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      Heavy Metal Pollution Impacts Soil Bacterial Community Structure and Antimicrobial Resistance at the Birmingham 35th Avenue Superfund Site

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          ABSTRACT

          Heavy metals (HMs) are known to modify bacterial communities both in the laboratory and in situ. Consequently, soils in HM-contaminated sites such as the U.S. Environmental Protection Agency (EPA) Superfund sites are predicted to have altered ecosystem functioning, with potential ramifications for the health of organisms, including humans, that live nearby. Further, several studies have shown that heavy metal-resistant (HMR) bacteria often also display antimicrobial resistance (AMR), and therefore HM-contaminated soils could potentially act as reservoirs that could disseminate AMR genes into human-associated pathogenic bacteria. To explore this possibility, topsoil samples were collected from six public locations in the zip code 35207 (the home of the North Birmingham 35th Avenue Superfund Site) and in six public areas in the neighboring zip code, 35214. 35027 soils had significantly elevated levels of the HMs As, Mn, Pb, and Zn, and sequencing of the V4 region of the bacterial 16S rRNA gene revealed that elevated HM concentrations correlated with reduced microbial diversity and altered community structure. While there was no difference between zip codes in the proportion of total culturable HMR bacteria, bacterial isolates with HMR almost always also exhibited AMR. Metagenomes inferred using PICRUSt2 also predicted significantly higher mean relative frequencies in 35207 for several AMR genes related to both specific and broad-spectrum AMR phenotypes. Together, these results support the hypothesis that chronic HM pollution alters the soil bacterial community structure in ecologically meaningful ways and may also select for bacteria with increased potential to contribute to AMR in human disease.

          IMPORTANCE Heavy metals cross-select for antimicrobial resistance in laboratory experiments, but few studies have documented this effect in polluted soils. Moreover, despite decades of awareness of heavy metal contamination at the EPA Superfund site in North Birmingham, Alabama, this is the first analysis of the impact of this pollution on the soil microbiome. Specifically, this work advances the understanding of the relationship between heavy metals, microbial diversity, and patterns of antibiotic resistance in North Birmingham soils. Our results suggest that polluted soils carry a risk of increased exposure to antibiotic-resistant infections in addition to the direct health consequences of heavy metals. Our work provides important information relevant to both political and scientific efforts to advance environmental justice for the communities that call Superfund neighborhoods home.

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          clusterProfiler: an R package for comparing biological themes among gene clusters.

          Increasing quantitative data generated from transcriptomics and proteomics require integrative strategies for analysis. Here, we present an R package, clusterProfiler that automates the process of biological-term classification and the enrichment analysis of gene clusters. The analysis module and visualization module were combined into a reusable workflow. Currently, clusterProfiler supports three species, including humans, mice, and yeast. Methods provided in this package can be easily extended to other species and ontologies. The clusterProfiler package is released under Artistic-2.0 License within Bioconductor project. The source code and vignette are freely available at http://bioconductor.org/packages/release/bioc/html/clusterProfiler.html.
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            The Molecular Evolutionary Genetics Analysis (Mega) software implements many analytical methods and tools for phylogenomics and phylomedicine. Here, we report a transformation of Mega to enable cross-platform use on Microsoft Windows and Linux operating systems. Mega X does not require virtualization or emulation software and provides a uniform user experience across platforms. Mega X has additionally been upgraded to use multiple computing cores for many molecular evolutionary analyses. Mega X is available in two interfaces (graphical and command line) and can be downloaded from www.megasoftware.net free of charge.
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              Basic local alignment search tool.

              A new approach to rapid sequence comparison, basic local alignment search tool (BLAST), directly approximates alignments that optimize a measure of local similarity, the maximal segment pair (MSP) score. Recent mathematical results on the stochastic properties of MSP scores allow an analysis of the performance of this method as well as the statistical significance of alignments it generates. The basic algorithm is simple and robust; it can be implemented in a number of ways and applied in a variety of contexts including straightforward DNA and protein sequence database searches, motif searches, gene identification searches, and in the analysis of multiple regions of similarity in long DNA sequences. In addition to its flexibility and tractability to mathematical analysis, BLAST is an order of magnitude faster than existing sequence comparison tools of comparable sensitivity.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                Microbiol Spectr
                Microbiol Spectr
                spectrum
                Microbiology Spectrum
                American Society for Microbiology (1752 N St., N.W., Washington, DC )
                2165-0497
                23 March 2023
                Mar-Apr 2023
                23 March 2023
                : 11
                : 2
                : e02426-22
                Affiliations
                [a ] Department of Biology, University of Alabama at Birmingham, Birmingham, Alabama, USA
                [b ] Alabama College of Osteopathic Medicine, Dothan, Alabama, USA
                University of Texas at San Antonio
                Author notes

                Anuradha Goswami and Sarah J. Adkins-Jablonsky contributed equally to this article. Anuradha Goswami was listed first because she completed the project after Sarah J. Adkins-Jablonsky completed her Ph.D.

                The authors declare no conflict of interest.

                Author information
                https://orcid.org/0000-0001-9079-0082
                Article
                02426-22 spectrum.02426-22
                10.1128/spectrum.02426-22
                10101053
                36951567
                2edf3dec-d08c-473d-9607-1504eb531862
                Copyright © 2023 Goswami et al.

                This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International license.

                History
                : 11 July 2022
                : 23 February 2023
                Page count
                supplementary-material: 0, Figures: 5, Tables: 1, Equations: 0, References: 76, Pages: 14, Words: 9488
                Funding
                Funded by: National Science Foundation (NSF), FundRef https://doi.org/10.13039/100000001;
                Award ID: OCE-1851085
                Award Recipient :
                Funded by: National Science Foundation (NSF), FundRef https://doi.org/10.13039/100000001;
                Award ID: 1450078
                Award Recipient :
                Funded by: National Science Foundation (NSF), FundRef https://doi.org/10.13039/100000001;
                Award ID: DGE-1945997
                Award Recipient :
                Categories
                Research Article
                microbial-ecology, Microbial Ecology
                Custom metadata
                March/April 2023

                antimicrobial resistance,topsoil,heavy metal pollution,superfund site

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