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Cited by 340Gut microbiota and healthGastrointestinal motility and disordersProbiotics and Fermented Foods

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Intestinal Microbiota in Healthy Adults: Temporal Analysis Reveals Individual and Common Core and Relation to Intestinal Symptoms

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Jalanka-Tuovinen, Jonna, Salonen, Anne, Nikkilä, Janne, Immonen, Outi, Kekkonen, Riina, Lahti, Leo, Palva, Airi, de Vos, Willem M.·2011·PLoS ONE
DOI 10.1371/journal.pone.0023035PMC PMC3145776
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Abstract

BACKGROUND: While our knowledge of the intestinal microbiota during disease is accumulating, basic information of the microbiota in healthy subjects is still scarce. The aim of this study was to characterize the intestinal microbiota of healthy adults and specifically address its temporal stability, core microbiota and relation with intestinal symptoms. We carried out a longitudinal study by following a set of 15 healthy Finnish subjects for seven weeks and regularly assessed their intestinal bacteria and archaea with the Human Intestinal Tract (HIT) Chip, a phylogenetic microarray, in conjunction with qPCR analyses. The health perception and occurrence of intestinal symptoms was recorded by questionnaire at each sampling point. PRINCIPAL FINDINGS: A high overall temporal stability of the microbiota was observed. Five subjects showed transient microbiota destabilization, which correlated not only with the intake of antibiotics but also with overseas travelling and temporary illness, expanding the hitherto known factors affecting the intestinal microbiota. We identified significant correlations between the microbiota and common intestinal symptoms, including abdominal pain and bloating. The most striking finding was the inverse correlation between Bifidobacteria and abdominal pain: subjects who experienced pain had over five-fold less Bifidobacteria compared to those without pain. Finally, a novel computational approach was used to define the common core microbiota, highlighting the role of the analysis depth in finding the phylogenetic core and estimating its size. The in-depth analysis suggested that we share a substantial number of our intestinal phylotypes but as they represent highly variable proportions of the total community, many of them often remain undetected. CONCLUSIONS/SIGNIFICANCE: A global and high-resolution microbiota analysis was carried out to determine the temporal stability, the associations with intestinal symptoms, and the individual and common core microbiota in healthy adults. The findings provide new approaches to define intestinal health and to further characterize the microbial communities inhabiting the human gut.

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Figures

Figure 1 Hierarchical clustering of the HITChip profiles of 15 subjects and their six timepoints. The subject-wise clustering is highlighted with boxes and the temporal variation is displayed with the variable length of the branches. Red vertical line is drawn at Pearson correlation of 0.925, below which the intra-individual sample similarity was detected only in the five unstable subjects (5,6,8,9 and 11) discussed in the text.
Figure 1 Hierarchical clustering of the HITChip profiles of 15 subjects and their six timepoints. The subject-wise clustering is highlighted with boxes and the temporal variation is displayed with the variable length of the branches. Red vertical line is drawn at Pearson correlation of 0.925, below which the intra-individual sample similarity was detected only in the five unstable subjects (5,6,8,9 and 11) discussed in the text.CC BY · PubMed Central
Figure 2 Microbiota composition of the study subjects. Relative abundance of the phylotypes that contributed over 0.5% to the total HITChip signal was summed up to phylum level, except Firmicutes, which were summed up to class or Clostridium cluster level (left y-axis). The qPCR-based quantification of the methanogens is shown on the right y-axis.
Figure 2 Microbiota composition of the study subjects. Relative abundance of the phylotypes that contributed over 0.5% to the total HITChip signal was summed up to phylum level, except Firmicutes, which were summed up to class or Clostridium cluster level (left y-axis). The qPCR-based quantification of the methanogens is shown on the right y-axis.CC BY · PubMed Central
Figure 3 Correlation heatmap of the microbiota profiles and intestinal symptoms. The heatmap visualizes all significant (q-value <0.005) Spearman correlations between the intestinal symptoms and the HITChip-measured abundance of bacterial phylotypes. Each row represents a single phylotype, whose genus-level assignments are listed below the rows, or in the middle when several rows refer to the same genus-level group. The negative correlations between symptoms are indicated in red and the positive correlations with yellow; non-significant correlations are shown in gray.
Figure 3 Correlation heatmap of the microbiota profiles and intestinal symptoms. The heatmap visualizes all significant (q-value <0.005) Spearman correlations between the intestinal symptoms and the HITChip-measured abundance of bacterial phylotypes. Each row represents a single phylotype, whose genus-level assignments are listed below the rows, or in the middle when several rows refer to the same genus-level group. The negative correlations between symptoms are indicated in red and the positive correlations with yellow; non-significant correlations are shown in gray.CC BY · PubMed Central
Figure 4 Quantification of Bidifobacteria in relation to abdominal pain. The samples were divided into two groups: with and without concurrent abdominal pain, and the abundance of Bifidobacteria in each group was determined using A. HITChip and B. qPCR. The difference between the groups was statistically significant (q≤0.02 in A; p<0.05 in B). The box extends from 25th percentile to 75th percentile, with a line at the median; the whiskers extent to the highest and lowest values.
Figure 4 Quantification of Bidifobacteria in relation to abdominal pain. The samples were divided into two groups: with and without concurrent abdominal pain, and the abundance of Bifidobacteria in each group was determined using A. HITChip and B. qPCR. The difference between the groups was statistically significant (q≤0.02 in A; p<0.05 in B). The box extends from 25th percentile to 75th percentile, with a line at the median; the whiskers extent to the highest and lowest values.CC BY · PubMed Central
Figure 5 Definition of the common core microbiota. A. Perspective plot is used to visualize how the number of phylotypes in the common core is a function of the selected abundance and prevalence. Light gray indicates the area where no phylotypes passed the given criteria. B. The common core microbiota in the healthy subjects. The y-axis represents the range of the phylotype count shared, thus forming the common core, in the nine healthy subjects. The line visualizes how the number of the phylotypes depends on the selected percentile abundance, and how it decreases drastically when the phylotypes with lowest abundance are excluded. List shows phylum-level summary of the phylotypes that contributed with over 0.03% relative abundance C. The common core phylotypes summarized to genus-level taxa. The boxplots visualize the intra-individual variation in the abundances of the core taxa. Bacteroides fragilis et rel. and Bifidobacteria (two leftmost boxes) are visualized for reference purposes. These taxa were not part of the common core due to their large intra- and inter-individual variation. For boxplot details, please see the legend for Figure 4.
Figure 5 Definition of the common core microbiota. A. Perspective plot is used to visualize how the number of phylotypes in the common core is a function of the selected abundance and prevalence. Light gray indicates the area where no phylotypes passed the given criteria. B. The common core microbiota in the healthy subjects. The y-axis represents the range of the phylotype count shared, thus forming the common core, in the nine healthy subjects. The line visualizes how the number of the phylotypes depends on the selected percentile abundance, and how it decreases drastically when the phylotypes with lowest abundance are excluded. List shows phylum-level summary of the phylotypes that contributed with over 0.03% relative abundance C. The common core phylotypes summarized to genus-level taxa. The boxplots visualize the intra-individual variation in the abundances of the core taxa. Bacteroides fragilis et rel. and Bifidobacteria (two leftmost boxes) are visualized for reference purposes. These taxa were not part of the common core due to their large intra- and inter-individual variation. For boxplot details, please see the legend for Figure 4.CC BY · PubMed Central

