A neural network model predicts community-level signaling states in a diverse microbial community.

Signal crosstalk within biological communication networks is common, and such crosstalk can have unexpected consequences for decision making in heterogeneous communities of cells. Here we examined crosstalk within a bacterial community composed of five strains of Bacillus subtilis, with each strain producing a variant of the quorum sensing peptide ComX. In isolation, each strain produced one variant of the ComX signal to induce expression of genes associated with bacterial competence. When strains were combined, a mixture of ComX variants was produced resulting in variable levels of gene expression. To examine gene regulation in mixed communities, we implemented a neural network model. Experimental quantification of asymmetric crosstalk between pairs of strains parametrized the model, enabling the accurate prediction of activity within the full five-strain network. Unlike the single strain system in which quorum sensing activated upon exceeding a threshold concentration of the signal, crosstalk within the five-strain community resulted in multiple community-level quorum sensing states, each with a unique combination of quorum sensing activation among the five strains. Quorum sensing activity of the strains within the community was influenced by the combination and ratio of strains as well as community dynamics. The community-level signaling state was altered through an external signal perturbation, and the output state depended on the timing of the perturbation. Given the ubiquity of signal crosstalk in diverse microbial communities, the application of such neural network models will increase accuracy of predicting activity within microbial consortia and enable new strategies for control and design of bacterial signaling networks.

Single-cell variability of growth interactions within a two-species bacterial community.

Cell-cell interaction networks have been examined in many high diversity microbial communities using macroscale approaches. Microscale studies of multispecies communities are lacking and it remains unclear how macroscale trends scale down to small groups of cells. Experimental approaches using microfluidic devices have revealed heterogeneity in the behavior of single cells, however, this analysis has not been extended towards the variability of cell-cell interactions. Using a microwell device, we analyzed cell growth within hundreds of replicate microbial communities consisting of two species and small population sizes. The wells of the devices were inoculated with a coculture of Escherichia coli and Enterobacter cloacae. Each species expressed a unique fluorescent protein enabling simultaneously tracking of cell number for each species over time. Growth dynamics within the device were consistent with bulk measurements. The device enabled monitoring of replicate, isolated coculture populations at high magnification, revealing both the growth interaction between the two species and the variability of such cell-cell interactions within small groups of cells. The device enables new experimental measurements of the heterogeneity of interactions within small, multispecies populations of bacteria.

Quantifying the strength of quorum sensing crosstalk within microbial communities.

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.

Efflux pump gene amplifications bypass necessity of multiple target mutations for resistance against dual-targeting antibiotic.

Antibiotics that have multiple cellular targets theoretically reduce the frequency of resistance evolution, but adaptive trajectories and resistance mechanisms against such antibiotics are understudied. Here we investigate these in methicillin resistant Staphylococcus aureus (MRSA) using experimental evolution upon exposure to delafloxacin (DLX), a novel fluoroquinolone that targets both DNA gyrase and topoisomerase IV. We show that selection for coding sequence mutations and genomic amplifications of the gene encoding a poorly characterized efflux pump, SdrM, leads to high DLX resistance, circumventing the requirement for mutations in both target enzymes. In the evolved populations, sdrM overexpression due to genomic amplifications containing sdrM and two adjacent genes encoding efflux pumps results in high DLX resistance, while the adjacent hitchhiking efflux pumps contribute to streptomycin cross-resistance. Further, lack of sdrM necessitates mutations in both target enzymes to evolve DLX resistance, and sdrM thus increases the frequency of resistance evolution. Finally, sdrM mutations and amplifications are similarly selected in two diverse clinical isolates, indicating the generality of this DLX resistance mechanism. Our study highlights that instead of reduced rates of resistance, evolution of resistance to multi-targeting antibiotics can involve alternate high-frequency evolutionary paths, that may cause unexpected alterations of the fitness landscape, including antibiotic cross-resistance.

Disruption of microbial communication yields a two-dimensional percolation transition.

Bacteria communicate with each other to coordinate macroscale behaviors including pathogenesis, biofilm formation, and antibiotic production. Empirical evidence suggests that bacteria are capable of communicating at length scales far exceeding the size of individual cells. Several mechanisms of signal interference have been observed in nature, and how interference influences macroscale activity within microbial populations is unclear. Here we examined the exchange of quorum sensing signals to coordinate microbial activity over long distances in the presence of a variable amount of interference through a neighboring signal-degrading strain. As the level of interference increased, communication over large distances was disrupted and at a critical amount of interference, large-scale communication was suppressed. We explored this transition in experiments and reaction-diffusion models, and confirmed that this transition is a two-dimensional percolation transition. These results demonstrate the utility of applying physical models to emergence in complex biological networks to probe robustness and universal quantitative features.

Engineering bacteria for biogenic synthesis of chalcogenide nanomaterials.

Microbes naturally build nanoscale structures, including structures assembled from inorganic materials. Here, we combine the natural capabilities of microbes with engineered genetic control circuits to demonstrate the ability to control biological synthesis of chalcogenide nanomaterials in a heterologous host. We transferred reductase genes from both Shewanella sp. ANA-3 and Salmonella enterica serovar Typhimurium into a heterologous host (Escherichia coli) and examined the mechanisms that regulate the properties of biogenic nanomaterials. Expression of arsenate reductase genes and thiosulfate reductase genes in E. coli resulted in the synthesis of arsenic sulfide nanomaterials. In addition to processing the starting materials via redox enzymes, cellular components also nucleated the formation of arsenic sulfide nanomaterials. The shape of the nanomaterial was influenced by the bacterial culture, with the synthetic E. coli strain producing nanospheres and conditioned media or cultures of wild-type Shewanella sp. producing nanofibres. The diameter of these nanofibres also depended on the biological context of synthesis. These results demonstrate the potential for biogenic synthesis of nanomaterials with controlled properties by combining the natural capabilities of wild microbes with the tools from synthetic biology.

Biogenic Control of Manganese Doping in Zinc Sulfide Nanomaterial Using Shewanella oneidensis MR-1.

Bacteria naturally alter the redox state of many compounds and perform atom-by-atom nanomaterial synthesis to create many inorganic materials. Recent advancements in synthetic biology have spurred interest in using biological systems to manufacture nanomaterials, implementing biological strategies to specify the nanomaterial characteristics such as size, shape, and optical properties. Here, we combine the natural synthetic capabilities of microbes with engineered genetic control circuits toward biogenically synthesized semiconductor nanomaterials. Using an engineered strain of Shewanella oneindensis with inducible expression of the cytochrome complex MtrCAB, we control the reduction of manganese (IV) oxide. Cytochrome expression levels were regulated using an inducer molecule, which enabled precise modulation of dopant incorporation into manganese doped zinc sulfide nanoparticles (Mn:ZnS). Thereby, a synthetic gene circuit controlled the optical properties of biogenic quantum dots. These biogenically assembled nanomaterials have similar physical and optoelectronic properties to chemically synthesized particles. Our results demonstrate the promise of implementing synthetic gene circuits for tunable control of nanomaterials made by biological systems.