Skip to main content

The influence of maternal unhealthy diet on maturation of offspring gut microbiota in rat

Abstract

Background

Despite well-known effects of diet on gut microbiota diversity, relatively little is known about how maternal diet quality shapes the longitudinal maturation of gut microbiota in offspring. To investigate, we fed female rats standard chow (Chow) or a western-style, high-choice cafeteria diet (Caf) prior to and during mating, gestation and lactation. At weaning (3 weeks), male and female offspring were either maintained on their mother’s diet (ChowChow, CafCaf groups) or switched to the other diet (ChowCaf, CafChow). Fecal microbial composition was assessed in dams and longitudinally in offspring at 3, 7 and 14 weeks of age.

Results

The effect of maternal diet on maturation of offspring gut microbiota was assessed by α- and β-diversities, Deseq2/LEfSe, and SourceTracker analyses. Weanling gut microbiota composition was characterised by reduced α- and β-diversity profiles that clustered away from dams and older siblings. After weaning, offspring gut microbiota came to resemble an adult-like gut microbiota, with increased α-diversity and reduced dissimilarity of β-diversity. Similarly, Deseq2/LEfSe analyses found fewer numbers of altered operational taxonomic units (OTUs) between groups from weaning to adulthood. SourceTracker analyses indicated a greater overall contribution of Caf mothers’ microbial community (up to 20%) to that of their offspring than the contribution of Chow mothers (up to 8%). Groups maintained on the maternal diet (ChowChow, CafCaf), versus those switched to the other diet (ChowCaf, CafChow) post-weaning significantly differed from each other at 14 weeks (Permutational Multivariate Analysis of Variance), indicating interactive effects of maternal and post-weaning diet on offspring gut microbiota maturation. Nevertheless, this developmental trajectory was unaffected by sex and appeared consistent between ChowChow, CafCaf, ChowCaf and CafChow groups.

Conclusions

Introducing solid food at weaning triggered the maturation of offspring gut microbiota to an adult-like profile in rats, in line with previous human studies. Postweaning Caf diet exposure had the largest impact on offspring gut microbiota, but this was modulated by maternal diet history. An unhealthy maternal Caf diet did not alter the developmental trajectory of offspring gut microbiota towards an adult-like profile, insofar as it did not prevent the age-associated increase in α-diversity and reduction in β-diversity dissimilarity.

Introduction

The gut microbiota has significant impacts on host growth and development. Evidence shows that microbiota colonization in early life plays a critical role in the establishment and development of gut microbial community in later life, in turn influencing a range of health outcomes [1, 2]. Vertical microbial transmission from mother to offspring has been documented in animals [3, 4] and humans [5,6,7,8]. Accumulating evidence implicates maternal gut microbiota as a significant source of offspring gut microbiota colonization. Development of the gut microbiota is shaped by interactions with host genetics, age, diet, and living conditions [9].

Diet is a critical determinant of gut microbiota diversity. An unhealthy maternal diet affects offspring microbial communities, with common species identified in mother and offspring microbial communities [10, 11]. However, it remains to be determined whether the longitudinal maturation of offspring gut microbiota is affected by an unhealthy maternal diet.

Mothers’ habitual dietary patterns considerably shape the dietary patterns of their offspring [12,13,14,15]. Given that offspring are likely to consume a habitual dietary pattern similar to that of their mother, it is critical to identify whether the shared microbiota characteristics of mothers and their offspring result from consuming a common diet, or from vertical transmission of gut microbiota in early life. More specifically, it is unknown whether different types of maternal diet can have adverse effects on offspring gut microbiota maturation.

To address this knowledge gap, we used a rat model to test how maternal diet affects the development of the microbiota in offspring, and the extent to which these effects persist when offspring are (a) maintained on the same diet (maternal diet = postnatal diet) or (b) shifted to a different diet (maternal diet ≠ postnatal diet). We assessed the effects of highly processed foods eaten by people by using a validated Cafeteria-style diet (Caf) model [16] on faecal microbial communities in mothers, and their male and female offspring at 3 (weaning), 7 and 14 weeks of age. This design allows us to assess the contributions of species associated with maternal microbiota to offspring microbial community over time. The primary aim of this study was to investigate whether maternal diet affects the development of the microbiota in offspring, and the extent to which these effects interact with offspring diet. Phenotypic changes in offspring including body weight and adiposity were reported in Tajaddini et al. [17]. We found that maternal Caf consumption alters offspring gut microbial communities at weaning; however, after the introduction of solid food, the trajectory of offspring gut microbiota maturation was not affected by maternal Caf diet, and more strongly impacted by offspring diet post-weaning.

