New Results

Maternal diet and gut microbiome composition modulate early life immune responses

Erica T. Grant, Marie Boudaud, Arnaud Muller, Andrew J. Macpherson, Mahesh S. Desai
doi: https://doi.org/10.1101/2023.03.06.531289

Abstract

In early life, the intestinal mucosa and immune system undergo a critical developmental process to contain the expanding gut microbiome while promoting tolerance towards commensals, yet the influence of maternal diet and gut microbial composition on offspring immune maturation remains poorly understood. We colonized gnotobiotic mice with a defined consortium of 14 strains, fed them a fiber-free diet, and then longitudinally assessed offspring development during the weaning period. Unlike pups born to dams fed a standard, fiber-rich chow, pups of fiber-deprived dams demonstrated delayed colonization with Akkermansia muciniphila, a mucin-foraging bacterium that can also utilize milk oligosaccharides. The pups of fiber-deprived dams exhibited an enrichment of colonic tissue transcripts corresponding to defense response pathways and a peak in Il22 expression at weaning. Removal of A. muciniphila from the community, but maintenance on the fiber-rich diet, was associated with reduced proportions of RORγt-positive innate and adaptive immune cell subsets. Our results highlight the potent influence of maternal dietary fiber intake and discrete changes in microbial composition on the postnatal microbiome assemblage and early immune priming.

Introduction

Dietary fiber plays a major role in shaping the colonic gut microbiome and host immunity, however the impact of maternal dietary fiber intake on the offspring’s microbiome and immune development is largely associative for the early life period (Mirpuri, 2021). In adult mice, dietary fiber deprivation leads to microbiome-driven thinning of the mucus layer, which can increase susceptibility to a range of conditions including enteric pathogen infection (Desai et al, 2016; Neumann et al, 2021), graft-versus-host disease (Hayase et al, 2022), and food allergy (Parrish et al, 2022a). Although exposure to microbial metabolites in utero initiates innate immune responses and barrier development in pups (De Agüero et al, 2016), the postnatal period is also critical for healthy maturation of intestinal function and adaptive immunity in a complex process that is partially driven by a response to the colonizing microbiome (Kalbermatter et al, 2021; Wells et al, 2022). In particular, from 2–4 weeks of age, mouse pups transition from breast milk to solid food with an accompanying shift in microbial composition and a vigorous immune response to the expanding microbiota (Al Nabhani et al, 2019). Without this “weaning reaction”, as observed in germ-free and broad-spectrum antibiotic-treated mice, Al Nabhani et al reported increased susceptibility to inflammatory pathologies (Al Nabhani et al, 2019). However, it remains unclear how variations in the maternal diet or defined differences in microbial composition affect early life immune priming (Ansaldo et al, 2021).

We therefore set out to investigate the influence of maternal dietary fiber intake on the offspring colonic development by feeding dams either a standard fiber-rich (FR) chow or a custom fiber-free (FF) diet (Desai et al, 2016) (Fig. 1a). To standardize the bacterial composition and facilitate interpretation of the microbial shifts, we utilized a gnotobiotic mouse model consisting of 14 bacterial strains (14-member synthetic human gut microbiota or 14SM) that form a functionally diverse community (Desai et al, 2016; Steimle et al, 2021). Although this community was designed to resemble an adult microbiota, one member— Akkermansia muciniphila—is capable of degrading milk oligosaccharides and is an early colonizer of the gut (Kostopoulos et al, 2020). This taxon is also enriched under fiber-deprived conditions in adult mice (Desai et al, 2016) and appears to have immunogenic properties when present in 14SM, including a high IgA-coating index (Pereira et al, 2022). We sought to determine the role of this particular microbe in early life development on the same FR diet by employing mice colonized with the full community except A. muciniphila (13SM). By employing a longitudinal sampling approach among the pups of each diet and SM combination, we isolated dietary and microbial drivers of early-life immune development. We show that, while maternal diet had a strong impact on the host epithelial transcriptome, the presence or absence of A. muciniphila was a key contributing factor in shaping immune cell differentiation during this critical early life window.

Figure 1.
Figure 1. Delayed expansion of Akkermansia among offspring of fiber-deprived dams.

A. Schematic representation of the study design.

B. Stream plot showing the relative abundance of the 14 bacterial strains in the colons of pups born to 14SM FF-fed mice, 14SM FR-fed mice and 13SM FR-fed dams. Distal colon contents were analyzed by qPCR using primers specific to each bacteria and present once per genome.

C. Line plots of the mean relative abundances and SD of each bacterial strain from ages 10 to 30 days. Data were normally distributed according to the Kolmogorov-Smirnov test and statistical significance compared to the 14SM FR control at each time point was calculated by two-way ANOVA with false-discovery adjustment using the Benjamini and Hochberg method. The adjusted p values are indicated for 14SM FF vs 14SM FR (red) and 13SM FR vs 14SM FR (orange).

