Open AccessModeling population dynamics in a microbial consortium under control of a synthetic pheromone‐mediated communication system
Author(s) -
Hoffmann Andreas,
Haas Christiane,
Hennig Stefan,
Ostermann Kai,
Bley Thomas,
Löser Christian,
Walther Thomas
Publication year - 2019
Publication title -
engineering in life sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.547
H-Index - 57
eISSN - 1618-2863
pISSN - 1618-0240
DOI - 10.1002/elsc.201800107
Subject(s) - population , bioreactor , pheromone , biology , computational biology , saccharomyces cerevisiae , biochemical engineering , biomass (ecology) , strain (injury) , biological system , microbiology and biotechnology , biochemistry , yeast , genetics , ecology , engineering , botany , demography , anatomy , sociology
Microbial consortia can be used to catalyze complex biotransformations. Tools to control the behavior of these consortia in a technical environment are currently lacking. In the present study, a synthetic biology approach was used to build a model consortium of two Saccharomyces cerevisiae strains where growth and expression of the fluorescent marker protein EGFP by the receiver strain is controlled by the concentration of α‐factor pheromone, which is produced by the emitter strain. We have developed a quantitative experimental and theoretical framework to describe population dynamics in the model consortium. We measured biomass growth and metabolite production in controlled bioreactor experiments, and used flow cytometry to monitor changes of the subpopulations and protein expression under different cultivation conditions. This dataset was used to parameterize a segregated mathematical model, which took into account fundamental growth processes, pheromone‐induced growth arrest and EGFP production, as well as pheromone desensitization after extended exposure. The model was able to predict the growth dynamics of single‐strain cultures and the consortium quantitatively and provides a basis for using this approach in actual biotransformations.