Bayesian inference of agent-based models: a tool for studying kidney branching morphogenesis

Ben Lambert, Adam L. MacLean, Alexander G. Fletcher, Alexander N. Combes, Melissa H. Little, Helen M. Byrne

Research output: Contribution to journalArticleResearchpeer-review

9 Citations (Scopus)

Abstract

The adult mammalian kidney has a complex, highly-branched collecting duct epithelium that arises as a ureteric bud sidebranch from an epithelial tube known as the nephric duct. Subsequent branching of the ureteric bud to form the collecting duct tree is regulated by subcellular interactions between the epithelium and a population of mesenchymal cells that surround the tips of outgrowing branches. The mesenchymal cells produce glial cell-line derived neurotrophic factor (GDNF), that binds with RET receptors on the surface of the epithelial cells to stimulate several subcellular pathways in the epithelium. Such interactions are known to be a prerequisite for normal branching development, although competing theories exist for their role in morphogenesis. Here we introduce the first agent-based model of ex vivo kidney uretic branching. Through comparison with experimental data, we show that growth factor-regulated growth mechanisms can explain early epithelial cell branching, but only if epithelial cell division depends in a switch-like way on the local growth factor concentration; cell division occurring only if the driving growth factor level exceeds a threshold. We also show how a recently-developed method, “Approximate Approximate Bayesian Computation”, can be used to infer key model parameters, and reveal the dependency between the parameters controlling a growth factor-dependent growth switch. These results are consistent with a requirement for signals controlling proliferation and chemotaxis, both of which are previously identified roles for GDNF.

Original languageEnglish
Pages (from-to)1673-1697
Number of pages25
JournalJournal of Mathematical Biology
Volume76
Issue number7
DOIs
Publication statusPublished - 1 Jun 2018
Externally publishedYes

Keywords

  • Cellular automaton
  • Developmental processes
  • Mathematical modelling
  • Morphology
  • Organogenesis

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