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Wang M, Wang S, Li H, Mao Z, Lu Y, Cheng Y, Han X, Wang Y, Liu Y, Wan S, Zhou LJ, Wu QL. Methylparaben changes the community composition, structure, and assembly processes of free-living bacteria, phytoplankton, and zooplankton. ENVIRONMENTAL RESEARCH 2024; 262:119944. [PMID: 39245310 DOI: 10.1016/j.envres.2024.119944] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/15/2024] [Revised: 08/31/2024] [Accepted: 09/05/2024] [Indexed: 09/10/2024]
Abstract
Parabens are common contaminants in river and lake environments. However, few studies have been conducted to determine the effects of parabens on bacteria, phytoplankton, and zooplankton communities in aquatic environments. In this study, the effect of methylparaben (MP) on the diversity and community structure of the aquatic plankton microbiome was investigated by incubating a microcosm with MP at 0.1, 1, 10, and 100 μg/L for 7 days. The results of the Simpson index showed that MP treatment altered the α-diversity of free-living bacteria (FL), phytoplankton, and zooplankton but had no significant effect on the α-diversity of particle-attached bacteria (PA). Further, the relative abundances of the sensitive bacteria Chitinophaga and Vibrionimonas declined after MP addition. Moreover, the relative abundances of Desmodesmus sp. HSJ717 and Scenedesmus armatus, of the phylum Chlorophyta, were significantly lower in the MP treatment group than in the control group. In addition, the relative abundance of Stoeckeria sp. SSMS0806, of the Dinophyta phylum, was higher than that in the control group. MP addition also increased the relative abundance of Arthropoda but decreased the relative abundance of Rotifera and Ciliophora. The β-diversity analysis showed that FL and phytoplankton communities were clustered separately after treatment with different MP concentrations. MP addition changed community assembly mechanisms in the microcosm, including increasing the stochastic processes for FL and the deterministic processes for PA and phytoplankton. Structural equation modeling analysis showed a significant negative relationship between bacteria richness and phytoplankton richness, and a significant positive relationship between phytoplankton (richness and community composition) and zooplankton. Overall, this study emphasizes that MP, at environmental concentrations, can change the diversity and structure of plankton microbial communities, which might have a negative effect on ecological systems.
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Affiliation(s)
- Man Wang
- School of Life Sciences, Institute of Life Science and Green Development, Hebei University, Baoding, 071002, China; Key Laboratory of Lake and Watershed Science for Water Security, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing, 210008, China; State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing, 210008, China
| | - Shengxing Wang
- School of Life Sciences, Institute of Life Science and Green Development, Hebei University, Baoding, 071002, China; Key Laboratory of Lake and Watershed Science for Water Security, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing, 210008, China; State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing, 210008, China
| | - Huabing Li
- Key Laboratory of Lake and Watershed Science for Water Security, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing, 210008, China; State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing, 210008, China
| | - Zhendu Mao
- State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing, 210008, China; Center for Evolution and Conservation Biology, Southern Marine Sciences and Engineering Guangdong Laboratory (Guangzhou), Guangzhou, 511458, China
| | - Yiwei Lu
- School of Life Sciences, Institute of Life Science and Green Development, Hebei University, Baoding, 071002, China; State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing, 210008, China; College of Food Science and Technology, Hebei Agricultural University, Baoding, 071001, China
| | - Yunshan Cheng
- State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing, 210008, China; School of Ecology and Environment, Anhui Normal University, Wuhu, 050031, China
| | - Xiaotong Han
- School of Life Sciences, Institute of Life Science and Green Development, Hebei University, Baoding, 071002, China; State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing, 210008, China
| | - Yujing Wang
- Key Laboratory of Lake and Watershed Science for Water Security, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing, 210008, China; State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing, 210008, China
| | - Yanru Liu
- School of Life Sciences, Institute of Life Science and Green Development, Hebei University, Baoding, 071002, China; State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing, 210008, China
| | - Shiqiang Wan
- School of Life Sciences, Institute of Life Science and Green Development, Hebei University, Baoding, 071002, China
| | - Li-Jun Zhou
- Key Laboratory of Lake and Watershed Science for Water Security, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing, 210008, China; State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing, 210008, China.
| | - Qinglong L Wu
- Key Laboratory of Lake and Watershed Science for Water Security, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing, 210008, China; State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing, 210008, China; Center for Evolution and Conservation Biology, Southern Marine Sciences and Engineering Guangdong Laboratory (Guangzhou), Guangzhou, 511458, China.
