Microbial Changes during Pregnancy, Birth, and Infancy

Several healthy developmental processes such as pregnancy, fetal development and infant development include a multitude of physiological changes: weight gain, hormonal and metabolic changes, as well as immune changes. In this review we present an additional important factor which both influences and is affected by these physiological processes- the microbiome. We summarize the known changes in microbiota composition at a variety of body sites including gut, vagina, oral cavity and placenta, throughout pregnancy, fetal development and early childhood. There is still a lot to be discovered; yet several pieces of research point to the healthy desired microbial changes. Future research is likely to unravel precise roles and mechanisms of the microbiota in gestation; perhaps linking the metabolic, hormonal and immune changes together. Although some research has started to link microbial dysbiosis and specific microbial populations with unhealthy pregnancy complications, it is important to first understand the context of the natural healthy microbial changes occurring. Until recently the placenta and developing fetus were considered to be germ free, containing no apparent microbiome. We present multiple study results showing distinct microbiota compositions in the placenta and meconium, alluding to early microbial colonization. These results may change dogmas and our overall understanding of the importance and roles of microbiota from the beginning of life. We further review the main factors shaping the infant microbiome- modes of delivery, feeding, weaning, and exposure to antibiotics. Taken together, we are starting to build a broader understanding of healthy vs. abnormal microbial alterations throughout major developmental time-points

Microbiome Preprocessing Machine Learning Pipeline

Background16S sequencing results are often used for Machine Learning (ML) tasks. 16S gene sequences are represented as feature counts, which are associated with taxonomic representation. Raw feature counts may not be the optimal representation for ML.MethodsWe checked multiple preprocessing steps and tested the optimal combination for 16S sequencing-based classification tasks. We computed the contribution of each step to the accuracy as measured by the Area Under Curve (AUC) of the classification.ResultsWe show that the log of the feature counts is much more informative than the relative counts. We further show that merging features associated with the same taxonomy at a given level, through a dimension reduction step for each group of bacteria improves the AUC. Finally, we show that z-scoring has a very limited effect on the results.ConclusionsThe prepossessing of microbiome 16S data is crucial for optimal microbiome based Machine Learning. These preprocessing steps are integrated into the MIPMLP - Microbiome Preprocessing Machine Learning Pipeline, which is available as a stand-alone version at: https://github.com/louzounlab/microbiome/tree/master/Preprocess or as a service at http://mip-mlp.math.biu.ac.il/Home Both contain the code, and standard test sets

A Guide to Enterotypes across the Human Body: Meta-Analysis of Microbial Community Structures in Human Microbiome Datasets

Recent analyses of human-associated bacterial diversity have categorized individuals into ‘enterotypes’ or clusters based on the abundances of key bacterial genera in the gut microbiota. There is a lack of consensus, however, on the analytical basis for enterotypes and on the interpretation of these results. We tested how the following factors influenced the detection of enterotypes: clustering methodology, distance metrics, OTU-picking approaches, sequencing depth, data type (whole genome shotgun (WGS) vs.16S rRNA gene sequence data), and 16S rRNA region. We included 16S rRNA gene sequences from the Human Microbiome Project (HMP) and from 16 additional studies and WGS sequences from the HMP and MetaHIT. In most body sites, we observed smooth abundance gradients of key genera without discrete clustering of samples. Some body habitats displayed bimodal (e.g., gut) or multimodal (e.g., vagina) distributions of sample abundances, but not all clustering methods and workflows accurately highlight such clusters. Because identifying enterotypes in datasets depends not only on the structure of the data but is also sensitive to the methods applied to identifying clustering strength, we recommend that multiple approaches be used and compared when testing for enterotypes

Analysis of gut microbial regulation of host gene expression along the length of the gut and regulation of gut microbial ecology through MyD88

