Analysis of microbial community biodiversity in activated sludge from a petrochemical plant Translated title: O lodo ativo da planta de uma indústria de petróleo é constituído por uma microbiota ainda a ser identificada – ScienceOpen
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      Analysis of microbial community biodiversity in activated sludge from a petrochemical plant Translated title: O lodo ativo da planta de uma indústria de petróleo é constituído por uma microbiota ainda a ser identificada

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          Abstract

          Abstract The active sludge process is one of the most-used techniques for the biodegradation of organic compounds present in effluents from an assortment of wastewaters. This study investigated the bacterial community structure of a petroleum industry’s activated sludge and its physical and chemical parameters using high-throughput sequencing. Samples were collected over one year: autumn 2015 (C1), winter 2015 (C2), spring 2015 (C3), and summer 2016 (C4). Total DNA was extracted, and the primers targeting the V4 region of the 16S rRNA gene were used for amplicon sequencing. The majority of the detected microorganisms were considered rare microbiota, presenting a relative abundance below 1% of the total sequences. All of the sequences were classified at the phylum level, and up to 55% of the ASVs (Amplicon Sequence Variants) were associated with known bacterial genera. Proteobacteria was the most abundant phylum in three seasons, while the phylum Armatimonadota dominated in one season. The genus Hyphomicrobium was the most abundant in autumn, winter and summer, and an ASV belonging to the family Fimbriimonadaceae was the most abundant in the spring. Canonical Correspondence Analysis showed that physicochemical parameters of SS, SD and TSS are correlated, as well as ammoniacal nitrogen. Sample C3 presented the highest values of COD, AN and solids (SS, SD and TSS). The highest COD, AN, and solids values are correlated to the high frequency of the phylum Armatimonadota in C3.

          Translated abstract

          Resumo O processo de lodo ativo é uma das técnicas mais utilizadas para biodegradação de compostos orgânicos presentes nos efluentes de uma variedade de águas residuais. A estrutura da comunidade bacteriana do lodo ativado de uma indústria de petróleo e sua relação com parâmetros físicos e químicos foram investigadas por meio de sequenciamento de alto rendimento. As amostras foram coletadas durante um período de um ano: outono de 2015 (C1), inverno de 2015 (C2), primavera de 2015 (C3) e verão de 2016 (C4). O DNA total foi extraído e para amplificação foram utilizados primers específicos para região V4 do gene 16S rRNA. A maioria dos microrganismos detectados foi considerada microbiota rara, apresentando abundância relativa abaixo de 1% do total de sequências. Em geral, quase a totalidade das sequências (99,9%) foi classificada em nível de filo, mas apenas algumas ASVs (23,7%) foram associadas a gênero bacteriano conhecido. As proteobactérias foram o filo mais abundante em três das estações, enquanto o filo Armatimonadota dominou em uma estação. O gênero Hyphomicrobium foi o gênero mais abundante no outono, inverno e verão, e uma ASV pertencente à família Fimbriimonadaceae (filo Armatimonadetes) foi o microrganismo mais abundante na primavera. A Análise de Correspondência Canônica (CCA) indica uma diferença consistente da comunidade bacteriana da primavera quando comparada com amostras de outras estações. Os resultados mostram uma correlação entre o filo Armatimonadota e a alta concentração de DQO, NA e sólidos.

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          Most cited references49

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          DADA2: High resolution sample inference from Illumina amplicon data

          We present DADA2, a software package that models and corrects Illumina-sequenced amplicon errors. DADA2 infers sample sequences exactly, without coarse-graining into OTUs, and resolves differences of as little as one nucleotide. In several mock communities DADA2 identified more real variants and output fewer spurious sequences than other methods. We applied DADA2 to vaginal samples from a cohort of pregnant women, revealing a diversity of previously undetected Lactobacillus crispatus variants.
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            The SILVA ribosomal RNA gene database project: improved data processing and web-based tools

            SILVA (from Latin silva, forest, http://www.arb-silva.de) is a comprehensive web 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. The referred database release 111 (July 2012) contains 3 194 778 small subunit and 288 717 large subunit rRNA gene sequences. Since the initial description of the project, substantial new features have been introduced, including advanced quality control procedures, an improved rRNA gene aligner, online tools for probe and primer evaluation and optimized browsing, searching and downloading on the website. Furthermore, the extensively curated SILVA taxonomy and the new non-redundant SILVA datasets provide an ideal reference for high-throughput classification of data from next-generation sequencing approaches.
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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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                Author and article information

                Journal
                ambiagua
                Revista Ambiente & Água
                Rev. Ambient. Água
                Instituto de Pesquisas Ambientais em Bacias Hidrográficas (Taubaté, SP, Brazil )
                1980-993X
                2021
                : 16
                : 3
                : e2655
                Affiliations
                [2] Porto Alegre Rio Grande do Sul orgnamePontifícia Universidade Católica do Rio Grande do Sul orgdiv1Instituto do Petróleo e dos Recursos Naturais Brazil leticia.marconatto@ 123456pucrs.br
                [3] Porto Alegre Rio Grande do Sul orgnameUniversidade Federal do Rio Grande do Sul orgdiv1Departamento de Microbiologia, Imunologia e Parasitologia orgdiv2Intituto de Ciências Básicas da Saúde Brazil svands@ 123456ufrgs.br
                [1] Porto Alegre Rio Grande do Sul orgnameUniversidade Federal do Rio Grande do Sul orgdiv1Instituto de Ciências Básicas da Saúde orgdiv2Programa de Pós-graduação em Microbiologia Agrícola e do Ambiente Brazil themis.antunes@ 123456gmail.com
                Article
                S1980-993X2021000300308 S1980-993X(21)01600300308
                10.4136/ambi-agua.2655
                840a0253-c924-4018-9f52-4299f5d96ddf

                This work is licensed under a Creative Commons Attribution 4.0 International License.

                History
                : 02 October 2020
                : 03 May 2021
                Page count
                Figures: 0, Tables: 0, Equations: 0, References: 49, Pages: 0
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                SciELO Brazil

                Categories
                Articles

                wastewater sludge,comunidade bacteriana,lodo ativado,sequenciamento de alto rendimento,bacterial community,high throughput sequencing

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