TY - JOUR A1 - Arias-Andres, Maria A1 - Rojas-Jimenez, Keilor A1 - Grossart, Hans-Peter T1 - Collateral effects of microplastic pollution on aquatic microorganisms BT - An ecological perspective JF - Trends in Analytical Chemistry N2 - Microplastics (MP) provide a unique and extensive surface for microbial colonization in aquatic ecosystems. The formation of microorganism-microplastic complexes, such as biofilms, maximizes the degradation of organic matter and horizontal gene transfer. In this context, MP affect the structure and function of microbial communities, which in turn render the physical and chemical fate of MP. This new paradigm generates challenges for microbiology, ecology, and ecotoxicology. Dispersal of MP is concomitant with that of their associated microorganisms and their mobile genetic elements, including antibiotic resistance genes, islands of pathogenicity, and diverse metabolic pathways. Functional changes in aquatic microbiomes can alter carbon metabolism and food webs, with unknown consequences on higher organisms or human microbiomes and hence health. Here, we examine a variety of effects of MP pollution from the microbial ecology perspective, whose repercussions on aquatic ecosystems begin to be unraveled. (C) 2018 Elsevier B.V. All rights reserved. KW - Microplastics (MP) KW - Biofilms KW - HGT KW - Microbial ecology KW - Carbon cycling KW - Aquatic ecosystems KW - Health risk assessment Y1 - 2018 U6 - https://doi.org/10.1016/j.trac.2018.11.041 SN - 0165-9936 SN - 1879-3142 VL - 112 SP - 234 EP - 240 PB - Elsevier CY - Oxford ER - TY - JOUR A1 - Fournier, Bertrand A1 - Steiner, Magdalena A1 - Brochet, Xavier A1 - Degrune, Florine A1 - Mammeri, Jibril A1 - Carvalho, Diogo Leite A1 - Siliceo, Sara Leal A1 - Bacher, Sven A1 - Peña-Reyes, Carlos Andrés A1 - Heger, Thierry Jean T1 - Toward the use of protists as bioindicators of multiple stresses in agricultural soils BT - a case study in vineyard ecosystems JF - Ecological indicators : integrating monitoring, assessment and management N2 - Management of agricultural soil quality requires fast and cost-efficient methods to identify multiple stressors that can affect soil organisms and associated ecological processes. Here, we propose to use soil protists which have a great yet poorly explored potential for bioindication. They are ubiquitous, highly diverse, and respond to various stresses to agricultural soils caused by frequent management or environmental changes. We test an approach that combines metabarcoding data and machine learning algorithms to identify potential stressors of soil protist community composition and diversity. We measured 17 key variables that reflect various potential stresses on soil protists across 132 plots in 28 Swiss vineyards over 2 years. We identified the taxa showing strong responses to the selected soil variables (potential bioindicator taxa) and tested for their predictive power. Changes in protist taxa occurrence and, to a lesser extent, diversity metrics exhibited great predictive power for the considered soil variables. Soil copper concentration, moisture, pH, and basal respiration were the best predicted soil variables, suggesting that protists are particularly responsive to stresses caused by these variables. The most responsive taxa were found within the clades Rhizaria and Alveolata. Our results also reveal that a majority of the potential bioindicators identified in this study can be used across years, in different regions and across different grape varieties. Altogether, soil protist metabarcoding data combined with machine learning can help identifying specific abiotic stresses on microbial communities caused by agricultural management. Such an approach provides complementary information to existing soil monitoring tools that can help manage the impact of agricultural practices on soil biodiversity and quality. KW - Biomonitoring KW - Machine learning KW - Predictive model KW - Soil function KW - Soil KW - quality KW - Microbial ecology Y1 - 2022 U6 - https://doi.org/10.1016/j.ecolind.2022.108955 SN - 1470-160X SN - 1872-7034 VL - 139 PB - Elsevier CY - Amsterdam ER -