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      Pathogens and host immunity in the ancient human oral cavity

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      1 , 2 , 3 , 4 , 3 , 4 , 5 , 1 , 5 , 6 , 7 , 8 , 2 , 6 , 6 , 6 , 6 , 9 , 10 , 11 , 12 , 13 , 14 , 1 , 15 , 16 , 5 , 6 , 17 , 17 , 5 , 18 , 19 ,   16 , 3 , 4 , 2 , 6 , 16 , 20 , 1 , 16
      Nature genetics

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          Abstract

          Calcified dental plaque (dental calculus) preserves for millennia and entraps biomolecules from all domains of life and viruses. We report the first high-resolution taxonomic and protein functional characterization of the ancient oral microbiome and demonstrate that the oral cavity has long served as a reservoir for bacteria implicated in both local and systemic disease. We characterize: (i) the ancient oral microbiome in a diseased state, (ii) 40 opportunistic pathogens, (iii) the first evidence of ancient human-associated putative antibiotic resistance genes, (iv) a genome reconstruction of the periodontal pathogen Tannerella forsythia, (v) 239 bacterial and 43 human proteins, allowing confirmation of a long-term association between host immune factors, “red-complex” pathogens, and periodontal disease, and (vi) DNA sequences matching dietary sources. Directly datable and nearly ubiquitous, dental calculus permits the simultaneous investigation of pathogen activity, host immunity, and diet, thereby extending the direct investigation of common diseases into the human evolutionary past.

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          The Proteomics Identifications (PRIDE) database and associated tools: status in 2013

          The PRoteomics IDEntifications (PRIDE, http://www.ebi.ac.uk/pride) database at the European Bioinformatics Institute is one of the most prominent data repositories of mass spectrometry (MS)-based proteomics data. Here, we summarize recent developments in the PRIDE database and related tools. First, we provide up-to-date statistics in data content, splitting the figures by groups of organisms and species, including peptide and protein identifications, and post-translational modifications. We then describe the tools that are part of the PRIDE submission pipeline, especially the recently developed PRIDE Converter 2 (new submission tool) and PRIDE Inspector (visualization and analysis tool). We also give an update about the integration of PRIDE with other MS proteomics resources in the context of the ProteomeXchange consortium. Finally, we briefly review the quality control efforts that are ongoing at present and outline our future plans.
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            ARDB—Antibiotic Resistance Genes Database

            The treatment of infections is increasingly compromised by the ability of bacteria to develop resistance to antibiotics through mutations or through the acquisition of resistance genes. Antibiotic resistance genes also have the potential to be used for bio-terror purposes through genetically modified organisms. In order to facilitate the identification and characterization of these genes, we have created a manually curated database—the Antibiotic Resistance Genes Database (ARDB)—unifying most of the publicly available information on antibiotic resistance. Each gene and resistance type is annotated with rich information, including resistance profile, mechanism of action, ontology, COG and CDD annotations, as well as external links to sequence and protein databases. Our database also supports sequence similarity searches and implements an initial version of a tool for characterizing common mutations that confer antibiotic resistance. The information we provide can be used as compendium of antibiotic resistance factors as well as to identify the resistance genes of newly sequenced genes, genomes, or metagenomes. Currently, ARDB contains resistance information for 13 293 genes, 377 types, 257 antibiotics, 632 genomes, 933 species and 124 genera. ARDB is available at http://ardb.cbcb.umd.edu/.
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              Toward an ecological classification of soil bacteria.

