Bartacek, Jan

Cytryn, Eddie

Dottorini, Giulia

Franco, David Calderón

Gajdos, Stanislav

Khalifa, Leron

Manaia, Célia M.

Nielsen, Per Halkjær

Purkrtova, Sabina

Teixeira, A. Margarida

Vaz-Moreira, Ivone

Weissbrodt, David

English

Repositório Institucional da Universidade Católica Portuguesa

Biomarkers for monitoring antibiotic resistance in aquatic environments A. Margarida Teixeiraa (s-anmariteixeira@ucp.pt), Ivone Vaz-Moreiraa, David Calderón Francob,David Weissbrodtb,g, Sabina Purkrtovac, Stanislav Gajdosd, Giulia Dottorinie, Per HalkjærNielsene, Leron Khalifaf, Eddie Cytrynf, Jan Bartacekd, Célia M. Manaiaaa Universidade Católica Portuguesa, CBQF - Centro de Biotecnologia e Química Fina – Laboratório Associado, Escola Superior de Biotecnologia, Rua de Diogo Botelho 1327, 4169-005 Porto, PortugalbDepartment of Biotechnology, Environmental Biotechnology Section, Delft University of Technology, van der Maasweg 9, Delft 2629 HZ, the NetherlandscDepartment of Biochemistry and Microbiology, Faculty of Food and Biochemical Technology, University of Chemistry and Technology Prague, 5 Technická, 166 28 Prague, Czech RepublicdDepartment of Water Technology and Environmental Engineering, Faculty of Environmental Technology, University of Chemistry and Technology Prague, 5 Technická, 166 28 Prague, Czech RepubliceDepartment of Chemistry and Bioscience, Section of Biotechnology, Center for Microbial Communities, Aalborg University, 9220 Aalborg, Denmarkf Institute of Soil, Water and Environmental Sciences, The Volcani Institute, Agricultural Research Organization, P.O Box 15159, Rishon Lezion 7528809, Israelg Department of Biotechnology and Food Science, Norwegian University of Science and Technology, 7034 Trondheim, Norway Introduction Objectives MethodsConclusionsAcknowledgements: This work has received funding from European Research Council under European Union’s Horizon 2020 Research and Innovation through the projects"REPARES" Programme Grant Agreement 857552, and "DSWAP" under PRIMA grant 1822. National Funds from FCT – Fundação para a Ciência e a Tecnologia(UID/Multi/50016/2019). AMRT was supported by the FCT Ph.D grant UI/BD/151388/2021 and FSE (Fundo Social Europeu).✓ The tested biomarkers were found to discriminate between different types of sample, allowing the assessment of the efficacy of wastewatertreatment or the impact of discharges from WWTPs or other sources on the aquatic environment.✓ The selection of suitable biomarkers that can typify different water sources and levels of contamination with ARGs and MGEs, together withharmonised qPCR procedures, may facilitate regular and integrated regulatory requirements for antibiotic resistance monitoring in wastewater andrelated aquatic environments.✓ Identify appropriate biomarkers, whose detection and quantification could indicate anthropogenic sources of contamination;✓ Track the spread of antibiotic resistance in (waste)water;✓ Facilitate regular antibiotic resistance monitoring for regulatory purposes.ResultsFigure 1: Gene abundance (log (gene copy/mL of sample)) in wastewater and surface water. α, β, γ and ε indicate significantly (p < 0.05) different Tukey´s groups comparing the genotype of samples: influent, sludge, effluent, and surface water. Figure 2: Principal Component Analysis (PCA) based on biomarker distribution in the different types ofsample: influent (I), effluent (E), sludge (S) and surface water (SW up and down) samples, based on thequantification by qPCR of the ten biomarkers (intI1, sul1, ermB, ermF, aph(3’’)-Ib, uidA, qacEΔ1, tetX,crAssphage and mefC), for the five countries in the study (NL = The Netherlands, CZ= Czech Republic, DK =Denmark, IL=Israel and PT= Portugal).Figure 3: Biomarkers abundance hierarchical cluster analysis. Euclidean distance using mean linkage between average samples from influent, sludge, effluent and surface water and blind test samples (BT1-15) from influent, effluent (secondary and UV treatment), surface water (river) for all biomarkers (intI1, sul1, ermB, ermF, aph(3’’)-Ib, uidA, qacEΔ1, tetX, mefC and crAssphage). Metagenomic approach qPCR approachFigure 4: Pearson's correlation coefficient (R) between the concentration (log (gene copy/mL of sample)) of the biomarkers intI1, ermB, ermF, tetX and the 16S rRNA gene abundance (log (gene copy/ 16S rRNA copy number)).

Biomarkers for monitoring antibiotic resistance in aquatic environments

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Biomarkers for monitoring antibiotic resistance in aquatic environments

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Repositório Institucional da Universidade Católica Portuguesa