↓ Skip to main content

PLOS

Branch Mode Selection during Early Lung Development

Overview of attention for article published in PLoS Computational Biology, February 2012
Altmetric Badge

Mentioned by

twitter
1 X user
facebook
1 Facebook page

Readers on

mendeley
92 Mendeley
Title
Branch Mode Selection during Early Lung Development
Published in
PLoS Computational Biology, February 2012
DOI 10.1371/journal.pcbi.1002377
Pubmed ID
Authors

Denis Menshykau, Conradin Kraemer, Dagmar Iber

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.

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 92 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 3 3%
Unknown 89 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 20 22%
Researcher 17 18%
Student > Bachelor 11 12%
Student > Master 11 12%
Professor > Associate Professor 9 10%
Other 12 13%
Unknown 12 13%
Readers by discipline Count As %
Agricultural and Biological Sciences 30 33%
Biochemistry, Genetics and Molecular Biology 14 15%
Medicine and Dentistry 7 8%
Mathematics 6 7%
Physics and Astronomy 6 7%
Other 16 17%
Unknown 13 14%