Biogeographical distribution of gut microbiome composition and function is partially recapitulated by fecal transplantation into germ-free mice - PubMed (original) (raw)
. 2025 Jan 2;19(1):wrae250.
doi: 10.1093/ismejo/wrae250.
Venu Lagishetty 1, Ezinne Aja 1 2, Nerea Arias-Jayo 1, Candace Chang 1, Megan Hauer 1, William Katzka 1 2, Yi Zhou 1 3, Farzaneh Sedighian 1 4, Carolina Koletic 1, Fengting Liang 1, Tien S Dong 1 4, Jamilla Situ 1, Ryan Troutman 1, Heidi Buri 1, Shrikant Bhute 1 2, Carra A Simpson 1, Jonathan Braun 5, Noam Jacob 1 4 5, Jonathan P Jacobs 1 2 4
Affiliations
- PMID: 39680691
- PMCID: PMC11973428
- DOI: 10.1093/ismejo/wrae250
Biogeographical distribution of gut microbiome composition and function is partially recapitulated by fecal transplantation into germ-free mice
Julianne C Yang et al. ISME J. 2025.
Abstract
Fecal microbiota transplantation has been vital for establishing whether host phenotypes can be conferred through the microbiome. However, whether the existing microbial ecology along the mouse gastrointestinal tract can be recapitulated in germ-free mice colonized with stool remains unknown. We first identified microbes and their predicted functions specific to each of six intestinal regions in three cohorts of specific pathogen-free mice spanning two facilities. Of these region-specific microbes, the health-linked genus Akkermansia was consistently enriched in the lumen of the small intestine compared to the colon. Predictive functional modeling on 16S rRNA gene amplicon sequencing data recapitulated in shotgun sequencing data revealed increased microbial central metabolism, lipolytic fermentation, and cross-feeding in the small intestine, whereas butyrate synthesis was colon-enriched. Neuroactive compound metabolism also demonstrated regional specificity, including small intestine-enriched gamma-aminobutyric acid degradation and colon-enriched tryptophan degradation. Specifically, the jejunum and ileum stood out as sites with high predicted metabolic and neuromodulation activity. Differences between luminal and mucosal microbiomes within each site of the gastrointestinal tract were largely facility-specific, though there were a few consistent patterns in microbial metabolism in specific pathogen-free mice. These included luminal enrichment of central metabolism and cross-feeding within both the small intestine and the colon, and mucosal enrichment of butyrate synthesis within the colon. Across three cohorts of germ-free mice colonized with mice or human stool, compositional and functional region specificity were inconsistently reproduced. These results underscore the importance of investigating the spatial variation of the gut microbiome to better understand its impact on host physiology.
Keywords: fecal microbiota transplantation; gastrointestinal tract; gut biogeography; gut ecology; gut microbiome; microbial metabolism; small intestine microbiome; spatial organization.
Published by Oxford University Press on behalf of the International Society for Microbial Ecology 2024.
Conflict of interest statement
At the time of manuscript submission, V.L. is an employee of Kite Pharma. C.S. is an employee of AbbVie. J.S. is an employee of Abiosciences. J.C.Y. is an employee of Merck. All other authors declare no competing interests.
Figures
Graphical Abstract
Figure 1
Study design and datasets. (A) To profile both longitudinal and transverse differences in the microbiome, we utilized 16S rRNA gene sequencing of luminal and mucosal samples collected along the GI tract and shotgun sequencing of jejunum and DC luminal samples. We define “interregional” differences as comparing the colon to small intestine (SI), “intraregional” differences as comparing the three SI regions to each other and as comparing the three colon regions to each other, and “region-specific” features as features which significantly distinguish the DC from the five other intestinal sites. (B) Three SPF mouse cohorts from two facilities (UCLA O. SPF, UCLA V. SPF—containing mucosal samples only, and CS SPF) and three colonized germ-free mice cohorts (SPF gavage, HUM SD gavage, HUM MD gavage—containing 16S rRNA gene sequencing data only) were used in this study. Intestinal regions are abbreviated in this diagram as follows: SI—small intestine, duodenum—duo, jejunum—Jej, ileum—Ile, cecum—Cec, proximal colon—PC, distal colon—DC. Figure created with Biorender.
Figure 2
Taxonomic composition of mice cohorts. (A) Stacked column charts illustrating the relative abundances of genera comprising at least 0.1% of the overall composition or phyla (B) of mucosal samples across six cohorts. (C) Stacked column charts illustrating the relative abundances of genera comprising at least 0.1% of the overall composition or phyla (D) of luminal samples across five cohorts. The color legend for phyla is shown in a single column at the right, while the color legend for genera is shown at the bottom of the figure. Intestinal regions are abbreviated as follows: Duodenum—D, jejunum—J, ileum—I, cecum—C, proximal colon—PC, distal colon—DC. If the genus name is unknown, it is labeled by its family name (f); if the family name is also unknown, it is labeled by its order (o).
Figure 3
Interregional and intraregional differences in alpha- and beta-diversity in luminal samples. Violin plots comparing either (A) the total number of ASVs or (B) Pielou’s evenness indices across six intestinal regions in the five luminal datasets. Thick lines indicate the comparison between colon and SI. Thin lines indicate the comparison between DC and each of five other regions. Statistical comparisons were made through fitting the distributions of alpha-diversity indices to linear mixed-effects models with site (encoding SI/colon, or encoding six regions) as a fixed effect and MouseID as a random effect, *P < 0.05, **P < 0.01, ***P < 0.001. PCoA plots illustrating interregional (C) differences, colonic intraregional differences (D), and small intestinal intraregional differences in beta-diversity (E). _R_2 and P values associated with site were calculated by repeat-measures aware PERMANOVA. Intestinal regions are abbreviated as follows: Duodenum—D, jejunum- J, cecum—C, proximal colon—PC, distal colon—DC.
