Particle-attached riverine bacteriome shifts in a pollutant-resistant and pathogenic community during a Mediterranean extreme storm event
2020
Noyer, Mégane | Reoyo-Prats, Brice | Bernard, Maria | Verneau, Olivier | Palacios, Carmen | Centre de Formation et de Recherche sur les Environnements Méditérranéens (CEFREM) ; Université de Perpignan Via Domitia (UPVD)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS) | Génétique Animale et Biologie Intégrative (GABI) ; AgroParisTech-Université Paris-Saclay-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE) | Ecole Doctorale Energie et Environnement (E2-UPVD) 2014-ED.305-05 2017-19-ED.305 | Region Occitanie | DEBiMicro (2013 BQR CEFREM) | StepBiodiv (2015-2017 VEOLIA-Eau Perpignan) | DEBi2Micro (2016-17 EC2CO CNRS INSU)
International audience
Mostrar más [+] Menos [-]Inglés. Rivers are representative of the overall contamination found in their catchment area. Contaminant concentrations in watercourses depend on numerous factors including land use and rainfall events. Globally, in Mediterranean regions, rainstorms are at the origin of fluvial multipollution phenomena as a result of Combined Sewer Overflows (CSOs) and floods. Large loads of urban-associated microorganisms, including faecal bacteria, are released from CSOs which place public health - as well as ecosystems - at risk. The impacts of freshwater contamination on river ecosystems have not yet been adequately addressed, as is the case for the release of pollutant mixtures linked to extreme weather events. In this context, microbial communities provide critical ecosystem services as they are the only biological compartment capable of degrading or transforming pollutants. Through the use of 16S rRNA gene metabarcoding of environmental DNA at different seasons and during a flood event in a typical Mediterranean coastal river, we show that the impacts of multipollution phenomena on structural shifts in the particle-attached riverine bacteriome were greater than those of seasonality. Key players were identified via multivariate statistical modelling combined with network module eigengene analysis. These included species highly resistant to pollutants as well as pathogens. Their rapid response to contaminant mixtures makes them ideal candidates as potential early biosignatures of multipollution stress. Multiple resistance gene transfer is likely enhanced with drastic consequences for the environment and human-health, particularly in a scenario of intensification of extreme hydrological events.
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