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Reiß F, Kiefer N, Purahong W, Borken W, Kalkhof S, Noll M. Active soil microbial composition and proliferation are directly affected by the presence of biocides from building materials. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 912:168689. [PMID: 38000743 DOI: 10.1016/j.scitotenv.2023.168689] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/19/2022] [Revised: 09/20/2023] [Accepted: 11/16/2023] [Indexed: 11/26/2023]
Abstract
Combinations of biocides are commonly added to building materials to prevent microbial growth and thereby cause degradation of the façades. These biocides reach the environment by leaching from façades posing an environmental risk. Although ecotoxicity to the aquatic habitat is well established, there is hardly any data on the ecotoxicological effects of biocides on the soil habitat. This study aimed to characterize the effect of the biocides terbutryn, isoproturon, octhilinone, and combinations thereof on the total and metabolically active soil microbial community composition and functions. Total soil microbial community was retrieved directly from the nucleic acid extracts, while the DNA of the active soil microbial community was separated after bromodeoxyuridine labeling. Bacterial 16S rRNA gene and fungal internal transcribed spacer region gene-based amplicon sequencing was carried out for both active and total, while gene copy numbers were quantified only for the total soil microbial community. Additionally, soil respiration and physico-chemical parameters were analyzed to investigate overall soil microbial activity. The bacterial and fungal gene copy numbers were significantly affected by single biocides and combined biocide soil treatment but not soil respiration and physico-chemical parameters. While the total soil microbiome experienced only minor effects from single and combined biocide treatment, the active soil microbiome was significantly impacted in its diversity, richness, composition, and functional patterns. The active bacterial richness was more sensitive than fungal richness. However, the adverse effects of the biocide combination treatments on soil bacterial richness were highly dependent on the identities of the biocide combination. Our results demonstrate that the presence of biocides frequently used in building materials affects the active soil microbiome. Thereby, the approach described herein can be used as an ecotoxicological measure for the effect on complex soil environments in future studies.
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Affiliation(s)
- Fabienne Reiß
- Institute for Bioanalysis, Department of Applied Natural Sciences and Health, Coburg University of Applied Sciences and Arts, Coburg, Germany
| | - Nadine Kiefer
- Institute for Bioanalysis, Department of Applied Natural Sciences and Health, Coburg University of Applied Sciences and Arts, Coburg, Germany
| | - Witoon Purahong
- Department of Soil Ecology, Helmholtz Centre for Environmental Research-UFZ, Halle (Saale), Germany
| | - Werner Borken
- Bayreuth Center of Ecology and Environmental Research (BayCEER), University of Bayreuth, Bayreuth, Germany
| | - Stefan Kalkhof
- Institute for Bioanalysis, Department of Applied Natural Sciences and Health, Coburg University of Applied Sciences and Arts, Coburg, Germany; Proteomics Unit, Fraunhofer Institute for Cell Therapy and Immunology, Leipzig, Germany
| | - Matthias Noll
- Institute for Bioanalysis, Department of Applied Natural Sciences and Health, Coburg University of Applied Sciences and Arts, Coburg, Germany; Bayreuth Center of Ecology and Environmental Research (BayCEER), University of Bayreuth, Bayreuth, Germany.
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Abd Rahman H, Sedaralit MF, Zainal S, de Rezende JR. Modelling Reservoir Souring Mitigation Strategy Based on Dynamic Microorganisms Interactions. DAY 2 TUE, NOVEMBER 01, 2022 2022. [DOI: 10.2118/211359-ms] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/01/2023]
Abstract
Abstract
Managing reservoir souring is on of the challenge in oil and gas industry, especially fields without previous records of H2S productions. Due to activities such as waterflooding, reservoirs’ conditions were changed, which indirectly inducing the environment to start producing H2S gas. In low temperature fields, main contributor to the H2S production was identified as biogenic process, where microorganisms catalyzed the sour gas production. Conventionally, sulphate reducing microorganism was always blamed as the culprit in contributing towards H2S production. However, abundance of literatures discussed about contribution of other microorganisms towards souring processes. Due to the complexity of their interactions, current approach to treat or control biogenic souring became one of the most challenging issues. This study will focus on the laboratory studies of sulphide production by microorganisms and modelling various microorganisms interactions towards chemical treatment introduced to mitigate it.
