title: Design and mathematical modelling of a synthetic symbiotic ecosystem.
abstract: Artificial microbial ecosystems have been increasingly used to understand principles of ecology. These systems offer unique capabilities to mimic a variety of ecological interactions that otherwise would be difficult to study experimentally in a reasonable period of time. However, the elucidation of the genetic bases for these interactions remains a daunting challenge. To address this issue, we have designed and analysed a synthetic symbiotic ecosystem in which the genetic nature of the microbial interactions is defined explicitly. A mathematical model of the gene regulatory network in each species and their interaction through quorum sensing mediated intercellular signalling was derived to investigate the effect of system components on cooperative behaviour. Dynamic simulation and bifurcation analysis showed that the designed system admits a stable coexistence steady state for sufficiently large initial cell concentrations of the two species. The steady-state fraction of each species could be altered by varying model parameters associated with gene transcription and signalling molecule synthesis rates. The design also admitted a stable steady state corresponding to extinction of the two species for low initial cell concentrations and stable periodic solutions over certain domains of parameter space. The mathematical analysis was shown to provide insights into natural microbial ecosystems and to allow identification of molecular targets for engineering system behaviour.
authors.affiliation: Department of Chemical Engineering, University of Massachusetts Amherst, Amherst, MA 01003, USA.
authors.forename: P K R
authors.initials: PK
authors.lastname: Kambam
authors.forename: M A
authors.initials: MA
authors.lastname: Henson
authors.forename: L
authors.initials: L
authors.lastname: Sun
mesh_terms: D018407:Bacterial Physiological Phenomena; D049109:Cell Proliferation; D003198:Computer Simulation; D017753:Ecosystem; D015964:Gene Expression Regulation, Bacterial / Q000502:physiology*; D008954:Models, Biological; D053038:Quorum Sensing / Q000502:physiology*; D013559:Symbiosis / Q000502:physiology*