Shaping bacterial population behavior through computer-interfaced control of individual cells
Year: 2017
Type: article
Abstract: Bacteria in groups vary individually, and interact with other bacteria and the environment to produce population-level patterns of gene expression. Investigating such behavior in detail requires measuring and controlling populations at the single-cell level alongside precisely specified interactions and environmental characteristics. Here we present an automated, programmable platform that combines image-based gene expression and growth measurements with on-line optogenetic expression control for hundreds of individual Escherichia coli cells over days, in a dynamically adjustable environment. This integrated platform broadly enables experiments that bridge individual and population behaviors. We demonstrate: (i) population structuring by independent closed-loop control of gene expression in many individual cells, (ii) cell-cell variation control during antibiotic perturbation, (iii) hybrid bio-digital circuits in single cells, and freely specifiable digital communication between individual bacteria. These examples showcase the potential for real-time integration of theoretical models with measurement and control of many individual cells to investigate and engineer microbial population behavior.
Source: Nature Communications
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $4,788
Awards: G1536877525, G3207356259, G393177772, Biophysics of information processing in gene regulation, Des modèles de population aux populations de modèles: observation, modélisation et contrôle de l'expression génique au niveau de la cellule unique, G5702163051, International IST Postdoctoral Fellowship Programme, G7240651115, G7428494302, Computer aided Control of Gene Expression, Mixed-Effects Models of Intracellular Processes: Methods, Tools and Applications
OpenAlex ID: W2767587403