{"title":"Multidimensional tolerance landscapes reveal antibiotic-environment interactions affecting population dynamics of wastewater bacteria","authors":"Marie Rescan, Meritxell Gros, Carles M. Borrego","doi":"10.1016/j.watres.2025.123720","DOIUrl":null,"url":null,"abstract":"City sewers harbor diverse bacterial communities that are continuously exposed to a myriad of antibiotic residues resulting from human consumption and excretion. Despite their sub-inhibitory concentrations in sewage, these pharmaceutical residues affect the growth rate and the yield of susceptible wastewater-associated bacteria. Moreover, environmental conditions in sewers are complex, including variations in temperature and, in many coastal city sewers, salinity. These variables can modulate antibiotic tolerance and therefore affect the dynamics of microbial populations. To explore such interactions between antibiotics and abiotic environmental factors, we built continuous multivariate tolerance landscapes for three bacterial species commonly detected in sewage: <em>Escherichia coli</em>, the emerging pathogen <em>Streptococcus suis</em>, and a typical sewer dweller, <em>Arcobacter cryaerophilus</em>. We projected their intrinsic growth rate and carrying capacity onto a complex environment including temperature, salinity, and a range of concentrations of two antibiotics frequently measured in urban wastewater (ciprofloxacin and azithromycin). We revealed that antibiotic tolerance was maximal at salinities close to seawater for both <em>E. coli</em> and <em>S. suis</em>, and that the direction of the interaction between antibiotics and temperature is species dependent. In <em>E. coli</em>, we additionally observed a third-order interaction among salinity, temperature and antibiotics, highlighting the limits of predicting field dynamics of bacterial populations using standard laboratory measures. We projected these tolerance curves onto time series data of temperature and conductivity measured in the sewers of Barcelona. Our model highlights that low concentrations of antibiotics could exclude the most sensitive species, while interactions between antibiotics, temperature, and salinity substantially affected the dynamics of the more tolerant ones.","PeriodicalId":443,"journal":{"name":"Water Research","volume":"6 1","pages":""},"PeriodicalIF":11.4000,"publicationDate":"2025-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Water Research","FirstCategoryId":"93","ListUrlMain":"https://doi.org/10.1016/j.watres.2025.123720","RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, ENVIRONMENTAL","Score":null,"Total":0}
引用次数: 0
Abstract
City sewers harbor diverse bacterial communities that are continuously exposed to a myriad of antibiotic residues resulting from human consumption and excretion. Despite their sub-inhibitory concentrations in sewage, these pharmaceutical residues affect the growth rate and the yield of susceptible wastewater-associated bacteria. Moreover, environmental conditions in sewers are complex, including variations in temperature and, in many coastal city sewers, salinity. These variables can modulate antibiotic tolerance and therefore affect the dynamics of microbial populations. To explore such interactions between antibiotics and abiotic environmental factors, we built continuous multivariate tolerance landscapes for three bacterial species commonly detected in sewage: Escherichia coli, the emerging pathogen Streptococcus suis, and a typical sewer dweller, Arcobacter cryaerophilus. We projected their intrinsic growth rate and carrying capacity onto a complex environment including temperature, salinity, and a range of concentrations of two antibiotics frequently measured in urban wastewater (ciprofloxacin and azithromycin). We revealed that antibiotic tolerance was maximal at salinities close to seawater for both E. coli and S. suis, and that the direction of the interaction between antibiotics and temperature is species dependent. In E. coli, we additionally observed a third-order interaction among salinity, temperature and antibiotics, highlighting the limits of predicting field dynamics of bacterial populations using standard laboratory measures. We projected these tolerance curves onto time series data of temperature and conductivity measured in the sewers of Barcelona. Our model highlights that low concentrations of antibiotics could exclude the most sensitive species, while interactions between antibiotics, temperature, and salinity substantially affected the dynamics of the more tolerant ones.
期刊介绍:
Water Research, along with its open access companion journal Water Research X, serves as a platform for publishing original research papers covering various aspects of the science and technology related to the anthropogenic water cycle, water quality, and its management worldwide. The audience targeted by the journal comprises biologists, chemical engineers, chemists, civil engineers, environmental engineers, limnologists, and microbiologists. The scope of the journal include:
•Treatment processes for water and wastewaters (municipal, agricultural, industrial, and on-site treatment), including resource recovery and residuals management;
•Urban hydrology including sewer systems, stormwater management, and green infrastructure;
•Drinking water treatment and distribution;
•Potable and non-potable water reuse;
•Sanitation, public health, and risk assessment;
•Anaerobic digestion, solid and hazardous waste management, including source characterization and the effects and control of leachates and gaseous emissions;
•Contaminants (chemical, microbial, anthropogenic particles such as nanoparticles or microplastics) and related water quality sensing, monitoring, fate, and assessment;
•Anthropogenic impacts on inland, tidal, coastal and urban waters, focusing on surface and ground waters, and point and non-point sources of pollution;
•Environmental restoration, linked to surface water, groundwater and groundwater remediation;
•Analysis of the interfaces between sediments and water, and between water and atmosphere, focusing specifically on anthropogenic impacts;
•Mathematical modelling, systems analysis, machine learning, and beneficial use of big data related to the anthropogenic water cycle;
•Socio-economic, policy, and regulations studies.