Large-scale-free network organisation is likely key for biofilm phase transition

Abstract

Non-linear Kuramoto model has been used to study synchronised or sync behaviour in numerous fields; however, its application in biology is scarce. Here, the basic model has been introduced and examples where large-scale small-world or scale-free networks are crucial for spontaneous sync have been provide even for low coupling strength. This information was next checked for relevance in living systems where it is now well known that biological networks are scale-free. A recent transcriptome-wide data analysis of a Saccharomyces cerevisiae biofilm showed that low- to middle-expressed genes are key for scale invariance in biology. Together, the current data indicate that a biological network connectivity structure with low coupling strength, or expression levels, is sufficient for sync behaviour. For biofilm regulation, it may, therefore, be necessary to investigate large-scale low-expression genes rather than small-scale high-expression genes.

Keywords

• biology computing
• synchronisation
• data analysis
• complex networks
• molecular biophysics
• biofilm phase transition
• nonlinear kuramoto model
• sync behaviour
• biology
• large-scale small-world
• scale-free networks
• low coupling strength
• living systems
• biological networks
• saccharomyces cerevisiae biofilm
• scale invariance
• biological network connectivity structure
• biofilm regulation
• large-scale low-expression genes
• small-scale high-expression genes
• large scale-free network organisation
• transcriptome-wide data analysis