Methods

Ethics statement

The experimental protocol was approved by the Animal Care and Ethics Committee of the University of New South Wales (Ethics number: 19/74A) in accordance with the guidelines for the use and care of animals for scientific purposes 8th edition (National Health and Medical Research Council, Australia).

Subjects (and experimental design)

This is a secondary study from a cohort of obese and lean mothers previously described [17]. Young adult female (approximately 7–8 weeks of age; body weight ~ 200 g) and male (approximately 8–9 weeks of age; body weight ~ 300 g) Sprague–Dawley rats (Animal Resource Centre, WA, Australia) were housed at 18–22 °C (12 h light/dark cycle) and maintained ad libitum on water and standard chow (14 kJ/g, 65% carbohydrate, 22% protein and 13% fat; Premium Rat Maintenance diet, Gordon’s Stockfeeds, NSW, Australia). Following acclimatization, female rats were weight-matched, then randomly allocated to either standard chow (Chow) or Caf diet groups. Diets comprised standard chow or chow plus Caf diet consisting of chow and water, 10% sucrose solution and a selection of cakes, biscuits and protein sources (e.g., meat pie and dim sims), that varied daily [16]. Detailed macronutrient and micronutrient components of the Caf diet have been previously described [16]. After 6 weeks of diet, females were mated with chow fed males by co-housing 2–3 females and one male for five days, after which males were removed [17]. Pregnancy was inferred based on weight gain and females were housed individually from approximately gestation day 16. Litters were standardized to six male and six female pups, where possible [17] on postnatal day (PND) 1. Dams and offspring were weighed every three days during lactation. The experimental design is shown in Fig. 1. At weaning (PND20) and at 14 weeks of age, offspring were anaesthetized by i.p. injection of ketamine/xylazine, and decapitated. Retroperitoneal (RP) adipose tissue was collected bilaterally, identified as the triangular pad of fat attached to the lateral abdominal wall; feces were collected at PND20, 14 weeks (at cull) and to provide an intermediate timepoint, an extra collection was taken at 7 weeks in conscious rats.

Fig. 1
figure 1

Experimental design. Female rats were fed chow or Caf diet for 6 weeks, then mated with chow fed males. Fecal samples were collected from mothers and pups at weaning (3 weeks of age). Pups were weaned onto chow or Caf diet, and feces were sampled from a subset of offspring at 7 weeks, and from all remaining pups at 14 weeks of age. Experimental groups consisted of Chow Father; Chow Mother; Caf Mother; Chow Weaner; Caf Weaner; ChowChow; ChowCaf; CafChow; CafCaf at both 7 weeks and 14 weeks; ChowCaf 14 weeks; CafChow 14 weeks; and CafCaf 14 weeks

Fecal DNA extraction

Fecal DNA extraction was performed using the PowerFecal DNA Isolation Kit (MoBio Laboratories, Carlsbad, CA, USA) according to the manufacturer’s instructions. DNA concentration and quality were measured using a DeNovix DS-11 Spectrophotometer (DeNovis, Inc., Delaware, USA).

16S rRNA amplicon sequencing and raw data analysis

Composition of the microbial communities was assessed by Illumina amplicon sequencing (2 × 250 bp MiSeq chemistry, V4 region, 515F-806R primer pair; Ramaciotti Center for Genomics, UNSW Sydney) using a standard protocol [18]. The sequence data were then analyzed using MOTHUR [19], which included removal of ambiguous bases and homopolymers longer than 15 base pairs, alignment with SILVA database, chimera checking with UCHIME, classification against the RDP Ribosomal Database training set (version16_022016), and removal of singletons. Sequences were clustered into operational taxonomic units (OTU) at 97% nucleotide identity to generate an OTU table with the taxonomy and number of sequences per OTU in each sample. Commands were derived from MiSeq SOP [20] and modified as required. Sequence data were subsampled to n = 30,113 total clean reads/sample.

Data analysis

OTU tables were standardized by dividing feature read counts by total number of reads in each sample. Standardized data were then square root transformed. All statistical analyses examined sex-specific differences in the offspring. α-diversity (species richness, species evenness and Shannon’s diversity index) analyses, Non-metric Multi-dimensional Scaling (NMDS) plots, Permutational Multivariate Analysis of Variance (PERMANOVA) and Permutational Analysis of Multivariate Dispersions (PERMDISP) were generated using a Bray–Curtis resemblance matrix on PRIMER (Primer-e Ltd., Plymouth, United Kingdom) [20]. Linear Discriminant Analysis (LDA) Effect Size (LEfSe) [22] was performed using the Galaxy web application [23]. The R package Phyloseq [24] was used for the negative binomial Wald test in DESeq2 [25]. P values were adjusted for multiple testing using Benjamini–Hochberg false discovery rate correction in DESeq2. Differentially abundant OTUs were defined as those that were present in over 50% of rats, and which were significantly different in both LEfSe and DESeq2 analyses. SourceTracker [26] analysis assessed similarities between maternal and offspring microbiota via the Galaxy web application [23, 27].

