Network-based approaches to quantify multicellular development

Matthew Jackson, Salva Duran-Nebreda, George Bassel

Research output: Contribution to journalArticlepeer-review

12 Citations (Scopus)
150 Downloads (Pure)

Abstract

Multicellularity and cellular cooperation confer novel functions on organs following a structure–function relationship. How regulated cell migration, division and differentiation events generate cellular arrangements has been investigated, providing insight into the regulation of genetically encoded patterning processes. Much less is known about the higher-order properties of cellular organization within organs, and how their functional coordination through global spatial relations shape and constrain organ function. Key questions to be addressed include: why are cells organized in the way they are? What is the significance of the patterns of cellular organization selected for by evolution? What other configurations are possible? These may be addressed through a combination of global cellular interaction mapping and network science to uncover the relationship between organ structure and function. Using this approach, global cellular organization can be discretized and analysed, providing a quantitative framework to explore developmental processes. Each of the local and global properties of integrated multicellular systems can be analysed and compared across different tissues and models in discrete terms. Advances in high-resolution microscopy and image analysis continue to make cellular interaction mapping possible in an increasing variety of biological systems and tissues, broadening the further potential application of this approach. Understanding the higher-order properties of complex cellular assemblies provides the opportunity to explore the evolution and constraints of cell organization, establishing structure–function relationships that can guide future organ design.
Original languageEnglish
Article number20170484
JournalJournal of The Royal Society Interface
Volume14
Issue number135
DOIs
Publication statusPublished - Oct 2017

Keywords

  • development
  • network science
  • self-organization
  • structure–function
  • complexity
  • multicellularity

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