Periodic Reporting for period 1 - DEAR-Waste (Dynamics of communities and Evolution of Antibiotic Resistance in Wastewater)
Reporting period: 2022-09-01 to 2024-08-31
Environmental antibiotic resistance poses a significant threat to both human and veterinary health, making it a central focus of the European One Health Action Plan Against Antimicrobial Resistance. Urban sewers, rich in diverse bacterial communities, are constantly exposed to antibiotic residues from human waste. This exposure creates a reservoir of antibiotic-resistant bacteria. To predict the evolution of antibiotic resistance in these environments, it is essential to understand the dynamics of wastewater bacterial communities exposed to antibiotics. However, the complexity of sewer environments, which contain multiple interacting abiotic factors, complicates such predictions. These factors may interact in non-additive ways, further influencing the evolutionary landscape. Additionally, interactions between bacterial species within the sewer microbiome affect growth and competition, operating through both density- and frequency-dependent processes. These interspecies interactions can alter the competitive fitness of antibiotic-resistant strains, thereby influencing evolutionary outcomes.
The DEAR-Waste project seeks to unravel these complexities by studying the dynamics of bacterial communities and antibiotic resistance evolution in urban sewers. The project also aims to establish wastewater as a valuable model system for fundamental research on community dynamics and microbial evolution. By exploring how diverse factors within sewers interact to drive resistance, DEAR-Waste contribute valuable insights for managing antibiotic resistance, ultimately supporting efforts to protect public and veterinary health.
The DEAR-Waste project seeks to unravel these complexities by studying the dynamics of bacterial communities and antibiotic resistance evolution in urban sewers. The project also aims to establish wastewater as a valuable model system for fundamental research on community dynamics and microbial evolution. By exploring how diverse factors within sewers interact to drive resistance, DEAR-Waste contribute valuable insights for managing antibiotic resistance, ultimately supporting efforts to protect public and veterinary health.
To analyze the effects of interactions between abiotic environmental parameters and antibiotics, three isolated bacterial species (E. coli, A. cryaerophilus, and S. suis) were exposed to cross-factor combinations of salinity, temperature, and either azithromycin or ciprofloxacin. The population density was measured by photospectrometry, and the resulting data were used to parameterize a generalized tolerance curve, mapping growth proxies (r and K) onto a multidimensional space defined by these environmental parameters.
This multidimensional tolerance curve was then projected onto temperature and conductivity measurements sampled in two Barcelona sewer to predict the population dynamics of these three species under realistic conditions, with or without the presence of environmental concentrations of antibiotics.
We subsequently quantified how environmental abiotic parameters influenced interspecies interactions and how these interactions, in turn, affected tolerance to abiotic conditions. This was achieved by monitoring the same species within synthetic communities of up to three species. Their frequency and density were tracked via flow cytometry, using two markers to differentiate them by genome size and GRAM status.
To dissect the interactions between temperature, salinity, and antibiotics, RNA from E. coli was extracted and sequenced following exposure to cross-factor conditions involving these three variables. Bioinformatic and statistical analyses were then conducted to relate environmental parameter values to gene expression plasticity and fitness in these complex environments.
This multidimensional tolerance curve was then projected onto temperature and conductivity measurements sampled in two Barcelona sewer to predict the population dynamics of these three species under realistic conditions, with or without the presence of environmental concentrations of antibiotics.
We subsequently quantified how environmental abiotic parameters influenced interspecies interactions and how these interactions, in turn, affected tolerance to abiotic conditions. This was achieved by monitoring the same species within synthetic communities of up to three species. Their frequency and density were tracked via flow cytometry, using two markers to differentiate them by genome size and GRAM status.
To dissect the interactions between temperature, salinity, and antibiotics, RNA from E. coli was extracted and sequenced following exposure to cross-factor conditions involving these three variables. Bioinformatic and statistical analyses were then conducted to relate environmental parameter values to gene expression plasticity and fitness in these complex environments.
Data from controlled laboratory experiments were used to parameterize a quantitative Hutchinsonian niche, mapping species performance across a multidimensional environmental space, for three bacterial species commonly found in city sewers. Temperature and salinity could reduce antibiotic fitness effects by up to 100-fold. Under sewer-specific conditions of temperature and salinity, environmental antibiotic concentrations should exclude certain species, with fluctuations in these abiotic parameters exerting much stronger effects in the presence of antibiotics than in their absence.
A new protocol was developed to track the frequency of specific species within synthetic communities via flow cytometry.
Transcriptomic analysis revealed novel pathways of antibiotic tolerance activated by temperature and salinity. These findings suggest a strong impact of the abiotic environment on the dynamics of antibiotic resistance evolution. Further research is needed to assess the extent of this impact in the environment.
A new protocol was developed to track the frequency of specific species within synthetic communities via flow cytometry.
Transcriptomic analysis revealed novel pathways of antibiotic tolerance activated by temperature and salinity. These findings suggest a strong impact of the abiotic environment on the dynamics of antibiotic resistance evolution. Further research is needed to assess the extent of this impact in the environment.