Statistical analyses were performed with SPSS, including independent samples t tests, one way and two-way Analysis of variance (ANOVA). For α-diversity measures (Species richness, Evenness and Shannon index), independent samples t tests were used to compare chow and Caf mothers. Two-way ANOVA (maternal diet × sex) was used for comparisons between weanlings. Four-way ANOVA was used to assess differences between the four offspring groups (ChowChow, ChowCaf, CafChow, CafCaf) at 7 and 14 weeks of age (2 (maternal diet) × 2 (postnatal diet) × [2] (time) × 2 (sex)). β-diversity was examined by PERMANOVA, with a single factor of diet for mothers (Chow and Caf), and two factors (diet and sex) for weanlings. For postweaning data, four factors (maternal diet, postnatal diet, age, and sex) were used in analysis of overall offspring microbial composition, followed by PERMDISP analysis. Figures were generated in GraphPad Prism and PRIMER. Results are expressed as mean ± SEM and were considered significant at p ≤ 0.05.

Results

Influence of maternal and postnatal diets on body weight

Table 1 shows anthropometric data of rats used in this study which was a subset of animals from our previous study [17]. The Caf diet increased maternal consumption of sugar, saturated fat and protein, relative to chow diet [17]. Prior to mating, mothers fed the Caf diet had significantly elevated adiposity but no significant change in fasting blood glucose. When euthanized after lactation, RP fat mass was still elevated in Caf versus control dams, with no difference in body weight or girth [17].

Table 1 Anthropometric data of animals used in this study

Mothers body weight from diet day 30 to the end of lactation was analysed by two-way repeated measures ANOVA. Caf diet consumption significantly increased dams body weight across time (main effect of maternal diet, F = 19.87, p < 0.001); and main effect of time (F = 283.5, p < 0.0001) with significant interaction between maternal diet and time (F = 38.46, p < 0.0001) (Table 1). Retroperitoneal (RP) fat in Caf mothers was significantly heavier than Chow mothers (t = 2.20, p < 0.05). For weanlings, maternal diet and sex did not affect body weight. Interestingly, RP fat mass differed according to maternal diet (main effect of maternal diet, F = 21.8, p < 0.01) and sex (main effect of sex, F = 11.4, p < 0.01), however there was no significant maternal diet × sex interaction. At 7 weeks, body weight differed according to postnatal diet (main effect of postnatal diet, F = 70.0, p < 0.01) and sex (main effect of sex, F = 589.6, p < 0.01). Maternal diet did not affect body weight nor was there any maternal diet, postnatal diet and sex interactions. At 14 weeks, significant sex × maternal diet interaction on RP fat (F = 6.17, p < 0.05) and body weight (F = 4.3, p < 0.05) indicated that maternal diet differentially affected males and females. Also, there was a significant sex × postnatal diet interaction (F = 31.66, p < 0.01) for RP fat mass. However, there was no significant three-way (maternal diet × postnatal diet × sex) or two-way (maternal diet × postnatal diet) interaction on body weight and RP fat.

For additional phenotypic data of mothers and offspring, overall macronutrient intake and 24 h food consumption in the dams, see the related study [17] and our previous work [28]. Gut microbial diversity of each group was assessed by 16S rRNA genes from fecal samples collected at times shown in Fig. 1.

Lasting effects of maternal obesogenic diet consumption on gut microbiota α-diversity in mothers and offspring

We first examined α-diversity measures across groups and time. Caf diet consumption significantly depleted species richness, evenness and the Shannon diversity index in Caf mothers (t = 3.05, p < 0.01, Fig. 2A; t = 3.84, p < 0.01, Fig. 2B; and t = 3.42, p < 0.01, Fig. 2C respectively).

Fig. 2
figure 2

α-diversity across groups and time. A Species Richness; B Evenness; and C Shannon Index. **p < 0.01 independent t test; *p < 0.05 main effect of maternal diet. #p < 0.05; ##p < 0.01; ###p < 0.001 by Post hoc comparisons. Data are displayed as mean ± SEM. Chow: chow diet; Caf: Cafeteria diet; ChowChow: maternal chow diet and postnatal chow diet; ChowCaf: maternal chow diet and postnatal Caf diet; CafChow: maternal Caf diet and postnatal chow diet; CafCaf: maternal Caf diet and postnatal Caf diet

At weaning, two-way ANOVA (maternal diet × sex) indicated that maternal Caf diet consumption significantly reduced species richness (F (1,32) = 7.475, p = 0.01), evenness (F (1,32) = 7.347, p = 0.011) and the Shannon diversity index (F (1,32) = 8.290, p = 0.007) regardless of offspring sex, with no significant interactions between maternal diet and sex (Fig. 2A–C). There was no significant cage effect on weaner’s species richness, evenness and Shannon index.

