TY - JOUR T1 - Enhanced Population Control in Synthetic Bacterial Consortium by Interconnected Carbon Cross-Feeding JF - bioRxiv DO - 10.1101/717926 SP - 717926 AU - Pauli S. Losoi AU - Ville P. Santala AU - Suvi M. Santala Y1 - 2019/01/01 UR - http://biorxiv.org/content/early/2019/07/29/717926.abstract N2 - Engineered microbial consortia can provide several advantages over monocultures in terms of utilization of mixed substrates, resistance to perturbations, and division of labor in complex tasks. However, maintaining stability, reproducibility, and control over population levels in variable conditions can be challenging in multi-species cultures. In our study, we modeled and constructed a synthetic symbiotic consortium with a genetically encoded carbon cross-feeding system. The system is based on strains of Escherichia coli and Acinetobacter baylyi ADP1, both engineered to be incapable of growing on glucose on their own. In a culture supplemented with glucose as the sole carbon source, growth of the two strains is afforded by the exchange of gluconate and acetate, resulting in inherent control over carbon availability and population balance. We investigated the system robustness in terms of stability and population control under different inoculum ratios, substrate concentrations, and cultivation scales, both experimentally and by modeling. To illustrate how the system might facilitate division of genetic circuits among synthetic microbial consortia, a green fluorescent protein sensitive to pH and a slowly-maturing red fluorescent protein were expressed in the consortium as measures of a circuit’s susceptibility to external and internal variability, respectively. The symbiotic consortium maintained stable and linear growth and circuit performance regardless of the initial substrate concentration or inoculum ratios. The developed cross-feeding system provides simple and reliable means for population control without expression of non-native elements or external inducer addition, being potentially exploitable in consortia applications involving precisely defined cell tasks or division of labor. ER -