Despite the critical role of the human microbiota in health, our understanding of microbiota compositional dynamics during and after pregnancy is incomplete. We conducted a case-control study of 49 pregnant women, 15 of whom delivered preterm. From 40 of these women, we analyzed bacterial taxonomic composition of 3,767 specimens collected prospectively and weekly during gestation and monthly after delivery from the vagina, distal gut, saliva, and tooth/ gum. Linear mixed-effects modeling, medoid-based clustering, and Markov chain modeling were used to analyze community temporal trends, community structure, and vaginal community state transitions. Microbiota community taxonomic composition and diversity remained remarkably stable at all four body sites during pregnancy (P > 0.05 for trends over time). Prevalence of a Lactobacillus-poor vaginal community state type (CST 4) was inversely correlated with gestational age at delivery (P = 0.0039). Risk for preterm birth was more pronounced for subjects with CST 4 accompanied by elevated Gardnerella or Ureaplasma abundances. This finding was validated with a set of 246 vaginal specimens from nine women (four of whom delivered preterm). Most women experienced a postdelivery disturbance in the vaginal community characterized by a decrease in Lactobacillus species and an increase in diverse anaerobes such as Peptoniphilus, Prevotella, and Anaerococcus species. This disturbance was unrelated to gestational age at delivery and persisted for up to 1 y. These findings have important implications for predicting premature labor, a major global health problem, and for understanding the potential impact of a persistent, altered postpartum microbiota on maternal health, including outcomes of pregnancies following short interpregnancy intervals.16S rRNA gene | pregnancy | preterm birth | microbiome | premature labor

Preterm birth (PTB) is the leading cause of neonatal morbidity and mortality. Previous studies have suggested that the maternal vaginal microbiota contributes to the pathophysiology of PTB, but conflicting results in recent years have raised doubts. We conducted a study of PTB compared with term birth in two cohorts of pregnant women: one predominantly Caucasian (n = 39) at low risk for PTB, the second predominantly African American and at high-risk (n = 96). We profiled the taxonomic composition of 2,179 vaginal swabs collected prospectively and weekly during gestation using 16S rRNA gene sequencing. Previously proposed associations between PTB and lower Lactobacillus and higher Gardnerella abundances replicated in the low-risk cohort, but not in the high-risk cohort. High-resolution bioinformatics enabled taxonomic assignment to the species and subspecies levels, revealing that Lactobacillus crispatus was associated with low risk of PTB in both cohorts, while Lactobacillus iners was not, and that a subspecies clade of Gardnerella vaginalis explained the genus association with PTB. Patterns of cooccurrence between L. crispatus and Gardnerella were highly exclusive, while Gardnerella and L. iners often coexisted at high frequencies. We argue that the vaginal microbiota is better represented by the quantitative frequencies of these key taxa than by classifying communities into five community state types. Our findings extend and corroborate the association between the vaginal microbiota and PTB, demonstrate the benefits of high-resolution statistical bioinformatics in clinical microbiome studies, and suggest that previous conflicting results may reflect the different risk profile of women of black race.pregnancy | prematurity | vaginal microbiota | Lactobacillus | Gardnerella P reterm birth (PTB; delivery at <37 gestational wk) affects ≈12% of US births and is the leading cause of neonatal death and morbidity worldwide. Multiple lines of evidence support a role for the indigenous microbial communities of the mother (the maternal microbiota) in the pathophysiology of PTB. Microbial invasion of the amniotic cavity is one of the most frequent causes of spontaneous PTB (1), and the most common invading taxa are consistent with maternal origin (2-4). Bacterial vaginosis (BV), a condition involving an altered vaginal microbiota, has been consistently identified as a risk factor for PTB (5, 6). Multiple studies have also found chronic periodontitis, another condition associated with an altered microbiota, to be a risk factor for PTB (7,8).High-throughput sequencing methods have facilitated new lines of investigation into the microbial etiology of PTB (9, 10). Amplification and high-throughput sequencing of the 16S rRNA gene (metabarcoding) simultaneously measures the presence and relative abundance of thousands of bacterial taxa (composition), and resolves differences to the level of genus and sometimes species or subspecies. To date, metabarcoding studies of the relationship between the vaginal microbiota and PTB have y...