Results and discussion

Gut microbiome colonization is shaped by maternal diet

Consistent with previous reports (Earle et al, 2015; Desai et al, 2016), we observed an elevated relative abundance of Akkermansia muciniphila in the parent mice fed a fiber-free (FF) diet compared to those on a standard fiber-rich (FR) chow (Table S2). We expected to observe similarly high levels of A. muciniphila in the offspring of FF-fed dams; however, the expansion of A. muciniphila was delayed among mice born to FF-fed dams (Fig. 1A–C). This contrasts with the microbiome development of 14SM FR pups, which showed strong initial colonization with A. muciniphila during suckling, as anticipated given its ability to consume milk oligosaccharides (Kostopoulos et al, 2020). When mice began to consume a solid food diet between ages 15 to 20 days, the profiles rapidly stabilized and resembled compositions observed in adult mice fed the respective diets (Table S2, S3). Among 14SM FF mice, A. muciniphila (mucin specialist), Bacteroides caccae (mucin generalist), Clostridium symbiosum (an emerging biomarker for colorectal cancer (Xie et al, 2017)), and Desulfovibrio piger (sulfate reducer) significantly expanded to comprise approximately three-fourths of the microbiome composition.

Colonic transcriptome reflects differences in maternal diet

A. muciniphila has been previously associated with regulation of host metabolic activity (Yoon et al, 2021) and intestinal adaptive immunity in adult mice (Ansaldo et al, 2019), but little is known about its immune influence in early life. Therefore, to address the host physiological effects of this striking difference in the abundance of A. muciniphila according to diet (Fig. 1), we performed total RNA sequencing on colon of 15 day-old pups born to FR and FF 14SM dams as well as FR 13SM dams without A. muciniphila (Fig. 2). Relative to the control group (14SM FR), we detected changes in the expression level of 32 transcripts according to the maternal diet (14SM FF) and 57 transcripts regulated by the presence of A. muciniphila (13SM FR) (Fig. 2A upper table, Fig. 2B, Fig. S1B). Performing a pathway level analysis based on Gene Ontology (GO) terms for biological processes, we found differential enrichment according to the diet (14SM FR vs 14SM FF), but not to the presence of A. muciniphila (14SM FR vs 13SM FR) (Fig. 2A, lower table). Comparing host transcriptomes according to diet revealed an enrichment in FF 14SM pups of transcripts involved in epithelial barrier development and cell–cell adhesion (Myh1, Myh8, and Myot), as well as peptide cross-linking (Sprr1a and F13a1), anoikis or apoptosis associated with cell detachment from the epithelial tissue (Clca3a2 and Itga5), oxidative stress-induced intrinsic apoptotic signaling pathways (Hspb1 and Nox1), and response to interferon-beta (Tgtp2, Gbp2 and Igtp) (Fig 2B and B, Table S8). Some of these transcripts, including Nox1 (Szanto et al, 2005), Itga5 (Zhu et al, 2021), and Hspb1 (Arrigo et al, 2007), are also implicated in colon cancer progression, suggesting potential pathological development.

Figure 2.
Figure 2. Maternal diet alters colonic transcriptome of offspring at age 15 days.

A. Table depicting counts of genes with differential transcription groups after filtering reads not present at least once across all samples (top) and differentially enriched pathways between groups according to the Gene Ontologies (GO) terms for all processes (bottom).

B. Volcano plot showing gene abbreviations for transcripts that were significantly enriched in 14SM FF or 14SM FR after correction for multiple comparisons using DESeq2.

C. Network plots displaying pathways for biological processes and their associated genes that were differentially represented in pups born to 14SM FF vs 14SM FR dams. Top five up- and down-regulated pathways for biological processes are shown; all pathways can be found in Table S8.

D. mRNA expression of Ifng, Tnfa, Il17f, and Il22. Transcription levels were normalized by Hprt, which was the most stable among the three housekeeping genes tested (Hprt, Hsp90, Gapdh). Longitudinal data of mean ± SEM is shown for 14SM FF, 14SM FR, and 13SM FR pups at age 10-20 days (circles) with statistical significance calculated using two-way ANOVA factored on group and time point compared to the 14SM FR control. In addition to the 14SM FF, 14SM FR, and 13SM FR groups, we report transcript levels for pups born to germfree (GF) FF or FR dams at age 15 days (squares) with statistical significance based on a one-way ANOVA with false-discovery adjustment using the Benjamini and Hochberg method. Outliers removed using ROUT method with Q = 1%.

