Mutations have been investigated for more than a century but never observed directly in single cells, which hampered the characterization of their dynamics and fitness effects. We accomplished this recently in Escherichia coli by developing a new methodology (L. Robert et al. Science).
Our approach for studying mutations is at the single-cell level, in real-time and with high-throughput. It combines microfluidics, time-lapse imaging, automated image analysis, and a fluorescent tag of the mismatch repair system.
We propose here to extend our approach and develop new tools to control quantitatively the mutation dynamics and the selection force acting on the cells during mutation accumulation. We will also develop a dedicated and automated image analysis software.
Thus, we will build an integrated single-cell level system for investigating mutations and evolution through a fine-tuning of the key factors guiding evolutionary changes.