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The role of breast-feeding in infant immune system: a systems perspective on the intestinal microbiome.

Praveen P, Jordan F, Priami C, Morine MJ - Microbiome (2015)

Bottom Line: This study aims at better understanding the effects of microbial community and feeding mode (breast-fed and formula-fed) on the immune system, by comparing intestinal metagenomic and transcriptomic data from breast-fed and formula-fed babies.Our results show that breast-fed samples co-express genes associated with immunological, metabolic, and biosynthetic activities.Our findings revealed that there is co-expression of more genes in breast-fed samples but lower microbial diversity compared to formula-fed.

View Article: PubMed Central - PubMed

Affiliation: The Microsoft Research-University of Trento Centre for Computational and Systems Biology, 38068, Rovereto, Italy. praveen@cosbi.eu.

ABSTRACT

Background: The human intestinal microbiota changes from being sparsely populated and variable to possessing a mature, adult-like stable microbiome during the first 2 years of life. This assembly process of the microbiota can lead to either negative or positive effects on health, depending on the colonization sequence and diet. An integrative study on the diet, the microbiota, and genomic activity at the transcriptomic level may give an insight into the role of diet in shaping the human/microbiome relationship. This study aims at better understanding the effects of microbial community and feeding mode (breast-fed and formula-fed) on the immune system, by comparing intestinal metagenomic and transcriptomic data from breast-fed and formula-fed babies.

Results: We re-analyzed a published metagenomics and host gene expression dataset from a systems biology perspective. Our results show that breast-fed samples co-express genes associated with immunological, metabolic, and biosynthetic activities. The diversity of the microbiota is higher in formula-fed than breast-fed infants, potentially reflecting the weaker dependence of infants on maternal microbiome. We mapped the microbial composition and the expression patterns for host systems and studied their relationship from a systems biology perspective, focusing on the differences.

Conclusions: Our findings revealed that there is co-expression of more genes in breast-fed samples but lower microbial diversity compared to formula-fed. Applying network-based systems biology approach via enrichment of microbial species with host genes revealed the novel key relationships of the microbiota with immune and metabolic activity. This was supported statistically by data and literature.

No MeSH data available.


Related in: MedlinePlus

a Pearson correlation between the microbial abundance and the expression levels of associated human genes obtained via text mining and also found to be differentially expressed. The relationship with human genes for each microbial species is in Fig. 4. The microbial species marked with asterisk (*) are differentially abundant. The black horizontal line is the mean of absolute Pearson correlation coefficient between randomly generated pairs of genes and microbes. The missing sample (BF or FF) had an NA as correlation values due to zero abundance or zero standard deviation in any of the random variables. b The top GO terms (Biological Process) for human genes related to microbial species. The width of sectors represents the number of associated terms in the corresponding categories, and the radius indicates the number of genes annotated with corresponding terms
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Fig5: a Pearson correlation between the microbial abundance and the expression levels of associated human genes obtained via text mining and also found to be differentially expressed. The relationship with human genes for each microbial species is in Fig. 4. The microbial species marked with asterisk (*) are differentially abundant. The black horizontal line is the mean of absolute Pearson correlation coefficient between randomly generated pairs of genes and microbes. The missing sample (BF or FF) had an NA as correlation values due to zero abundance or zero standard deviation in any of the random variables. b The top GO terms (Biological Process) for human genes related to microbial species. The width of sectors represents the number of associated terms in the corresponding categories, and the radius indicates the number of genes annotated with corresponding terms

Mentions: We extracted the relations of microbes with the human genes from bibliographic knowledgebase (see “Methods”). These genes do not necessarily represent a physical interaction with microbe or its biomolecules but rather a dependence relationship in either direction (gray edges in Fig. 4). Looking at the related genes (square nodes) for differentially abundant microbes (a network specific to differentially abundant species is available in Additional file 1) revealed that they are mostly related to the host genes (Fig. 4, yellow nodes in circle and squares) that already have a higher degree. To further verify these relationships, we analyzed which host genes have been found to be in a dependence relation with the corresponding microbial species via a bivariate analysis. For this, we used the pairs of microbes and the host genes related to these microbes as shown in Fig. 4. To illustrate, if a microbe M is related to host genes X, Y, and Z; then, we compute the correlation for abundance of M and expression level of X, Y, and Z along the samples. Thus, we get three correlation values for microbe M, i.e., M~X, M~Y, and M~Z. This was carried out for all the microbes and their corresponding genes (related to these microbes). The Pearson correlation coefficients were computed between microbial abundance and the expression levels of corresponding DE genes (a set of n correlation coefficients for a species enriched with n genes) showed a higher correlation (p value ≤0.05) for B. bifidum and R. gnavus. Figure 5a shows the boxplot for the correlations between each microbial species, paired with its corresponding genes extracted from literature. The results cannot be computed in terms of p values as the two other differentially abundant microbes (B. breve and B. longum) were not detected in both types of sample. We compared these correlation coefficients against the mean of absolute correlation between 1000 randomly permuted microbial species and host gene pairs, which was found to be <0.2. Furthermore, we also generated random pairs of genes and microbes and computed similar correlations (abundance~expression level) to check if the correlations for actual relationships are better than these random pairs. We compared these correlation coefficients against the mean of absolute correlation between 1000 randomly permuted microbial species and host gene pairs, which was found to be <0.2 (indicated by the black line in Fig. 5a). This approach also served as a validation for our literature-mining pipeline to find genes related to microbial species.Fig. 4


The role of breast-feeding in infant immune system: a systems perspective on the intestinal microbiome.

