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      Deep Sequencing of the Oral Microbiome Reveals Signatures of Periodontal Disease

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          Abstract

          The oral microbiome, the complex ecosystem of microbes inhabiting the human mouth, harbors several thousands of bacterial types. The proliferation of pathogenic bacteria within the mouth gives rise to periodontitis, an inflammatory disease known to also constitute a risk factor for cardiovascular disease. While much is known about individual species associated with pathogenesis, the system-level mechanisms underlying the transition from health to disease are still poorly understood. Through the sequencing of the 16S rRNA gene and of whole community DNA we provide a glimpse at the global genetic, metabolic, and ecological changes associated with periodontitis in 15 subgingival plaque samples, four from each of two periodontitis patients, and the remaining samples from three healthy individuals. We also demonstrate the power of whole-metagenome sequencing approaches in characterizing the genomes of key players in the oral microbiome, including an unculturable TM7 organism. We reveal the disease microbiome to be enriched in virulence factors, and adapted to a parasitic lifestyle that takes advantage of the disrupted host homeostasis. Furthermore, diseased samples share a common structure that was not found in completely healthy samples, suggesting that the disease state may occupy a narrow region within the space of possible configurations of the oral microbiome. Our pilot study demonstrates the power of high-throughput sequencing as a tool for understanding the role of the oral microbiome in periodontal disease. Despite a modest level of sequencing (∼2 lanes Illumina 76 bp PE) and high human DNA contamination (up to ∼90%) we were able to partially reconstruct several oral microbes and to preliminarily characterize some systems-level differences between the healthy and diseased oral microbiomes.

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          Periodontitis: a polymicrobial disruption of host homeostasis.

          Periodontitis, or gum disease, affects millions of people each year. Although it is associated with a defined microbial composition found on the surface of the tooth and tooth root, the contribution of bacteria to disease progression is poorly understood. Commensal bacteria probably induce a protective response that prevents the host from developing disease. However, several bacterial species found in plaque (the 'red-complex' bacteria: Porphyromonas gingivalis, Tannerella forsythia and Treponema denticola) use various mechanisms to interfere with host defence mechanisms. Furthermore, disease may result from 'community-based' attack on the host. Here, I describe the interaction of the host immune system with the oral bacteria in healthy states and in diseased states.
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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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              Defining the healthy "core microbiome" of oral microbial communities

              Background Most studies examining the commensal human oral microbiome are focused on disease or are limited in methodology. In order to diagnose and treat diseases at an early and reversible stage an in-depth definition of health is indispensible. The aim of this study therefore was to define the healthy oral microbiome using recent advances in sequencing technology (454 pyrosequencing). Results We sampled and sequenced microbiomes from several intraoral niches (dental surfaces, cheek, hard palate, tongue and saliva) in three healthy individuals. Within an individual oral cavity, we found over 3600 unique sequences, over 500 different OTUs or "species-level" phylotypes (sequences that clustered at 3% genetic difference) and 88 - 104 higher taxa (genus or more inclusive taxon). The predominant taxa belonged to Firmicutes (genus Streptococcus, family Veillonellaceae, genus Granulicatella), Proteobacteria (genus Neisseria, Haemophilus), Actinobacteria (genus Corynebacterium, Rothia, Actinomyces), Bacteroidetes (genus Prevotella, Capnocytophaga, Porphyromonas) and Fusobacteria (genus Fusobacterium). Each individual sample harboured on average 266 "species-level" phylotypes (SD 67; range 123 - 326) with cheek samples being the least diverse and the dental samples from approximal surfaces showing the highest diversity. Principal component analysis discriminated the profiles of the samples originating from shedding surfaces (mucosa of tongue, cheek and palate) from the samples that were obtained from solid surfaces (teeth). There was a large overlap in the higher taxa, "species-level" phylotypes and unique sequences among the three microbiomes: 84% of the higher taxa, 75% of the OTUs and 65% of the unique sequences were present in at least two of the three microbiomes. The three individuals shared 1660 of 6315 unique sequences. These 1660 sequences (the "core microbiome") contributed 66% of the reads. The overlapping OTUs contributed to 94% of the reads, while nearly all reads (99.8%) belonged to the shared higher taxa. Conclusions We obtained the first insight into the diversity and uniqueness of individual oral microbiomes at a resolution of next-generation sequencing. We showed that a major proportion of bacterial sequences of unrelated healthy individuals is identical, supporting the concept of a core microbiome at health.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                1932-6203
                2012
                4 June 2012
                : 7
                : 6
                : e37919
                Affiliations
                [1 ]Center for Bioinformatics and Computational Biology, University of Maryland, College Park, Maryland, United States of America
                [2 ]Department of Computer Science, University of Maryland, College Park, Maryland, United States of America
                [3 ]Bioinformatics Program, Boston University, Boston, Massachusetts, United States of America
                [4 ]Biological Sciences Graduate Program, University of Maryland, College Park, Maryland, United States of America
                [5 ]Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, Maryland, United States of America
                [6 ]Department of Biology, Boston University, Boston, Massachusetts, United States of America
                [7 ]Department of Biomedical Engineering, Boston University, Boston, Massachusetts, United States of America
                [8 ]The Forysth Institute, Department of Periodontology, Cambridge, Massachusetts, United States of America
                [9 ]Children’s Informatics Program, Harvard-Massachusetts Institute of Technology Division of Health Sciences and Technology, Boston, Massachusetts, United States of America
                [10 ]The McKusick-Nathans Institute for Genetic Medicine, The Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America
                [11 ]Center for Anti-Inflammatory Therapeutics; Boston University Goldman School of Dental Medicine, Boston, Massachusetts, United States of America
                Baylor College of Medicine, United States of America
                Author notes

                Conceived and designed the experiments: SK DS MP SA. Performed the experiments: BL LF NK VM MG DDS TG TJT YCC SL OCS HH. Analyzed the data: SK DS MP SA. Contributed reagents/materials/analysis tools: BL LF NK VM MG DDS TG TJT YCC SL OCS HH SK DS MP SA. Wrote the paper: BL LF NK VM MG DDS TG TJT YCC SL OCS HH SK DS MP SA.

                Article
                PONE-D-11-24763
                10.1371/journal.pone.0037919
                3366996
                22675498
                e2bb6271-96be-498e-ad4a-1e59e5f8ba1c
                Liu et al. 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
                : 12 December 2011
                : 30 April 2012
                Page count
                Pages: 16
                Categories
                Research Article
                Biology
                Computational Biology
                Genomics
                Sequence Analysis
                Signaling Networks
                Immunology
                Microbiology
                Bacterial Pathogens
                Host-Pathogen Interaction
                Computer Science
                Computing Systems
                Molecular Computing
                Medicine
                Clinical Immunology
                Immunity
                Infectious Diseases
                Bacterial Diseases
                Perio-Endo
                Periodontal Abscesses

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                Uncategorized

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