Research ArticleMicrobiome

Antibiotics, birth mode, and diet shape microbiome maturation during early life

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Science Translational Medicine  15 Jun 2016:
Vol. 8, Issue 343, pp. 343ra82
DOI: 10.1126/scitranslmed.aad7121
  • Fig. 1. Microbial and dietary succession viewed over the first 2 years of life.

    Mean relative abundance (RA) of fecal bacteria at the genus level at each month of life, for taxa with ≥1% mean RA across all samples. (A) All 43 infant subjects during the first 2 years of life. (B to E) The first 6 months of life for the 32 subjects who were not antibiotic-exposed, organized by delivery mode (vaginal or cesarean) and predominant feeding mode (breast or formula). Vaginal-breast, n = 15; cesarean-breast, n = 7; vaginal-formula, n = 3; cesarean-formula, n = 7. (F) Dietary trends in all infants across the study period.

  • Fig. 2. α-Diversity during the first 2 years of life in relation to antibiotic treatment, delivery mode, and predominant diet.

    (A to I) Left: Mean phylogenetic diversity ± SEM. Middle: Mean observed OTUs ± SEM. Right: Mean Shannon equitability (evenness) ± SEM. α-Diversity is shown for antibiotic use (A to C), delivery mode (D to F), and diet (G to I). Asterisks indicate significant linear longitudinal model (LLM) (P < 0.05) group differences at baseline or rate-of-change differences across age ranges (dotted lines demarcate time periods tested).

  • Fig. 3. Antibiotic exposure alters bacterial abundance.

    Antibiotic exposure significantly altered abundance of diverse bacterial taxa over the first 2 years of life. On the basis of LEfSe analysis, red-shaded taxa (rows) were significantly (P < 0.05) more abundant in antibiotic-exposed infants at the given time points (columns); blue shading indicates more abundant taxa in unexposed infants.

  • Fig. 4. Antibiotic exposure delays microbiota maturation during early life.

    (A) Microbiota-by-age Z (MAZ) scores at each month of life between antibiotic-exposed and unexposed infants (infants never exposed to systemic pharmacologic antibiotic doses before the sampling time). MAZ scores indicate the number of SDs from the mean predicted age of age-matched control samples, as a function of microbiota maturation. Gray margins represent 95% confidence interval (CI). Asterisks indicate significant (LLM, P < 0.05) group differences at baseline or rate-of-change differences across age ranges (dotted lines demarcate time periods tested). The “unexposed” group contains both training set samples (from children who were never exposed to prenatal, perinatal, or postnatal systemic antibiotics; were vaginally delivered; and were dominantly breast-fed) and all other samples from children who had not been previously exposed to systemic postnatal antibiotics, regardless of delivery mode and diet. This accounts for the observed deviation from a 0 MAZ score in the unexposed group, as other factors influenced maturation. (B) OTU abundance heatmaps illustrate the RA Z scores of 22 maturation marker OTUs in the antibiotic-exposed and unexposed groups throughout the first 2 years of life. These OTUs were selected as those that best predict age of life in the control group and hence can be used as markers of normal maturation. Substantial departures from the normal maturation profile alter predicted age of other samples. The color scale represents RA Z scores for each OTU (that is, the number of SDs from the mean RA of that OTU) across all samples at that age. Red text indicates OTUs that appear most suppressed during months 6 to 12 after antibiotic exposure.

  • Fig. 5. Delivery mode alters microbial diversity and composition.

    (A) Unweighted UniFrac principal coordinates (PCs) analysis of the infant microbiome in relation to delivery mode over the first 2 years of life. Permutational MANOVA, P < 0.05 (table S7). (B) Bacteroides RA (means ± SEM) over time in relation to delivery mode. Asterisks and brackets indicate significant (LLM, P < 0.05) rate-of-change differences across age ranges (dotted lines demarcate time periods tested). (C) Cesarean section significantly altered abundance of diverse bacterial taxa over time. Red-shaded taxa (rows) were significantly more abundant (LEfSe, P < 0.05) in cesarean-delivered infants at the given time points (columns); blue shading indicates more abundant taxa in vaginally delivered infants.

  • Fig. 6. Bipartite network comparing the relationships among all samples (squares) and OTUs (circles).