The postnatal period is critical for the development of the immune system as a weaning reaction to colonizing microbes was shown to be protective against diseases in adulthood among mice colonized with segmented filamentous bacteria (Al Nabhani et al, 2019). Thus, in order to provide a longitudinal element to the transcriptomic data, we performed RT-qPCR to quantify the relative expression of transcripts corresponding to select cytokines involved in immunity and epithelial barrier maintenance (Fig. 2D). We noted an induction of Infg around 15 days among all groups, which is considered characteristic of the weaning reaction. Tnfa, another marker of the weaning reaction, was only elevated in the pups of 14SM fiber-deprived dams. By comparing transcript expression levels to germ-free (GF) mice at age 15 days (Fig. 2D), we see that some of the observed pro-inflammatory shifts can be attributed to a combination of diet and microbiome composition. In particular, at age 15 days, the FF diet increased the transcript levels of Ifng, Il17f, and Il23 among germ-free pups of fiber-deprived dams, relative to germ-free, fiber-rich-fed offspring (Fig. 2D, Fig. S1C). At the same age, only pups of 14SM FF-fed dams displayed a strong elevation in Tnfa and Il22 transcript levels, reflecting compounding effects of the maternal diet and microbiome.

Immune development due to maternal fiber deprivation modified by microbiota

The transcript-level results underscore the potent impact of the maternal diet in shaping the developing epithelial barrier and host immune system. Therefore, to confirm that these changes translate into the profile of immune cell populations, we performed flow cytometry on cells isolated from the colonic lamina propria (cLP) at age 15 days (Fig. 3, Fig. S2). As an effect of colonization, we observed elevated levels of NK cells and ILC3 among 14SM pups compared to GF pups (Fig. 3A). Consistent with the host transcriptomic data, maternal dietary fiber intake appeared to play a role in immune cell profiles of both 14SM and GF pups. Particularly, pups of 14SM FF dams had lower levels of ILC2 and higher levels of ILC3 NCR- compared to pups of 14SM FR dams (Fig. 3A). In the adaptive arm however, the 14SM colonization lowered the proportions of CD8+, CD4+, Tregs and Th1 cells (Fig. 3B). By contrast, Th17 cells were induced by the colonization but lower among pups of fiber-deprived dams, suggesting that the maternal dietary fiber intake differentially affects innate and adaptive RORgt+ cells in the pup’s colons.

Figure 3.
Figure 3. Maternal diet and microbiome shapes innate and adaptive neonatal immune cell populations.

A. For 14SM and GF FF- and FR-fed mice at age 15 days, the proportion of cytotoxic natural killer (cNK), innate lymphoid cell (ILC) type 1, ILC type 2, ILC type 3, natural cytotoxicity receptor (NCR) positive ILC3, and NCR negative ILC3 populations among CD45+ cells.

B. For 14SM and GF FF- and FR-fed mice at age 15 days, the proportion of CD8+ T cells, CD4+ T cells, Tregs (total FoxP3+), Th1 cells (Tbet+), Th2 (GATA3+), and Th17 (RORgt+) populations among CD45+ cells.

C. For 13SM, 14SM, and GF FR-fed at age 15 days, the proportion of cNK, ILC1, ILC2, ILC3, NCR+ ILC3, and NCR-ILC3 populations among CD45+ cells.

D. For 13SM, 14SM, and GF FR-fed at age 15 days, the proportion of CD8+ T cells, CD4+ T cells, Tregs, Th1, Th2, and Th17 populations among CD45+ cells.

Statistical significance is based on a two-way ANOVA (A-B) or one-way ANOVA (C-D) with false-discovery adjustment using the Benjamini and Hochberg method.

Given that a trend toward ILC3 induction was also observed in GF pups of dams fed the FF diet, relative to the GF FR group, it is also possible that dietary metabolites other than bacterially produced SCFA play a role in shaping host immunity. In particular, even in the absence of a microbiota, AhR activation through the binding of these metabolites might promote epithelial protection via ILC3 rather than ILC2 induction (Qiu et al, 2012; Li et al, 2018). AhR ligands, which may be derived from microbial or host degradation of dietary tryptophan metabolites, stimulate production of IL-22 from ILC3s (Qiu et al, 2012; Li et al, 2018), both of which were elevated among pups of 14SM FF-fed dams at 15 days of age. The expansion of these innate subsets also leads to apoptosis of commensal-specific CD4+ and CD8+ T cells (Hepworth et al, 2015; Liu et al, 2019). A fixed number of cells were stained per organ, therefore, although GF mice have higher proportions of adaptive cell subsets (namely CD8+, CD4+, Tregs, and Th1 cells), this is likely a reflection of their lower proportions of innate cells, consistent with previous reports (Macpherson & Harris, 2004; Kennedy et al, 2018). The absolute counts of regulatory T cells are expected to be lower in GF mice compared to colonized mice (Macpherson & Harris, 2004; Hrncir et al, 2008).