              Although researchers have begun cataloging the incredible diversity of bacteria found in soil, we are largely unable to interpret this information in an ecological context, including which groups of bacteria are most abundant in different soils and why. With this study, we examined how the abundances of major soil bacterial phyla correspond to the biotic and abiotic characteristics of the soil environment to determine if they can be divided into ecologically meaningful categories. To do this, we collected 71 unique soil samples from a wide range of ecosystems across North America and looked for relationships between soil properties and the relative abundances of six dominant bacterial phyla (Acidobacteria, Bacteroidetes, Firmicutes, Actinobacteria, alpha-Proteobacteria, and the beta-Proteobacteria). Of the soil properties measured, net carbon (C) mineralization rate (an index of C availability) was the best predictor of phylum-level abundances. There was a negative correlation between Acidobacteria abundance and C mineralization rates (r2 = 0.26, P < 0.001), while the abundances of beta-Proteobacteria and Bacteroidetes were positively correlated with C mineralization rates (r2 = 0.35, P < 0.001 and r2 = 0.34, P < 0.001, respectively). These patterns were explored further using both experimental and meta-analytical approaches. We amended soil cores from a specific site with varying levels of sucrose over a 12-month period to maintain a gradient of elevated C availabilities. This experiment confirmed our survey results: there was a negative relationship between C amendment level and the abundance of Acidobacteria (r2 = 0.42, P < 0.01) and a positive relationship for both Bacteroidetes and beta-Proteobacteria (r2 = 0.38 and 0.70, respectively; P < 0.01 for each). Further support for a relationship between the relative abundances of these bacterial phyla and C availability was garnered from an analysis of published bacterial clone libraries from bulk and rhizosphere soils. Together our survey, experimental, and meta-analytical results suggest that certain bacterial phyla can be differentiated into copiotrophic and oligotrophic categories that correspond to the r- and K-selected categories used to describe the ecological attributes of plants and animals. By applying the copiotroph-oligotroph concept to soil microorganisms we can make specific predictions about the ecological attributes of various bacterial taxa and better understand the structure and function of soil bacterial communities.
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                Author and article information

                Journal
                9216904
                2419
                Nat Genet
                Nat. Genet.
                Nature genetics
                1061-4036
                1546-1718
                6 March 2014
                23 February 2014
                April 2014
                01 October 2014
                : 46
                : 4
                : 336-344
                Affiliations
                [1 ]Centre for Evolutionary Medicine, Institute of Anatomy, University of Zürich, Switzerland
                [2 ]Department of Anthropology, University of Oklahoma, Norman, OK, USA
                [3 ]Institute of Molecular Life Sciences, University of Zürich, Switzerland
                [4 ]Swiss Institute of Bioinformatics, Lausanne, Switzerland
                [5 ]Functional Genomics Center Zürich, University of Zürich/Swiss Federal Institute of Technology (ETH) Zürich, Switzerland
                [6 ]BioArCh, Department of Archaeology, University of York, UK
                [7 ]University of Leicester Archaeological Services (ULAS), School of Archaeology and Ancient History, University of Leicester, UK
                [8 ]Department of Physics, University of York, UK
                [9 ]Centre of Dental Medicine, Institute of Oral Biology, University of Zürich, Switzerland
                [10 ]Research Group on Plant Foods in Hominin Dietary Ecology, Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany
                [11 ]Department of Human Evolution, Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany
                [12 ]Department of Prehistory and Archaeology, University of Valéncia, Spain
                [13 ]Research Group Neuro-Endocrine-Immune Interactions, Institute of Anatomy, University of Zürich, Switzerland
                [14 ]Zürich Center for Integrative Human Physiology, University of Zürich, Switzerland
                [15 ]Department of Biology, Microbiology, University of Copenhagen, Denmark
                [16 ]Centre for GeoGenetics, Natural History Museum of Denmark, University of Copenhagen, Denmark
                [17 ]Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen
                [18 ]Department of Immunology and Infectious Diseases, Forsyth Institute, Cambridge, MA, USA
                [19 ]Department of Oral Medicine, Infection, and Immunity, Harvard School of Dental Medicine, Harvard University, Boston, MA, USA
                [20 ]Ancient DNA Laboratory, Murdoch University, Western Australia, Australia
                Author notes
                Correspondence and requests for materials should be addressed to C.W. ( twarinner@ 123456gmail.com ) or E.C. ( ecappellini@ 123456gmail.com )
                [*]

                These authors jointly directed this work.

                Author Contributions: C.W. conceived the project. R.S. and F.R. contributed samples. C.W., E.C., M.J.C., M.T.P.G., C.M., A.R. and Y.H. designed the experiments. C.W., E.C., N.S., C.T., A.R., Y.H., D.S.G., S.C., S.F., H.L., P.N., C.K., J.O., K.Y.T., and E.E. performed the experiments. J.R., R.V., C.W., C.M., J.G., A.R., Y.H., R.Y.T., S.F., C.S., S.C., D.S.G., J.H., J.S.C., LH, and TK analyzed the data. S.B.O., Y.H., E.W., C.M.L., M.T.P.G., M.J.C., and F.R. contributed material support to the project. Y.H. wrote the supplementary Raman section. C.W. wrote the paper, with critical input from C.M.L., M.T.P.G., M.J.C., C.M., E.W., E.C., and the remaining authors.

                Article
                EMS57001
                10.1038/ng.2906
                3969750
                24562188
                2907462d-ac90-4972-b396-f20c408ee7ca
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