Praveen P, Jordan F, Priami C, Morine MJ - Microbiome (2015)

a Pearson correlation between the microbial abundance and the expression levels of associated human genes obtained via text mining and also found to be differentially expressed. The relationship with human genes for each microbial species is in Fig. 4. The microbial species marked with asterisk (*) are differentially abundant. The black horizontal line is the mean of absolute Pearson correlation coefficient between randomly generated pairs of genes and microbes. The missing sample (BF or FF) had an NA as correlation values due to zero abundance or zero standard deviation in any of the random variables. b The top GO terms (Biological Process) for human genes related to microbial species. The width of sectors represents the number of associated terms in the corresponding categories, and the radius indicates the number of genes annotated with corresponding terms
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4581423&req=5

Fig5: a Pearson correlation between the microbial abundance and the expression levels of associated human genes obtained via text mining and also found to be differentially expressed. The relationship with human genes for each microbial species is in Fig. 4. The microbial species marked with asterisk (*) are differentially abundant. The black horizontal line is the mean of absolute Pearson correlation coefficient between randomly generated pairs of genes and microbes. The missing sample (BF or FF) had an NA as correlation values due to zero abundance or zero standard deviation in any of the random variables. b The top GO terms (Biological Process) for human genes related to microbial species. The width of sectors represents the number of associated terms in the corresponding categories, and the radius indicates the number of genes annotated with corresponding terms
Mentions: We extracted the relations of microbes with the human genes from bibliographic knowledgebase (see “Methods”). These genes do not necessarily represent a physical interaction with microbe or its biomolecules but rather a dependence relationship in either direction (gray edges in Fig. 4). Looking at the related genes (square nodes) for differentially abundant microbes (a network specific to differentially abundant species is available in Additional file 1) revealed that they are mostly related to the host genes (Fig. 4, yellow nodes in circle and squares) that already have a higher degree. To further verify these relationships, we analyzed which host genes have been found to be in a dependence relation with the corresponding microbial species via a bivariate analysis. For this, we used the pairs of microbes and the host genes related to these microbes as shown in Fig. 4. To illustrate, if a microbe M is related to host genes X, Y, and Z; then, we compute the correlation for abundance of M and expression level of X, Y, and Z along the samples. Thus, we get three correlation values for microbe M, i.e., M~X, M~Y, and M~Z. This was carried out for all the microbes and their corresponding genes (related to these microbes). The Pearson correlation coefficients were computed between microbial abundance and the expression levels of corresponding DE genes (a set of n correlation coefficients for a species enriched with n genes) showed a higher correlation (p value ≤0.05) for B. bifidum and R. gnavus. Figure 5a shows the boxplot for the correlations between each microbial species, paired with its corresponding genes extracted from literature. The results cannot be computed in terms of p values as the two other differentially abundant microbes (B. breve and B. longum) were not detected in both types of sample. We compared these correlation coefficients against the mean of absolute correlation between 1000 randomly permuted microbial species and host gene pairs, which was found to be <0.2. Furthermore, we also generated random pairs of genes and microbes and computed similar correlations (abundance~expression level) to check if the correlations for actual relationships are better than these random pairs. We compared these correlation coefficients against the mean of absolute correlation between 1000 randomly permuted microbial species and host gene pairs, which was found to be <0.2 (indicated by the black line in Fig. 5a). This approach also served as a validation for our literature-mining pipeline to find genes related to microbial species.Fig. 4

Bottom Line: This study aims at better understanding the effects of microbial community and feeding mode (breast-fed and formula-fed) on the immune system, by comparing intestinal metagenomic and transcriptomic data from breast-fed and formula-fed babies.Our results show that breast-fed samples co-express genes associated with immunological, metabolic, and biosynthetic activities.Our findings revealed that there is co-expression of more genes in breast-fed samples but lower microbial diversity compared to formula-fed.

View Article: PubMed Central - PubMed

Affiliation: The Microsoft Research-University of Trento Centre for Computational and Systems Biology, 38068, Rovereto, Italy. praveen@cosbi.eu.

ABSTRACT

Background: The human intestinal microbiota changes from being sparsely populated and variable to possessing a mature, adult-like stable microbiome during the first 2 years of life. This assembly process of the microbiota can lead to either negative or positive effects on health, depending on the colonization sequence and diet. An integrative study on the diet, the microbiota, and genomic activity at the transcriptomic level may give an insight into the role of diet in shaping the human/microbiome relationship. This study aims at better understanding the effects of microbial community and feeding mode (breast-fed and formula-fed) on the immune system, by comparing intestinal metagenomic and transcriptomic data from breast-fed and formula-fed babies.

Results: We re-analyzed a published metagenomics and host gene expression dataset from a systems biology perspective. Our results show that breast-fed samples co-express genes associated with immunological, metabolic, and biosynthetic activities. The diversity of the microbiota is higher in formula-fed than breast-fed infants, potentially reflecting the weaker dependence of infants on maternal microbiome. We mapped the microbial composition and the expression patterns for host systems and studied their relationship from a systems biology perspective, focusing on the differences.

Conclusions: Our findings revealed that there is co-expression of more genes in breast-fed samples but lower microbial diversity compared to formula-fed. Applying network-based systems biology approach via enrichment of microbial species with host genes revealed the novel key relationships of the microbiota with immune and metabolic activity. This was supported statistically by data and literature.

No MeSH data available.


Related in: MedlinePlus