Biology subjects

Emonet, T.

Publications and source records attributed to Emonet, T..

2 recordsLinked to original sources

bioRxiv2018

Spatial Self-Organization Resolves Conflicts Between Individuality and Collective Migration

Collective behavior can spontaneously emerge when individuals follow common rules of interaction. However, the behavior of each individual will differ due to existing genetic and non-genetic variation within the population. It remains unclear how this individuality is managed to achieve collective behavior. We quantified individuality in bands of clonal Escherichia coli cells that migrate collectively along a channel by following a self-generated gradient of attractant. We discovered that despite substantial differences in individual chemotactic abilities, the cells are able to migrate as a coherent group by spontaneously sorting themselves within the moving band. This sorting mechanism ensures that differences between individual chemotactic abilities are compensated by differences in the local steepness of the traveling gradient each individual must navigate, and determines the minimum performance required to travel with the band. By resolving conflicts between individuality and collective migration, this mechanism enables populations to maintain advantageous diversity while on the move.

biophysics↗

bioRxiv2017

Generation And Attenuation Of Variability In A Bacterial Signalling Network Revealed By Single-Cell FRET

We present in vivo single-cell FRET measurements in the Escherichia coli chemotaxis system that reveal pervasive signaling variability, both across cells in isogenic populations and within individual cells over time. We quantify cell-to-cell variability of adaptation, ligand response, as well as steady-state output level, and analyze the role of network design in shaping this diversity from gene expression noise. In the absence of changes in gene expression, we find that single cells demonstrate strong temporal fluctuations. We provide evidence that such signaling noise can arise from at least two sources: (i) stochastic activities of adaptation enzymes, and (ii) receptor-kinase dynamics in the absence of adaptation. We demonstrate that under certain conditions, (ii) can generate giant fluctuations that drive signaling activity of the entire cell into a stochastic two-state switching regime. Our findings underscore the importance of molecular noise, arising not only in gene expression but also in protein networks.

systems biology↗