Started with microorganisms sampling from fields with high SRB, the samples were then enriched in the laboratory. To identify microorganismss from samples, cultures were sent for PCR and DNA sequencing. Based on the results, microorganisms were profiled. Batch test were conducted by dosing pre-determined dosage of biocide and nitrate. Production of sulphide were monitored up to 92days. Based on the sulphide production, effectiveness of the treatments were determined.
A model, which previously developed to determine the potential of reservoir souring, enhanced with addition of dynamic interaction of microorganisms. Factors such as nutrients, type of microorganisms, treatment chemicals, and their byproducts contributed towards the model. microorganisms.
In the batch test, chemicals were dosed once into culture. Results obtained shows that nitrate treatment suppressed the sulphide production for ashort term period, where after the nitrate depleted, the number of microorganisms and sulphide productions were bounced back. Biocidetreatment, in contrast, generally suppressed all microorganisms in the cultures, effectively control the microorganisms number and maintaining low sulphide production for the entire duration of the experiment.
The model that being developed in this study tested with synthetic data that mimick to field conditions, type of microorganisms and chemical treatments to observe their output pattern. It was found that the pattern output from the synthetic data matched with experimental results, which shows the model was sensitive and reliable to model the mitigation and control strategy for biogenic reservoir souring. The model based on dynamic interactions of microorganisms towards chemical treatments (biocide and/or nitrate) is the novel element in this study. Past studies were always focus on single population model, which SRB is the main input for the model, while this study enhanced its accuracy by introducing multi-population factor.
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Scheffer G, Hubert CRJ, Enning DR, Lahme S, Mand J, de Rezende JR. Metagenomic Investigation of a Low Diversity, High Salinity Offshore Oil Reservoir. Microorganisms 2021; 9:2266. [PMID: 34835392 PMCID: PMC8621343 DOI: 10.3390/microorganisms9112266] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2021] [Revised: 09/27/2021] [Accepted: 09/28/2021] [Indexed: 12/22/2022] Open
Abstract
Oil reservoirs can represent extreme environments for microbial life due to low water availability, high salinity, high pressure and naturally occurring radionuclides. This study investigated the microbiome of saline formation water samples from a Gulf of Mexico oil reservoir. Metagenomic analysis and associated anaerobic enrichment cultures enabled investigations into metabolic potential for microbial activity and persistence in this environment given its high salinity (4.5%) and low nutrient availability. Preliminary 16S rRNA gene amplicon sequencing revealed very low microbial diversity. Accordingly, deep shotgun sequencing resulted in nine metagenome-assembled genomes (MAGs), including members of novel lineages QPJE01 (genus level) within the Halanaerobiaceae, and BM520 (family level) within the Bacteroidales. Genomes of the nine organisms included respiratory pathways such as nitrate reduction (in Arhodomonas, Flexistipes, Geotoga and Marinobacter MAGs) and thiosulfate reduction (in Arhodomonas, Flexistipes and Geotoga MAGs). Genomic evidence for adaptation to high salinity, withstanding radioactivity, and metal acquisition was also observed in different MAGs, possibly explaining their occurrence in this extreme habitat. Other metabolic features included the potential for quorum sensing and biofilm formation, and genes for forming endospores in some cases. Understanding the microbiomes of deep biosphere environments sheds light on the capabilities of uncultivated subsurface microorganisms and their potential roles in subsurface settings, including during oil recovery operations.
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Affiliation(s)
- Gabrielle Scheffer
- Department of Biological Sciences, University of Calgary, Calgary, AB T2N 1N4, Canada;
| | - Casey R. J. Hubert
- Department of Biological Sciences, University of Calgary, Calgary, AB T2N 1N4, Canada;
- School of Natural and Environmental Sciences, Newcastle University, Newcastle upon Tyne NE1 7RU, UK; (S.L.); (J.R.d.R.)
| | - Dennis R. Enning
- Faculty of Life Sciences and Technology, Berlin University of Applied Sciences and Technology, D-13347 Berlin, Germany;
| | - Sven Lahme
- School of Natural and Environmental Sciences, Newcastle University, Newcastle upon Tyne NE1 7RU, UK; (S.L.); (J.R.d.R.)
- Exxon Mobil Upstream Research Company, Spring, TX 77389, USA;
| | - Jaspreet Mand
- Exxon Mobil Upstream Research Company, Spring, TX 77389, USA;
| | - Júlia R. de Rezende
- School of Natural and Environmental Sciences, Newcastle University, Newcastle upon Tyne NE1 7RU, UK; (S.L.); (J.R.d.R.)
- The Lyell Centre, Heriot-Watt University, Edinburgh EH14 4AS, UK
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