Figure 4
Unsupervised learning reveals four clusters of region-specific genera. Heatmaps illustrating the enrichment or depletion of genera within a site (D, J, I, C, PC) relative to DC in luminal samples from (A) UCLA O. SPF, (B) CS SPF, (C) HUM MD gavage, (D) SPF gavage, and (E) HUM SD gavage. For heatmaps A-E, the color of the bar on the left represents cluster membership. The color of each tile represents the effect size, while asterisks within each tile indicate genera which were significantly different following Benjamini-Hochberg multiple hypothesis correction, *q < 0.05. The rows are labeled by genus, with the label color representing the phylum. Genera which are both shared and have the same directionality in at least three datasets are highlighted. Unidentified genera are labeled with the family (f) name, or with the order name (o) if the family is also not known. (F) Upset plot showing the total number of region-specific genera identified for each dataset in the “set size” panel, with the “intersection” panel illustrating the number of region-specific genera either unique to a dataset or shared across datasets as indicated by the dot matrix. Region-specific species (only those which are named) identified from shotgun sequencing for (G) UCLA O. SPF, (H) CS SPF, (I) HUM SD gavage, or (J) SPF gavage datasets are shown as barplots. Species labels are colored according to phylum.
Figure 5
Predicted microbial metabolism exhibits interregional specificity. KEGG orthologs predicted from compositional data were grouped into gut metabolic modules, followed by module enrichment analysis. Metabolic modules were subsequently grouped into higher-order categories visualized in these metabolic maps, which were adapted from the GOMIXER pathways mapper. The color of the category indicates whether all pathways were enriched, all depleted, or were differentially enriched in the SI relative to the colon, with the legend shown at the bottom right of the figure. Metabolic maps are shown for luminal samples from (A) UCLA O. SPF, (B) CS SPF, (C) SPF gavage, (D) HUM SD gavage, and (E) HUM MD gavage datasets.
Figure 6
Predicted gut-metabolic modules exhibit region specificity. KEGG orthologs predicted from compositional data were grouped into gut metabolic modules (GMMs) for module enrichment analysis. Significant GMMs that were consistently differentially abundant in proximal regions of the intestines (duodenum—D, jejunum- J, cecum—C, or proximal colon—PC) compared to the DC in at least three out of five luminal cohorts are shown in this figure. GMMs are grouped into higher-order categories for visualization, with carbohydrates shown in (A), proteolytic fermentation in (B), lipolytic fermentation, sugar acid, and nitrate reduction categories shown in (C), cross-feeding and butyrate in (D), and central metabolism in (E). Line graphs depict regression coefficients and their standard errors for each region-DC comparison. Each cohort is represented by a different color line, with the legend for all plots given at the top of the figure. The asterisk indicates that the region—DC comparison was significant (*q < 0.05) following multiple hypothesis correction, while the asterisk highlight color corresponds to the cohort as indicated in the legend. (F) Upset plot showing the total number of region-specific GMMs identified for each dataset in the “set size” panel, with the “intersection” panel illustrating the number of region-specific genera either unique to a dataset or shared across datasets as indicated by the dot matrix.
Figure 7
Predicted gut-brain modules exhibit region specificity. KEGG orthologs predicted from compositional data were grouped into gut brain modules (GBMs) for module enrichment analysis. (A–E) line graphs show the regression coefficients and their standard errors for each region—DC comparison, corresponding to five significant GBMs that were consistently differentially enriched in proximal regions of the intestines (duodenum—D, jejunum- J, cecum—C, or proximal colon—PC) compared to the DC in at least three of 5 luminal datasets. Each dataset is represented by a different color line, with the legend for all line plots shown at the top of the figure. The asterisk indicates that the site-DC comparison was significant following multiple hypothesis correction, *q < 0.05, while the asterisk highlight color corresponds to the cohort as indicated in the legend. (F) Upset plot showing the total number of region-specific GBMs identified for each dataset in the “set size” panel, with the “intersection” panel illustrating the number of region-specific genera either unique to a dataset or shared across datasets as indicated by the dot matrix. (G) Barplots showing the jejunal vs. distal colon enrichment of the five GBMs as determined by shotgun sequencing for each of four cohorts.
Figure 8
Summary of key findings on biogeographical distribution of microbes and their predicted functions. Along the longitudinal axis, key interregional findings are summarized in the comparison of small intestine to colon at the top, while select region-specific findings are highlighted in the middle. The direction of the arrow indicates the enrichment (up) or the depletion (down) of its associated feature within the region relative to the reference. These findings align with known oxygen and host dietary macromolecule availability gradients at the bottom of the figure. Along the transverse axis, findings were primarily region-independent, with the lumen exhibiting increased metabolic activity compared to the mucosa. However, within the colon, polysaccharide degradation was increased in the lumen while butyrate production was increased in the mucosa. The degree of overlap of the circles indicate the relative extent to which these longitudinal and transverse biogeographical distributions are reproducible across facilities or recapitulated with fecal orogastric gavage. Figure created with Biorender.
References
- Jacobs J, Braun J. Chapter 5—the mucosal microbiome: Imprinting the immune system of the intestinal tract. In: Mestecky J, Strober W, Russell MW, Kelsall BL, Cheroutre H, Lambrecht BN, eds. Mucosal Immunology (Fourth Edition). Cambridge, MA: Academic Press; 2015:63–77. 10.1016/B978-0-12-415847-4.00005-7. -DOI
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