Comparative microbial metagenomic analysis of drinking water plants and wastewater treatment plants in Istanbul

IntroductionWastewater treatment plants (WWTPs) and drinking-water treatment plants (DWTPs) are critical for public health due to the potential risks posed by microorganisms that may persist after treatment. The aim of this study was to detect the microbiome profiles of waters from both DWTPs and WW...

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Main Authors: Mehmet Demirci, Cankut Çubuk, Ferhat Dasdemir, Abdulkerim Suat Saribas, Esra Billur Balcıoglu, Dogukan Ozbey, Dogu Yorulmaz, Tugba Olmez Hanci, Safak Basa, Bekir Sami Kocazeybek
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Language:English
Published: Frontiers Media S.A. 2025-01-01
Series:Frontiers in Microbiology
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Online Access:https://www.frontiersin.org/articles/10.3389/fmicb.2025.1488268/full
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author Mehmet Demirci
Cankut Çubuk
Ferhat Dasdemir
Abdulkerim Suat Saribas
Esra Billur Balcıoglu
Dogukan Ozbey
Dogu Yorulmaz
Tugba Olmez Hanci
Safak Basa
Bekir Sami Kocazeybek
Bekir Sami Kocazeybek
author_facet Mehmet Demirci
Cankut Çubuk
Ferhat Dasdemir
Abdulkerim Suat Saribas
Esra Billur Balcıoglu
Dogukan Ozbey
Dogu Yorulmaz
Tugba Olmez Hanci
Safak Basa
Bekir Sami Kocazeybek
Bekir Sami Kocazeybek
author_sort Mehmet Demirci
collection DOAJ
description IntroductionWastewater treatment plants (WWTPs) and drinking-water treatment plants (DWTPs) are critical for public health due to the potential risks posed by microorganisms that may persist after treatment. The aim of this study was to detect the microbiome profiles of waters from both DWTPs and WWTPs under the Istanbul Water and Sewerage Administration (ISKI), identify the antimicrobial resistance profiles in all these facilities, and observe the differences in the microbiome between the inlet and outlet of different WWTPs.MethodsA total of 52 samples were examined, comprising 18 samples from DWTPs and 34 samples from WWTPs. All water samples underwent pre-isolation filtration. DNA isolation was conducted using filter material, followed by sequencing on a NovaSeq 6000 instrument. Kraken2 tools and R scripts were used for statistical analysis and data visualization.ResultsThe microbial metagenomic analysis identified 71 phyla, 113 classes, 217 orders, 480 families, and 1,282 genera across all samples. There were unclassified microbes (53.14% vs. 58.75%), Eukaryota (3.64% vs. 3.5%), Archaea (0.08% vs. 0.03%), bacteria (42% vs. 36.25%), and viruses (0.02% vs. 0.04%) in the raw water and ozonation unit outlet of DWTPs. The inlet and outlet of WWTPs showed unclassified microbes (52.68% vs. 59.62%), Eukaryota (0.6% vs. 1.72%), Archaea (0.26% vs. 0.15%), bacteria (46.43% vs. 38.43%), and viruses (0.05% vs. 0.04%). No statistically significant results were found in the analysis of raw waters collected from DWTPs and samples taken from the ozonation unit outlet—from the phylum level to the genus level (p > 0.05). The inlet and outlet points of WWTPs showed no statistically significant results from the phylum to species levels (p > 0.05). The most detected genera were Desulfobacter (4.82%) in preliminary WWTPs, Thauera (1.93%) in biological WWTPs, Pseudomonas (1.44%) in advanced biological WWTPs, Acidovorax (1.85%) in biological package WWTPs, and Pseudomonas (11.55%) in plant-based WWTPs. No antimicrobial resistance gene markers were detected in water samples from raw water inlets and ozonation unit outlets from DWTPs, membrane wastewater recovery plants, or ultraviolet (UV) recycling facilities. The ANT(3″), Erm, and Sul resistance gene markers were detected in all raw WWTPs samples.DiscussionThere were no significant microbial risk differentiation between biological WWTPs and advanced biological WWTPs. The data could serve as preliminary information for future research. More extensive studies are needed, with multiple sample tracking in these facilities and their feeding basins.
