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. 2011 Oct 26;3(106):106ra106.
doi: 10.1126/scitranslmed.3002701.

The impact of a consortium of fermented milk strains on the gut microbiome of gnotobiotic mice and monozygotic twins

Nathan P McNulty  1 , Tanya Yatsunenko, Ansel Hsiao, Jeremiah J Faith, Brian D Muegge, Andrew L Goodman, Bernard Henrissat, Raish Oozeer, Stéphanie Cools-Portier, Guillaume Gobert, Christian Chervaux, Dan Knights, Catherine A Lozupone, Rob Knight, Alexis E Duncan, James R Bain, Michael J Muehlbauer, Christopher B Newgard, Andrew C Heath, Jeffrey I Gordon
Affiliations

The impact of a consortium of fermented milk strains on the gut microbiome of gnotobiotic mice and monozygotic twins

Nathan P McNulty et al. Sci Transl Med. .

Abstract

Understanding how the human gut microbiota and host are affected by probiotic bacterial strains requires carefully controlled studies in humans and in mouse models of the gut ecosystem where potentially confounding variables that are difficult to control in humans can be constrained. Therefore, we characterized the fecal microbiomes and metatranscriptomes of adult female monozygotic twin pairs through repeated sampling 4 weeks before, 7 weeks during, and 4 weeks after consumption of a commercially available fermented milk product (FMP) containing a consortium of Bifidobacterium animalis subsp. lactis, two strains of Lactobacillus delbrueckii subsp. bulgaricus, Lactococcus lactis subsp. cremoris, and Streptococcus thermophilus. In addition, gnotobiotic mice harboring a 15-species model human gut microbiota whose genomes contain 58,399 known or predicted protein-coding genes were studied before and after gavage with all five sequenced FMP strains. No significant changes in bacterial species composition or in the proportional representation of genes encoding known enzymes were observed in the feces of humans consuming the FMP. Only minimal changes in microbiota configuration were noted in mice after single or repeated gavage with the FMP consortium. However, RNA-Seq analysis of fecal samples and follow-up mass spectrometry of urinary metabolites disclosed that introducing the FMP strains into mice results in significant changes in expression of microbiome-encoded enzymes involved in numerous metabolic pathways, most prominently those related to carbohydrate metabolism. B. animalis subsp. lactis, the dominant persistent member of the FMP consortium in gnotobiotic mice, up-regulates a locus in vivo that is involved in the catabolism of xylooligosaccharides, a class of glycans widely distributed in fruits, vegetables, and other foods, underscoring the importance of these sugars to this bacterial species. The human fecal metatranscriptome exhibited significant changes, confined to the period of FMP consumption, that mirror changes in gnotobiotic mice, including those related to plant polysaccharide metabolism. These experiments illustrate a translational research pipeline for characterizing the effects of FMPs on the human gut microbiome.

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Conflict of interest statement

Competing interests: The authors declare that they have no competing interests.

