The main objective of the project is to develop technics and study social interactions between pathogenic bacteria at the single-cell level. We were successful in achieving our aims. On the technical side, we developed: (i) experimental protocols that allow us to follow behavioural interaction and gene expression patterns of individual bacteria over time using fluorescent microscopy and flow cytometry; (ii) a pipeline for automated high-throughput image analysis; and (iii) a individual-based simulation platform, where we can study bacterial interactions in silico and parameterise our mathematical models with data from experiments. In addition, we established a microscopy protocol to study interactions between pathogenic bacteria within a living host (i.e. the nematode Caenorhabditis elegans).
On the scientific side, we applied these techniques and protocols to conduct a number of innovative studies. Below, there is a brief overview of our main achievements.
(a) We used gene-expression reporters combined with single-cell microscopy to study social interactions in Pseudomonas aeruginosa, an important opportunistic pathogen. In particular, we focussed on the sharing of beneficial compounds secreted by bacteria and shared between group members. We examined the physical boundaries of siderophore sharing (Weigert and Kümmerli 2017 Proc B), optimality patterns in compound production and sharing (Schiessl et al. 2019 Evolution), how group-coordinated behaviour can help in competition against other species (Leinweber et al. 2018 Evolution), and how individual bacteria coordinate their actions at the group level (Mridha & Kümmerli 2021 bioRxiv).
(b) We used gene-expression reporters combined with flow cytometry to explore chemical communication between individual bacteria of P. aeruginosa. We discovered that bacteria in a clonal population, albeit coordinating their actions overall, take different communication trajectories over time (Jayakumar et al. 2021 bioRxiv).
(c) We developed an agent-based modelling platform that allows us to study social interactions between bacterial individuals in silico (Wechsler et al. 2019 J Evol Biol). The platform is particularly useful when parameterized with data from experiments. This is what we did in a study on Bacillus subtilis, where we could demonstrate the costs and benefits of division of labor over biofilm matrix production (Dragos et al. 2018 Current Biology).
(d) We used single-time laps microscopy to analyze competitive behaviors and its fitness consequences between the two bacterial pathogens P. aeruginosa and Staphylococcus aureus. This project demonstrates the power of the single-cell perspective to unravel unknown patterns of microbe-microbe interactions (Niggli et al. 2021 Front. Cell. Infect. Microbiol.)
(e) We used the established host-pathogen system to study how social interactions drive virulence evolution (Granato et al. 2018 ISME J), and how bacteria colonize and interact inside the living host (Rezzoagli et al. 2019 ISME J).
(f) Two avenues of applied applications/exploitations arose from the above work. First, we showed that siderophore-based interactions are relevant in the plant rhizosphere and we have identified plant-beneficial bacteria that can protect crop plants from infections due to their siderophore actions (Gu et al. 2020 Nat Microbiol). Second, we showed that treatments that target bacterial social interactions (siderophore sharing and chemical communication) can synergize with antibiotics and even revert selection for antibiotic resistance (Rezzoagli et al. 2020 PLoS Biol).