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spelling doaj-art-95b6afa792194157a303577b7e7b7f412025-01-20T07:20:30ZengFrontiers Media S.A.Frontiers in Microbiology1664-302X2025-01-011610.3389/fmicb.2025.14882681488268Comparative microbial metagenomic analysis of drinking water plants and wastewater treatment plants in IstanbulMehmet Demirci0Cankut Çubuk1Ferhat Dasdemir2Abdulkerim Suat Saribas3Esra Billur Balcıoglu4Dogukan Ozbey5Dogu Yorulmaz6Tugba Olmez Hanci7Safak Basa8Bekir Sami Kocazeybek9Bekir Sami Kocazeybek10Department of Medical Microbiology, Faculty of Medicine, Kirklareli University, Kırklareli, TürkiyeCentre for Experimental Medicine and Rheumatology, William Harvey Research Institute, Queen Mary University of London and Barts NIHR BRC & NHS Trust, Charterhouse Square, London, United KingdomDepartment of Medical Microbiology, Faculty of Medicine, Istanbul University-Cerrahpaşa, Istanbul, TürkiyeDepartment of Medical Microbiology, Faculty of Medicine, Istanbul University-Cerrahpaşa, Istanbul, TürkiyeDivision of Marine Sciences and Management, Department of Chemical Oceanography, Istanbul University Institute of Marine Sciences and Management, Istanbul, TürkiyeDepartment of Medical Microbiology, Faculty of Medicine, Istanbul University-Cerrahpaşa, Istanbul, TürkiyeFaculty of Medicine, Medical Faculty Student, Istanbul University-Cerrahpaşa, Istanbul, TürkiyeIstanbul Water and Sewerage Administration, Istanbul, TürkiyeIstanbul Water and Sewerage Administration, Istanbul, TürkiyeDepartment of Medical Microbiology, Faculty of Medicine, Istanbul University-Cerrahpaşa, Istanbul, TürkiyeIstanbul Water and Sewerage Administration, Istanbul, TürkiyeIntroductionWastewater treatment plants (WWTPs) and drinking-water treatment plants (DWTPs) are critical for public health due to the potential risks posed by microorganisms that may persist after treatment. The aim of this study was to detect the microbiome profiles of waters from both DWTPs and WWTPs under the Istanbul Water and Sewerage Administration (ISKI), identify the antimicrobial resistance profiles in all these facilities, and observe the differences in the microbiome between the inlet and outlet of different WWTPs.MethodsA total of 52 samples were examined, comprising 18 samples from DWTPs and 34 samples from WWTPs. All water samples underwent pre-isolation filtration. DNA isolation was conducted using filter material, followed by sequencing on a NovaSeq 6000 instrument. Kraken2 tools and R scripts were used for statistical analysis and data visualization.ResultsThe microbial metagenomic analysis identified 71 phyla, 113 classes, 217 orders, 480 families, and 1,282 genera across all samples. There were unclassified microbes (53.14% vs. 58.75%), Eukaryota (3.64% vs. 3.5%), Archaea (0.08% vs. 0.03%), bacteria (42% vs. 36.25%), and viruses (0.02% vs. 0.04%) in the raw water and ozonation unit outlet of DWTPs. The inlet and outlet of WWTPs showed unclassified microbes (52.68% vs. 59.62%), Eukaryota (0.6% vs. 1.72%), Archaea (0.26% vs. 0.15%), bacteria (46.43% vs. 38.43%), and viruses (0.05% vs. 0.04%). No statistically significant results were found in the analysis of raw waters collected from DWTPs and samples taken from the ozonation unit outlet—from the phylum level to the genus level (p > 0.05). The inlet and outlet points of WWTPs showed no statistically significant results from the phylum to species levels (p > 0.05). The most detected genera were Desulfobacter (4.82%) in preliminary WWTPs, Thauera (1.93%) in biological WWTPs, Pseudomonas (1.44%) in advanced biological WWTPs, Acidovorax (1.85%) in biological package WWTPs, and Pseudomonas (11.55%) in plant-based WWTPs. No antimicrobial resistance gene markers were detected in water samples from raw water inlets and ozonation unit outlets from DWTPs, membrane wastewater recovery plants, or ultraviolet (UV) recycling facilities. The ANT(3″), Erm, and Sul resistance gene markers were detected in all raw WWTPs samples.DiscussionThere were no significant microbial risk differentiation between biological WWTPs and advanced biological WWTPs. The data could serve as preliminary information for future research. More extensive studies are needed, with multiple sample tracking in these facilities and their feeding basins.https://www.frontiersin.org/articles/10.3389/fmicb.2025.1488268/fullmicrobial metagenomic analysiswastewaterdrinking watermicrobiomeantimicrobial resistance (AMR) gene
spellingShingle Mehmet Demirci
Cankut Çubuk
Ferhat Dasdemir
Abdulkerim Suat Saribas
Esra Billur Balcıoglu
Dogukan Ozbey
Dogu Yorulmaz
Tugba Olmez Hanci
Safak Basa
Bekir Sami Kocazeybek
Bekir Sami Kocazeybek
Comparative microbial metagenomic analysis of drinking water plants and wastewater treatment plants in Istanbul
Frontiers in Microbiology
microbial metagenomic analysis
wastewater
drinking water
microbiome
antimicrobial resistance (AMR) gene
title Comparative microbial metagenomic analysis of drinking water plants and wastewater treatment plants in Istanbul
title_full Comparative microbial metagenomic analysis of drinking water plants and wastewater treatment plants in Istanbul
title_fullStr Comparative microbial metagenomic analysis of drinking water plants and wastewater treatment plants in Istanbul
title_full_unstemmed Comparative microbial metagenomic analysis of drinking water plants and wastewater treatment plants in Istanbul
title_short Comparative microbial metagenomic analysis of drinking water plants and wastewater treatment plants in Istanbul
title_sort comparative microbial metagenomic analysis of drinking water plants and wastewater treatment plants in istanbul
topic microbial metagenomic analysis
wastewater
drinking water
microbiome
antimicrobial resistance (AMR) gene
url https://www.frontiersin.org/articles/10.3389/fmicb.2025.1488268/full
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