BackgroundThe gut microbiota has profound effects on host physiology but local host-microbial interactions in the gut are only poorly characterised and are likely to vary from the sparsely colonised duodenum to the densely colonised colon. Microorganisms are recognised by pattern recognition receptors such as Toll-like receptors, which signal through the adaptor molecule MyD88.MethodsTo identify host responses induced by gut microbiota along the length of the gut and whether these required MyD88, transcriptional profiles of duodenum, jejunum, ileum and colon were compared from germ-free and conventionally raised wild-type and Myd88-/- mice. The gut microbial ecology was assessed by 454-based pyrosequencing and viruses were analysed by PCR.ResultsThe gut microbiota modulated the expression of a large set of genes in the small intestine and fewer genes in the colon but surprisingly few microbiota-regulated genes required MyD88 signalling. However, MyD88 was essential for microbiota-induced colonic expression of the antimicrobial genes Reg3β and Reg3γ in the epithelium, and Myd88 deficiency was associated with both a shift in bacterial diversity and a greater proportion of segmented filamentous bacteria in the small intestine. In addition, conventionally raised Myd88-/- mice had increased expression of antiviral genes in the colon, which correlated with norovirus infection in the colonic epithelium.ConclusionThis study provides a detailed description of tissue-specific host transcriptional responses to the normal gut microbiota along the length of the gut and demonstrates that the absence of MyD88 alters gut microbial ecology

A Guide to Enterotypes across the Human Body: Meta- Analysis of Microbial Community Structures in Human Microbiome Datasets

Recent analyses of human-associated bacterial diversity have categorized individuals into ‘enterotypes’ or clusters based on the abundances of key bacterial genera in the gut microbiota. There is a lack of consensus, however, on the analytical basis for enterotypes and on the interpretation of these results. We tested how the following factors influenced the detection of enterotypes: clustering methodology, distance metrics, OTU-picking approaches, sequencing depth, data type (whole genome shotgun (WGS) vs.16S rRNA gene sequence data), and 16S rRNA region. We included 16S rRNA gene sequences from the Human Microbiome Project (HMP) and from 16 additional studies and WGS sequences from the HMP and MetaHIT. In most body sites, we observed smooth abundance gradients of key genera without discrete clustering of samples. Some body habitats displayed bimodal (e.g., gut) or multimodal (e.g., vagina) distributions of sample abundances, but not all clustering methods and workflows accurately highlight such clusters. Because identifying enterotypes in datasets depends not only on the structure of the data but is also sensitive to the methods applied to identifying clustering strength, we recommend that multiple approaches be used and compared when testing for enterotypes

Preterm infant meconium microbiota transplant induces growth failure, inflammatory activation, and metabolic disturbances in germ-free mice

Preterm birth may result in adverse health outcomes. Very preterm infants typically exhibit postnatal growth restriction, metabolic disturbances, and exaggerated inflammatory responses. We investigated the differences in the meconium microbiota composition between very preterm (37 weeks) human neonates by 16S rRNA gene sequencing. Human meconium microbiota transplants to germ-free mice were conducted to investigate whether the meconium microbiota is causally related to the preterm infant phenotype in an experimental model. Our results indicate that very preterm birth is associated with a distinct meconium microbiota composition. Fecal microbiota transplant of very preterm infant meconium results in impaired growth, altered intestinal immune function, and metabolic parameters as compared to term infant meconium transplants in germ-free mice. This finding suggests that measures aiming to minimize the long-term adverse consequences of very preterm birth should be commenced during pregnancy or directly after birth.</p

Direct sequencing of the human microbiome readily reveals community differences

Future sequencing of the human microbiota will require greater breadth rather than depth

Disruption of paternal circadian rhythm affects metabolic health in male offspring via nongerm cell factors

