Associations between the gut microbiome and metabolome in early life
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo Sapiens
TISSUE(S): Feces
PROVIDER: ST001813 | MetabolomicsWorkbench |
REPOSITORIES: MetabolomicsWorkbench
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Project description:BackgroundThe infant intestinal microbiome plays an important role in metabolism and immune development with impacts on lifelong health. The linkage between the taxonomic composition of the microbiome and its metabolic phenotype is undefined and complicated by redundancies in the taxon-function relationship within microbial communities. To inform a more mechanistic understanding of the relationship between the microbiome and health, we performed an integrative statistical and machine learning-based analysis of microbe taxonomic structure and metabolic function in order to characterize the taxa-function relationship in early life.ResultsStool samples collected from infants enrolled in the New Hampshire Birth Cohort Study (NHBCS) at approximately 6-weeks (n = 158) and 12-months (n = 282) of age were profiled using targeted and untargeted nuclear magnetic resonance (NMR) spectroscopy as well as DNA sequencing of the V4-V5 hypervariable region from the bacterial 16S rRNA gene. There was significant inter-omic concordance based on Procrustes analysis (6 weeks: p = 0.056; 12 months: p = 0.001), however this association was no longer significant when accounting for phylogenetic relationships using generalized UniFrac distance metric (6 weeks: p = 0.376; 12 months: p = 0.069). Sparse canonical correlation analysis showed significant correlation, as well as identifying sets of microbe/metabolites driving microbiome-metabolome relatedness. Performance of machine learning models varied across different metabolites, with support vector machines (radial basis function kernel) being the consistently top ranked model. However, predictive R2 values demonstrated poor predictive performance across all models assessed (avg: - 5.06% -- 6 weeks; - 3.7% -- 12 months). Conversely, the Spearman correlation metric was higher (avg: 0.344-6 weeks; 0.265-12 months). This demonstrated that taxonomic relative abundance was not predictive of metabolite concentrations.ConclusionsOur results suggest a degree of overall association between taxonomic profiles and metabolite concentrations. However, lack of predictive capacity for stool metabolic signatures reflects, in part, the possible role of functional redundancy in defining the taxa-function relationship in early life as well as the bidirectional nature of the microbiome-metabolome association. Our results provide evidence in favor of a multi-omic approach for microbiome studies, especially those focused on health outcomes.
| S-EPMC8400760 | biostudies-literature
Project description:In early life, the intestinal mucosa and immune system undergo a critical developmental process to contain the expanding gut microbiome while promoting tolerance towards commensals, yet the influence of maternal diet and microbial composition on offspring immune maturation remains poorly understood. We colonized germ-free mice with a consortium of 14 strains, fed them a standard fiber-rich chow or a fiber-free diet, and then longitudinally assessed offspring development during the weaning period. Unlike pups born to dams fed the fiber-rich diet, pups of fiber-deprived dams demonstrated delayed colonization with Akkermansia muciniphila, a mucin-foraging bacterium that can also utilize milk oligosaccharides. The pups of fiber-deprived dams exhibited an enrichment of colonic transcripts corresponding to defense response pathways and a peak in Il22 expression at weaning. Removal of A. muciniphila from the community, but maintenance on the fiber-rich diet, was associated with reduced proportions of RORγt-positive innate and adaptive immune cell subsets. Our results highlight the potent influence of maternal dietary fiber intake and discrete changes in microbial composition on the postnatal microbiome assemblage and early immune development.
| S-SCDT-10_15252-EMMM_202217241 | biostudies-other
Project description:BackgroundGut microbiota may play a role in egg allergy. We sought to examine the association between early-life gut microbiota and egg allergy.MethodsWe studied 141 children with egg allergy and controls from the multicenter Consortium of Food Allergy Research study. At enrollment (age 3 to 16 months), fecal samples were collected, and clinical evaluation, egg-specific IgE measurement, and egg skin prick test were performed. Gut microbiome was profiled by 16S rRNA sequencing. Analyses for the primary outcome of egg allergy at enrollment, and the secondary outcomes of egg sensitization at enrollment and resolution of egg allergy by age 8 years, were performed using Quantitative Insights into Microbial Ecology, Phylogenetic Investigation of Communities by Reconstruction of Unobserved States, and Statistical Analysis of Metagenomic Profiles.ResultsCompared to controls, increased alpha diversity and distinct taxa (PERMANOVA P = 5.0 × 10-4 ) characterized the early-life gut microbiome of children with egg allergy. Genera from the Lachnospiraceae, Streptococcaceae, and Leuconostocaceae families were differentially abundant in children with egg allergy. Predicted metagenome functional analyses showed differential purine metabolism by the gut microbiota of egg-allergic subjects (Kruskal-Wallis Padj = 0.021). Greater gut microbiome diversity and genera from Lachnospiraceae and Ruminococcaceae were associated with egg sensitization (PERMANOVA P = 5.0 × 10-4 ). Among those with egg allergy, there was no association between early-life gut microbiota and egg allergy resolution by age 8 years.ConclusionThe distinct early-life gut microbiota in egg-allergic and egg-sensitized children identified by our study may point to targets for preventive or therapeutic intervention.