Akkermansia muciniphila alters innate and adaptive immunity in early life

To determine the role of A. muciniphila in the aforementioned colonization effect (Fig. 3A, B), we compared the immune cell profiles of pups born to FR-fed 14SM, 13SM and GF dams (Fig. 3C, D). Compared to GF pups, the pups born to mothers without A. muciniphila (13SM) had lower induction of ILC3 and Th17 cells, and lower repression of CD8+, CD4+, Tregs, Th1 and Th2 cells (p=0.052) than pups born to 14SM dams (Fig 3C, D). Interestingly, the group with the highest levels of A. muciniphila at this time point (14SM FR) also had an enrichment of Th17 cells (Fig. 3D). Th17 cells play a key role in progression of multiple sclerosis, an autoimmune disease that has also been correlatively linked to presence of A. muciniphila in patients (Jangi et al, 2016) and mechanistically in mouse models of multiple sclerosis (Lin et al, 2021). Although the precise nature of the link between Akkermansia and exacerbation of autoimmune encephalomyelitis has not yet been shown (e.g. MAMP recognition, physiological alterations from mucin-degrading activities), this relationship bears further investigation to identify potential therapeutic targets.

Conclusion

Summarizing these findings, we demonstrate 1) that the maternal diet alters the host transcriptomic profile among pups during the weaning period and 2) that the inclusion or exclusion of a single bacterium from a defined community has demonstrable effects on the immune development of the pups (Fig. 4). The mechanisms behind such immunomodulatory effects can be via microbial metabolites such as SCFA or AhR ligands, or via surface molecules such as LPS (Davis et al, 2022). In the latter instance, Kostopoulos et al. demonstrated that A. muciniphila produces more immune-regulatory pili-protein when grown on human milk, highlighting diet-dependent factors that can indirectly strengthen barrier integrity via the microbiome (Kostopoulos et al, 2020). In line with this, we found that presence of A. muciniphila skews toward a type 3 response, whereas its absence appears to favor a type 1 or 2 response. Overall, our results highlight the importance of the maternal microbiome composition and dietary fiber intake in postnatal microbiome maturation and immune development, which could have implications for development of various immune-mediated diseases later in life.

Figure 4.
Figure 4. Summary of key transcriptional, cellular, and microbial shifts among pups of 14SM fiber-deprived dams.

Maternal milk components (immunoglobulins, altered milk glycan structures) among fiber-deprived dams are predicted to inhibit the establishment of mucin-degrading bacteria in the suckling period, after which this functional group rapidly expands, following a pattern inverse to pups of FR-fed dams. These microbial changes are accompanied by an array of host changes characterized by transcripts involved in epithelial development and innate defense signaling as well as differential priming of key immune cell subsets.

In this study, we assessed the compounding effects of a fiber-free diet across generations with mice pups weaned onto the same diet as the dams. While this experimental setup more closely resembles a real-world scenario, future studies could isolate the effects of the maternal fiber-deprived diet alone by weaning mice onto the same standard chow. Furthermore, we note that it would be of interest to interrogate the long-term health consequences of the observed differences in early life immune priming (Fig. 4). Mouse models of multiple sclerosis or allergy might be particularly interesting based on the immune cell subsets that were strongly affected by the maternal diet or microbiome changes in this experiment.

Additionally, future studies should characterize the maternal milk components improve understanding of the mechanisms for A. muciniphila suppression, which occurred only in pups born to fiber-deprived dams. As illustrated in Fig. 4, a potential explanation for this phenomenon includes changes in quantity or specificity of IgG—the dominant maternal antibody transferred via murine breast milk (Zheng et al, 2020). In adult mice, this role is carried out by IgA, which can regulate the composition and metabolic output of the gut microbiome (Nakajima et al, 2018). Another explanation for A. muciniphila suppression may be related to differences in the types of linkages presented by the milk oligosaccharides, which could hamper their effective utilization by A. muciniphila. To this point, Kostopoulos et al. demonstrated that A. muciniphila can degrade 2’-fucosyllactose, lacto-N-tetraose, lacto-N-triose II, lactose, and 3’-sialyllactoses (Kostopoulos et al, 2020), although it also bears mentioning that these structures are common components of human milk, which is expected to have a slightly different compositional and structural makeup compared to murine milk (Luna et al, 2022). Improved understanding of these milk-associated mechanisms in both humans and rodent models are warranted, as these insights could provide tools to augment growth or activity of A. muciniphila in various disease contexts.

