Abstract
New small-scale, low-cost bioreactors provide researchers with exquisite control of environmental parameters of microbial cultures over long durations, allowing them to perform sophisticated, high-quality quantitative experiments that are particularly useful in systems biology, synthetic biology and bioengineering. However, existing setups are limited in their automated measurement capabilities, primarily because sensitive and specific measurements require bulky, expensive, stand-alone instruments. Here, we present ReacSight, a generic and flexible strategy to enhance bioreactor arrays for automated measurements and reactive experiment control. On the hardware side, ReacSight leverages a pipetting robot for sample collection, handling and loading. On the software side, ReacSight provides a versatile instrument control architecture and a generic event system for reactive experiment control. ReacSight is ideally suited to integrate open-source, open-hardware components but can also accommodate closed-source, GUI-only components (e.g. cytometers). We use ReacSight to assemble a platform for cytometry-based characterization and reactive optogenetic control of parallel yeast continuous cultures. Using a dedicated bioreactor array, we showcase its capabilities on three applications. First, we achieve parallel real-time control of gene expression with light in different bioreactors. Second, we explore the impact of nutrient scarcity on fitness and cellular stress using well-controlled, high-information content competition assays. Third, we exploit nutrient scarcity to achieve dynamic control over the composition of a two-strain consortium. To illustrate the genericity of ReacSight, we also assemble an equivalent platform using the optogenetic-ready, open-hardware and commercially available Chi.Bio bioreactors.
Competing Interest Statement
The authors have declared no competing interest.
Footnotes
Genericity of ReacSight further demonstrated via the construction of another platform using Chi.Bio reactors, additional case study: dynamic control of the composition of a two-strain consortium.