Adult offspring microbiota composition at 7- and 14-week timepoints was analyzed by 2 (maternal diet) × 2 (postnatal diet) × 2 (time) × 2 (sex) factorial ANOVA. A significant three-way interaction between maternal diet, postnatal diet and time were found for species richness (F (1,161) = 7.550, p = 0.007), evenness (F (1,161) = 14.217, p < 0.001) and Shannon index (F (1,161) = 12.547, p = 0.001), while offspring sex did not interact with these variables (Additional file 1: Fig. S1).

To clarify the source of these interactions, we compared the effects of Caf diet on offspring α-diversity measures over time using post hoc comparisons applying the Bonferroni correction. Species richness was significantly reduced in the CafCaf group at 7 weeks compared with ChowChow group at 7 and 14 weeks (p < 0.01 and p < 0.001 respectively) and CafCaf group at 14 weeks (p < 0.01). By 14 weeks, intriguingly, species richness in CafCaf group was no longer different from other groups (Fig. 2A). Similar effects were seen for evenness and Shannon index measures, which were both significantly reduced in the CafCaf group at 7 weeks compared to ChowChow group at 7 and 14 weeks and CafCaf group at 14 weeks. At 14 weeks, evenness and Shannon diversity did not differ between groups (Fig. 2B–C). Finally, we entered cage as a covariate in the three-way analyses. For 7 and 14 week measures, there was some evidence that species richness differed between cages (p = 0.03) but critically, this factor did not interact with maternal and offspring diet factors (all ps > 0.05), and thus did not appear to determine the results of interest.

Next, we examined the effect of diet switch (maternal diet ≠ postnatal diet) on offspring α diversity measures over time. Offspring from Caf dams switched to chow at weaning (CafChow group) did not differ in α diversity measures (species richness, evenness and Shannon index) relative to the ChowChow group at 7 and 14 weeks (Fig. 2A–C). Likewise, offspring from chow dams switched to Caf (ChowCaf group) did not differ in α-diversity measures from ChowChow group at 7 and 14 weeks. Evenness and Shannon index in the ChowCaf group at 14 weeks was significantly increased compared with the CafCaf group at 7 weeks (Fig. 2B–C).

β-diversity of gut microbiota shifted over time in a host age-dependent manner

We first examined the impact of chow and Caf diet on gut microbial communities of mothers, and offspring at weaning, 7 and 14 weeks; all groups clustered differently regardless of diet type at the OTU level, as indicated by non-metric multidimensional scaling (NMDS) plots (Fig. 3A and B; and Additional file 3: Fig. S3A–D) and PCO (Additional file 2: Fig. S2). PERMANOVA analyses (999 permutations) confirmed significant differences in β-diversity between Chow and Caf mother (F(1,18) = 6.7575, p = 0.001) and between Chow weaner and Caf weaner (F(1,33) = 6.4525, p = 0.001) (Table 2). There was no significant interaction between maternal diet and sex on β-diversity of weanlings.

Fig. 3
figure 3

β-diversity. Non-metric multidimensional scaling (NMDS) plots following square root transformation and Bray–Curtis resemblance of relative abundance data at the OTU level. A NMDS for Weaner (Chow or Caf), 7wks (ChowChow or CafCaf) and 14wks (ChowChow or CafCaf); Father (Chow only), Mother (Chow or Caf) are also shown. B NMDS for Weaner (Chow or Caf), 7wks (ChowCaf or CafChow) and 14 wks (ChowCaf or CafChow); Father (Chow only), Mother (Chow or Caf) are also shown. Chow: chow diet; Caf: Cafeteria diet; ChowChow: maternal chow diet and postnatal chow diet; ChowCaf: maternal chow diet and postnatal Caf diet; CafChow: maternal Caf diet and postnatal chow diet; CafCaf: maternal Caf diet and postnatal Caf diet

Table 2 Summary of PERMANOVA analyses

Results from PERMANOVA (999 permutations) analyses are summarised in Table 2. For β-diversity of offspring at 7 and 14 weeks, we performed PERMANOVA using a 2 (maternal diet) × 2 (postnatal diet) × 2 (time) × 2 (sex) design. The analysis indicated a significant 3-way interaction between maternal diet, postnatal diet and time (F(1,154) = 2.0437, p = 0.005) (Table 2). PERMDISP (variation of Bray–Curtis similarities) confirmed no systematic differences in sample dispersion (Mother: F(1,18) = 0.0267, p = 0.889; Weaner: F(1,35) = 2.213, p = 0.169; 7 and 14 weeks: F(7, 162) = 1.444, p = 0.262). Pairwise comparisons between offspring groups at 7 and 14 weeks confirmed that microbiota composition significantly differed between all groups (largest p < 0.033).