    (A) The distance between sample nodes and OTU nodes is a function of shared microbial composition. Samples with a large degree of OTU overlap (weighted by the number of observations of that OTU) form clusters. Edges connect a sample to each OTU detected in that sample, revealing shared OTUs between samples. Sample nodes and edges are colored by sample type; the border of sample nodes is a function of the age of the child, including prepartum (negative) values for maternal samples (key at top left). OTU nodes are colored by taxonomic family affiliation; the size of each OTU node is a function of that OTU’s overall abundance, registered as OTU count in all samples (key at middle left). See Fig. 7 for specific analyses. (B) Unweighted UniFrac distance between maternal vaginal, rectal, and stool microbiota and child stool microbiota as a function of child age. Shorter distance indicates greater similarity between microbial communities. (C) Unweighted UniFrac distance between stool microbiota from the same child (self) and other children (nonself) as a function of the difference in age between sampling (Δ months). (D) Unweighted UniFrac distance between maternal vaginal microbiota and stool microbiota of vaginally born dyads, unrelated children, or cesarean-delivered dyads as a function of child age. For (B) to (D), lines indicate rolling average mean values, and gray shading is 95% CI. ANOVA P values are shown.

  • Fig. 7. Shared OTUs reveal microbial relatedness among mothers and children.

    (A) Shared OTU counts (median ± quartiles) between individual stool samples (top), rectal swabs and stool samples (middle), and vaginal swabs and stool samples (bottom), represented in Fig. 6. Distributions represent the total number of OTUs within a single sample (blue) or shared OTUs between samples from the same individual (self, yellow), another individual (nonself, white/black), or a mother-infant dyad (red). Lowercase letters indicate significantly different shared OTU count distributions [one-way ANOVA, P < 0.0001, followed by false discovery rate (FDR)–corrected Fisher’s protected least significant difference (PLSD) test]. Key indicates coloring for box plots in (A) or line plots in (B) to (I). (B to I) Shared OTU counts over time between mothers and unrelated children, mother-infant dyads, and total OTUs in child stool samples. (C) Samples from the same child or unrelated children at different times (Δ months). (D) Mothers’ rectal swabs and stool samples from their own children (dyad) or unrelated children. (E) Mothers’ vaginal swabs and stool samples from unrelated children or dyads of children delivered vaginally or by cesarean section. (F) Vaginal and rectal swabs from the same mother or other mothers. (G) Stool samples from the same mother or other mothers. (H) Rectal swabs from the same mother or other mothers. (I) Vaginal swabs from the same mother or other mothers. (B), (D), and (E) compare mothers versus children, and x axes indicate the child’s age (months). For (C) and (F) to (I), x axes indicate the differences in child age (Δ months) between the times when these samples were obtained. Lines indicate rolling average mean values, and gray shading is equal to 95% CI. *P < 0.0001, ANOVA, followed by FDR-corrected Fisher’s PLSD test.

  • Table 1. Characteristics of the 43 children in the study including systemic antibiotic exposure, delivery mode, and diet.
    Vaginal delivery (n = 24)Cesarean section (n = 19)
    Antibiotics +Antibiotics −Antibiotics +Antibiotics −
    Breast milk–dominant10 (23%)*10 (23%)8 (19%)3 (7%)
    Formula-dominant2 (5%)2 (5%)5 (12%)3 (7%)

    *The number of children (percentage of total) categorized by delivery mode, whether they were exposed to antibiotics at any time during the study, and their predominant diet during the first 3 months of life.

    Supplementary Materials

    • www.sciencetranslationalmedicine.org/cgi/content/full/8/343/343ra82/DC1

      Materials and Methods

      Fig. S1. LEfSe analysis of differentially abundant taxa between vaginally born, predominantly breast-fed (n = 15) and cesarean-delivered, predominantly formula-fed children (n = 7) from 1 to 6 months of life.

      Fig. S2. Antibiotic exposures did not alter short-term α-diversity in individual subjects.

      Fig. S3. Functional maturation of the microbiome is delayed by antibiotic exposure.

      Fig. S4. Functional maturation of the microbiome is altered by formula feeding.

      Fig. S5. Enumeration of 16S ribosomal RNA genes in fecal specimens in children at 1 and 12 months of age, by quantitative polymerase chain reaction.

