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      Antibiotic susceptibility signatures identify potential antimicrobial targets in the Acinetobacter baumannii cell envelope

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          Abstract

          A unique, protective cell envelope contributes to the broad drug resistance of the nosocomial pathogen Acinetobacter baumannii. Here we use transposon insertion sequencing to identify A. baumannii mutants displaying altered susceptibility to a panel of diverse antibiotics. By examining mutants with antibiotic susceptibility profiles that parallel mutations in characterized genes, we infer the function of multiple uncharacterized envelope proteins, some of which have roles in cell division or cell elongation. Remarkably, mutations affecting a predicted cell wall hydrolase lead to alterations in lipooligosaccharide synthesis. In addition, the analysis of altered susceptibility signatures and antibiotic-induced morphology patterns allows us to predict drug synergies; for example, certain beta-lactams appear to work cooperatively due to their preferential targeting of specific cell wall assembly machineries. Our results indicate that the pathogen may be effectively inhibited by the combined targeting of multiple pathways critical for envelope growth.

          Abstract

          A unique cell envelope contributes to the antibiotic resistance of the pathogen Acinetobacter baumannii. Here, Geisinger et al. identify A. baumannii mutants with altered antibiotic susceptibility, infer the function of uncharacterized proteins involved in envelope synthesis, and predict antibiotic synergies.

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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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            Molecular basis of bacterial outer membrane permeability revisited.

            Gram-negative bacteria characteristically are surrounded by an additional membrane layer, the outer membrane. Although outer membrane components often play important roles in the interaction of symbiotic or pathogenic bacteria with their host organisms, the major role of this membrane must usually be to serve as a permeability barrier to prevent the entry of noxious compounds and at the same time to allow the influx of nutrient molecules. This review summarizes the development in the field since our previous review (H. Nikaido and M. Vaara, Microbiol. Rev. 49:1-32, 1985) was published. With the discovery of protein channels, structural knowledge enables us to understand in molecular detail how porins, specific channels, TonB-linked receptors, and other proteins function. We are now beginning to see how the export of large proteins occurs across the outer membrane. With our knowledge of the lipopolysaccharide-phospholipid asymmetric bilayer of the outer membrane, we are finally beginning to understand how this bilayer can retard the entry of lipophilic compounds, owing to our increasing knowledge about the chemistry of lipopolysaccharide from diverse organisms and the way in which lipopolysaccharide structure is modified by environmental conditions.
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              Tn-seq; high-throughput parallel sequencing for fitness and genetic interaction studies in microorganisms

              Biological pathways are structured in complex networks of interacting genes. Solving the architecture of such networks may provide valuable information, such as how microorganisms cause disease. Here we present a method (Tn-seq) for accurately determining quantitative genetic interactions on a genome-wide scale in microorganisms. Tn-seq is based on the assembly of a saturated Mariner transposon insertion library. After library selection, changes in frequency of each insertion mutant are determined by sequencing of the flanking regions en masse. These changes are used to calculate each mutant’s fitness. Fitness was determined for each gene of the gram-positive bacterium Streptococcus pneumoniae, a causative agent of pneumonia and meningitis. A genome-wide screen for genetic interactions identified both alleviating and aggravating interactions that could be further divided into seven distinct categories. Due to the wide activity of the Mariner transposon, Tn-seq has the potential to contribute to the exploration of complex pathways across many different species.
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                Author and article information

                Contributors
                e.geisinger@northeastern.edu
                ralph.isberg@tufts.edu
                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Publishing Group UK (London )
                2041-1723
                9 September 2020
                9 September 2020
                2020
                : 11
                : 4522
                Affiliations
                [1 ]GRID grid.261112.7, ISNI 0000 0001 2173 3359, Department of Biology, , Northeastern University, ; Boston, MA 02115 USA
                [2 ]GRID grid.67033.31, ISNI 0000 0000 8934 4045, Department of Molecular Biology and Microbiology, , Tufts University School of Medicine, ; Boston, MA 02111 USA
                [3 ]GRID grid.38142.3c, ISNI 000000041936754X, Laboratory of Systems Pharmacology, , Harvard Medical School, ; Boston, MA 02115 USA
                [4 ]GRID grid.208226.c, ISNI 0000 0004 0444 7053, Biology Department, , Boston College, ; Chestnut Hill, MA 02467 USA
                Author information
                http://orcid.org/0000-0001-9661-8072
                http://orcid.org/0000-0001-9084-3367
                http://orcid.org/0000-0002-1876-4733
                http://orcid.org/0000-0001-6895-6795
                http://orcid.org/0000-0002-8330-3554
                Article
                18301
                10.1038/s41467-020-18301-2
                7481262
                32908144
                bfabed9e-a7ee-4a68-83e2-6143c7d42ff2
                © The Author(s) 2020

                Open Access This 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 2 March 2020
                : 13 August 2020
                Categories
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                Custom metadata
                © The Author(s) 2020

                Uncategorized
                dna replication,antimicrobials,cellular microbiology,microbial genetics
                Uncategorized
                dna replication, antimicrobials, cellular microbiology, microbial genetics

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