Background & Aims-The ability to obtain unlimited numbers of human hepatocytes would improve development of cell-based therapies for liver diseases, facilitate the study of liver biology and improve the early stages of drug discovery. Embryonic stem cells are pluripotent, can potentially differentiate into any cell type and could therefore be developed as a source of human hepatocytes.

The maintenance of pregnancy relies on finely tuned immune adaptations. We demonstrate that these adaptations are precisely timed, reflecting an immune clock of pregnancy in women delivering at term. Using mass cytometry, the abundance and functional responses of all major immune cell subsets were quantified in serial blood samples collected throughout pregnancy. Cell signaling–based Elastic Net, a regularized regression method adapted from the elastic net algorithm, was developed to infer and prospectively validate a predictive model of interrelated immune events that accurately captures the chronology of pregnancy. Model components highlighted existing knowledge and revealed previously unreported biology, including a critical role for the interleukin-2–dependent STAT5ab signaling pathway in modulating T cell function during pregnancy. These findings unravel the precise timing of immunological events occurring during a term pregnancy and provide the analytical framework to identify immunological deviations implicated in pregnancy-related pathologies.

A new biochemical method for estimating the virtual number of mitochondria (mt) per cell was developed and used together with a plasmid probe to measure mt DNA/mitochondrion and mt DNA/cell. These methods were used in five cell types from four mammalian species. Mt DNA/mitochondrion was essentially constant in all cell types (mean 2.6 +/- 0.30 SE mitochondrial DNA molecules/mt). Mt DNA molecules/cell encompassed an eight-fold range between various cell types (low 220 +/- 6.2; high 1,720 +/- 162 mt DNA molecules/cell). Virtual mt number/cell ranged from 83 +/- 17 to 677 +/- 80 (SE) mt/cell in various cell types. All five mammalian virtual mitochondria contained the same genomic mass. The number of virtual mitochondria per cell and amount of mt DNA per cell appear to be closely regulated within a given cell type but differ widely from cell type to cell type.

Noninvasive blood tests that provide information about fetal development and gestational age could potentially improve prenatal care. Ultrasound, the current gold standard, is not always affordable in low-resource settings and does not predict spontaneous preterm birth, a leading cause of infant death. In a pilot study of 31 healthy pregnant women, we found that measurement of nine cell-free RNA (cfRNA) transcripts in maternal blood predicted gestational age with comparable accuracy to ultrasound but at substantially lower cost. In a related study of 38 women (23 full-term and 15 preterm deliveries), all at elevated risk of delivering preterm, we identified seven cfRNA transcripts that accurately classified women who delivered preterm up to 2 months in advance of labor. These tests hold promise for prenatal care in both the developed and developing worlds, although they require validation in larger, blinded clinical trials.

Motivation: Multiple biological clocks govern a healthy pregnancy. These biological mechanisms produce immunologic, metabolomic, proteomic, genomic and microbiomic adaptations during the course of pregnancy. Modeling the chronology of these adaptations during full-term pregnancy provides the frameworks for future studies examining deviations implicated in pregnancy-related pathologies including preterm birth and preeclampsia. Results: We performed a multiomics analysis of 51 samples from 17 pregnant women, delivering at term. The datasets included measurements from the immunome, transcriptome, microbiome, proteome and metabolome of samples obtained simultaneously from the same patients. Multivariate predictive modeling using the Elastic Net (EN) algorithm was used to measure the ability of each dataset to predict gestational age. Using stacked generalization, these datasets were combined into a single model. This model not only significantly increased predictive power by combining all datasets, but also revealed novel interactions between different biological modalities. Future work includes expansion of the cohort to preterm-enriched populations and in vivo analysis of immune-modulating interventions based on the mechanisms identified. Availability and implementation: Datasets and scripts for reproduction of results are available through: https://nalab.stanford.edu/multiomics-pregnancy/.

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