July 08, 2022
Bulletin interne de l'Institut Pasteur
ReacSight: a software solution to automate experiments in your lab in a flexible, reactive and affordable manner
Researchers in the InBio team* have developed ReacSight, a Python software solution to enhance sensitive measurement devices (plate-readers, cytometers, etc.) with pipetting capabilities and to create reactive bioreactor-based platforms having real-time sampling and analysis capabilities. Automation improves throughput and reproducibility of experiments.
Small-scale, low-cost bioreactors are emerging as powerful tools for microbial systems and synthetic biology research. They allow tight control of cell culture parameters (e.g. temperature, cell density, media renewal rate) over long periods (several days). These unique features enable researchers to perform sophisticated experiments and to achieve high experimental reproducibility.
However, existing setups are limited in their measurement capabilities. It is often essential to monitor key characteristics of the cultured cell population over time, such as gene expression levels, cellular stress levels, cell size and morphology, cell cycle progression, proportions of different genotypes or phenotypes. Researchers usually need to manually extract, process and measure culture samples to run them through sensitive and specialized instruments. Manual procedures are tedious, error-prone, and significantly limit the available temporal resolution and reactiveness.
Researchers in the InBio team, an Inria–Institut Pasteur joint research group, have developed ReacSight, a generic and flexible strategy to enhance bioreactor arrays for automated measurements and reactive experiment control [1]. It can also be used to enhance any computer-controlled plate-based measurement device with pipetting capabilities and automation. ReacSight leverages the affordable Opentrons pipetting robots. It is ideally suited to integration of open-source, open-hardware components but can also accommodate closed-source, GUI-only components (e.g. cytometers). Several applications can be found in [1] and [2]. For example, combining bioreactors, a pipetting robot and a cytometer, and using optogenetics in yeast, they controlled gene expression in real-time with high precision and created an artificial consortium with tuneable composition. Also, connecting a plate-reader with a pipetting robot, they created a “mini-turbidostat” system and investigated the effect of repeated antimicrobial treatments on bacterial isolates.
Automated platforms increase throughput. For example, cytometry measurements can be taken every 2 hours over 5 days for 8 bioreactors running in parallel. But automation also improves reactiveness. For example, warning or error messages can be posted on the Discord messaging platform to contact the user on their computer or phone in real-time. Smart experiments can also be done in which the experiment plan is not determined at the beginning of the experiment but is dynamically updated based on the data collected. Lastly, automation improves documentation quality and facilitates troubleshooting and reproducibility. The team is currently extending the software to connect it with the Institut Pasteur's eLabJournal solution.
In the same spirit, the InBio team has developed MicroMator, another software tool to automate experiments. It streamlines the use of Micromanager and enables the realization of smart, reactive microscopy experiments [3]. MicroMator also fosters throughput, reproducibility and reactivity.
Do not hesitate to contact the InBio team for any questions you might have on the implementation of reactive experimental platforms for your research.
Contact: gregory.batt@inria.fr
*the InBio – Experimental and Computational Methods for Modeling Cellular Processes team
ReacSight: a strategy to enhance bioreactor arrays for automated measurements and reactive experiment control