Pregnancy's stronghold on the vaginal microbiome.

To assess the vaginal microbiome throughout full-term uncomplicated pregnancy.Vaginal swabs were obtained from twelve pregnant women at 8-week intervals throughout their uncomplicated pregnancies. Patients with symptoms of vaginal infection or with recent antibiotic use were excluded. Swabs were obtained from the posterior fornix and cervix at 8-12, 17-21, 27-31, and 36-38 weeks of gestation. The microbial community was profiled using hypervariable tag sequencing of the V3-V5 region of the 16S rRNA gene, producing approximately 8 million reads on the Illumina MiSeq.Samples were dominated by a single genus, Lactobacillus, and exhibited low species diversity. For a majority of the patients (n = 8), the vaginal microbiome was dominated by Lactobacillus crispatus throughout pregnancy. Two patients showed Lactobacillus iners dominance during the course of pregnancy, and two showed a shift between the first and second trimester from L. crispatus to L. iners dominance. In all of the samples only these two species were identified, and were found at an abundance of higher than 1% in this study. Comparative analyses also showed that the vaginal microbiome during pregnancy is characterized by a marked dominance of Lactobacillus species in both Caucasian and African-American subjects. In addition, our Caucasian subject population clustered by trimester and progressed towards a common attractor while African-American women clustered by subject instead and did not progress towards a common attractor.Our analyses indicate normal pregnancy is characterized by a microbiome that has low diversity and high stability. While Lactobacillus species strongly dominate the vaginal environment during pregnancy across the two studied ethnicities, observed differences between the longitudinal dynamics of the analyzed populations may contribute to divergent risk for pregnancy complications. This helps establish a baseline for investigating the role of the microbiome in complications of pregnancy such as preterm labor and preterm delivery

Potential contribution of the uterine microbiome in the development of endometrial cancer

Abstract Background Endometrial cancer studies have led to a number of well-defined but mechanistically unconnected genetic and environmental risk factors. One of the emerging modulators between environmental triggers and genetic expression is the microbiome. We set out to inquire about the composition of the uterine microbiome and its putative role in endometrial cancer. Methods We undertook a study of the microbiome in samples taken from different locations along the female reproductive tract in patients with endometrial cancer (n = 17), patients with endometrial hyperplasia (endometrial cancer precursor, n = 4), and patients afflicted with benign uterine conditions (n = 10). Vaginal, cervical, Fallopian, ovarian, peritoneal, and urine samples were collected aseptically both in the operating room and the pathology laboratory. DNA extraction was followed by amplification and high-throughput next generation sequencing (MiSeq) of the 16S rDNA V3-V5 region to identify the microbiota present. Microbiota data were summarized using both α-diversity to reflect species richness and evenness within bacterial populations and β-diversity to reflect the shared diversity between bacterial populations. Statistical significance was determined through the use of multiple testing, including the generalized mixed-effects model. Results The microbiome sequencing (16S rDNA V3-V5 region) revealed that the microbiomes of all organs (vagina, cervix, Fallopian tubes, and ovaries) are significantly correlated (p 4.5). Conclusions Our results suggest that the detection of A. vaginae and the identified Porphyromonas sp. in the gynecologic tract combined with a high vaginal pH is statistically associated with the presence of endometrial cancer. Given the documented association of the identified microorganisms with other pathologies, these findings raise the possibility of a microbiome role in the manifestation, etiology, or progression of endometrial cancer that should be further investigated

Individualized medicine and the microbiome of the reproductive tract

Humans have evolved along with the millions of microorganisms that populate their bodies. These microbes (1014) outnumber human cells by 10 to 1 and account for 3x 106 genes, more than ten times the 25,000 human genes. This microbial metagenome acts as our other genome and like our own genes, is unique to the individual. Recent international efforts such as the Human Microbiome Project (HMP) and the MetaHIT Project have helped catalog these microbial genomes using culture-independent, high-throughput, next-generation sequencing. This manuscript will describe recent efforts to define microbial diversity in the female reproductive tract because of the impact that microbial function has on reproductive efficiency. In this review, we will discuss current evidence that microbial communities are critical for maintaining reproductive health and how perturbations of microbial community structures can impact reproductive health from the aspect of infection, reproductive cyclicity, pregnancy and disease states. Investigations of the human microbiome are propelling interventional strategies from treating medical populations to treating individual patients. In particular, we highlight how understanding and defining microbial community structures in different disease and physiological states heave lead to the discovery of biomarkers and, more importantly, the development and implementation of microbial intervention strategies (probiotics) into modern day medicine. Finally this review will conclude with a literature summary of the effectiveness of microbial intervention strategies that have been implemented in animal and human models of disease and the potential for integrating these microbial intervention strategies into standard clinical practice

Estimation of species richness according to Chao 1 index.

<p>A – African-American subjects (Red – N009, Orange – N018, Blue – N017). Diversity between subjects is significant and therefore does not allow for the grouping of the subjects for analytical purposes. B – Caucasian subjects. No significant differences in diversity were found among subjects.</p

Principal Component Analysis (PCA) of temporal dynamics of the vaginal microbiome during pregnancy.

<p>Arrows indicate shifts from the first timepoint, taken at 8–12 weeks, and the subsequent timepoints. Notice that all temporal profiles that involve L. iners dominance involve a shift in the microbiome profile while purely <i>L. crispatus</i> dominated temporal profiles do not. Visualization carried out using Matplotlib version 1.2.1 (The MathWorks, Inc.).</p

Pie charts representing the bacterial distribution found in each of the samples represented.

<p>Subject 101 is representative of 7 other patients with similar profiles (Subjects 104, 105, 106, 107, 109, 113 and 114). Subject 103 and Subject 110 have similar profiles. Subject 108 and Subject 111 have similar profiles. Divisions within the pie charts represent different OTUs (Operational Taxonomic Units – Strain level). “Other” represents OTUs with ≤1% abundance that belong to various species, excluding <i>L. crispatus</i> and <i>L. iners</i>.</p

Significant parameters found in the metadata.

<p>Significant differences from the <i>L. crispatus</i> profile, as determined by t-test, are highlighted by *.</p

Pregnancy effect in African-American and Caucasian subjects as measured by Chao1 diversity Index.

<p>Diversity is significantly reduced during pregnancy in both ethnicities (**p<0.01, Monte Carlo analyses, 999 permutations).</p

Unweighted Unifrac beta-diversity between pregnant and non-pregnant subjects within each ethnicity.

<p>Caucasians show significant convergence as a result of pregnancy (results confounded by platform effects – See <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0098514#pone.0098514.s004" target="_blank">Table S1</a>) while African-Americans show significant divergence in pregnancy when compared to non-pregnant subjects. **p<0.001, Monte Carlo analyses, 999 permutations.</p

Unweighted PCA analysis by Subject and Trimester.

<p>A – African-American by Subject. Clustering by Subject can be observed. B – Caucasian by Subject. No clear clustering is observed. C – African-American by Trimester. No common attractor can be identified. D – Caucasian by Trimester. A common attractor can be observed. Plots C and D – 1^st Trimester – Red; 2^nd Trimester – Blue; 3^rd Trimester – Orange.</p