This work highlights numerous underexplored factors related to the potential for maternal fiber deprivation to alter postnatal establishment of mucin-degrading gut bacteria and immune maturation. The elevated levels of RORgt-induced innate and adaptive cell subsets among A. muciniphila-colonized mice is important for preventing translocation of gut microbes into the host (De Agüero et al, 2016) and can also be associated with protection against chronic inflammation via TLR4 (Liu et al, 2022). Considering A. muciniphila is only found in approximately half of the human population (Geerlings et al, 2018), linking this bacterium to exacerbation or amelioration of specific gut-linked diseases is particularly interesting as it highlights its potential as a biomarker for disease risk. Although A. muciniphila has been proposed as a probiotic (Cheng & Xie, 2021), mainly due to its strong benefits in countering metabolic diseases, the various conflicting reports involving this bacterium and health, as discussed by Cirstea et al. (Cirstea et al, 2018), caution against premature generalizations and underscore the need to consider factors such as diet and underlying disease context. Ultimately, insights provided by the present study and follow-up works are expected to hold translational relevance in improving human health outcomes as modern lifestyle practices (e.g. antibiotics use, Western-style diets) contribute to perturbation of the gut microbiota and immune function across generations (Sonnenburg et al, 2016) and in early life (Robertson et al, 2019).

Materials and Methods

Mice

All experimental procedures involving animals (i.e. initial gavage of parental mice) were approved by the Luxembourgish Ministry of Agriculture, Viticulture and Rural Development (LUPA 2019/49). Mouse work was performed according to the “Règlement grand-ducal du 11 janvier 2013 relatif à la protection des animaux utilisés à des fins scientifiques” based on the “Directive 2010/63/EU” on the protection of animals used for scientific purposes. Mice were housed in the germ-free facility of the University of Luxembourg in either colonization-specific isolators or individually ventilated cages. Germ-free Swiss Webster mice were orally gavaged with 13SM or 14SM at 6–8 weeks of age. Gnotobiotic mice and germ-free (GF) controls were fed the respective diets for at least 20 days prior to start of breeding. Mouse pups between ages 10–30 days were sacked by decapitation (age 10 days) or cervical dislocation (age >15 days) at 5-day intervals to collect endpoint measures.

Diet formulation

Detailed compositions of the fiber-rich (FR) and fiber-free (FF) diets used in this study are as previously reported (Parrish et al, 2022c). Gnotobiotic FR mice were fed a standard rodent chow (SAFE®R04, Augy, France). The FF diet is a modified version of Harlan TD.08810 diet, manufactured by the same vendor as the standard chow, as previously reported(Parrish et al, 2022b).

Bacterial culturing and colonization of 13- or 14-member synthetic microbiota (SM)

Culturing and colonization of GF mice with the 13- or 14-member synthetic microbiota (SM) was performed as previously described (Steimle et al, 2021). The 14SM community contains the following bacteria (all type strains, unless otherwise indicated): Akkermansia muciniphila, Collinsella aerofaciens, Desulfovibrio piger, Escherichia coli HS, Faecalibacterium prausnitzii A2-165, Roseburia intestinalis, Marvinbryantia formatexigens, Clostridium symbiosum, Eubacterium rectale A1-86, Barnesiella intestinihominis, Bacteroides caccae, Bacteroides uniformis, Bacteroides ovatus, and Bacteroides thetaiotaomicron. The 13SM mice were orally gavaged with the same strains with the exception of A. muciniphila. Bacterial colonization among the parental mice was verified by qPCR of fecal DNA at 7 days post-oral gavage using strain-specific primers. Note that R. intestinalis and E. rectale did not consistently transfer to the pups during the early life period, despite being detected in the parents.

Tissue processing

Distal colons were washed in PBS to collect contents, then transferred to 1 ml RNAprotect Tissue Reagent (Qiagen, Hilden, Germany) for transcript analyses. Tissues were held in RNAprotect at 4°C for 2 days, after which the reagent was removed and the tissues stored at –80°C. For mice that would undergo FACS analyses, the entire colon was transferred into ice-cold 3 ml Hank’s balanced salt solution (HBSS) containing 10 mM HEPES and without Ca2+ and Mg2+. Cells from the colonic lamina propria (cLP) were isolated using a Lamina Propria Dissociation Kit (Miltenyi Biotec, Bergisch Gladbach, Germany) on the gentleMACS Dissociator (Miltenyi Biotec), following the manufacturer’s instructions. Cells were washed, counted, and re-suspended in FACS buffer (PBS; 1% FCS; 5mM EDTA) until cell staining.