Continuous Caf diet consumption altered abundance of OTUs

Figure 4 shows representative taxa on phylum (A) and genus (B) levels in each group. The top 100 OTUs were selected to generate heat maps on phylum (A) and genus level (B), and the heatmaps were normalised by row. At phylum level, Firmicutes was more abundant in both chow and Caf mothers compared with Bacteroidetes; on the other hand, Bacteroides was more abundant in both chow and Caf weanlings compared with Firmicutes. Proteobacteria and Verrucomicrobia were highly abundant in chow and Caf weanlings respectively.

Fig. 4
figure 4

Representative taxa on the phylum and genus levels in each group. Microbial taxa top 100 OTUs were selected to generate heat maps on phylum level (A) and genus level (B). The relative abundance of phylum and genus levels were normalised by row

Next, DESeq2 and LEfSe analyses were used to identify OTUs that were differentially enriched or depleted by Caf diet exposure between groups and across time. To assess the effects of diet exposure, we selected OTUs only if the adjusted p value was < 0.05 from both DESeq2 and LEfSe analyses. Enriched/depleted OTUs meeting these criteria were then assessed and the top 100 OTUs were selected. In mothers, a total of 16 OTUs (10 depleted, 6 enriched) were significantly affected by Caf diet (Fig. 5A). Maternal Caf diet was associated with depletion of several OTUs in Lactobacillus and Alloprevotella genera, while several OTUs in the Blautia and Ruminococcus genera were enriched. At weaning, 8 OTUs were enriched while 31 were depleted in the offspring of Caf dams relative to those from chow dams (Fig. 5B). There were 9 OTUs commonly affected by maternal Caf diet in both mothers and weanlings (see underlined taxa in Fig. 5A and B; E). At 7 weeks, 48 OTUs were significantly affected in CafCaf compared to ChowChow offspring, while at 14 weeks, 9 OTUs differed significantly in abundance in CafCaf compared to ChowChow offspring (Fig. 5C and D). The relative abundance of Ruminococcus_Otu00086 was consistently and significantly decreased in CafCaf offspring at 3, 7 and 14 weeks (Fig. 5F).

Fig. 5
figure 5

OTUs significantly altered between groups. Microbial taxa among the top 100 OTUs identified to significantly differ in abundance between A mothers (Chow vs. Caf); B weanlings (Chow vs Caf), underlined OTUs indicate 9 common taxa between mothers and weanlings; C offspring at 7 weeks (ChowChow vs CafCaf); and D offspring at 14 weeks (ChowChow vs. CafCaf) by DESeq2 (padj < 0.05) and LEfSe (LDA Score > 2.0, p < 0.05). In DESeq2, negative (red) Log2foldchange value denotes decreased abundance and positive (green) Log2foldchange value denotes increased abundance in A Caf mother; B Caf weaner; C 7 week offspring in CafCaf group; and D 14 week offspring in CafCaf group. E Differential OTUs 7 OTUs and 30 OTUs were uniquely altered in Mothers and Weanlings by maternal Caf diet, with 9 common OTUs in Caf Mothers and Caf Weanlings. F Relative abundance of Ruminococcus_Otu00086 in 3-, 7- and 14-week offspring fed Caf diet compared with offspring fed chow diet. Note differences were significant using both LEfSe and DESeq2

We further explored OTUs affected by postnatal diet switch by comparing ChowChow and ChowCaf groups. There were 22 OTUs at 7 weeks and 45 OTUs at 14 weeks that significantly differed in abundance between ChowCaf and ChowChow groups by Log2foldchange and LDA score. Fifteen OTUs were commonly affected at both 7 and 14 weeks, characterised by significantly depleted abundance of Alistipes, Alloprevotella and Prevotella genera and increased abundance of Phascolarctobacterium and Ruminococcaceae genera (Table 3). On the other hand, 32 OTUs at 7 weeks and 33 OTUs at 14 weeks significantly differed in abundance between CafChow and CafCaf groups; 14 OTUs were altered at both timepoints, with decreased abundance of Ruminococcus and Lachnospiraceae genera and increased abundance of Lactobacillus and Collinsella genera in the CafCaf group (Table 4). For the comparison between ChowChow and CafChow groups, no OTUs survived FDR correction.

