Meconium

BackgroundPreterm birth is the second leading cause of death in children under the age of five years worldwide, but the etiology of many cases remains enigmatic. The dogma that the fetus resides in a sterile environment is being challenged by recent findings and the question has arisen whether microbes that colonize the fetus may be related to preterm birth. It has been posited that meconium reflects the in-utero microbial environment. In this study, correlations between fetal intestinal bacteria from meconium and gestational age were examined in order to suggest underlying mechanisms that may contribute to preterm birth.MethodsMeconium from 52 infants ranging in gestational age from 23 to 41 weeks was collected, the DNA extracted, and 16S rRNA analysis performed. Resulting taxa of microbes were correlated to clinical variables and also compared to previous studies of amniotic fluid and other human microbiome niches.FindingsIncreased detection of bacterial 16S rRNA in meconium of infants of InterpretationThis provides the first evidence to support the hypothesis that the fetal intestinal microbiome derived from swallowed amniotic fluid may be involved in the inflammatory response that leads to premature birth.

BackgroundEmerging evidence suggests that the in utero environment is not sterile as once presumed. Work in the mouse demonstrated transmission of commensal bacteria from mother to fetus during gestation, though it is unclear what modulates this process. We have previously shown in the nonhuman primate that, independent of obesity, a maternal high-fat diet during gestation and lactation persistently shapes the juvenile gut microbiome. We therefore sought to interrogate in a population-based human longitudinal cohort whether a maternal high-fat diet similarly alters the neonatal and infant gut microbiome in early life.MethodsA representative cohort was prospectively enrolled either in the early third trimester or intrapartum (n = 163), with a subset consented to longitudinal sampling through the postpartum interval (n = 81). Multiple body site samples, including stool and meconium, were collected from neonates at delivery and by 6 weeks of age. A rapid dietary questionnaire was administered to estimate intake of fat, added sugars, and fiber over the past month (National Health and Examination Survey). DNA was extracted from each infant meconium/stool sample (MoBio) and subjected to 16S rRNA gene sequencing and analysis.ResultsOn average, the maternal dietary intake of fat ranged from 14.0 to 55.2 %, with an average intake of 33.1 % (σ = 6.1 %). Mothers whose diets significantly differed from the mean (±1 standard deviation) were separated into two distinct groups, a control group (n = 13, μ = 24.4 %) and a high-fat group (n = 13, μ = 43.1 %). Principal coordinate analysis revealed that the microbiome of the neonatal stool at birth (meconium) clustered differently by virtue of maternal gestational diet (PERMANOVA p = 0.001). LEfSe feature selection identified several taxa that discriminated the groups, with a notable relative depletion of Bacteroides in the neonates exposed to a maternal high-fat gestational diet (Student's t-test, p ConclusionsSimilar to the primate, independent of maternal body mass index, a maternal high-fat diet is associated with distinct changes in the neonatal gut microbiome at birth which persist through 4-6 weeks of age. Our findings underscore the importance of counseling pregnant mothers on macronutrient consumption during pregnancy and lactation.

ObjectivesThis study was aimed to assess the diversity of the meconium microbiome and determine if the bacterial community is affected by maternal diabetes status.MethodsThe first intestinal discharge (meconium) was collected from 23 newborns stratified by maternal diabetes status: 4 mothers had pre-gestational type 2 diabetes mellitus (DM) including one mother with dizygotic twins, 5 developed gestational diabetes mellitus (GDM) and 13 had no diabetes. The meconium microbiome was profiled using multi-barcode 16S rRNA sequencing followed by taxonomic assignment and diversity analysis.ResultsAll meconium samples were not sterile and contained diversified microbiota. Compared with adult feces, the meconium showed a lower species diversity, higher sample-to-sample variation, and enrichment of Proteobacteria and reduction of Bacteroidetes. Among the meconium samples, the taxonomy analyses suggested that the overall bacterial content significantly differed by maternal diabetes status, with the microbiome of the DM group showing higher alpha-diversity than that of no-diabetes or GDM groups. No global difference was found between babies delivered vaginally versus via Cesarean-section. Regression analysis showed that the most robust predictor for the meconium microbiota composition was the maternal diabetes status that preceded pregnancy. Specifically, Bacteroidetes (phyla) and Parabacteriodes (genus) were enriched in the meconium in the DM group compared to the no-diabetes group.ConclusionsOur study provides evidence that meconium contains diversified microbiota and is not affected by the mode of delivery. It also suggests that the meconium microbiome of infants born to mothers with DM is enriched for the same bacterial taxa as those reported in the fecal microbiome of adult DM patients.

IntroductionEarly gut microbiota development plays an important role in lifelong human health, and meconium offers a unique matrix to understand prenatal microbial exposures. This study from the LIMIT cohort aimed at investigating associations between maternal pre-pregnancy body mass index (pre-BMI) and gestational weight gain (GWG), as well as other maternal lifestyle and environmental factors, with the structure of meconium microbiota at delivery.MethodsTwo hundred pregnant women were enrolled during the pre-hospital care before birth at Fondazione IRCCS Policlinico San Matteo (Pavia), according to the inclusion/exclusion criteria. Mothers were grouped based on their GWG gain category according to the IOM guidelines. 168 meconium samples were analyzed using a targeted long-reads sequence approach. Bacterial 16S rRNA (V1-V8) amplicons were sequenced using the Oxford Nanopore PromethION platform. Supervised analyses assessed associations between maternal variables and bacterial diversity, while an unsupervised learning approach based on the Partitioning Around Medoids (PAM) clustering algorithm was applied to identify specific microbial clusters unrelated to the cohort's metadata.ResultsNo significant associations were observed between GWG, pre-BMI or other lifestyle factors and overall microbial diversity. Unsupervised learning revealed five distinct meconium microbial clusters, i.e. "microbiota-types", related to different taxonomic profiles, determined by the variations in specific bacterial species.ConclusionNo significant influence of the studied variables was observed on meconium microbiota. However, the meconium microbial communities appear to organize into enterotype-like structures, highlighting the need for longitudinal studies to identify key determinants of early colonization.