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Cited by 230Gut microbiota and healthInfant Nutrition and HealthOral microbiology and periodontitis research

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Intestinal Microbiota in Healthy U.S. Young Children and Adults—A High Throughput Microarray Analysis

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Ringel-Kulka, Tamar, Cheng, Jing, Ringel, Yehuda, Salojärvi, Jarkko, Carroll, Ian, Palva, Airi, de Vos, Willem M., Satokari, Reetta·2013·PLoS ONE
DOI 10.1371/journal.pone.0064315PMC PMC3662718
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Abstract

UNLABELLED: It is generally believed that the infant's microbiota is established during the first 1-2 years of life. However, there is scarce data on its characterization and its comparison to the adult-like microbiota in consecutive years. AIM: To characterize and compare the intestinal microbiota in healthy young children (1-4 years) and healthy adults from the North Carolina region in the U.S. using high-throughput bacterial phylogenetic microarray analysis. METHODS: Detailed characterization and comparison of the intestinal microbiota of healthy children aged 1-4 years old (n = 28) and healthy adults of 21-60 years (n = 23) was carried out using the Human Intestinal Tract Chip (HITChip) phylogenetic microarray targeting the V1 and V6 regions of 16S rRNA and quantitative PCR. RESULTS: The HITChip microarray data indicate that Actinobacteria, Bacilli, Clostridium cluster IV and Bacteroidetes are the predominant phylum-like groups that exhibit differences between young children and adults. The phylum-like group Clostridium cluster XIVa was equally predominant in young children and adults and is thus considered to be established at an early age. The genus-like level show significant 3.6 fold (higher or lower) differences in the abundance of 26 genera between young children and adults. Young U.S. children have a significantly 3.5-fold higher abundance of Bifidobacterium species than the adults from the same location. However, the microbiota of young children is less diverse than that of adults. CONCLUSIONS: We show that the establishment of an adult-like intestinal microbiota occurs at a later age than previously reported. Characterizing the microbiota and its development in the early years of life may help identify 'windows of opportunity' for interventional strategies that may promote health and prevent or mitigate disease processes.

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Figure 1 Principal component analysis (PCA) (A) and redundancy analysis (RDA) (B) of fecal samples from healthy young children and adults at the phylum-like level. Log transformed data were used for analysis. In PCA, The first two principal components capture 21% (PCA1) and 16% (PCA2) of variance respectively. RDA plot shows the result from supervised PCA, where group assignment of subjects (adults or children) was used as a dependent variable. In RDA, first and second ordination axes are plotted, explaining 13% and 20% of the variance. Separation between children and adults is significant (p = 0.0002, permutation test).
Figure 1 Principal component analysis (PCA) (A) and redundancy analysis (RDA) (B) of fecal samples from healthy young children and adults at the phylum-like level. Log transformed data were used for analysis. In PCA, The first two principal components capture 21% (PCA1) and 16% (PCA2) of variance respectively. RDA plot shows the result from supervised PCA, where group assignment of subjects (adults or children) was used as a dependent variable. In RDA, first and second ordination axes are plotted, explaining 13% and 20% of the variance. Separation between children and adults is significant (p = 0.0002, permutation test).CC BY · PubMed Central
Figure 2 Principal component analysis (PCA) (A) and redundancy analysis (RDA) (B) of fecal samples from healthy young children and adults at the genus-like level. Log transformed data were used for analysis. In PCA, the first two principal components capture 33% (PCA1) and 11% (PCA2) of variance respectively. RDA plot shows the result from supervised PCA, where group assignment of subjects (adults or children) was used as a dependent variable. In RDA, first and second ordination axes are plotted, explaing 13% and 64% of the variance. Separation between children and adults is significant (p = 0.003, permutation test).
Figure 2 Principal component analysis (PCA) (A) and redundancy analysis (RDA) (B) of fecal samples from healthy young children and adults at the genus-like level. Log transformed data were used for analysis. In PCA, the first two principal components capture 33% (PCA1) and 11% (PCA2) of variance respectively. RDA plot shows the result from supervised PCA, where group assignment of subjects (adults or children) was used as a dependent variable. In RDA, first and second ordination axes are plotted, explaing 13% and 64% of the variance. Separation between children and adults is significant (p = 0.003, permutation test).CC BY · PubMed Central
Figure 3 Phylum-level distribution of bacteria in fecal samples of healthy young children and adults.
Figure 3 Phylum-level distribution of bacteria in fecal samples of healthy young children and adults.CC BY · PubMed Central
Figure 4 Genera within the Clostridium cluster XIVa. The error bar shows the standard error.
Figure 4 Genera within the Clostridium cluster XIVa. The error bar shows the standard error.CC BY · PubMed Central
Figure 5 Intestinal microbiota diversity in healthy young children and adults estimated by Simpson reciprocal index (1/D) and Shannon index. The whiskers show the highest and lowest value after excluding outliers (dots). The outliers are defined as more than 3/2 times of upper quartile or less than 3/2 times of lower quartile. Boxplot shows 25th and 75th percentile, with a line at median. The subjects are divided into two groups Adults (>21Y) and Children (<4Y) (A, C) or four groups‘<2Y’, ‘2-3Y’, ‘3-4Y’ and Adults (>21Y) (B, D). A) Simpson index of diversity shows a significant difference between adults and children (p = 0.007), B) Simpson index of diversity shows significant differences between ‘<2Y’and ‘3-4Y’ age groups and adults (*p = 0.006, **p = 0.002 respectively). C) Shannon index of diversity shows significant difference between adults and children (p = 0.001), D) Shannon index of diversity shows significant difference between ‘<2Y’, ‘3-4Y’ and adults, (*p = 0.003, **p = 0.001 respectively). Significant difference is also observed between ‘2-3Y’and ‘3-4Y’ age groups (***p = 0.043).
Figure 5 Intestinal microbiota diversity in healthy young children and adults estimated by Simpson reciprocal index (1/D) and Shannon index. The whiskers show the highest and lowest value after excluding outliers (dots). The outliers are defined as more than 3/2 times of upper quartile or less than 3/2 times of lower quartile. Boxplot shows 25th and 75th percentile, with a line at median. The subjects are divided into two groups Adults (>21Y) and Children (<4Y) (A, C) or four groups‘<2Y’, ‘2-3Y’, ‘3-4Y’ and Adults (>21Y) (B, D). A) Simpson index of diversity shows a significant difference between adults and children (p = 0.007), B) Simpson index of diversity shows significant differences between ‘<2Y’and ‘3-4Y’ age groups and adults (*p = 0.006, **p = 0.002 respectively). C) Shannon index of diversity shows significant difference between adults and children (p = 0.001), D) Shannon index of diversity shows significant difference between ‘<2Y’, ‘3-4Y’ and adults, (*p = 0.003, **p = 0.001 respectively). Significant difference is also observed between ‘2-3Y’and ‘3-4Y’ age groups (***p = 0.043).CC BY · PubMed Central
Figure 6 Bifidobacterium species adundances in fecal samples from healthy young children and adults reported as a ratio with respect to the average amount of 16S rRNA Bifidobacterium gene copies in all adults. A significant 5.05 (±0.70) fold increase was found in healthy young children compared to adults.
Figure 6 Bifidobacterium species adundances in fecal samples from healthy young children and adults reported as a ratio with respect to the average amount of 16S rRNA Bifidobacterium gene copies in all adults. A significant 5.05 (±0.70) fold increase was found in healthy young children compared to adults.CC BY · PubMed Central