Circadian rhythm synchronizes each body function with the environment and regulates physiology. Disruption of normal circadian rhythm alters organismal physiology and increases disease risk. Recent epidemiological data and studies in model organisms have shown that maternal circadian disruption is important for offspring health and adult phenotypes. Less is known about the role of paternal circadian rhythm for offspring health. Here, we disrupted circadian rhythm in male mice by night-restricted feeding and showed that paternal circadian disruption at conception is important for offspring feeding behavior, metabolic health, and oscillatory transcription. Mechanistically, our data suggest that the effect of paternal circadian disruption is not transferred to the offspring via the germ cells but initiated by corticosterone-based parental communication at conception and programmed during in utero development through a state of fetal growth restriction. These findings indicate paternal circadian health at conception as a newly identified determinant of offspring phenotypes

Dysbiosis of Skin Microbiota in Psoriatic Patients: Co-occurrence of Fungal and Bacterial Communities

Psoriasis is a chronic inflammatory skin disease, whose pathogenesis involves dysregulated interplay among immune cells, keratinocytes and environmental triggers, including microbiota. Bacterial and fungal dysbiosis has been recently associated with several chronic immune-mediated diseases including psoriasis. In this comprehensive study, we investigated how different sampling sites and methods reflect the uncovered skin microbiota composition. After establishing the most suitable approach, we further examined correlations between bacteria and fungi on the psoriatic skin. We compared microbiota composition determined in the same sample by sequencing two distinct hypervariable regions of the 16S rRNA gene. We showed that using the V3V4 region led to higher species richness and evenness than using the V1V2 region. In particular, genera, such as Staphylococcus and Micrococcus were more abundant when using the V3V4 region, while Planococcaceae, on the other hand, were detected only by the V1V2 region. We performed a detailed analysis of skin microbiota composition of psoriatic lesions, unaffected psoriatic skin, and healthy control skin from the back and elbow. Only a few discriminative features were uncovered, mostly specific for the sampling site or method (swab, scraping, or biopsy). Swabs from psoriatic lesions on the back and the elbow were associated with increased abundance of Brevibacterium and Kocuria palustris and Gordonia, respectively. In the same samples from psoriatic lesions, we found a significantly higher abundance of the fungus Malassezia restricta on the back, while Malassezia sympodialis dominated the elbow mycobiota. In psoriatic elbow skin, we found significant correlation between occurrence of Kocuria, Lactobacillus, and Streptococcus with Saccharomyces, which was not observed in healthy skin. For the first time, we showed here a psoriasis-specific correlation between fungal and bacterial species, suggesting a link between competition for niche occupancy and psoriasis. However, it still remains to be elucidated whether observed microbial shift and specific inter-kingdom relationship pattern are of primary etiological significance or secondary to the disease

Neonatal antibiotic exposure impairs child growth during the first six years of life by perturbing intestinal microbial colonization

Exposure to antibiotics in the first days of life is thought to affect various physiological aspects of neonatal development. Here, we investigate the long-term impact of antibiotic treatment in the neonatal period and early childhood on child growth in an unselected birth cohort of 12,422 children born at full term. We find significant attenuation of weight and height gain during the first 6 years of life after neonatal antibiotic exposure in boys, but not in girls, after adjusting for potential confounders. In contrast, antibiotic use after the neonatal period but during the first 6 years of life is associated with significantly higher body mass index throughout the study period in both boys and girls. Neonatal antibiotic exposure is associated with significant differences in the gut microbiome, particularly in decreased abundance and diversity of fecal Bifidobacteria until 2 years of age. Finally, we demonstrate that fecal microbiota transplant from antibiotic-exposed children to germ-free male, but not female, mice results in significant growth impairment. Thus, we conclude that neonatal antibiotic exposure is associated with a long-term gut microbiome perturbation and may result in reduced growth in boys during the first six years of life while antibiotic use later in childhood is associated with increased body mass index. In this study, Omry Koren, Samuli Rautava and colleagues report a sex-specific association between neonatal antibiotic exposure and weight and height gain during the first six years of life and showing that boys but not girls exposed to neonatal antibiotics exhibit impaired weight and height development