Background: Understanding the normal temporal variation in the human microbiome is critical to developing treatments for putative microbiome-related afflictions such as obesity, Crohn's disease, inflammatory bowel disease and malnutrition. Sequencing and computational technologies, however, have been a limiting factor in performing dense time series analysis of the human microbiome. Here, we present the largest human microbiota time series analysis to date, covering two individuals at four body sites over 396 timepoints. Results: We find that despite stable differences between body sites and individuals, there is pronounced variability in an individual's microbiota across months, weeks and even days. Additionally, only a small fraction of the total taxa found within a single body site appear to be present across all time points, suggesting that no core temporal microbiome exists at high abundance (although some microbes may be present but drop below the detection threshold). Many more taxa appear to be persistent but non-permanent community members. Conclusions: DNA sequencing and computational advances described here provide the ability to go beyond infrequent snapshots of our human-associated microbial ecology to high-resolution assessments of temporal variations over protracted periods, within and between body habitats and individuals. This capacity will allow us to define normal variation and pathologic states, and assess responses to therapeutic interventions.

The purpose of this study was to evaluate the composition and richness of bacterial communities associated with low-birthweight (LBW) infants in relation to host body site, individual, and age. Bacterial 16S rRNA genes from saliva samples, skin swabs, and stool samples collected on postnatal days 8, 10, 12, 15, 18, and 21 from six LBW (five premature) infants were amplified, pyrosequenced, and analyzed within a comparative framework that included analogous data from normal-birthweight (NBW) infants and healthy adults. We found that body site was the primary determinant of bacterial community composition in the LBW infants. However, site specificity depended on postnatal age: saliva and stool compositions diverged over time but were not significantly different until the babies were 15 days old. This divergence was primarily driven by progressive temporal turnover in the distal gut, which proceeded at a rate similar to that of age-matched NBW infants. Neonatal skin was the most adult-like in microbiota composition, while saliva and stool remained the least so. Compositional variation among infants was marked and depended on body site and age. Only the smallest, most premature infant received antibiotics during the study period; this heralded a coexpansion of Pseudomonas aeruginosa and a novel Mycoplasma sp. in the oral cavity of this vaginally delivered, intubated patient. We conclude that concurrent molecular surveillance of multiple body sites in LBW neonates reveals a delayed compositional differentiation of the oral cavity and distal gut microbiota and, in the case of one infant, an abundant, uncultivated oral Mycoplasma sp., recently detected in human vaginal samples. IMPORTANCE Complications of premature birth are the most common cause of neonatal mortality. Colonization by the indigenous microbiota, which begins at delivery, may predispose some high-risk newborns to invasive infection or necrotizing enterocolitis (NEC), and protect others, yet neonatal microbiome dynamics are poorly understood. Here, we present the first cultivation-independent time series tracking microbiota assembly across multiple body sites in a synchronous cohort of hospitalized low-birthweight (LBW) neonates. We take advantage of archived samples and publically available sequence data and compare our LBW infant findings to those from normal-birthweight (NBW) infants and healthy adults. Our results suggest potential windows of opportunity for the dispersal of microbes within and between hosts and support recent findings of substantial baseline spatiotemporal variation in microbiota composition among high-risk newborns.

The vaginal ecosystem is closely tied to human health and reproductive outcomes, yet its dynamics in the wake of childbirth remain poorly characterized. Here, we profile the vaginal microbiota and cytokine milieu of participants sampled longitudinally throughout pregnancy and for at least one year postpartum. We show that delivery, regardless of mode, is associated with a vaginal pro-inflammatory cytokine response and the loss of Lactobacillus dominance. By contrast, neither the progression of gestation nor the approach of labor strongly altered the vaginal ecosystem. At 9.5-months postpartum—the latest timepoint at which cytokines were assessed—elevated inflammation coincided with vaginal bacterial communities that had remained perturbed (highly diverse) from the time of delivery. Time-to-event analysis indicated a one-year postpartum probability of transitioning to Lactobacillus dominance of 49.4%. As diversity and inflammation declined during the postpartum period, dominance by L. crispatus, the quintessential health-associated commensal, failed to return: its prevalence before, immediately after, and one year after delivery was 41%, 4%, and 9%, respectively. Revisiting our pre-delivery data, we found that a prior live birth was associated with a lower odds of L. crispatus dominance in pregnant participants—an outcome modestly tempered by a longer ( > 18-month) interpregnancy interval. Our results suggest that reproductive history and childbirth in particular remodel the vaginal ecosystem and that the timing and degree of recovery from delivery may help determine the subsequent health of the woman and of future pregnancies.

Diverse and non- Lactobacillus -dominated vaginal microbial communities are associated with adverse health outcomes such as preterm birth and the acquisition of sexually transmitted infections. Despite the importance of recognizing and understanding the key risk-associated features of these communities, their heterogeneous structure and properties remain ill-defined. Clustering approaches are commonly used to characterize vaginal communities, but they lack sensitivity and robustness in resolving substructures and revealing transitions between potential sub-communities. Here, we address this need with an approach based on mixed membership topic models. Using longitudinal data from cohorts of pregnant and non-pregnant study participants, we show that topic models more accurately describe sample composition, longitudinal changes, and better predict the loss of Lactobacillus dominance. We identify several non- Lactobacillus -dominated sub-communities common to both cohorts and independent of reproductive status. In non-pregnant individuals, we find that the menstrual cycle modulates transitions between and within sub-communities, as well as the concentrations of half of the cytokines and 18% of metabolites. Overall, our analyses based on mixed membership models reveal substructures of vaginal ecosystems which may have important clinical and biological associations.

Lactose intolerance is a gastrointestinal disorder diagnosed with a lactose hydrogen breath test. Lifestyle changes such as diet interventions can impact the gut microbiome; however, the role of the microbiome in lactose intolerance is unclear.

Diverse and non- Lactobacillus -dominated vaginal microbial communities are associated with adverse health outcomes such as preterm birth and the acquisition of sexually transmitted infections. Despite the importance of recognizing and understanding the key risk-associated features of these communities, their heterogeneous structure and properties remain ill-defined. Clustering approaches are commonly used to characterize vaginal communities, but they lack sensitivity and robustness in resolving substructures and revealing transitions between potential sub-communities. Here, we address this need with an approach based on mixed membership topic models, using longitudinal data from cohorts of pregnant and non-pregnant study participants. We identify several non- Lactobacillus -dominated sub-communities common to both cohorts and independent of reproductive status. In non-pregnant individuals, we find that the menstrual cycle modulates transitions between and within sub-communities. In addition, a specific non- Lactobacillus -dominated sub-community, which was associated with preterm delivery in pregnant participants, was also more common during menses, a time of elevated vaginal inflammation in non-pregnant participants. Overall, our analyses based on mixed membership models reveal substructures of vaginal ecosystems which may have important clinical and biological associations.