+1 Recommend
0 collections
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Metatranscriptomics of the Human Oral Microbiome during Health and Disease


      Read this article at

          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.


          The human microbiome plays important roles in health, but when disrupted, these same indigenous microbes can cause disease. The composition of the microbiome changes during the transition from health to disease; however, these changes are often not conserved among patients. Since microbiome-associated diseases like periodontitis cause similar patient symptoms despite interpatient variability in microbial community composition, we hypothesized that human-associated microbial communities undergo conserved changes in metabolism during disease. Here, we used patient-matched healthy and diseased samples to compare gene expression of 160,000 genes in healthy and diseased periodontal communities. We show that health- and disease-associated communities exhibit defined differences in metabolism that are conserved between patients. In contrast, the metabolic gene expression of individual species was highly variable between patients. These results demonstrate that despite high interpatient variability in microbial composition, disease-associated communities display conserved metabolic profiles that are generally accomplished by a patient-specific cohort of microbes.


          The human microbiome project has shown that shifts in our microbiota are associated with many diseases, including obesity, Crohn’s disease, diabetes, and periodontitis. While changes in microbial populations are apparent during these diseases, the species associated with each disease can vary from patient to patient. Taking into account this interpatient variability, we hypothesized that specific microbiota-associated diseases would be marked by conserved microbial community behaviors. Here, we use gene expression analyses of patient-matched healthy and diseased human periodontal plaque to show that microbial communities have highly conserved metabolic gene expression profiles, whereas individual species within the community do not. Furthermore, disease-associated communities exhibit conserved changes in metabolic and virulence gene expression.

          Related collections

          Most cited references11

          • Record: found
          • Abstract: found
          • Article: not found

          The subgingival microbiome in health and periodontitis and its relationship with community biomass and inflammation.

          The goals of this study were to better understand the ecology of oral subgingival communities in health and periodontitis and elucidate the relationship between inflammation and the subgingival microbiome. Accordingly, we used 454-pyrosequencing of 16S rRNA gene libraries and quantitative PCR to characterize the subgingival microbiome of 22 subjects with chronic periodontitis. Each subject was sampled at two sites with similar periodontal destruction but differing in the presence of bleeding, a clinical indicator of increased inflammation. Communities in periodontitis were also compared with those from 10 healthy individuals. In periodontitis, presence of bleeding was not associated with different α-diversity or with a distinct microbiome, however, bleeding sites showed higher total bacterial load. In contrast, communities in health and periodontitis largely differed, with higher diversity and biomass in periodontitis. Shifts in community structure from health to periodontitis resembled ecological succession, with emergence of newly dominant taxa in periodontitis without replacement of primary health-associated species. That is, periodontitis communities had higher proportions of Spirochetes, Synergistetes, Firmicutes and Chloroflexi, among other taxa, while the proportions of Actinobacteria, particularly Actinomyces, were higher in health. Total Actinomyces load, however, remained constant from health to periodontitis. Moreover, an association existed between biomass and community structure in periodontitis, with the proportion of specific taxa correlating with bacterial load. Our study provides a global-scale framework for the ecological events in subgingival communities that underline the development of periodontitis. The association, in periodontitis, between inflammation, community biomass and community structure and their role in disease progression warrant further investigation.
            • Record: found
            • Abstract: found
            • Article: not found

            Moderated statistical tests for assessing differences in tag abundance.

            Digital gene expression (DGE) technologies measure gene expression by counting sequence tags. They are sensitive technologies for measuring gene expression on a genomic scale, without the need for prior knowledge of the genome sequence. As the cost of sequencing DNA decreases, the number of DGE datasets is expected to grow dramatically. Various tests of differential expression have been proposed for replicated DGE data using binomial, Poisson, negative binomial or pseudo-likelihood (PL) models for the counts, but none of the these are usable when the number of replicates is very small. We develop tests using the negative binomial distribution to model overdispersion relative to the Poisson, and use conditional weighted likelihood to moderate the level of overdispersion across genes. Not only is our strategy applicable even with the smallest number of libraries, but it also proves to be more powerful than previous strategies when more libraries are available. The methodology is equally applicable to other counting technologies, such as proteomic spectral counts. An R package can be accessed from http://bioinf.wehi.edu.au/resources/
              • Record: found
              • Abstract: found
              • Article: not found

              Xenobiotics shape the physiology and gene expression of the active human gut microbiome.

              The human gut contains trillions of microorganisms that influence our health by metabolizing xenobiotics, including host-targeted drugs and antibiotics. Recent efforts have characterized the diversity of this host-associated community, but it remains unclear which microorganisms are active and what perturbations influence this activity. Here, we combine flow cytometry, 16S rRNA gene sequencing, and metatranscriptomics to demonstrate that the gut contains a distinctive set of active microorganisms, primarily Firmicutes. Short-term exposure to a panel of xenobiotics significantly affected the physiology, structure, and gene expression of this active gut microbiome. Xenobiotic-responsive genes were found across multiple bacterial phyla, encoding antibiotic resistance, drug metabolism, and stress response pathways. These results demonstrate the power of moving beyond surveys of microbial diversity to better understand metabolic activity, highlight the unintended consequences of xenobiotics, and suggest that attempts at personalized medicine should consider interindividual variations in the active human gut microbiome. Copyright © 2013 Elsevier Inc. All rights reserved.

                Author and article information

                American Society of Microbiology (1752 N St., N.W., Washington, DC )
                1 April 2014
                Mar-Apr 2014
                : 5
                : 2
                : e01012-14
                [ a ]Department of Molecular Biosciences, Institute for Cellular and Molecular Biology, Center for Infectious Disease, University of Texas, Austin, Texas, USA
                [ b ]Department of Periodontology, School of Dentistry, Ege University, Izmir, Turkey
                Author notes
                Address correspondence to Marvin Whiteley, mwhiteley@ 123456austin.utexas.edu .

                Present address: Peter Jorth, Department of Microbiology, University of Washington, Seattle, Washington, USA.

                Editor Roberto Kolter, Harvard Medical School

                Copyright © 2014 Jorth et al.

                This is an open-access article distributed under the terms of the Creative Commons Attribution-Noncommercial-ShareAlike 3.0 Unported license, which permits unrestricted noncommercial use, distribution, and reproduction in any medium, provided the original author and source are credited.

                : 3 March 2014
                : 6 March 2014
                Page count
                Pages: 10
                Research Article
                Custom metadata
                March/April 2014

                Life sciences
                Life sciences


                Comment on this article