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      Widely Used Benzalkonium Chloride Disinfectants Can Promote Antibiotic Resistance

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          ABSTRACT

          While the misuse of antibiotics has clearly contributed to the emergence and proliferation of resistant bacterial pathogens, with major health consequences, it remains less clear if the widespread use of disinfectants, such as benzalkonium chlorides (BAC), a different class of biocides than antibiotics, has contributed to this problem. Here, we provide evidence that exposure to BAC coselects for antibiotic-resistant bacteria and describe the underlying genetic mechanisms. After inoculation with river sediment, BAC-fed bioreactors selected for several bacterial taxa, including the opportunistic pathogen Pseudomonas aeruginosa, that were more resistant to several antibiotics than their counterparts in a control (no BAC) bioreactor. A metagenomic analysis of the bioreactor microbial communities, confirmed by gene cloning experiments with the derived isolates, suggested that integrative and conjugative elements encoding a BAC efflux pump together with antibiotic resistance genes were responsible for these results. Furthermore, the exposure of the P. aeruginosa isolates to increasing concentrations of BAC selected for mutations in pmrB (polymyxin resistance) and physiological adaptations that contributed to a higher tolerance to polymyxin B and other antibiotics. The physiological adaptations included the overexpression of mexCD-oprJ multidrug efflux pump genes when BAC was added in the growth medium at subinhibitory concentrations. Collectively, our results demonstrated that disinfectants promote antibiotic resistance via several mechanisms and highlight the need to remediate (degrade) disinfectants in nontarget environments to further restrain the spread of antibiotic-resistant bacteria.

          IMPORTANCE Benzalkonium chlorides (BAC) are biocides broadly used in disinfectant solutions. Disinfectants are widely used in food processing lines, domestic households, and pharmaceutical products and are typically designed to have a different mode of action than antibiotics to avoid interfering with the use of the latter. Whether exposure to BAC makes bacteria more resistant to antibiotics remains an unresolved issue of obvious practical consequences for public health. Using an integrated approach that combines metagenomics of natural microbial communities with gene cloning experiments with isolates and experimental evolution assays, we show that the widely used benzalkonium chloride disinfectants promote clinically relevant antibiotic resistance. Therefore, more attention should be given to the usage of these disinfectants, and their fate in nontarget environments should be monitored more tightly.

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          featureCounts: An efficient general-purpose program for assigning sequence reads to genomic features

          , , (2013)
          Next-generation sequencing technologies generate millions of short sequence reads, which are usually aligned to a reference genome. In many applications, the key information required for downstream analysis is the number of reads mapping to each genomic feature, for example to each exon or each gene. The process of counting reads is called read summarization. Read summarization is required for a great variety of genomic analyses but has so far received relatively little attention in the literature. We present featureCounts, a read summarization program suitable for counting reads generated from either RNA or genomic DNA sequencing experiments. featureCounts implements highly efficient chromosome hashing and feature blocking techniques. It is considerably faster than existing methods (by an order of magnitude for gene-level summarization) and requires far less computer memory. It works with either single or paired-end reads and provides a wide range of options appropriate for different sequencing applications. featureCounts is available under GNU General Public License as part of the Subread (http://subread.sourceforge.net) or Rsubread (http://www.bioconductor.org) software packages.
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            Identification of mutations in laboratory-evolved microbes from next-generation sequencing data using breseq.

            Next-generation DNA sequencing (NGS) can be used to reconstruct eco-evolutionary population dynamics and to identify the genetic basis of adaptation in laboratory evolution experiments. Here, we describe how to run the open-source breseq computational pipeline to identify and annotate genetic differences found in whole-genome and whole-population NGS data from haploid microbes where a high-quality reference genome is available. These methods can also be used to analyze mutants isolated in genetic screens and to detect unintended mutations that may occur during strain construction and genome editing.
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              The enveomics collection: a toolbox for specialized analyses of microbial genomes and metagenomes

              Genomic and metagenomic analyses are increasingly becoming commonplace in several areas of biological research, but recurrent specialized analyses are frequently reported as in-house scripts rarely available after publication. We describe the enveomics collection, a growing set of actively maintained scripts for several recurrent and specialized tasks in microbial genomics and metagenomics, and present a graphical user interface and several case studies. Our resource includes previously described as well as new algorithms such as Transformed-space Resampling In Biased Sets (TRIBS), a novel method to evaluate phylogenetic under- or over-dispersion in reference sets with strong phylogenetic bias. The enveomics collection is freely available under the terms of the Artistic License 2.0 at https://github.com/lmrodriguezr/enveomics and for online analysis at http://enve-omics.ce.gatech.edu
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                Author and article information

                Journal
                Applied and Environmental Microbiology
                Appl Environ Microbiol
                American Society for Microbiology
                0099-2240
                1098-5336
                September 01 2018
                August 17 2018
                June 29 2018
                : 84
                : 17
                Article
                10.1128/AEM.01201-18
                6102991
                29959242
                fdd06648-2914-4fc4-afa0-4c9de1d1b201
                © 2018
                History

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