Bayesian-based decipherment of in-depth information in bacterial chemical sensing beyond pleasant/unpleasant responses

Abstract

AbstractChemical sensing is vital to the survival of all organisms. Bacterial chemotaxis is conducted by multiple receptors that sense chemicals to regulate a single signalling system controlling the transition between the direction (clockwise vs. counterclockwise) of flagellar rotation. Such an integrated system seems better suited to judge chemicals as either favourable or unfavourable, but not for identification purposes though differences in their affinities to the receptors may cause difference in response strength. Here, an experimental setup was developed to monitor behaviours of multiple cells stimulated simultaneously as well as a statistical framework based on Bayesian inferences. Although responses of individual cells varied substantially, ensemble averaging of the time courses seemed characteristic to attractant species, indicating we can extract information of input chemical species from responses of the bacterium. Furthermore, two similar, but distinct, beverages elicited attractant responses of cells with profiles distinguishable with the Bayesian procedure. These results provide a basis for novel bio-inspired sensors that could be used with other cell types to sense wider ranges of chemicals.