      Fig. S6. Average RA of Bacteroides in children in relation to feeding and delivery mode in the first 2 years of life.

      Fig. S7. Cesarean section exerts a modest impact on microbiota maturation.

      Fig. S8. Infant diet alters microbiota composition and maturation over the first 2 years of life.

      Fig. S9. RA heatmap of major taxa in 296 maternal samples.

      Fig. S10. Development of diversity of Bifidobacterium and Bacteroides OTUs in children in early life.

      Table S1. Baseline characteristics of the 53 mothers in the study.

      Table S2. Baseline characteristics of the 43 infants in the study.

      Table S3. Prenatal antimicrobial use by class and purpose.

      Table S4. Perinatal antibiotic use by class and indication.

      Table S5. Postnatal antimicrobial use by class and age of child.

      Table S6. LLM estimates of antibiotic treatment, diet, and delivery effects on α-diversity.

      Table S7. Permutational MANOVA scores of antibiotic, diet, and delivery effects on unweighted UniFrac distance β-diversity.

      Table S8. Permutational MANOVA scores of antibiotic, diet, and delivery effects on weighted UniFrac distance β-diversity.

      Table S9. LLM estimates of antibiotic, diet, and delivery effects on microbiome maturation MAZ scores.

      Table S10. LLM estimates of antibiotic, diet, and delivery effects on PICRUSt-predicted metagenome maturation MAZ scores.

      References (5665)

    • Supplementary Material for:

      Antibiotics, birth mode, and diet shape microbiome maturation during early life

      Nicholas A. Bokulich, Jennifer Chung, Thomas Battaglia, Nora Henderson, Melanie Jay, Huilin Li, Arnon D. Lieber, Fen Wu, Guillermo I. Perez-Perez, Yu Chen, William Schweizer, Xuhui Zheng, Monica Contreras, Maria Gloria Dominguez-Bello, Martin J. Blaser*

      *Corresponding author. Email: martin.blaser{at}nyumc.org

      Published 15 June 2016, Sci. Transl. Med. 8, 343ra82 (2016)
      DOI: 10.1126/scitranslmed.aad7121

      This PDF file includes:

      • Materials and Methods
      • Fig. S1. LEfSe analysis of differentially abundant taxa between vaginally born, predominantly breast-fed (n = 15) and cesarean-delivered, predominantly formula-fed children (n = 7) from 1 to 6 months of life.
      • Fig. S2. Antibiotic exposures did not alter short-term α-diversity in individual subjects.
      • Fig. S3. Functional maturation of the microbiome is delayed by antibiotic exposure.
      • Fig. S4. Functional maturation of the microbiome is altered by formula feeding.
      • Fig. S5. Enumeration of 16S ribosomal RNA genes in fecal specimens in children at 1 and 12 months of age, by quantitative polymerase chain reaction.
      • Fig. S6. Average RA of Bacteroides in children in relation to feeding and delivery mode in the first 2 years of life.
      • Fig. S7. Cesarean section exerts a modest impact on microbiota maturation.
      • Fig. S8. Infant diet alters microbiota composition and maturation over the first 2 years of life.
      • Fig. S9. RA heatmap of major taxa in 296 maternal samples.
      • Fig. S10. Development of diversity of Bifidobacterium and Bacteroides OTUs in children in early life.
      • Table S1. Baseline characteristics of the 53 mothers in the study.
      • Table S2. Baseline characteristics of the 43 infants in the study.
      • Table S3. Prenatal antimicrobial use by class and purpose.
      • Table S4. Perinatal antibiotic use by class and indication.
      • Table S5. Postnatal antimicrobial use by class and age of child.
      • Table S6. LLM estimates of antibiotic treatment, diet, and delivery effects on α-diversity.
      • Table S7. Permutational MANOVA scores of antibiotic, diet, and delivery effects on unweighted UniFrac distance β-diversity.
      • Table S8. Permutational MANOVA scores of antibiotic, diet, and delivery effects on weighted UniFrac distance β-diversity.
      • Table S9. LLM estimates of antibiotic, diet, and delivery effects on microbiome maturation MAZ scores.
      • Table S10. LLM estimates of antibiotic, diet, and delivery effects on PICRUSt-predicted metagenome maturation MAZ scores.
      • References (5665)

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