Figures

Figure 1
Figure 1. Experimental design for human and mouse studies
(A) Human study. Seven healthy lean MZ female twin pairs were sampled before, during, and after FMP consumption. (B) Gnotobiotic mouse study. Two groups of five germ-free mice were colonized by oral gavage at 6–8 weeks of age with a 15-member microbial consortium constituting a model human gut microbiota (day of gavage denoted by black arrows). Two weeks later, the five species FMP strain consortium was administered by oral gavage to each group of mice twice over two days (denoted by green arrows). Mice in the single treatment group underwent no further manipulations, whereas animals in the multiple treatment group received additional two-day gavages one and three weeks following the first gavage. Samples were collected at the indicated time points for profiling bacterial community membership (shotgun and 16S rRNA gene sequencing for human fecal samples, COPRO-Seq for mouse fecal and cecal samples), gene expression profiling (microbial RNA-Seq) and metabolite analysis (urines, GC/MS). The species comprising the model 15-member human community and the 5-member FMP consortium are listed in the gray and green boxes, respectively.
Figure 2
Figure 2. Metagenomic studies of human fecal microbiomes sampled over time
(A) 16S rRNA-based time course study of intra- and interpersonal variations in fecal bacterial community structure during the course of the 4-month study. Unweighted UniFrac measurements of community distances, from pairwise comparisons of all samples obtained from a given individual, from co-twins, and from unrelated individuals are plotted as mean values ±SEM. (B) Colored boxes represent the proportion of bacterial phylotypes that were consistently present within an individual over time (gray), between co-twins over time (orange), and in all 126 fecal samples (red). The white box represents the average number of species-level phylotypes found in a given sample. All measures of spread provided in parentheses represent ±SEM. (C) KEGG Orthology groups (KOs) consistently present within the fecal microbiome of an individual over time (gray), between co-twins over time (orange), and in all 48 microbiomes analyzed from the 4 sets of MZ twins during the 4 month study (red). The white box indicates the average number of unique KOs (±SEM) identified in a particular sample. All measures of spread provided in parentheses represent ±SEM. (D) Hellinger distance measurements of fecal microbiomes based on their KO content. Tests of statistical significance are based on 1000 permutations of a Hellinger distance matrix. Mean values (±SEM) are shown for the three types of comparisons (self-self; co-twin-co-twin; unrelated-unrelated individual).
Figure 3
Figure 3. Correspondence analysis of B. animalis subsp. lactis CAZyme gene expression
RNA-Seq data for all B. animalis subsp. lactis genes encoding known or predicted CAZymes were subjected to unconstrained correspondence analysis using the ‘vegan’ package in R. Correspondence analysis (CA) allows for the generation of biplots in which samples and genes can be plotted in the same ordinate space to reveal associations/anti-associations between the two. Circles represent individual CAZymes (genes). The genes ordinating furthest from the origin in the direction of one of the sample clusters (treatment groups) are labeled according to their locus number and are colored based on CAZyme family assignment (see Table to the right of the Figure for details; the abbreviation NA refers to no designation). Red triangles represent samples and are labeled according to the following nomenclature: LX, logarithmic phase cells in MRS with X being the technical replicate number (e.g. L1 refers to the first technical replicate harvested in log phase); SX, stationary phase cells in MRS with accompanying replicate number; MX, feces from designated gnotobiotic animals obtained 4 weeks after the initial invasion with the FMP strain consortium; PX, samples obtained after fermentation in the FMP dairy matrix. Each cluster of samples from a particular treatment is associated with a functionally related set of expressed CAZymes.
Figure 4
Figure 4. ‘Top-down’ analysis of the effects of the FMP strain consortium on the model 15-member community’s metatranscriptome
RNA-Seq reads were mapped to the sequenced genomes of the 15 community members. Transcript counts were normalized [reads per kb of gene length per million reads (RPKM), see Supplementary Material] and binned using the hierarchical levels of functional annotation employed by KEGG. For each KEGG category (A) or pathway (B) shown, boxplots depict the proportion of normalized read counts assignable to that annotation out of all reads which could be assigned annotations for that hierarchical level. Data shown correspond to the ‘multiple’ treatment group of mice (the group for which the most time points were collected), however, data for all mice are provided in Table S8. (C) Illustration of how a model community’s functional response (e.g., the increased expression of levanase-encoding genes) can be dissected to identify the subset of genes/species driving the response. Boxes denote top quartile, median, and bottom quartile. Whisker length represents 1.5x inter-quartile range (IQR), except where there are no outliers; in these situations, whiskers span the range from minimum to maximum values. Box color denotes the day fecal samples were obtained (day 14 is the pre-treatment timepoint immediately preceding gavage of the FMP strain consortium). When an asterisk is centered over a box, it indicates that there was a statistically significant change following administration of the FMP consortium relative to the pre-treatment timepoint (p<0.05 by paired, two-tailed Student’s t-test). The positioning of asterisks above versus below a box emphasizes the direction of change (above, upregulation; below, downregulation).
Figure 5
Figure 5. Mouse and human communities share transcriptional responses to the FMP strain consortium involving ECs related to carbohydrate metabolism
(A) Box plots of the proportion of all RPKM-normalized reads in mouse and human fecal metatranscriptomes represented by three ECs involved in plant biomass degradation. Individual samples are shown as black dots (n=2–10). Boxes are also colored by fold-change, as determined by comparing mean values at a given time point to the value at the pre-treatment time point [for gnotobiotic mice pre-treatment refers to day 14; in the case of humans, pre-treatment refers to the fecal sample collected 1 week prior to initiation of FMP consumption (sample ‘Pre1’ in Fig. 1A)]. Statistical significance was determined using the ShotgunFunctionalizeR package in R and an adjusted p-value cutoff of <0.01. Pre-treatment time points, and subsequent time points where expression levels were not significantly different from the pre-treatment mean are colored white. (B) Components of KEGG ‘starch and sucrose metabolism’, ‘pentose and glucuronate interconversions’ and ‘pentose phosphate’ pathways whose expression in the 15-member model community changed compared to pre-treatment values when the 5-member FMP strain consortium was introduced. Gray indicates that the fold-change was statistically significant (adjusted p-value <0.01). Ovals highlight the three enzymes shown in panel A. Dashed arrows indicate that multiple enzymatic reactions lead from these ECs and their indicated substrates to the products shown. These intermediate reactions have been omitted for clarity or because the omitted ECs did not manifest significant changes in their expression.
Figure 6
Figure 6. Select urinary metabolites whose levels are altered after the introduction of the FMP strain consortium into mice harboring a defined model human gut microbiota
The statistical significance in pairwise comparisons shown in panels A-C was evaluated using a two-tailed Student’s t-test on the log-transformed spectral abundance of the metabolite in each sample. Values for the statistical significance of differences between time points as evaluated by one-way ANOVA, followed by FDR-correction and a post-hoc Tukey HSD test are also provided in Table S12. Horizontal bars represent group means, vertical bars represent ± SEM. n/s; not significant.
Figure 7
Figure 7. Shared transcriptional responses to FMP strain exposure in mice and humans
The heatmap shows ECs that exhibit a statistically significant change in their expression (ShotgunFunctionalizeR, adjusted p < 0.01) and manifest a consistent direction of change in their expression in all four comparisons shown. Comparisons include those where the pre-treatment timepoint was compared with a timepoint shortly after FMP strains were introduced (mouse: ‘d15 vs d14’, human: ‘FMP1 vs Pre1’) and those where the pre-treatment period was compared to a timepoint several weeks after strain introduction (mouse: ‘d42multi vs d14’, human: ‘FMP4 vs Pre1’). ‘d42multi’ indicates the multiple-treatment group at day 42 of the mouse experiment. The colored boxes correspond to the KEGG categories that contain the ECs shown to the right of the heatmap. The scale refers to fold-difference in the mean of relative abundance of each EC between treatment and pre-treatment groups based on the mean number of normalized reads (RPKM) of transcripts assigned to a given EC. The 18 ECs shown at the bottom of the Figure are not associated with the five prominent KEGG categories listed. Their assigned categories are provided in Table S13.
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