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      Do initial concentration and activated sludge seasonality affect pharmaceutical biotransformation rate constants?

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          Abstract

          Abstract

          Pharmaceuticals find their way to the aquatic environment via wastewater treatment plants (WWTPs). Biotransformation plays an important role in mitigating environmental risks; however, a mechanistic understanding of involved processes is limited. The aim of this study was to evaluate potential relationships between first-order biotransformation rate constants ( k b ) of nine pharmaceuticals and initial concentration of the selected compounds, and sampling season of the used activated sludge inocula. Four-day bottle experiments were performed with activated sludge from WWTP Groesbeek (The Netherlands) of two different seasons, summer and winter, spiked with two environmentally relevant concentrations (3 and 30 nM) of pharmaceuticals. Concentrations of the compounds were measured by LC–MS/MS, microbial community composition was assessed by 16S rRNA gene amplicon sequencing, and k b values were calculated. The biodegradable pharmaceuticals were acetaminophen, metformin, metoprolol, terbutaline, and phenazone (ranked from high to low biotransformation rates). Carbamazepine, diatrizoic acid, diclofenac, and fluoxetine were not converted. Summer and winter inocula did not show significant differences in microbial community composition, but resulted in a slightly different k b for some pharmaceuticals. Likely microbial activity was responsible instead of community composition. In the same inoculum, different k b values were measured, depending on initial concentration. In general, biodegradable compounds had a higher k b when the initial concentration was higher. This demonstrates that Michealis-Menten kinetic theory has shortcomings for some pharmaceuticals at low, environmentally relevant concentrations and that the pharmaceutical concentration should be taken into account when measuring the k b in order to reliably predict the fate of pharmaceuticals in the WWTP.

          Key points

          Biotransformation and sorption of pharmaceuticals were assessed in activated sludge.

          Higher initial concentrations resulted in higher biotransformation rate constants for biodegradable pharmaceuticals.

          Summer and winter inocula produced slightly different biotransformation rate constants although microbial community composition did not significantly change.

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          Supplementary Information

          The online version contains supplementary material available at 10.1007/s00253-021-11475-9.

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          Most cited references55

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          phyloseq: An R Package for Reproducible Interactive Analysis and Graphics of Microbiome Census Data

          Background The analysis of microbial communities through DNA sequencing brings many challenges: the integration of different types of data with methods from ecology, genetics, phylogenetics, multivariate statistics, visualization and testing. With the increased breadth of experimental designs now being pursued, project-specific statistical analyses are often needed, and these analyses are often difficult (or impossible) for peer researchers to independently reproduce. The vast majority of the requisite tools for performing these analyses reproducibly are already implemented in R and its extensions (packages), but with limited support for high throughput microbiome census data. Results Here we describe a software project, phyloseq, dedicated to the object-oriented representation and analysis of microbiome census data in R. It supports importing data from a variety of common formats, as well as many analysis techniques. These include calibration, filtering, subsetting, agglomeration, multi-table comparisons, diversity analysis, parallelized Fast UniFrac, ordination methods, and production of publication-quality graphics; all in a manner that is easy to document, share, and modify. We show how to apply functions from other R packages to phyloseq-represented data, illustrating the availability of a large number of open source analysis techniques. We discuss the use of phyloseq with tools for reproducible research, a practice common in other fields but still rare in the analysis of highly parallel microbiome census data. We have made available all of the materials necessary to completely reproduce the analysis and figures included in this article, an example of best practices for reproducible research. Conclusions The phyloseq project for R is a new open-source software package, freely available on the web from both GitHub and Bioconductor.
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            Evaluation of general 16S ribosomal RNA gene PCR primers for classical and next-generation sequencing-based diversity studies

            16S ribosomal RNA gene (rDNA) amplicon analysis remains the standard approach for the cultivation-independent investigation of microbial diversity. The accuracy of these analyses depends strongly on the choice of primers. The overall coverage and phylum spectrum of 175 primers and 512 primer pairs were evaluated in silico with respect to the SILVA 16S/18S rDNA non-redundant reference dataset (SSURef 108 NR). Based on this evaluation a selection of ‘best available’ primer pairs for Bacteria and Archaea for three amplicon size classes (100–400, 400–1000, ≥1000 bp) is provided. The most promising bacterial primer pair (S-D-Bact-0341-b-S-17/S-D-Bact-0785-a-A-21), with an amplicon size of 464 bp, was experimentally evaluated by comparing the taxonomic distribution of the 16S rDNA amplicons with 16S rDNA fragments from directly sequenced metagenomes. The results of this study may be used as a guideline for selecting primer pairs with the best overall coverage and phylum spectrum for specific applications, therefore reducing the bias in PCR-based microbial diversity studies.
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              The SILVA and “All-species Living Tree Project (LTP)” taxonomic frameworks

              SILVA (from Latin silva, forest, http://www.arb-silva.de) is a comprehensive resource for up-to-date quality-controlled databases of aligned ribosomal RNA (rRNA) gene sequences from the Bacteria, Archaea and Eukaryota domains and supplementary online services. SILVA provides a manually curated taxonomy for all three domains of life, based on representative phylogenetic trees for the small- and large-subunit rRNA genes. This article describes the improvements the SILVA taxonomy has undergone in the last 3 years. Specifically we are focusing on the curation process, the various resources used for curation and the comparison of the SILVA taxonomy with Greengenes and RDP-II taxonomies. Our comparisons not only revealed a reasonable overlap between the taxa names, but also points to significant differences in both names and numbers of taxa between the three resources.
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                Author and article information

                Contributors
                t.vanbergen@science.ru.nl
                c.welte@science.ru.nl
                Journal
                Appl Microbiol Biotechnol
                Appl Microbiol Biotechnol
                Applied Microbiology and Biotechnology
                Springer Berlin Heidelberg (Berlin/Heidelberg )
                0175-7598
                1432-0614
                23 August 2021
                23 August 2021
                2021
                : 105
                : 16-17
                : 6515-6527
                Affiliations
                [1 ]GRID grid.5590.9, ISNI 0000000122931605, Department of Environmental Science, Institute for Water and Wetland Research, , Radboud University, ; Nijmegen, The Netherlands
                [2 ]GRID grid.5590.9, ISNI 0000000122931605, Department of Microbiology, Institute for Water and Wetland Research, , Radboud University, ; Nijmegen, The Netherlands
                [3 ]GRID grid.36120.36, ISNI 0000 0004 0501 5439, Faculty of Science, , Open Universiteit, ; Heerlen, The Netherlands
                [4 ]GRID grid.10417.33, ISNI 0000 0004 0444 9382, Radboud Institute for Health Sciences, Radboud University Medical Center, ; Nijmegen, The Netherlands
                Author information
                http://orcid.org/0000-0002-1568-8878
                Article
                11475
                10.1007/s00253-021-11475-9
                8403117
                34423412
                8fbd3cb0-070d-4631-b095-39c2ad3b2155
                © The Author(s) 2021

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 6 January 2021
                : 9 June 2021
                : 15 July 2021
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100003958, Stichting voor de Technische Wetenschappen;
                Award ID: 15759
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100003246, Nederlandse Organisatie voor Wetenschappelijk Onderzoek;
                Award ID: 024.002.002
                Award Recipient :
                Categories
                Environmental Biotechnology
                Custom metadata
                © Springer-Verlag GmbH Germany, part of Springer Nature 2021

                Biotechnology
                kinetics,sorption,organic micropollutants,wastewater treatment plants,bacterial community,nitrification

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