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      Branch Mode Selection during Early Lung Development

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          Abstract

          Many organs of higher organisms, such as the vascular system, lung, kidney, pancreas, liver and glands, are heavily branched structures. The branching process during lung development has been studied in great detail and is remarkably stereotyped. The branched tree is generated by the sequential, non-random use of three geometrically simple modes of branching (domain branching, planar and orthogonal bifurcation). While many regulatory components and local interactions have been defined an integrated understanding of the regulatory network that controls the branching process is lacking. We have developed a deterministic, spatio-temporal differential-equation based model of the core signaling network that governs lung branching morphogenesis. The model focuses on the two key signaling factors that have been identified in experiments, fibroblast growth factor (FGF10) and sonic hedgehog (SHH) as well as the SHH receptor patched (Ptc). We show that the reported biochemical interactions give rise to a Schnakenberg-type Turing patterning mechanisms that allows us to reproduce experimental observations in wildtype and mutant mice. The kinetic parameters as well as the domain shape are based on experimental data where available. The developed model is robust to small absolute and large relative changes in the parameter values. At the same time there is a strong regulatory potential in that the switching between branching modes can be achieved by targeted changes in the parameter values. We note that the sequence of different branching events may also be the result of different growth speeds: fast growth triggers lateral branching while slow growth favours bifurcations in our model. We conclude that the FGF10-SHH-Ptc1 module is sufficient to generate pattern that correspond to the observed branching modes.

          Author Summary

          Most organs of higher organisms, such as the vascular system, lung, kidney, pancreas, liver and glands, are heavily branched structures. The branching process during lung development has been studied in great detail and is remarkably stereotyped. The branched tree is generated by the sequential, non-random use of three geometrically simple modes of branching. While the branching sequence is identical in mice of identical genetic background it differs between mouse strains. This suggests that the positioning of branch points and the type of branching sensitively depends on information encoded in the genome. Encoding every branching point independently in the genome would require a large number of genes, and it is more likely that a recursive, self-organized process exists that determines the patterning. While many regulatory molecules have been identified an integrated understanding of the regulatory network (program) is missing. Based on available experimental data we have developed a model for lung branching. The model correctly predicts branching phenotypes in mutants and suggests that also the growth speed of the lung tip can affect the positioning and type of the next branching event.

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          Most cited references74

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          Electrochemical Methods: Fundamentals and Applications

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            Reaction-diffusion model as a framework for understanding biological pattern formation.

            The Turing, or reaction-diffusion (RD), model is one of the best-known theoretical models used to explain self-regulated pattern formation in the developing animal embryo. Although its real-world relevance was long debated, a number of compelling examples have gradually alleviated much of the skepticism surrounding the model. The RD model can generate a wide variety of spatial patterns, and mathematical studies have revealed the kinds of interactions required for each, giving this model the potential for application as an experimental working hypothesis in a wide variety of morphological phenomena. In this review, we describe the essence of this theory for experimental biologists unfamiliar with the model, using examples from experimental studies in which the RD model is effectively incorporated.
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              Fgf10 is essential for limb and lung formation.

              The interactions between fibroblast growth factors (FGF) and their receptors have important roles in mediating mesenchymal-epithelial cell interactions during embryogenesis. In particular, Fgf10 is predicted to function as a regulator of brain, lung and limb development on the basis of its spatiotemporal expression pattern in the developing embryo. To define the role of Fgf10, we generated Fgf10-deficient mice. Fgf10-/- mice died at birth due to the lack of lung development. Trachea was formed, but subsequent pulmonary branching morphogenesis was disrupted. In addition, mutant mice had complete truncation of the fore- and hindlimbs. In Fgf10-/- embryos, limb bud formation was initiated but outgrowth of the limb buds did not occur; however, formation of the clavicles was not affected. Analysis of the expression of marker genes in the mutant limb buds indicated that the apical ectodermal ridge (AER) and the zone of polarizing activity (ZPA) did not form. Thus, we show here that Fgf10 serves as an essential regulator of lung and limb formation.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS Comput Biol
                plos
                ploscomp
                PLoS Computational Biology
                Public Library of Science (San Francisco, USA )
                1553-734X
                1553-7358
                February 2012
                February 2012
                16 February 2012
                : 8
                : 2
                : e1002377
                Affiliations
                [1 ]Department for Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
                [2 ]SIB, Basel, Switzerland
                University of Auckland, New Zealand
                Author notes

                Conceived and designed the experiments: DI CK DM. Performed the experiments: DM. Analyzed the data: DM. Contributed reagents/materials/analysis tools: DM CK DI. Wrote the paper: DI DM.

                Article
                PCOMPBIOL-D-11-01050
                10.1371/journal.pcbi.1002377
                3280966
                22359491
                eb80fc81-781e-4a28-9ec4-b87a53d3fb90
                Menshykau et al. 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
                : 19 July 2011
                : 20 December 2011
                Page count
                Pages: 12
                Categories
                Research Article
                Biology
                Computational Biology
                Developmental Biology
                Organism Development

                Quantitative & Systems biology
                Quantitative & Systems biology

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