Ontology highlight
ABSTRACT:
PROVIDER: PRJNA633365 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR11804100_1.fastq.gz | Fastqsanger.gz | |||
| SRR11804100_2.fastq.gz | Fastqsanger.gz | |||
| SRR11804200_1.fastq.gz | Fastqsanger.gz | |||
| SRR11804200_2.fastq.gz | Fastqsanger.gz | |||
| SRR11804101_1.fastq.gz | Fastqsanger.gz |
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Project description:The majority of babies in the US are formula-fed instead of breast fed. There are major differences in the composition of formulas and breast milk and yet little is known about metabolic differences in babies as the result of feeding these very different diets and how that might affect development or disease risk in later life. One concern is that soy-based formulas might have adverse health effects in babies as a result of the presence of low levels of estrogenic phytochemicals – genistein and daidzein which are normally present in soy beans. In the current study, we used a piglet model to look at this question. Piglets were either fed breast milk from the sow or were fed two different infant formulas (cow’s milk-based or soy-based) from age 2 days to 21 days when pigs are normally weaned onto solid food. Blood glucose and lipids were measured. Formula-fed pigs were found to have lower cholesterol than breast fed piglets and in addition had larger stores of iron in their liver.Microarray analysis was carried out to see if changes in liver gene expression could explain these effects of formula feeding. It was found that overall gene expression profiles were influenced by formula feeding compared to breast fed neonates. Gender-independent and unique effects of formula influenced cholesterol and iron metabolism. Further, soy formula feeding in comparison to milk-based formula failed to reveal any estrogenic actions on hepatic gene expression in either male or female pigs.
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Project description:On going efforts are directed at understanding the mutualism between the gut microbiota and the host in breast-fed versus formula-fed infants. Due to the lack of tissue biopsies, no investigators have performed a global transcriptional (gene expression) analysis of the developing human intestine in healthy infants. As a result, the crosstalk between the microbiome and the host transcriptome in the developing mucosal-commensal environment has not been determined. In this study, we examined the host intestinal mRNA gene expression and microbial DNA profiles in full term 3 month-old infants exclusively formula fed (FF) (n=6) or breast fed (BF) (n=6) from birth to 3 months. Host mRNA microarray measurements were performed using isolated intact sloughed epithelial cells in stool samples collected at 3 months. Microbial composition from the same stool samples was assessed by metagenomic pyrosequencing. Both the host mRNA expression and bacterial microbiome phylogenetic profiles provided strong feature sets that clearly classified the two groups of babies (FF and BF). To determine the relationship between host epithelial cell gene expression and the bacterial colony profiles, the host transcriptome and functionally profiled microbiome data were analyzed in a multivariate manner. From a functional perspective, analysis of the gut microbiota's metagenome revealed that characteristics associated with virulence differed between the FF and BF babies. Using canonical correlation analysis, evidence of multivariate structure relating eleven host immunity / mucosal defense-related genes and microbiome virulence characteristics was observed. These results, for the first time, provide insight into the integrated responses of the host and microbiome to dietary substrates in the early neonatal period. Our data suggest that systems biology and computational modeling approaches that integrate “-omic” information from the host and the microbiome can identify important mechanistic pathways of intestinal development affecting the gut microbiome in the first few months of life. KEYWORDS: infant, breast-feeding, infant formula, exfoliated cells, transcriptome, metagenome, multivariate analysis, canonical correlation analysis 12 samples, 2 groups
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