New approaches to deal with drug-resistant pathogenic bacteria are urgent. We studied the antibacterial effect of chitosans against an Escherichia coli quorum sensing biosensor reporter strain and selected a non-toxic chitosan to evaluate its quorum sensing (QS) inhibition activity and its effect on bacterial aggregation. To this end, chitosans of varying degree of acetylation (DA) (12 to 69%) and molecular weight (M_w) (29 to 288 kDa) were studied. Only chitosans of low DA (~12%) inhibited bacterial growth, regardless of their M_w. A chitosan with medium degree of polymerization (named MDP) DA30, with experimental DA 42% and M_w 115 kDa was selected for further QS inhibition and scanning electron microscopy (SEM) imaging studies. MDP DA30 chitosan exhibited QS inhibition activity in an inverse dose-dependent manner (≤12.5 µg/mL). SEM images revealed that this chitosan, when added at low concentration (≤30.6 µg/mL), induced substantial bacterial aggregation, whereas at high concentration (234.3 µg/mL), it did not. Aggregation explains the QS inhibition activity as the consequence of retardation of the diffusion of N-acylated homoserine lactones (AHLs).

Quorum sensing (QS) explains a type of bacterial cell-cell communication mediated by exocellular compounds that act as autoinducers (AIs). As such, QS can be considered the most primordial form of language. QS has profound implications for the control of many important traits ( e.g. biofilm formation, secretion of virulence factors, etc.). Conceptually, the QS response can be split into its “listening” and “speaking” components, i.e. the power to sense AI levels vs. the ability to synthesize and release these molecules. By explaining the cell-density dependence of QS behavior as the consequence of the system’s arrival to a threshold AI concentration, models of QS have traditionally assumed a salient role for the “QS speaking” module during bacterial cell-to-cell communication. In this paper, we have provided evidence that challenges this AI-centered view of QS and establishes LuxR-like activators at the center of QS. Our observation that highly coordinated, cell-density dependent responses can occur in the absence of AI production, implies that the ability to launch such responses is engrained within the “QS listening” module. Our data indicates that once a critical threshold of intracellular activator monomers in complex with AI is reached, a highly orchestrated QS response ensues. While displaying a clear cell-density dependence, such response does not strictly require the sensing of population levels by individual cells. We additionally show, both in vivo and in silico , that despite their synchronous nature, QS responses do not require that all the cells in the population participate in the response. Central to our analysis was the discovery that percolation theory (PT) can be used to mathematically describe QS responses. While groundbreaking, our results are in agreement with and integrate the latest conclusions reached in the field. We explain for the first time, the cell-density-dependent synchronicity of QS responses as the function of a single protein, the LuxR-like activator, capable of coordinating the temporal response of a population of cells in the absence of cell-to-cell communication. Being QS the most primordial form of speech, our results have important implications for the evolution of language in its ancient chemical form. Abbreviations: 3D three dimensional a _c wthreshold intracellular concentration of activator molecules AHL acyl-homoserine lactone AHL _fisch N-(3-oxohexanoyl)-L-homoserine lactone AHL _viol N-hexanoyl-DL-homoserine-lactone AI autoinducer a.u arbitrary units BMB bromophenol blue CA trans-cinnamaldehyde Fl fluorescence intensity FI/OD600 density-normalized fluorescence intensity GFP green fluorescent protein M _w molecular weight PT percolation theory QS quorum sensing t _c percolation critical time wt wild type