Table 3 Common OTUs altered significantly in ChowCaf compared with ChowChow offspring at both 7 and 14 weeks
Table 4 Common OTUs altered significantly in CafCaf compared with CafChow offspring at both 7 and 14 weeks

Contribution of maternal and paternal gut microbial community to composition of offspring gut microbiota

We used SourceTracker [26] to assess any contributions of maternal and paternal gut microbial community to offspring. This revealed differential contributions of species associated with the gut microbiota from Chow mothers, Caf mothers, and fathers, to offspring gut microbiota. Pooled Chow mothers, Caf mothers and fathers were treated as separate sources contributing organisms to offspring gut microbial communities at weaning, 7 and 14 weeks of age (Fig. 6A–C). SourceTracker suggested that the microbiota composition of Caf mothers made a larger contribution to both Chow and Caf weanlings’ gut microbiota than did that of Chow mothers (Additional file 4: Fig. S4). Chow mothers’ contribution to offspring microbiota increased upon switching to postnatal chow diet over time, with offspring showing an increase in chow diet associated species. To a lesser extent, a similar trend was observed for offspring in the CafCaf group. On the other hand, Caf mothers’ contribution to offspring decreased upon switching to postnatal chow diet over time, and this was also observed in the CafCaf group. Paternal contribution to offspring gut microbiota was greatest in weanlings and decreased over time across groups (Additional file 4: Fig. S4).

Fig. 6
figure 6

SourceTracker analyses. Chow mothers, Caf mothers and Chow fathers were pooled separately and computed as sources that can contribute to offspring gut microbial communities. A shows offspring consuming same diet as mother; Chow and Caf weanlings, ChowChow and CafCaf offspring at 7 and 14 weeks. B compares offspring of Chow mothers; Chow weanlings, ChowChow and ChowCaf offspring at 7 and 14 weeks. C compares offspring of Caf mothers; Caf weanlings, CafChow and CafCaf offspring at 7 and 14 weeks. Individual rats are indicated on X axis (number indicates mother id, M or F indicates male or female). D Relative contribution of top 20 OTUs of Chow mother, Caf mother and Chow father gut microbiota to offspring gut microbiota

Figure 6D shows the contributions of top 20 OTUs from Chow and Caf mothers and fathers to offspring gut microbiota. SourceTracker indicated differential transmission according to maternal diet; for Caf mother microbiota, this tended towards Bacteroides_Otu00001 and Bacteroides_Otu00002, while the contribution of Chow mother microbiota tended towards Lachnospiraceae_unclassified_Otu00006, Prevotella_Otu00007, Lactobacillus_Otu00008 and Alloprevotella_Otu00009 (Fig. 5D). There was a greater influence of Caf mother (up to 22%) compared with Chow mother (up to 7%) and father (up to 4%) contribution to offspring (Fig. 6D). FASTA sequences of these OTUs were blasted against whole genome shotgun contigs (wgs) to identify bacterial species in the Basic Local Alignment Search Tool (BLAST) (https://blast.ncbi.nlm.nih.gov/Blast.cgi). The BLAST search showed that Bacteroides_Otu00001 had similarity to Bacteroides vulgatus (Phocaeicola vulgatus) (98.8%), Bacteroides_Otu00002 had similarity to Bacteroides acidifaciens (98.8%), Lactobacillus_Otu00008 had similarity to Lactobacillus murinus (Ligilactobacillus murinus) (98.4%) and Alloprevotella_Otu00009 had similarity to Alloprevotella rava (88.4%), whereas BLAST search for Lachnospraceae_unclassified_Otu00006 and Prevotella_Otu00007 did not result in identifiable species.

Discussion

Our study showed that the development of gut microbiota from weaning to adulthood in rats was characterized by increased α-diversity and reduced dissimilarity in β-diversity; changes that rapidly occurred after weaning onto solid food. These results are consistent with studies in people showing that the cessation of breast milk triggered infant gut microbiota development [29, 30], indicating a similar shift in the development of infant gut microbiota to adult-like gut microbiota across different species. Furthermore, we showed that maternal and postnatal consumption of a Caf diet comprised of palatable, processed foods eaten by people, reduced α diversity and altered β-diversity compared with maternal consumption of chow. On the other hand, a maternal Caf diet did not appear to prevent the age-associated increase in α diversity and reduction in β-diversity dissimilarity associated with the shift of offspring gut microbiota towards an adult-like profile.

At weaning, the gut microbial communities of offspring of Chow and Caf dams showed dramatically reduced α-diversity and altered β-diversity relative to their mothers and older offspring (7 and 14 weeks). At 7 weeks of age, α-diversity was suppressed in the CafCaf group compared with the ChowChow, ChowCaf and CafChow groups, suggesting an additive effect of maternal and postweaning exposure to Caf diet. The overall gut microbial composition (β-diversity) of 7 week-old ChowChow and CafCaf offspring clustered close to, but were nonetheless significantly different from, their respective mothers. In contrast, by 14 weeks of age, there was no difference in species richness, evenness and Shannon’s index across the four offspring groups. However, it is possible that the difference in gut microbial composition at 7 weeks of age might modulate the subsequent programming of offspring health in later life. This may suggest adaptation of offspring gut microbiota to different types of diet, however, there are complex interactions between maternal diet and postnatal diet over time. It is also possible that development of the gastrointestinal tract in offspring [31] might have contributed to the absence of group differences in later life, hence further investigation is warranted.

