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

      A Metagenomic Approach to Characterization of the Vaginal Microbiome Signature in Pregnancy


      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.


          While current major national research efforts ( i.e., the NIH Human Microbiome Project) will enable comprehensive metagenomic characterization of the adult human microbiota, how and when these diverse microbial communities take up residence in the host and during reproductive life are unexplored at a population level. Because microbial abundance and diversity might differ in pregnancy, we sought to generate comparative metagenomic signatures across gestational age strata. DNA was isolated from the vagina (introitus, posterior fornix, midvagina) and the V5V3 region of bacterial 16S rRNA genes were sequenced (454FLX Titanium platform). Sixty-eight samples from 24 healthy gravidae (18 to 40 confirmed weeks) were compared with 301 non-pregnant controls (60 subjects). Generated sequence data were quality filtered, taxonomically binned, normalized, and organized by phylogeny and into operational taxonomic units (OTU); principal coordinates analysis (PCoA) of the resultant beta diversity measures were used for visualization and analysis in association with sample clinical metadata. Altogether, 1.4 gigabytes of data containing >2.5 million reads (averaging 6,837 sequences/sample of 493 nt in length) were generated for computational analyses. Although gravidae were not excluded by virtue of a posterior fornix pH >4.5 at the time of screening, unique vaginal microbiome signature encompassing several specific OTUs and higher-level clades was nevertheless observed and confirmed using a combination of phylogenetic, non-phylogenetic, supervised, and unsupervised approaches. Both overall diversity and richness were reduced in pregnancy, with dominance of Lactobacillus species (L. iners crispatus, jensenii and johnsonii, and the orders Lactobacillales (and Lactobacillaceae family), Clostridiales, Bacteroidales, and Actinomycetales. This intergroup comparison using rigorous standardized sampling protocols and analytical methodologies provides robust initial evidence that the vaginal microbial 16S rRNA gene catalogue uniquely differs in pregnancy, with variance of taxa across vaginal subsite and gestational age.

          Related collections

          Most cited references 28

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

          Accurate determination of microbial diversity from 454 pyrosequencing data.

          We present an algorithm, PyroNoise, that clusters the flowgrams of 454 pyrosequencing reads using a distance measure that models sequencing noise. This infers the true sequences in a collection of amplicons. We pyrosequenced a known mixture of microbial 16S rDNA sequences extracted from a lake and found that without noise reduction the number of operational taxonomic units is overestimated but using PyroNoise it can be accurately calculated.
            • Record: found
            • Abstract: found
            • Article: not found

            Rapid denoising of pyrosequencing amplicon data: exploiting the rank-abundance distribution

            We developed a fast method for denoising pyrosequencing for community 16S rRNA analysis. We observe a 2–4 fold reduction in the number of observed OTUs (operational taxonomic units) comparing denoised with non-denoised data. ~50,000 sequences can be denoised on a laptop within an hour, two orders of magnitude faster than published techniques. We demonstrate the effects of denoising on alpha and beta diversity of large 16S rRNA datasets.
              • Record: found
              • Abstract: found
              • Article: not found

              Temperature gradient gel electrophoresis analysis of 16S rRNA from human fecal samples reveals stable and host-specific communities of active bacteria.

              The diversity of the predominant bacteria in the human gastrointestinal tract was studied by using 16S rRNA-based approaches. PCR amplicons of the V6 to V8 regions of fecal 16S rRNA and ribosomal DNA (rDNA) were analyzed by temperature gradient gel electrophoresis (TGGE). TGGE of fecal 16S rDNA amplicons from 16 individuals showed different profiles, with some bands in common. Fecal samples from two individuals were monitored over time and showed remarkably stable profiles over a period of at least 6 months. TGGE profiles derived from 16S rRNA and rDNA amplicons showed similar banding patterns. However, the intensities of bands with similar mobilities differed in some cases, indicating a different contribution to the total active fraction of the prominent fecal bacteria. Most 16S rRNA amplicons in the TGGE pattern of one subject were identified by cloning and sequence analysis. Forty-five of the 78 clones matched 15 bands, and 33 clones did not match any visible band in the TGGE pattern. Nested PCR of amplified 16S rDNA indicated preferential amplification of a sequence corresponding to 12 of the 33 nonmatching clones with similar mobilities in TGGE. The sequences matching 15 bands in the TGGE pattern showed 91.5 to 98.7% homology to sequences derived from different Clostridium clusters. Most of these were related to strains derived from the human intestine. The results indicate that the combination of cloning and TGGE analysis of 16S rDNA amplicons is a reliable approach to monitoring different microbial communities in feces.

                Author and article information

                Role: Editor
                PLoS One
                PLoS ONE
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                13 June 2012
                : 7
                : 6
                [1 ]Department of Obstetrics & Gynecology, Division of Maternal-Fetal Medicine, Baylor College of Medicine and Texas Children’s Hospital, Houston, Texas, United States of America
                [2 ]Department of Pathology & Immunology, Baylor College of Medicine and Texas Children’s Hospital, Houston, Texas, United States of America
                [3 ]Bioinformatics Research Laboratory, Baylor College of Medicine and Texas Children’s Hospital, Houston, Texas, United States of America
                [4 ]Harvard School of Public Health, Harvard University, Cambridge, Massachusetts, United States of America
                [5 ]Broad Institute, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America
                [6 ]Department of Molecular Virology and Microbiology, Baylor College of Medicine and Texas Children’s Hospital, Houston, Texas, United States of America
                Columbia University, United States of America
                Author notes

                Conceived and designed the experiments: KA JV. Performed the experiments: KA JP JV. Analyzed the data: KA KR JM NS TM CC S. Raza AM DG CH JV. Contributed reagents/materials/analysis tools: KA KR JM NS AM CH JV. Wrote the paper: KA KR JM CC DG CH JV. Critical review of the manuscript: IVdV. Clinical recruitment of subjects: S. Rosenbaum.

                Aagaard 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.
                Page count
                Pages: 15
                Research Article
                Computational Biology
                Applied Microbiology
                Medical Microbiology
                Microbial Pathogens
                Infectious Diseases
                Gynecologic Infections
                Infectious Disease Modeling
                Obstetrics and Gynecology
                Pregnancy Complications
                Preterm Labor
                Female Genital Diseases
                Genitourinary Infections



                Comment on this article