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      A New Family of Secreted Toxins in Pathogenic Neisseria Species

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          Abstract

          The genus Neisseria includes both commensal and pathogenic species which are genetically closely related. However, only meningococcus and gonococcus are important human pathogens. Very few toxins are known to be secreted by pathogenic Neisseria species. Recently, toxins secreted via type V secretion system and belonging to the widespread family of contact-dependent inhibition (CDI) toxins have been described in numerous species including meningococcus. In this study, we analyzed loci containing the maf genes in N. meningitidis and N. gonorrhoeae and proposed a novel uniform nomenclature for maf genomic islands (MGIs). We demonstrated that mafB genes encode secreted polymorphic toxins and that genes immediately downstream of mafB encode a specific immunity protein (MafI). We focused on a MafB toxin found in meningococcal strain NEM8013 and characterized its EndoU ribonuclease activity. maf genes represent 2% of the genome of pathogenic Neisseria, and are virtually absent from non-pathogenic species, thus arguing for an important biological role. Indeed, we showed that overexpression of one of the four MafB toxins of strain NEM8013 provides an advantage in competition assays, suggesting a role of maf loci in niche adaptation.

          Author Summary

          Many bacteria are able to secrete toxins targeted against neighboring cells. In order to protect themselves against their own toxin, they also express an “immunity” protein. In silico analysis of bacterial genomes predicts that numerous genes could encode potential new toxin-immunity systems. The recently described CDI system is involved in contact-dependent inhibition of growth and confers to its host strain a significant advantage in competitive ecosystems such as the gastro-intestinal tract. Indeed, an Escherichia coli CDI+ strain is able to outcompete CDI- strains and to become predominant. Here, we show that a large family of genes called “ maf”, found in pathogenic Neisseria species, encodes a toxin-immunity system. We demonstrate that a toxin named MafB MGI-1NEM8013 inhibits the growth of E. coli by degrading RNA and show that the immunity protein MafI MGI-1NEM8013 is able to abolish the toxicity. MafB toxins exhibit highly variable toxic domains. This variability of secreted toxins could be important to compete against bacteria of different species sharing the same reservoir. Since a strain may contain numerous toxin-immunity systems that can all play a role in interbacterial competition, deciphering interactions between these systems will allow a better understanding of complex bacterial communities.

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          Most cited references76

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          Prediction of lipoprotein signal peptides in Gram-negative bacteria.

          A method to predict lipoprotein signal peptides in Gram-negative Eubacteria, LipoP, has been developed. The hidden Markov model (HMM) was able to distinguish between lipoproteins (SPaseII-cleaved proteins), SPaseI-cleaved proteins, cytoplasmic proteins, and transmembrane proteins. This predictor was able to predict 96.8% of the lipoproteins correctly with only 0.3% false positives in a set of SPaseI-cleaved, cytoplasmic, and transmembrane proteins. The results obtained were significantly better than those of previously developed methods. Even though Gram-positive lipoprotein signal peptides differ from Gram-negatives, the HMM was able to identify 92.9% of the lipoproteins included in a Gram-positive test set. A genome search was carried out for 12 Gram-negative genomes and one Gram-positive genome. The results for Escherichia coli K12 were compared with new experimental data, and the predictions by the HMM agree well with the experimentally verified lipoproteins. A neural network-based predictor was developed for comparison, and it gave very similar results. LipoP is available as a Web server at www.cbs.dtu.dk/services/LipoP/.
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            Genomic islands in pathogenic and environmental microorganisms.

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              Genomic islands: tools of bacterial horizontal gene transfer and evolution

              Bacterial genomes evolve through mutations, rearrangements or horizontal gene transfer. Besides the core genes encoding essential metabolic functions, bacterial genomes also harbour a number of accessory genes acquired by horizontal gene transfer that might be beneficial under certain environmental conditions. The horizontal gene transfer contributes to the diversification and adaptation of microorganisms, thus having an impact on the genome plasticity. A significant part of the horizontal gene transfer is or has been facilitated by genomic islands (GEIs). GEIs are discrete DNA segments, some of which are mobile and others which are not, or are no longer mobile, which differ among closely related strains. A number of GEIs are capable of integration into the chromosome of the host, excision, and transfer to a new host by transformation, conjugation or transduction. GEIs play a crucial role in the evolution of a broad spectrum of bacteria as they are involved in the dissemination of variable genes, including antibiotic resistance and virulence genes leading to generation of hospital ‘superbugs’, as well as catabolic genes leading to formation of new metabolic pathways. Depending on the composition of gene modules, the same type of GEIs can promote survival of pathogenic as well as environmental bacteria.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS Pathog
                PLoS Pathog
                plos
                plospath
                PLoS Pathogens
                Public Library of Science (San Francisco, USA )
                1553-7366
                1553-7374
                January 2015
                8 January 2015
                : 11
                : 1
                : e1004592
                Affiliations
                [1 ]Institut Necker Enfants-Malades, INSERM U1151, Equipe 11, Paris, France
                [2 ]Université Paris Descartes; Sorbonne Paris Cité, Faculté de Médecine, Paris, France
                [3 ]Assistance Publique – Hôpitaux de Paris, Hôpital Necker Enfants Malades, Paris, France
                Vanderbilt University, United States of America
                Author notes

                The authors have declared that no competing interests exist.

                Conceived and designed the experiments: AJ AC XN. Performed the experiments: AJ DE ABJ PM AB AD. Analyzed the data: AJ ABJ AC XN. Wrote the paper: AJ AC XN.

                [¤]

                Current address: Unidade de Microbiologia Molecular e Infecção, Instituto de Medicina Molecular, Lisbon, Portugal

                Article
                PPATHOGENS-D-14-01435
                10.1371/journal.ppat.1004592
                4287609
                25569427
                79b8e5a6-eea0-4194-b15b-6498a6d081f2
                Copyright @ 2015

                This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 19 June 2014
                : 26 November 2014
                Page count
                Pages: 16
                Funding
                This work was supported by grants from Université Paris Descartes Paris Cité Sorbonne, the INSERM, the CNRS and La Fondation pour la Recherche Médicale (Equipe FRM DEQ20140329533). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology and Life Sciences
                Genetics
                Microbiology
                Molecular Biology
                Custom metadata
                The authors confirm that all data underlying the findings are fully available without restriction. All relevant data are within the paper and its Supporting Information files.

                Infectious disease & Microbiology
                Infectious disease & Microbiology

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