| S-EPMC6436531 | biostudies-literature
Project description:BackgroundGut microbiota may play a role in the natural history of cow's milk allergy.ObjectiveWe sought to examine the association between early-life gut microbiota and the resolution of cow's milk allergy.MethodsWe studied 226 children with milk allergy who were enrolled at infancy in the Consortium of Food Allergy observational study of food allergy. Fecal samples were collected at age 3 to 16 months, and the children were followed longitudinally with clinical evaluation, milk-specific IgE levels, and milk skin prick test performed at enrollment, 6 months, 12 months, and yearly thereafter up until age 8 years. Gut microbiome was profiled by 16s rRNA sequencing and microbiome analyses performed using Quantitative Insights into Microbial Ecology (QIIME), Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt), and Statistical Analysis of Metagenomic Profiles (STAMP).ResultsMilk allergy resolved by age 8 years in 128 (56.6%) of the 226 children. Gut microbiome composition at age 3 to 6 months was associated with milk allergy resolution by age 8 years (PERMANOVA P = .047), with enrichment of Clostridia and Firmicutes in the infant gut microbiome of subjects whose milk allergy resolved. Metagenome functional prediction supported decreased fatty acid metabolism in the gut microbiome of subjects whose milk allergy resolved (η2 = 0.43; ANOVA P = .034).ConclusionsEarly infancy is a window during which gut microbiota may shape food allergy outcomes in childhood. Bacterial taxa within Clostridia and Firmicutes could be studied as probiotic candidates for milk allergy therapy.
| S-EPMC5056801 | biostudies-literature
Project description:Despite multiple vaccine doses early in life, a substantial proportion of infants do not mount protective responses. In this study, we followed a cohort of children over the first 2 years of life, collecting microbiome and metabolome data longitudinally to investigate correlates of lower and higher responses to primary vaccinations. We found that the stool and nasopharyngeal microbiome developed with age, though demonstrated divergent timing and patterns in maturation. When measured at child age 2 months, evenness of genera in the stool microbiome correlated with lower vaccine responses, upregulated metabolome genes that encode for lipid A biosynthesis and oxidative phosphorylation correlated with higher vaccine responses, and abundance of phenylpyruvic acid in serum correlated with lower vaccine responses, measured 10 months later. Antibiotic exposure was associated with low vaccine response, and microbiome/metabolome features at child age 2 months, before childhood vaccinations commenced, correlated with variations in vaccine responses measured at child age 1 year. These results indicate that there may be potential to intervene before first childhood vaccinations to improve later protection. IMPORTANCE We show that simultaneous study of stool and nasopharyngeal microbiome reveals divergent timing and patterns of maturation, suggesting that local mucosal factors may influence microbiome composition in the gut and respiratory system. Antibiotic exposure in early life as occurs commonly, may have an adverse effect on vaccine responsiveness. Abundance of gut and/or nasopharyngeal bacteria with the machinery to produce lipopolysaccharide-a toll-like receptor 4 agonist-may positively affect future vaccine protection, potentially by acting as a natural adjuvant. The increased levels of serum phenylpyruvic acid in infants with lower vaccine-induced antibody levels suggest an increased abundance of hydrogen peroxide, leading to more oxidative stress in low vaccine-responding infants.
| S-EPMC10654091 | biostudies-literature
Project description:Microbial colonization of the human gut occurs soon after birth, proceeds through well-studied phases and is affected by lifestyle and other factors. Less is known about phage community dynamics during infant gut colonization due to small study sizes, an inability to leverage large databases and a lack of appropriate bioinformatics tools. Here we reanalysed whole microbial community shotgun sequencing data of 12,262 longitudinal samples from 887 children from four countries across four years of life as part of the The Environmental Determinants of Diabetes in the Young (TEDDY) study. We developed an extensive metagenome-assembled genome catalogue using the Marker-MAGu pipeline, which comprised 49,111 phage taxa from existing human microbiome datasets. This was used to identify phage marker genes and their integration into the MetaPhlAn 4 bacterial marker gene database enabled simultaneous assessment of phage and bacterial dynamics. We found that individual children are colonized by hundreds of different phages, which are more transitory than bacteria, accumulating a more diverse phage community over time. Type 1 diabetes correlated with a decreased rate of change in bacterial and viral communities in children aged one and two. The addition of phage data improved the ability of machine learning models to discriminate samples by country. Finally, although phage populations were specific to individuals, we observed trends of phage ecological succession that correlated well with putative host bacteria. This resource improves our understanding of phage-bacteria interactions in the developing early life microbiome.
