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      Effect of Co-contamination by PAHs and Heavy Metals on Bacterial Communities of Diesel Contaminated Soils of South Shetland Islands, Antarctica

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          Abstract

          Diesel oil is the main source of energy used in Antarctica. Since diesel is composed of toxic compounds such as polycyclic aromatic hydrocarbons (PAHs) and heavy metals, it represents a constant threat to the organisms inhabiting this continent. In the present study, we characterized the chemical and biological parameters of diesel-exposed soils obtained from King George Island in Antarctica. Contaminated soils present PAH concentrations 1000 times higher than non-exposed soils. Some contaminated soil samples also exhibited high concentrations of cadmium and lead. A 16S metagenome analysis revealed the effect of co-contamination on bacterial communities. An increase in the relative abundance of bacteria known as PAH degraders or metal resistant was determined in co-contaminated soils. Accordingly, the soil containing higher amounts of PAHs exhibited increased dehydrogenase activity than control soils, suggesting that the microorganisms present can metabolize diesel. The inhibitory effect on soil metabolism produced by cadmium was lower in diesel-contaminated soils. Moreover, diesel-contaminated soils contain higher amounts of cultivable heterotrophic, cadmium-tolerant, and PAH-degrading bacteria than control soils. Obtained results indicate that diesel contamination at King George island has affected microbial communities, favoring the presence of microorganisms capable of utilizing PAHs as a carbon source, even in the presence of heavy metals.

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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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            QIIME allows analysis of high-throughput community sequencing data.

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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
                Microorganisms
                Microorganisms
                microorganisms
                Microorganisms
                MDPI
                2076-2607
                07 November 2020
                November 2020
                : 8
                : 11
                : 1749
                Affiliations
                [1 ]BioNanotechnology and Microbiology Lab, Center for Bioinformatics and Integrative Biology (CBIB), Facultad de Ciencias de la Vida, Universidad Andres Bello, Republica # 330, Santiago 8370146, Chile; agranscheuch@ 123456gmail.com (A.G.-S.); ramoszjaviera@ 123456gmail.com (J.R.-Z.)
                [2 ]Departamento de Química Inorgánica y Analítica, Facultad de Ciencias Químicas y Farmacéuticas, Universidad de Chile, Sergio Livingstone Pohlhammer # 1007, Santiago 8380000, Chile; edfuentes@ 123456ciq.uchile.cl
                [3 ]Laboratorio de Microbiología Oral, Facultad de Odontología, Universidad de Chile, Sergio Livingstone Pohlhammer # 943, Santiago 8380453, Chile; denisseb@ 123456gmail.com
                Author notes
                [* ]Correspondence: jose.perez@ 123456unab.cl
                Author information
                https://orcid.org/0000-0002-9506-1716
                Article
                microorganisms-08-01749
                10.3390/microorganisms8111749
                7695015
                33171767
                71c61d6b-bdc0-437b-9786-d0ffc735af32
                © 2020 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 22 September 2020
                : 31 October 2020
                Categories
                Article

                antarctica,co-contamination,microbial population,pahs,cadmium,pah-degrading bacteria

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