Neonatal diet alters fecal microbiota and metabolome profiles at different ages in infants fed breast milk or formula

Abstract

Background: Neonatal diet has a large influence on child health and might modulate changes in fecal microbiota and metabolites.

Objectives: The aim is to investigate fecal microbiota and metabolites at different ages in infants who were breastfed (BF), received dairy-based milk formula (MF), or received soy-based formula (SF).

Methods: Fecal samples were collected at 3 (n = 16, 12, and 14, respectively), 6 (n = 20, 19, and 15, respectively), 9 (n = 12, 11, and 12, respectively), and 12 mo (n = 14, 14, and 15, respectively) for BF, MF, and SF infants. Infants that breastfed until 9 mo and switched to formula were considered as no longer breastfeeding at 12 mo. Microbiota data were obtained using 16S ribosomal RNA sequencing. Untargeted metabolomics was conducted using a Q-Exactive Hybrid Quadrupole-Orbitrap mass spectrometer. The data were analyzed using R (version 3.6.0) within the RStudio (version 1.1.463) platform.

Results: At 3, 6, and 9 mo of age BF infants had the lowest α-diversity, SF infants had the highest diversity, and MF was intermediate. Bifidobacterium was 2.6- to 5-fold lower in SF relative to BF infants through 1 y of life. An unidentified genus from Ruminococcaceae higher in the SF (2%) than in the MF (0.4%) and BF (0.08%) infants at 3 mo of age was observed. In BF infants higher levels of butyric acid, d-sphingosine, kynurenic acid, indole-3-lactic acid, indole-3-acetic acid, and betaine were observed than in MF and SF infants. At 3 mo Ruminococcaceae was positively correlated to azelaic, gentisic, isocitric, sebacic, and syringic acids. At 6 mo Oscillospira was negatively correlated with 3-hydroxybutyric-acid, hydroxy-hydrocinnamic acid, and betaine whereas Bifidobacterium was negatively associated with 5-hydroxytryptamine. At 12 mo of age, Lachnospiraceae was negatively associated with hydroxyphenyllactic acid.

Conclusions: Infant diet has a large impact on the fecal microbiome and metabolome in the first year of life.This study was registered at clinicaltrials.gov as NCT00616395.

Keywords: breastfeeding; formula diets; immune system; metabolites; microbiota.

Copyright © The Author(s) on behalf of the American Society for Nutrition 2020.

Figures

FIGURE 1

Flow diagram of the study participants showing enrollment, the number of stool samples collected, and the numbers of available samples for microbiota and metabolome data acquisition. The samples with low read counts and also the 6- and 9-mo NLB group for the microbiome data were excluded from analysis. After preprocessing and normalization of the metabolomics data, 2 samples in positive mode and 3 samples in negative mode were dropped. NLB, no longer breastfeeding.

FIGURE 2

Visualization of β-diversity (between-sample diversity) by PCoA in infants consuming differential diets at 3 (A), 6 (B), 9 (C), and 12 (D) mo of age. Data generated from 16S ribosomal RNA amplicon sequencing on fecal samples. β-Diversity estimated by Bray–Curtis dissimilarities at both genus and OTU levels. The first 2 components of PCoA scores (i.e., individual samples) are displayed for genera (large plots) and OTUs (inserts). Confidence regions of group clusters are presented as 95% confidence ellipses based on Hotelling's T2 statistic. Red circles indicate breastfed infants, dark blue triangles indicate cow milk formula-fed infants, grey diamonds indicate soy-formula-fed infants, and light blue upside-down triangles indicate infants that were no longer breastfeeding. Statistical difference in diet within an age group was assessed by pairwise comparison of diets by permutational multivariate ANOVA. P values were adjusted by FDR to control for the family-wise error rate. Sample numbers were n = 10–20 per group and age. FDR, false discovery rate; OTU, operational taxonomic unit; PCoA, principal coordinate analysis.

FIGURE 3

Visualization of variance associated with infant diet in fecal metabolomics data from infants consuming differential diets at 3 (A), 6 (B), 9 (C), and 12 (D) mo of age. Fecal metabolomics data were generated from LC-MS. Results from positive and negative modes were combined, log transformed, and scaled to unit variance before assessment by PCA. PCA scores (i.e., individual samples) for PCA components 1 and 2 are displayed. Confidence regions of group clusters are presented as 95% confidence ellipses based on Hotelling's T2 statistic. Red circles indicate BF infants, dark blue triangles indicate MF infants, grey diamonds indicate SF infants, and light blue upside-down triangles indicate NLB infants. Scores from PCA component 1 were assessed for differences in diet group by 1-factor ANOVA. Sample numbers were n = 10–20 per group and age. BF, breastfed; MF, cow milk formula fed; NLB, no longer breastfeeding; PCA, principal component analysis; SF, soy-based formula fed.

FIGURE 4

Correlation between fecal microbiota and metabolome in infants consuming differential diets at 3, 6, 9, and 12 mo of age. Genus-level microbial sequencing data and metabolomics data were assessed separately by PCA. Before PCA, sequencing data were transformed by center-log ratio to ensure the data were linearly related, whereas metabolomics data were log transformed and scaled to unit variance. PCA scores (individual samples) were plotted along components 1 and 2 and variation associated with diet was determined along the first components in both PCAs. The percentage explained variance for each component is provided in parentheses. The shapes of the PCA scores represent age (3 mo: circle; 6 mo: triangle; 9 mo: upside down triangle; 12 mo: diamond) and colors represent diet (red: BF; blue: MF; light blue: NLB; grey: SF). The linear relation between the first components for the microbial and metabolomics PCA is shown. The solid line is the best-fit line whereas the dotted lines represent 95% CIs. Pearson's r coefficient and P value are provided in the figure. Sample numbers were n = 10–20 per group and age. BF, breastfed; MF, cow milk formula fed; NLB, no longer breastfeeding; PC, principal component; PCA, principal component analysis; SF, soy-based formula fed.

FIGURE 5

Correlation heatmap of genera and metabolites from infants fed either breast milk, milk-based formula, or soy-based formula at 3 mo of age (n = 161). Circles represent significant Pearson's correlations (FDR-adjusted P values < 0.05). Orange circles indicate positive relations and blue circles indicate negative relations. Supplemental Table 9 gives Pearson's r coefficients, raw P values, and FDR-corrected P values of significant correlations. FDR, false discovery rate.

FIGURE 6

Correlation heatmap of genera and metabolites from infants fed either breast milk, milk-based formula, or soy-based formula at 6 mo of age (n = 160). Circles represent significant Pearson's correlations (FDR-adjusted P values < 0.05). Orange circles indicate positive relations and blue circles indicate negative relations. Supplemental Table 9 gives Pearson's r coefficients, raw P values, and FDR-corrected P values of significant correlations. FDR, false discovery rate; GUDCA, glycoursodeoxycholic acid.

FIGURE 7

Correlation heatmap of genera and metabolites from infants fed either breast milk, milk-based formula, or soy-based formula at 12 mo of age (n = 72). Circles represent significant Pearson's correlations (FDR-adjusted P values < 0.05). Orange circles indicate positive relations and blue circles indicate negative relations. Supplemental Table 9 gives Pearson's r coefficients, raw P values, and FDR-corrected P values of significant correlations. FDR, false discovery rate.