β-diversity of offspring gut microbiota exhibited greater similarity to the adult-like gut microbiota over time, both for groups whose postweaning diet was consistent with that of the mother (ChowChow and CafCaf) and for those whose postweaning diet differed from their mother (ChowCaf and CafChow groups). The trend of offspring gut microbiota maturation in this study, an increase in α-diversity and a decrease in dissimilarity of β-diversity is consistent with work by Bäckhed et al. (2015) examining the human gut microbiota in mother and infant dyads [29]. In addition, we show for first time that the developmental trajectory of infant gut microbiota was not affected by the type of maternal and postnatal diets. Maternal factors including the use of antibiotics and other medications, birth mode (vaginal vs C-section), diet and stress have been reported to influence the offspring gut microbiota [1]. However, there is still sparse longitudinal evidence of the impact of these factors on development of the gut microbiota.

Nonetheless, DESeq2 and LEfSe analyses identified multiple OTUs that were reliably altered in the CafCaf relative to the ChowChow group across development. At 7 weeks, the largest number of OTUs were altered in CafCaf group; in total 48; 31 OTUs were depleted and 17 OTUs were enriched. By 14 weeks, the number of altered OTUs in CafCaf group compared with ChowChow group was 9 OTUs in total, of which 1 taxon was depleted and 8 taxa were enriched. Thus fewer OTUs differed between groups over time, underlining an increasing similarity of α-diversity and β-diversity of offspring gut microbiota. On the other hand, the relative abundance of Ruminococcus_Otu00086 was consistently depleted in Caf weanlings and in group CafCaf at 7 and 14 weeks, compared with Chow groups. BLAST search with FASTA sequence of Otu_00086 did not identify any similarity to Ruminococcus species. Depletion of Otu_00086 was also observed in Caf dams (relative abundance 6.3%) compared with chow dams (42.2%). Together, this may indicate Ruminococcus is a potential biomarker for unhealthy dietary intake. Here offspring of Caf dams mirrored the effect of Caf diet on suppressing Ruminococcus, the effect that was consistent over time, since the depletion of the genus was observed in offspring gut microbiota from weaning to 14 weeks. In support, the relative abundance of Ruminococcus_Otu86 recovered after switching to chow diet. Ruminococcus are commensal bacteria and play key roles in plant fiber degradation (resistant starch) and butyrate production [32, 33]. Continuous Caf diet consumption suppressed the abundance of this beneficial bacteria, which has been shown previously to be depleted [34] in Caf fed rats compared with purified high fat diet and ‘western style’ diet fed animals. Our finding is consistent with findings of Sonnenberg et al. [35] describing extinction of taxa in mice consuming a western style diet lacking dietary fibre over multiple generations [35]. Hence, this may suggest that the Ruminococcus genera might be affected by highly processed foods containing food additives and insufficient dietary fibre, rather than an effect of the energy density of the food per se [36, 37].

SourceTracker analysis indicated a greater overall contribution of Caf mothers’ microbial community (up to 20%) to that of their offspring than the contribution of Chow mothers’ (up to 8%) of the offspring community. The greater contribution of Caf mothers may be due to higher energy efficiency of representative taxa, however, this needs to be interpreted with caution. Another intriguing finding was the greater contribution of Caf mothers’ microbial community to both Caf and chow weanlings gut microbial community at PND19. Caf mothers’ contribution was characterized by higher relative abundance of Bacteroides_Otu00001 (98% similarity to Bacteoides vulgatus) and Bacteroides_Otu00002 (98% similarity to Bacteroides acidifaciens). On the other hand, Chow mothers’ contribution was characterized by higher relative abundance of Lachnospiraceae_unclassified_Otu00006, Prevotella_Otu00007, Lactobacillus_Otu00008 (98% similarity to Lactobacillus murinus) and Alloprevotella_Otu00009 (88% similarity to Alloprevotella rava). Increased relative abundance of Bacteroides vulgatus was in line with a higher abundance of this species in high fat diet fed rats in our previous study [38].

Finally, we did not find any evidence that sex interacted with α-diversity and β-diversity measures on the development of offspring gut microbiota in this cohort.

