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      Spotlight on Antimicrobial Metabolites from the Marine Bacteria Pseudoalteromonas: Chemodiversity and Ecological Significance

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          Abstract

          This review is dedicated to the antimicrobial metabolite-producing Pseudoalteromonas strains. The genus Pseudoalteromonas hosts 41 species, among which 16 are antimicrobial metabolite producers. To date, a total of 69 antimicrobial compounds belonging to 18 different families have been documented. They are classified into alkaloids, polyketides, and peptides. Finally as Pseudoalteromonas strains are frequently associated with macroorganisms, we can discuss the ecological significance of antimicrobial Pseudoalteromonas as part of the resident microbiota.

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          BAGEL3: automated identification of genes encoding bacteriocins and (non-)bactericidal posttranslationally modified peptides

          Auke van Heel, Anne de Jong, Manuel Montalban-Lopez … (2013)
          Identifying genes encoding bacteriocins and ribosomally synthesized and posttranslationally modified peptides (RiPPs) can be a challenging task. Especially those peptides that do not have strong homology to previously identified peptides can easily be overlooked. Extensive use of BAGEL2 and user feedback has led us to develop BAGEL3. BAGEL3 features genome mining of prokaryotes, which is largely independent of open reading frame (ORF) predictions and has been extended to cover more (novel) classes of posttranslationally modified peptides. BAGEL3 uses an identification approach that combines direct mining for the gene and indirect mining via context genes. Especially for heavily modified peptides like lanthipeptides, sactipeptides, glycocins and others, this genetic context harbors valuable information that is used for mining purposes. The bacteriocin and context protein databases have been updated and it is now easy for users to submit novel bacteriocins or RiPPs. The output has been simplified to allow user-friendly analysis of the results, in particular for large (meta-genomic) datasets. The genetic context of identified candidate genes is fully annotated. As input, BAGEL3 uses FASTA DNA sequences or folders containing multiple FASTA formatted files. BAGEL3 is freely accessible at http://bagel.molgenrug.nl.
          Article 0 comments Cited 225 times – based on 0 reviews     Review now
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            NRPSpredictor2—a web server for predicting NRPS adenylation domain specificity

            Marc Röttig, Marnix H Medema, Kai Blin … (2011)
            The products of many bacterial non-ribosomal peptide synthetases (NRPS) are highly important secondary metabolites, including vancomycin and other antibiotics. The ability to predict substrate specificity of newly detected NRPS Adenylation (A-) domains by genome sequencing efforts is of great importance to identify and annotate new gene clusters that produce secondary metabolites. Prediction of A-domain specificity based on the sequence alone can be achieved through sequence signatures or, more accurately, through machine learning methods. We present an improved predictor, based on previous work (NRPSpredictor), that predicts A-domain specificity using Support Vector Machines on four hierarchical levels, ranging from gross physicochemical properties of an A-domain’s substrates down to single amino acid substrates. The three more general levels are predicted with an F-measure better than 0.89 and the most detailed level with an average F-measure of 0.80. We also modeled the applicability domain of our predictor to estimate for new A-domains whether they lie in the applicability domain. Finally, since there are also NRPS that play an important role in natural products chemistry of fungi, such as peptaibols and cephalosporins, we added a predictor for fungal A-domains, which predicts gross physicochemical properties with an F-measure of 0.84. The service is available at http://nrps.informatik.uni-tuebingen.de/.
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              Microbes Drive Evolution of Animals and Plants: the Hologenome Concept

              Eugene Rosenberg, Ilana Zilber-Rosenberg (2016)
              ABSTRACT The hologenome concept of evolution postulates that the holobiont (host plus symbionts) with its hologenome (host genome plus microbiome) is a level of selection in evolution. Multicellular organisms can no longer be considered individuals by the classical definitions of the term. Every natural animal and plant is a holobiont consisting of the host and diverse symbiotic microbes and viruses. Microbial symbionts can be transmitted from parent to offspring by a variety of methods, including via cytoplasmic inheritance, coprophagy, direct contact during and after birth, and the environment. A large number of studies have demonstrated that these symbionts contribute to the anatomy, physiology, development, innate and adaptive immunity, and behavior and finally also to genetic variation and to the origin and evolution of species. Acquisition of microbes and microbial genes is a powerful mechanism for driving the evolution of complexity. Evolution proceeds both via cooperation and competition, working in parallel.
              Article 0 comments Cited 170 times – based on 0 reviews     Review now
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                Author and article information

                Contributors
                Paola Laurienzo: Role: Academic Editor
                Journal
                Journal ID (nlm-ta): Mar Drugs
                Journal ID (iso-abbrev): Mar Drugs
                Journal ID (publisher-id): marinedrugs
                Title: Marine Drugs
                Publisher: MDPI
                ISSN (Electronic): 1660-3397
                Publication date (Electronic): 08 July 2016
                Publication date Collection: July 2016
                Volume: 14
                Issue: 7
                Electronic Location Identifier: 129
                Affiliations
                Laboratoire Universitaire de Biodiversité et d’Ecologie Microbienne LUBEM EA3882, Université de Brest, Technopole Brest-Iroise, 29280 Plouzané, France; clement.offret@ 123456univ-brest.fr (C.O.); florie.desriac@ 123456polytech-lille.fr (F.D.); patrick.lechevalier@ 123456univ-brest.fr (P.L.C.); jerome.mounier@ 123456univ-brest.fr (J.M.); camille.jegou@ 123456univ-brest.fr (C.J.)
                Author notes
                [* ]Correspondence: yannick.fleury@ 123456univ-brest.fr ; Tel.: +33-298-641-935
                [†]

                Present address: University of Lille, INRA, ISA; University of Artois; University of Littoral Côte d’Opale; Institute of Charles Viollette, EA 7394 Lille, France.

                Article
                Publisher ID: marinedrugs-14-00129
                DOI: 10.3390/md14070129
                PMC ID: 4962019
                PubMed ID: 27399731
                SO-VID: 2b1ada48-b7a4-4ee6-bcfd-9c9949690c19
                Copyright © © 2016 by the authors; licensee MDPI, Basel, Switzerland.
                License:

                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
                Date received : 30 May 2016
                Date accepted : 29 June 2016
                Categories
                Subject: Review

                ScienceOpen disciplines: Pharmacology & Pharmaceutical medicine
                Keywords: pseudoalteromonas,antimicrobial metabolites,alkaloid,polyketide,non ribosomal peptide,genome mining,marine host-associated microbiota,probiotic
                Data availability:
                ScienceOpen disciplines: Pharmacology & Pharmaceutical medicine
                Keywords: pseudoalteromonas, antimicrobial metabolites, alkaloid, polyketide, non ribosomal peptide, genome mining, marine host-associated microbiota, probiotic

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