Flow cytometry

A total of 1.5 × 106 cells per animal were transferred into a U-bottom 96-well plate for staining. For live/dead staining, cells were incubated in 100 µl PBS 1X containing 1.5 μL Zombie NIR Fixable Viability kit (BioLegend, San Diego, CA, USA) at 4°C for 30 min. Cells were washed twice using FACS buffer and subsequently fixed with the FoxP3 Fix/Perm kit (eBiosciences, Uithoorn, Netherlands) for 45 min at 4°C, followed by permeabilization wash. Purified Rat Anti-Mouse CD16/CD32 (Mouse BD Fc Block™, BD Biosciences, San Jose, CA, USA) was added at a concentration of 1 µg per 106 cells, incubated at 4°C for 30 min, then cells were washed twice in permeabilization buffer. Cells were stained with anti-CD4 BV605 (#100548, clone RM4-5, 1:700, Biolegend), anti-CD3 BV711 (#100241, clone 17A2, 1:88, Biolegend), anti-CD45 BV780 (#564225, clone 30-F11, 1:88, BD), anti-CD335/NKp46 FITC (#137606, clone 29A1.4, 1:100, Biolegend), anti-CD8 PE-Cy5 (#100710, clone 53-6.7, 1:700, Biolegend), anti-FoxP3 eF450 (#48-5773-82, clone FJK-16s, 1:200, eBiosciences), anti-GATA3 PE (#100710, clone 53-6.7, 1:44, Biolegend), anti-EOMES PE-eF610 (#61-4875-82, clone Dan11mag, 1:100, eBiosciences), anti-Tbet PE-Cy7 (#644824, clone 4B10, 1:44, Biolegend), and anti-RORgt APC (#17-6988-82, clone AFKJS-9, 1:22, eBiosciences). Cells were incubated with the staining mix for 30 min at 4°C, then washed twice with FACS buffer. Samples were acquired on a NovoCyte Quanteon flow cytometer (ACEA Biosciences Inc., San Diego, CA, USA). Raw fcs files were analyzed in FlowJo version 10.8.1, with innate cell populations gated as described by Burrows et al. (Burrows et al, 2020). An example of the gating strategy is illustrated in Fig. S2. The dataset was exported as a percent of the total CD45+ cells for subsequent statistical analyses.

DNA extraction and microbiome compositional analyses

Distal colon contents were collected by opening the colon longitudinally and washing tissue in 1 ml PBS. The PBS and contents were then centrifuged at 10 000 g for 10 min and the PBS supernatant was removed. Pelleted contents were stored at –20°C until DNA extraction using the phenol-chloroform method, as described by Steimle et al. (Steimle et al, 2021). The concentration of DNA was measured using a NanoPhotometer N60 (Implen, Munich, Germany). The purified DNA was diluted 10-fold and then subjected to qPCR with primers specific to each of the 14 bacterial strains, as previously described (Steimle et al, 2021). As the primers are specific to each strain and the target sequence is present only once in the respective genome (Desai et al, 2016), this method was used to allow for estimation of the number of each individual bacterial genomes or the absolute abundance of bacteria in the contents of the distal colon (Table S2, S3). In order to rule out contamination with non-14SM strains, we also performed 16S sequencing on a subset of samples. For this method, DNA concentration was assessed using the Qubit® dsDNA HS assay kit on a Qubit® 3.0 fluorometer (Life Technologies, Eugene, Oregon, USA). To rule out contamination with non-14SM members, sequencing of the V4 region of the 16S rRNA gene was carried out on an Illumina MiSeq system at the Integrated BioBank of Luxembourg (IBBL, Dudelange, Luxembourg), as previously described by Neumann et al. (Neumann et al, 2021). Raw fastq sequences were processed via QIIME2 version 2020.6 (Bolyen et al, 2019) using DADA2 (Callahan et al, 2016) for quality control. Taxonomic assignment was carried out with the SILVA 138 database (Quast et al, 2013) (Table S4).

RNA extraction

Colon tissues were stored at –80°C until RNA extraction. Tissues were incubated overnight at –80°C in 1 ml TRIzol™ Reagent (Life Technologies Europe BV, Bleiswijk, Netherlands). A 5mm autoclaved metal bead was added to the sample, followed by homogenization on a RETSCH Mixer Mill MM 400 for 5 min at 30 Hz. Samples were centrifuged at 4°C for 5 min at 12 000 × g. The supernatant was transferred to a new tube and incubated for 5 min at room temperature. For each sample, 200 µl pure chloroform was added, then mixed by shaking for 15 s and incubated at room temperature for 3 min. Next, samples were centrifuged for 15 min at 4°C, 12 000 × g, and the aqueous phase was recovered. A volume of 500 µl isopropanol was added, followed by vigorous mixing and incubation at room temperature for 10 min. Samples were centrifuged at the same settings as previously. Then, the pellet was recovered and washed in 1 ml ice-cold 75% ethanol and vortexed briefly before centrifugation at 4°C for 5 min at 7 500 × g. The supernatant was discarded and the pellets were air-dried for 10 min at 37°C before re-suspending in 50 µl Invitrogen™ UltraPure™ DNase/RNase-free distilled water (Life Technologies Europe BV, Bleiswijk, Netherlands). The RNA solution was further incubated for 15 min at 56°C to fully re-suspend the pellet. DNase treatment to remove genomic DNA was done by adding 2 µl DNAse I (1 U/µl), 10 µl DNase I Buffer (10X), plus 40 µl water for 30 min at 37°C. Next, 1 µl of 0.5M EDTA was added to each sample and the DNAse I was inactivated by heating at 65°C for 10 min. RNA purification was performed with the RNeasy mini kit (QIAGEN Benelux BV, Venlo, Netherlands) according to manufacturer’s instructions. RNA was eluted in Invitrogen™ UltraPure™ DNase/RNase-free distilled water (Life Technologies Europe BV, Bleiswijk, Netherlands) and stored at –80°C.