| S-EPMC11790489 | biostudies-literature
Project description:Exposure to early life stress (ELS), prenatal or postnatal during childhood and adolescence, can significantly impact mental and physical health. The role of the intestinal microbiome in human health, and particularly mental health, is becoming increasingly evident. This systematic review aims to summarize the clinical data evaluating the effect of ELS on the human intestinal microbiome. The systematic review (CRD42022351092) was performed following PRISMA guidelines, with ELS considered as exposure to psychological stressors prenatally and during early life (childhood and adolescence). Thirteen articles met all inclusion criteria, and all studies reviewed found a link between ELS and the gut microbiome in both prenatal and postnatal periods. However, we failed to find consensus microbiome signatures associated with pre- or postnatal stress, or both. The inconsistency of results is likely attributed to various factors such as different experimental designs, ages examined, questionnaires, timing of sample collection and analysis methods, small population sizes, and the type of stressors. Additional studies using similar stressors and validated stress measures, as well as higher-resolution microbiome analytical approaches, are needed to draw definitive conclusions about the links between stress and the human gut microbiome.
| S-EPMC10255201 | biostudies-literature
Project description:BackgroundThe effect of microbes on their human host is often mediated through changes in metabolite concentrations. As such, multiple tools have been proposed to predict metabolite concentrations from microbial taxa frequencies. Such tools typically fail to capture the dependence of the microbiome-metabolite relation on the environment.ResultsWe propose to treat the microbiome-metabolome relation as the equilibrium of a complex interaction and to relate the host condition to a latent representation of the interaction between the log concentration of the metabolome and the log frequencies of the microbiome. We develop LOCATE (Latent variables Of miCrobiome And meTabolites rElations), a machine learning tool to predict the metabolite concentration from the microbiome composition and produce a latent representation of the interaction. This representation is then used to predict the host condition. LOCATE's accuracy in predicting the metabolome is higher than all current predictors. The metabolite concentration prediction accuracy significantly decreases cross datasets, and cross conditions, especially in 16S data. LOCATE's latent representation predicts the host condition better than either the microbiome or the metabolome. This representation is strongly correlated with host demographics. A significant improvement in accuracy (0.793 vs. 0.724 average accuracy) is obtained even with a small number of metabolite samples ([Formula: see text]).ConclusionThese results suggest that a latent representation of the microbiome-metabolome interaction leads to a better association with the host condition than any of the two separated or the simple combination of the two. Video Abstract.
| S-EPMC10858481 | biostudies-literature
Project description:Fecal and breastmilk microbiome from a cohort of 93 infants. Fecal microbiome was sampled at 2 weeks, 6 weeks, 3 months and 6 months. Breastmilk microbiome of the mothers was sampled at 6 weeks. Microbiome composition was analyzed using 16S rRNA sequencing (Illumina Miseq).
| PRJEB50418 | ENA
Project description:Low-birth-weight (LBW) piglets are at a high-risk for postnatal growth failure, mortality, and metabolic disorders later in life. Early-life microbial exposure is a potentially effective intervention strategy for modulating the health and metabolism of the host. Yet, it has not been well elucidated whether the gut microbiota development in LBW piglets is different from their normal littermates and its possible association with metabolite profiles. In the current study, 16S rRNA gene sequencing and metabolomics was used to investigate differences in the fecal microbiota and metabolites between LBW and normal piglets during early-life, including day 3 (D3), 7 (D7), 14 (D14), 21 (D21, before weaning), and 35 (D35, after birth). Compared to their normal littermates, LBW piglets harbored low proportions of Faecalibacterium on D3, Flavonifractor on D7, Lactobacillus, Streptococcus, and Prevotella on D21, as well as Howardella on D21 and D35. However, the abundance of Campylobacter on D7 and D21, Prevotella on D14 and D35, Oscillibacter and Moryella on D14 and D21, and Bacteroides on D21 was significantly higher in LBW piglets when compared with normal piglets. The results of the metabolomics analysis suggested that LBW significantly affected fecal metabolites involved in fatty acid metabolism (e.g., linoleic acid, α-linolenic acid, and arachidonic acid), amino acid metabolism (e.g., valine, phenylalanine, and glutamic acid), as well as bile acid biosynthesis (e.g., glycocholic acid, 25-hydroxycholesterol, and chenodeoxycholic acid). Spearman correlation analysis revealed a significant negative association between Campylobacter and N1-acetylspermine on D7, Moryella and linoleic acid on D14, Prevotella and chenodeoxycholic acid on D21, and Howardella and phenylalanine on D35, respectively. Collectively, LBW piglets have a different gut bacterial community structure when compared with normal-birth-weight (NBW) piglets during early-life, especially from 7 to 21 days of age. Also, a distinctive metabolic status in LBW piglets might be partly associated with the altered intestinal microbiota. These findings may further elucidate the factors potentially associated with the impaired growth and development of LBW piglets and facilitate the development of nutritional interventions.
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