In utero human intestine contains maternally derived bacterial metabolites

Abstract

Background: Understanding when host-microbiome interactions are first established is crucial for comprehending normal development and identifying disease prevention strategies. Furthermore, bacterially derived metabolites play critical roles in shaping the intestinal immune system. Recent studies have demonstrated that memory T cells infiltrate human intestinal tissue early in the second trimester, suggesting that microbial components such as peptides that can prime adaptive immunity and metabolites that can influence the development and function of the immune system are also present in utero. Our previous study reported a unique fetal intestinal metabolomic profile with an abundance of several bacterially derived metabolites and aryl hydrocarbon receptor (AHR) ligands implicated in mucosal immune regulation.

Results: In the current study, we demonstrate that a number of microbiome-associated metabolites present in the fetal intestines are also present in the placental tissue, and their abundance is different across the fetal intestine, fetal meconium, fetal placental villi, and the maternal decidua. The fetal gastrointestinal samples and maternal decidua samples show substantially higher positive correlation on the abundance of these microbial metabolites than the correlation between the fetal gastrointestinal samples and meconium samples. The expression of genes associated with the transport and signaling of some microbial metabolites is also detectable in utero.

Conclusions: We suggest that the microbiome-associated metabolites are maternally derived and vertically transmitted to the fetus. Notably, these bacterially derived metabolites, particularly short-chain fatty acids and secondary bile acids, are likely biologically active and functional in regulating the fetal immune system and preparing the gastrointestinal tract for postnatal microbial encounters, as the transcripts for their various receptors and carrier proteins are present in second trimester intestinal tissue through single-cell transcriptomic data. Video Abstract.

Fig. 1

Sample separation and differential expression of individual metabolites. A t-distributed stochastic neighbor embedding (t-SNE) plot using all metabolites. B Heatmap showing normalized abundance of the top 20 abundant metabolites in the fetal GI samples (SI and LI), as well as their abundance in the meconium (SI Mec and LI Mec), PV, and maternal decidua samples. C, D, and E Volcano plots of differentially abundant metabolites between the GI and decidua groups, GI and meconium groups, and GI and PV groups, respectively. Top 10 significantly differentially abundant metabolites are labeled with the metabolite name

Fig. 2

Pathway enrichment. A, B, and C Integrated pathway analysis for differentially altered pathways between GI and decidua groups, between GI and meconium groups, and between GI and PV groups. The length of the bar is proportional to the q-value. Pathways with positive values on the x-axis (orange bar) are those enriched for in the decidua, meconium, and PV, respectively. Those with negative values (blue bars) are pathways enriched for in the GI samples

Fig. 3

Correlation between tissue groups of microbial metabolites, xenobiotics, and fetal metabolites. A Schematic of how the correlation between tissue would identify the source of bacterial metabolites. ${\rho }_{Dec\_GI}$ denotes the correlation of metabolite abundance in between decidua and GI tissues, and ${\rho }_{Mec\_GI}$ denotes the correlation of metabolite abundance between meconium and GI tissues. Maternal microbiota-derived metabolites that cross as metabolites are expected to have ${\rho }_{Dec\_GI}$ $\gg {\rho }_{Mec\_GI}$, while metabolites that are potentially locally produced by fetal microbiota within the GI track are expected to have ${\rho }_{Dec\_GI}$ $\ll$ ${\rho }_{Mec\_GI}$. B Heatmap showing normalized abundance of the 41 microbial-associated metabolites across sample types. C Pairwise correlation matrix of the 41 microbial metabolites between paired tissue samples from subject no. 16. D Boxplots visualizing the correlations between GI and decidua groups and between GI and meconium groups based on 41 microbial metabolites, 47 xenobiotics, and 8 fetal-derived metabolites respectively from Supplementary Table S4. Red asterisk points represent the pairwise correlations between tissue samples from subject no. 16. *P < 0.05, ***P < 0.001

Fig. 4

ANOVA analysis of SCFA, bile acids, and aromatic acids across tissues. A, B, C Boxplots of individual metabolite’s abundance for primary and secondary bile acids, SCFA, and aromatic amino acids and aromatic acids. *P < 0.05, **P < 0.01, ***P < 0.001. D Heatmap showing that microbial metabolites without significant difference across tissue groups (upper panel) and microbial metabolites significantly enriched in decidua samples (lower panel)

Fig. 5

Cell type-specific expression of genes associated with bile acid and SCFA transport and signaling. scRNAseq data from our previous published manuscript [39] (Fig. 1, Supplementary Table 1; first trimester (8- to 13-week gestational age) n = 14, second trimester (14- to 23-week gestational age) n = 13, neonatal (1–14 days old) n = 6, pediatric (4–12 years old) n = 8, and adult (25–70 years old) n = 7). Uniform manifold approximation and projection (UMAP) plot visualization of bile acid and SCFA-associated transport and signaling gene expression in fetal small intestine epithelial (A) and fetal immune cells (B). C Boxplots of the mean gene expression value of positive cells in each sample from the small intestine across developmental stages (related to Fig. 1 [33]). Each dot represents an individual sample. Data are presented as mean ± SEM. *P < 0.05, **P < 0.01, ***P < 0.001. Clarification of cell type abbreviation for epithelial lineage cells in A: SCs, stem cell; TA, transit-amplifying cells; eAE, early enterocytes; iAE, intermediate enterocytes; mAE, mature enterocytes; EEC, enteroendocrine cells. Immune lineage cells in B: Mϕ, macrophages; cDCs, conventional dendritic cells; ILC, innate lymphoid cells; NK, natural killer cells; Treg, regulatory T cells; Tmem, memory T cells