RT-qPCR

Complementary DNA libraries were prepared from 2000 ng purified RNA in 11 µl water, 1 µl 2.5 uM random primers and µl 500 uM dNTPs (Life Technologies Europe BV, Bleiswijk, Netherlands), heated to 65°C for 5 min (lid temperature 112°C), then incubated at 4°C for at least 1 min. Afterwards, 1x SSIV buffer, 1 µl DTT, 1 uL RNaseOUT, and 1 uL SuperScript™ IV Reverse Transcriptase (Life Technologies Europe BV, Bleiswijk, Netherlands) was added to each tube. Samples were held at 23°C for 10 min, then 50°C for 10 min, and finally heated to 80°C for 10 min to inactivate enzymes. Quantitative PCR was carried out according to standard protocols, briefly: 1 ul of template cDNA was mixed with 8.7 µl water,1.2 µl 1x buffer, 0.625 µl 2.5 mM MgCl2, 0.5 µl 400uM dNTPs, 0.1 µl each of 0.2 uM forward and reverse primers (Table S1), 0.125 µl 1x SYBR green fluorescent dye, and 0.1 µl 0.5 U Taq DNA polymerase (Life Technologies Europe BV, Bleiswijk, Netherlands). Samples were pre-denatured at 94°C for 5 min; then underwent 40 cycles at 94°C for 20 s, 60°C for 50 s, 72°C for 45 s. Finally, samples were maintained at 72°C for 5 min and the melting curve was generated over 15 s by heating from 65°C–95°C at 0.3°C increments. Transcript expression levels were normalized to levels of Hprt, which was identified as the most stable housekeeping gene over time and conditions using RefFinder, in comparison to Gapdh and Hsp90.

RNA sequencing and analysis

RNA integrity (RIN) was determined using a 2100 Bioanalyzer RNA Nanochip (Agilent, Santa Clara, CA, USA). Samples selected for RNA sequencing had RIN values ranging from 7.7–9.8. RNA libraries were prepared using an Illumina® Stranded Total RNA Prep kit, along with Ribo-Zero Plus to deplete ribosomal RNA. Samples were then sequenced in a 2 × 75 bp arrangement with a High Output Flow Cell on an Illumina NextSeq 550 system (Illumina, San Diego, CA, USA) at the LuxGen sequencing platform (Dudelange, Luxembourg). Adapters were removed using Cutadapt (Martin, 2011), followed by reads mapping and enumeration of gene counts with STAR 2.7.9a (Dobin et al, 2013) (Table S5). Transcripts that did not appear at least one time on average across all samples were filtered from downstream analyses. Two outliers were identified based on variation on PC1 from the top 500 most variable genes and excluded from subsequent analyses (Fig. S1a). Samples normalization was performed using the median of ratios method, followed by differential expression analysis in R using DESeq2 1.30.1 (Love et al, 2014). Default parameters were used and p values were adjusted according to the Benjamini-Hochberg method. Differential expression was considered significant based on an adjusted p value<0.05. Differential expression analysis was performed for pairwise comparisons 14SM FF vs 14SM FR (Table S6) and 14SM FR and 13SM FR (Table S7) (Love et al, 2014). Pathway-level analysis was also carried out in R using the clusterProfiler 3.18.1 enrichGO function (Yu et al, 2012) to identify up- or downregulated pathways according to Gene Ontology (GO) terms (Table S8).

Statistical analysis

Unless otherwise specified, statistical analyses were carried out using GraphPad Prism version 9.3.1 for Windows (GraphPad Software, San Diego, CA, USA). For FACS data with only one time point, an ordinary two-way ANOVA was fitted to main effects only (diet and colonization status) with multiple comparison correction using the Benjamini-Hochberg method. Only biologically-relevant pairwise statistical comparisons are shown: 13SM FR vs. 14SM FR, 13SM FR vs. GF FR, 14SM FR vs. 14SM FF, 14SM FR vs. GF FR, 14SM FF vs. GF FF, and GF FR vs. GF FF. Data are from independent experiments (pups born from up to 4 litters derived from 2–3 breeding pairs per condition).

