Dynamics of communities and Evolution of Antibiotic Resistance in Wastewater

ended

Environmental antibiotic resistance is a major threat to human and veterinary health and a key issue addressed by the European One Health Action Plan Against Antimicrobial Resistance. City sewers shelter rich and diverse bacterial communities that are continuously exposed to antibiotic residues from human excreta, thus becoming a reservoir of resistance. Predicting the risk of antibiotic resistance evolution in city sewers requires a comprehensive understanding of the dynamics and evolution of wastewater bacterial communities faced to such exposition. However, sewers are complex environments and contain multiple abiotic factors, which may act in non-additive ways. In addition, interactions between species within communities affect growth and consequently competition, through both density- and frequency-dependent processes. By changing the competitive ability of variants, such as antibiotic resistant phenotypes, interspecies interactions also change evolutionary processes. DEAR-Waste aims at understanding the dynamics of communities and antibiotic resistance evolution in city sewers, together with establishing wastewater as a model system for fundamental studies on community dynamics and evolution. DEAR-Waste adopts an interdisciplinary approach, combining high-throughput sequencing technologies, environmental chemistry, microbial ecology and evolution, time-series statistical analysis, and formal modelling. Data from synthetic mesocosms will parametrize the Hutchinsonian niche for population in communities: a tolerance curve mapping species performance onto a complex environmental space defined by the multidimensional abiotic environment and species interactions. Predictions from these curves will be tested against field measurements of microbial and chemical dynamics sampled in city sewers. An evolutionary experiment in similar mesocosms will finally quantify how environmental complexity and interspecies interactions modulate the evolution of antibiotic resistance.