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  1. C Liu, 2008, International Journal of Systematic and Evolutionary Microbiology, International Journal of Systematic and Evolutionary Microbiology, 58, 1896

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Metadata

Authors
Jalanka-Tuovinen, J., Salonen, A., Nikkilä, J., Immonen, O., Kekkonen, R., Lahti, L., Palva, A., & de Vos, W. M.
Affiliations
  • University of Helsinki (FI)
  • Valio (Finland) (FI)
Corresponding author
Salonen, Anne
ORCID
Venue
PLoS ONE
Publisher
Public Library of Science (PLoS)
Published
2011-07-28
Volume
6
Issue
7
Pages
e23035
ISSN
1932-6203 (ISSN-L)
DOI
10.1371/journal.pone.0023035
PMC
PMC3145776
OpenAlex
W2157800726
Cited by
340
References
75
Citations by year
2026: 2 · 2025: 7 · 2024: 19 · 2023: 17 · 2022: 23 · 2021: 20 · 2020: 23 · 2019: 19 · 2018: 19 · 2017: 34 · 2016: 32 · 2015: 28 · 2014: 31 · 2013: 44 · 2012: 20
FWCI
12.61
Type
journal article
Language
en
Open access
Licence
Locations
  • PLoS ONE (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Socio-Environmental Systems Modeling (acceptedVersion)
  • Työväentutkimus Vuosikirja (submittedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • Figshare (submittedVersion, cc-by)
  • Data Archiving and Networked Services (DANS) (submittedVersion, other-oa)
Funders
  • Tekes
  • Valio
  • Wageningen University and Research
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gut microbiota and health
  • Health Sciences › Medicine › Gastroenterology › Gastrointestinal motility and disorders
  • Life Sciences › Agricultural and Biological Sciences › Food Science › Probiotics and Fermented Foods
Keywords
gut microbiota, healthy adults, temporal stability, core microbiome, intestinal symptoms, abdominal pain, bloating, Bifidobacterium, antibiotics, archaea, gut health
MeSH terms
Adult, Bacteria, DNA, Bacterial, Double-Blind Method, Feces, Female, Humans, Intestinal Diseases, Intestines, Longitudinal Studies, Male, Middle Aged, Phylogeny, RNA, Messenger, RNA, Ribosomal, 16S, Biomarkers, Reverse Transcriptase Polymerase Chain Reaction, Oligonucleotide Array Sequence Analysis, Gene Expression Profiling, Biodiversity, Metagenome

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