Quantifying the strength of quorum sensing crosstalk within microbial communities

Abstract

In multispecies microbial communities, the exchange of signals such as acyl-homoserine lactones (AHL) enables communication within and between species of Gram-negative bacteria. This process, commonly known as quorum sensing, aids in the regulation of genes crucial for the survival of species within heterogeneous populations of microbes. Although signal exchange was studied extensively in well-mixed environments, less is known about the consequences of crosstalk in spatially distributed mixtures of species. Here, signaling dynamics were measured in a spatially distributed system containing multiple strains utilizing homologous signaling systems. Crosstalk between strains containing the lux, las and rhl AHL-receptor circuits was quantified. In a distributed population of microbes, the impact of community composition on spatio-temporal dynamics was characterized and compared to simulation results using a modified reaction-diffusion model. After introducing a single term to account for crosstalk between each pair of signals, the model was able to reproduce the activation patterns observed in experiments. We quantified the robustness of signal propagation in the presence of interacting signals, finding that signaling dynamics are largely robust to interference. The ability of several wild isolates to participate in AHL-mediated signaling was investigated, revealing distinct signatures of crosstalk for each species. Our results present a route to characterize crosstalk between species and predict systems-level signaling dynamics in multispecies communities.

Disruption of microbial communication yields a two-dimensional percolation transition

“…With the recent advances in systems and molecular biology, many new studies are being conducted to understand the complex behaviors of microbes that arise due to cellular and spatial heterogeneity [9,[26][27][28][41][42][43][44]. Several studies have shown that many cellular systems exhibit emergent phenomena previously studied in non-biological contexts and that can be explained using physical and statistical mechanical rules [45][46][47][48].…”

“…We developed a model that captured the dynamics of signal exchange and cell growth. The growth of the cells is modeled with a logistic growth equation [9,26],…”

“…GGA GAA AGG TAC CGC AAT GAC AGT AAA GAA ACT TTA TTT CAT CCC AG pZE_AiiA_R The reverse primer of the above. GAC TCA GCT AAT TAA GCT TTT ACG CTG CAA GGG CGT AAT TTT C B. Bacterial growth conditions Similar to Silva et al [9], the cells were grown in 5ml of Lysogenic broth (LB) which were in 14mL Falcon tubes with appropriate antibiotics for plasmid maintenance. The cultures were put into a shaker at 200 RPM and 37 o C. Cells were grown in liquid culture for 16 hours.…”

“…From a physics perspective, such multispecies communities offer a novel context in which to discover and characterize emergent, collective phenomena in strongly interacting many-body networks [9][10][11][12][13]. One particularly notable and relevant example of such collective behavior is percolation, where networks display an abrupt transition in large-scale global connectivity at a critical threshold of a varying parameter, typically occupation probability.…”

“…Quorum sensing (QS) regulates several collective, group-level behaviors, including pathogenesis [21,22], biofilm formation [23], antibiotic production [1,24,25], and bioluminescence [20]. Empirical evidence suggests that these behaviors can span large distances [9,20,26] .…”