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      Genome sequence and functional genomic analysis of the oil-degrading bacterium Oleispira antarctica

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      1 , 2 , 3 , 4 , 5 , 5 , 5 , 5 , 6 , 7 , 1 , 3 , 1 , 3 , 3 , 8 , 8 , 8 , 9 , 10 , 9 , 10 , 10 , 11 , 11 , 11 , 10 , 12 , 9 , 9 , 13 , 13 , 8 , 14 , 15 , 4 , 5 , 9 , 10 , 11 , 11 , 13 , 3 , 4 , 1 , 17 , a , 3 , 4

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          Abstract

          Ubiquitous bacteria from the genus Oleispira drive oil degradation in the largest environment on Earth, the cold and deep sea. Here we report the genome sequence of Oleispira antarctica and show that compared with Alcanivorax borkumensis—the paradigm of mesophilic hydrocarbonoclastic bacteria— O. antarctica has a larger genome that has witnessed massive gene-transfer events. We identify an array of alkane monooxygenases, osmoprotectants, siderophores and micronutrient-scavenging pathways. We also show that at low temperatures, the main protein-folding machine Cpn60 functions as a single heptameric barrel that uses larger proteins as substrates compared with the classical double-barrel structure observed at higher temperatures. With 11 protein crystal structures, we further report the largest set of structures from one psychrotolerant organism. The most common structural feature is an increased content of surface-exposed negatively charged residues compared to their mesophilic counterparts. Our findings are relevant in the context of microbial cold-adaptation mechanisms and the development of strategies for oil-spill mitigation in cold environments.

          Abstract

          Oleispira antarctica is an oil-degrading bacterium found in the cold and deep sea. Here Kube et al. report the genome sequence of O. antarctica and provide a comprehensive functional genetic and protein structural analysis, revealing insights into how this organism has adapted to its cold environment.

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          Most cited references 35

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          A rapid method of total lipid extraction and purification.

           E G BLIGH,  W. Dyer (1959)
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            Amelioration of bacterial genomes: rates of change and exchange.

            Although bacterial species display wide variation in their overall GC contents, the genes within a particular species' genome are relatively similar in base composition. As a result, sequences that are novel to a bacterial genome-i.e., DNA introduced through recent horizontal transfer-often bear unusual sequence characteristics and can be distinguished from ancestral DNA. At the time of introgression, horizontally transferred genes reflect the base composition of the donor genome; but, over time, these sequences will ameliorate to reflect the DNA composition of the new genome because the introgressed genes are subject to the same mutational processes affecting all genes in the recipient genome. This process of amelioration is evident in a large group of genes involved in host-cell invasion by enteric bacteria and can be modeled to predict the amount of time required after transfer for foreign DNA to resemble native DNA. Furthermore, models of amelioration can be used to estimate the time of introgression of foreign genes in a chromosome. Applying this approach to a 1.43-megabase continuous sequence, we have calculated that the entire Escherichia coli chromosome contains more than 600 kb of horizontally transferred, protein-coding DNA. Estimates of amelioration times indicate that this DNA has accumulated at a rate of 31 kb per million years, which is on the order of the amount of variant DNA introduced by point mutations. This rate predicts that the E. coli and Salmonella enterica lineages have each gained and lost more than 3 megabases of novel DNA since their divergence.
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              IslandViewer: an integrated interface for computational identification and visualization of genomic islands

              Summary: Genomic islands (clusters of genes of probable horizontal origin; GIs) play a critical role in medically important adaptations of bacteria. Recently, several computational methods have been developed to predict GIs that utilize either sequence composition bias or comparative genomics approaches. IslandViewer is a web accessible application that provides the first user-friendly interface for obtaining precomputed GI predictions, or predictions from user-inputted sequence, using the most accurate methods for genomic island prediction: IslandPick, IslandPath-DIMOB and SIGI-HMM. The graphical interface allows easy viewing and downloading of island data in multiple formats, at both the chromosome and gene level, for method-specific, or overlapping, GI predictions. Availability: The IslandViewer web service is available at http://www.pathogenomics.sfu.ca/islandviewer and the source code is freely available under the GNU GPL license. Contact: brinkman@sfu.ca
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                Author and article information

                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Pub. Group
                2041-1723
                23 July 2013
                : 4
                Affiliations
                [1 ]Max-Planck Institute for Molecular Genetics , Berlin-Dahlem D-14195, Germany
                [2 ]Section Phytomedicine, Department of Crop and Animal Sciences, Humboldt-Universität zu Berlin , Berlin-Dahlem D-14195, Germany
                [3 ]Environmental Microbiology Group, HZI—Helmholtz Centre for Infection Research , Braunschweig D-38124, Germany
                [4 ]School of Biological Sciences, Bangor University , Gwynedd, Wales LL57 2UW, UK
                [5 ]Institute of Catalysis, CSIC , Madrid 28049, Spain
                [6 ]Departamento de Química, Universidade de São Paulo , Ribeirao Preto 14049 901, Brazil
                [7 ]Department of Environmental Biotechnology, Helmholtz Centre for Environmental Research-UFZ , Leipzig D-04318, Germany
                [8 ]Proteomic Facility, National Centre for Biotechnology, CSIC , Madrid 28049, Spain
                [9 ]The Banting and Best Department of Medical Research, University of Toronto , Toronto, Ontario, Canada M5G 2C4
                [10 ]Biosciences Division, Midwest Center for Structural Genomics, Argonne National Laboratory , Argonne, Illinois 60439, USA
                [11 ]Department of Chemical Engineering and Applied Chemistry, C.H. Best Institute University of Toronto , Toronto, Canada M5G 1L6
                [12 ]Biosciences Division, Structural Biology Center, Argonne National Laboratory , Argonne, Illinois 60439, USA
                [13 ]Laboratory of Marine Molecular Microbiology, Institute for Coastal Marine Environment (IAMC) , CNR, Messina 98122, Italy
                [14 ]Department of Biochemistry, University of Pretoria , Pretoria 0002, South Africa
                [15 ]Proteomics Unit, UCM—Complutense University Madrid , Madrid 28040, Spain
                [17 ]Present address: Max-Planck Genome Centre Cologne, Max-Planck Institute for Plant Breeding Research , Cologne D-50829, Germany
                Author notes
                Article
                ncomms3156
                10.1038/ncomms3156
                3759055
                23877221
                Copyright © 2013, Nature Publishing Group, a division of Macmillan Publishers Limited. All Rights Reserved.

                This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-sa/3.0/

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