Data Availability

The datasets produced in this study are available in the following databases:

Conflict of interest

Mahesh S. Desai works as a consultant and an advisory board member at Theralution GmbH, Germany.

The Paper Explained

PROBLEM

There is a growing awareness that the early life period is a critical window for shaping the course of neonatal development and future health outcomes. However, little is known regarding the effects of maternal diet and microbiome composition on the interconnected establishment of the gut microbiome and host immunity in the progeny. We sought to understand the role of maternal dietary fiber intake on early life development by breeding mice colonized with a 14-member synthetic microbiota (SM), fed a fiber-deficient diet. We further investigated the effects of discrete changes in the maternal microbiome by colonizing a third breeding pair with the full SM except Akkermansia muciniphila, a somewhat controversial, health-associated commensal that can digest milk oligosaccharides and host mucins.

RESULTS

Pups born to dams fed a standard, fiber-rich chow showed initial colonization with A. muciniphila, followed by an expansion of fiber-degrading bacteria upon switching to solid food. Conversely, among pups of dams fed a fiber-free diet, A. muciniphila did not proliferate until after weaning, suggesting that maternal milk factors influenced by diet shape pups’ microbiome development. Pups of fiber-deprived dams expressed a significantly higher quantity of colonic tissue transcripts corresponding to defense response pathways against external antigens, and harbored lower proportions of group 2 innate lymphoid cells and Th17 cells. Pups of fiber-rich-fed mice lacking A. muciniphila demonstrated reduced proportions of innate and adaptive RORγt-positive immune cell subsets.

IMPACT

The link between A. muciniphila and RORγt-positive immune cell subsets represents an intriguing potential to alter immunity by targeting a single bacterium, however the mechanisms underlying this interaction warrant further investigation. The unexpected suppression of Akkermansia among pups of fiber-free fed dams during the weaning period encourages the characterization of maternal milk components that might be used to support or limit growth of certain bacteria during early life. Using a tractable gnotobiotic mouse model and custom diet, we highlight the powerful potential to manipulate the microbiome and immunity during early life, which may have important implications for prevention of modern diseases such as allergy and autoimmunity.

Supplementary Information

Figure S1.
Figure S1.

A. PCA plot of samples analyzed by RNA sequencing datasets. B.

B. Volcano plot showing transcripts that were significantly enriched in 14SM FR or 13SM FR after correction for multiple comparisons using DESeq2.

C. mRNA expression of Il12p40 and Il23. Transcription levels were normalized by Hprt, which was the most stable among the three housekeeping genes tested (Hprt, Hsp90, Gapdh). Longitudinal data of mean ± SEM is shown for 14SM FF, 14SM FR, and 13SM FR pups at age 10-20 days (circles) with statistical significance calculated using a two-way ANOVA factored on group and time point compared to the 14SM FR control. For Il23, we also report transcript levels for pups born to germfree (GF) FF or FR dams at age 15 days (squares) with statistical significance based on a one-way ANOVA with false-discovery adjustment using the Benjamini and Hochberg method. Outliers removed using ROUT method with Q = 1%.

Figure S2.
Figure S2.

Representative gating strategy for flow cytometry analysis.

Table S1. Primers for RT-qPCR against colonic cDNA transcript library.

Table S2. Absolute abundances of synthetic microbiota (SM) members among parent mice.

Table S3. Absolute abundances of synthetic microbiota (SM) members among individual pups.

Table S4. 16S rRNA gene sequencing to rule out contamination with non-14SM bacteria.

Table S5. Count table of transcripts mapping to genes by ENSEMBL identifier. Asterisk (*) indicates samples identified as outliers by PCA plotting.

Table S6. Differential enrichment analysis using DESeq2 for 14SM fiber-free and 14SM fiber-rich contrasts.

Table S7. Differential enrichment analysis using DESeq2 for 14SM fiber-rich and 13SM fiber-rich contrasts.

Table S8. Pathway level differential enrichment analysis using clusterProfiler (all processes) for 14SM fiber-free and 14SM fiber-rich contrasts.

Acknowledgements

Figure 4 was made using BioRender (Biorender.com). We thank the Luxembourg National Research Fund (FNR) for funding this research through CORE grants (C15/BM/10318186 and C18/BM/12585940) to M.S.D.; E.T.G. was supported by the FNR PRIDE (17/11823097) and the Fondation du Pélican de Mie et Pierre Hippert-Faber, under the aegis of the Fondation de Luxembourg; M.B. was supported by a European Commission Horizon 2020 Marie Skłodowska-Curie Actions individual fellowship (897408).

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Maternal diet and gut microbiome composition modulate early life immune responses
Erica T. Grant, Marie Boudaud, Arnaud Muller, Andrew J. Macpherson, Mahesh S. Desai
bioRxiv 2023.03.06.531289; doi: https://doi.org/10.1101/2023.03.06.531289
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