science (San Francisco, USA )
          1553-734X
          1553-7358
          May 2013
          May 2013
          2 May 2013
          : 9
          : 5
          : e1003026
          Affiliations
          [1 ]Instituto de Física, Universidad Nacional Autónoma de México (UNAM), México, Distrito Federal, México
          [2 ]Universidad Autónoma de la Ciudad de México, Mexico, Distrito Federal, México
          [3 ]Instituto de Ecología, Universidad Nacional Autónoma de México, México, Distrito Federal, México
          [4 ]Centro de Ciencias de la Complejidad-C3, Universidad Nacional Autónoma de México, Distrito Federal, México
          Northeastern University, United States of America
          Author notes

          The authors have declared that no competing interests exist.

          Conceived and designed the experiments: RAB EA EOG ERAB. Performed the experiments: RAB JRRA MAN YCP. Analyzed the data: RAB JRRA MAN EA EOG VHH YCP ERAB. Contributed reagents/materials/analysis tools: RAB JRRA MAN EA YCP ERAB. Wrote the paper: RAB JRRA MAN EA EOG ERAB.

          Article
          PCOMPBIOL-D-12-01251
          10.1371/journal.pcbi.1003026
          3642054
          23658505
          2312e9a7-cd86-474e-b06a-41b97b05e1e3
          Copyright @ 2013

          This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

          History
          : 2 August 2012
          : 25 February 2013
          Page count
          Pages: 12
          Funding
          JRRA, EA and EOG were supported by scholarships from CONACYT and Universidad Nacional Autonoma de Mexico Graduate Programmes. ERAB was funded by CONACYT 81542, 180380, 180098 and PAPIIT IN229009-3 grants, and by the Miller Institute for Basic Research in Science, University of California, Berkeley (UCB). RAB acknowledges financial support from CONACYT through project No. 179616. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
          Categories
          Research Article
          Biology

          Quantitative & Systems biology
          Quantitative & Systems biology

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