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  1. Legendre PL, Legendre L (1998) Numerical ecology: Elsevier.

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Metadata

Authors
Ringel-Kulka, T., Cheng, J., Ringel, Y., Salojärvi, J., Carroll, I., Palva, A., de Vos, W. M., & Satokari, R.
Affiliations
  • University of Helsinki (FI)
  • University of North Carolina at Chapel Hill (US)
ORCID
Venue
PLoS ONE
Publisher
Public Library of Science (PLoS)
Published
2013-05-23
Volume
8
Issue
5
Pages
e64315
ISSN
1932-6203 (ISSN-L)
DOI
10.1371/journal.pone.0064315
PMC
PMC3662718
OpenAlex
W1987296519
Cited by
230
References
62
Citations by year
2026: 4 · 2025: 15 · 2024: 13 · 2023: 18 · 2022: 23 · 2021: 25 · 2020: 50 · 2019: 15 · 2018: 14 · 2017: 8 · 2016: 13 · 2015: 18 · 2014: 12 · 2013: 2
FWCI
6.71
Type
journal article
Language
en
Open access
Licence
Locations
  • PLoS ONE (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, other-oa)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Socio-Environmental Systems Modeling (acceptedVersion)
  • RePEc: Research Papers in Economics (submittedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • Figshare (submittedVersion, cc-by)
  • Työväentutkimus Vuosikirja (submittedVersion)
  • Data Archiving and Networked Services (DANS) (submittedVersion, other-oa)
Funders
  • Academy of Finland
  • National Institutes of Health
  • National Institute of Diabetes and Digestive and Kidney Diseases (DK075621, K23DK075621)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gut microbiota and health
  • Health Sciences › Nursing › Nutrition and Dietetics › Infant Nutrition and Health
  • Health Sciences › Dentistry › Periodontics › Oral microbiology and periodontitis research
Keywords
gut microbiota, gut microbiota development, children versus adults, Bifidobacterium, Clostridium cluster XIVa, Clostridium cluster IV, Bacteroidetes, actinobacteria, bacilli, microbial diversity, 16S rRNA, healthy adults
MeSH terms
Adult, Bifidobacterium, Child, Preschool, Clostridium, Feces, Female, Genes, Bacterial, Health, Humans, Infant, Intestines, Male, Middle Aged, Phylogeny, RNA, Ribosomal, 16S, Oligonucleotide Array Sequence Analysis, Principal Component Analysis, Actinobacteria, Bacteroidetes, Young Adult, Molecular Typing, Microbiota

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