The study has some limitations. As the Caf style diet used mirrors the western diet eaten by people [16], by design, it includes foods containing various additives, preservatives, emulsifiers and colorants which can affect gut microbial diversity, in addition to being low in fibre. Future studies using purified diets could delineate the differential impacts of individual diet components on development of gut microbiota. As offspring gut microbial diversity rapidly changes on introduction of solid foods at weaning, it would be interesting to sample soon after the introduction of solid foods to provide additional insight into microbiota development in early life. This study assessed maternal microbial community based on feces collected from the mother at weaning. Recent evidence indicates that maternal microbial communities fluctuate during gestation [39]. Hence, maternal gut microbiota at weaning might differ from that found pre-mating, during gestation and lactation. Lastly, the paternal microbiota was assessed by sampling feces from fathers at weaning, which may not accurately reflect the paternal microbiota at mating.

Conclusion

This study using rats showed that cessation of lactation triggered offspring gut microbiota maturation, in line with past human studies. The introduction to solid food drives early life gut microbiota maturation towards adult-like gut microbiota over time by an increase in α-diversity and reduction in dissimilarity of β-diversity. Unhealthy maternal diets can shift β-diversity of the growth trajectory of offspring gut microbiota. Intriguingly, despite identifying several enriched and depleted bacteria in rats exposed to postweaning Caf diet, the overall maturation of gut microbiota in offspring was not affected by diet type. Our results are in line with previous work and underscore the notion that introduction of solid food plays an important role in shaping early life gut microbiota composition.

Availability of data and materials

The sequence data for this study have been deposited in the European Nucleotide Archive (ENA) at EMBL-EBI under accession number PRJEB46141 (https://www.ebi.ac.uk/ena/browser/view/PRJEB46141).

Abbreviations

ANOVA:

Analysis of variance

BLAST:

Basic Local Alignment Search Tool

Caf:

Cafeteria diet

CafCaf:

Maternal caf diet and postnatal caf diet

CafChow:

Maternal caf diet and postnatal chow diet

Chow:

Standard chow diet

ChowCaf:

Maternal chow diet and postnatal caf diet

ChowChow:

Maternal chow diet and postnatal chow diet

LDA:

Linear Discriminant Analysis

LEfSe:

Linear Discriminant Analysis Effect Size

NMDS:

Non-metric multidimensional scaling

OTU:

Operational taxonomic unit

PERMANOVA:

Permutational Multivariate Analysis of Variance

PERMDISP:

Permutational Analysis of Multivariate Dispersions

References

  1. Calatayud M, Koren O, Collado MC. Maternal microbiome and metabolic health program microbiome development and health of the offspring. Trends Endocrinol Metab. 2019;30(10):735–44.

    CAS  Article  Google Scholar 

  2. Wang S, Ryan CA, Boyaval P, Dempsey EM, Ross RP, Stanton C. Maternal vertical transmission affecting early-life microbiota development. Trends Microbiol. 2020;28(1):28–45.

    CAS  Article  Google Scholar 

  3. Barden M, Richards-Rios P, Ganda E, Lenzi L, Eccles R, Neary J, et al. Maternal influences on oral and faecal microbiota maturation in neonatal calves in beef and dairy production systems. Anim Microbiome. 2020;2(1):31.

    Article  Google Scholar 

  4. Funkhouser LJ, Bordenstein SR. Mom knows best: the universality of maternal microbial transmission. PLoS Biol. 2013;11(8): e1001631.

    CAS  Article  Google Scholar 

  5. Asnicar F, Manara S, Zolfo M, Truong DT, Scholz M, Armanini F, et al. Studying vertical microbiome transmission from mothers to infants by strain-level metagenomic profiling. mSystems. 2017;2(1):e00164-16.

  6. Ferretti P, Pasolli E, Tett A, Asnicar F, Gorfer V, Fedi S, et al. Mother-to-infant microbial transmission from different body sites shapes the developing infant gut microbiome. Cell Host Microbe. 2018;24(1):133-45.e5.

    CAS  Article  Google Scholar 

  7. Murphy K, Curley D, O’Callaghan TF, O’Shea CA, Dempsey EM, O’Toole PW, et al. The composition of human milk and infant faecal microbiota over the first three months of life: a pilot study. Sci Rep. 2017;7(1):40597.

    CAS  Article  Google Scholar 

  8. Wang S, Zeng S, Egan M, Cherry P, Strain C, Morais E, et al. Metagenomic analysis of mother-infant gut microbiome reveals global distinct and shared microbial signatures. Gut Microbes. 2021;13(1):1–24.

    Article  Google Scholar 

  9. Van Daele E, Knol J, Belzer C. Microbial transmission from mother to child: improving infant intestinal microbiota development by identifying the obstacles. Crit Rev Microbiol. 2019;45(5–6):613–48.

    Article  Google Scholar 

  10. Bhagavata Srinivasan SP, Raipuria M, Bahari H, Kaakoush NO, Morris MJ. Impacts of diet and exercise on maternal gut microbiota are transferred to offspring. Front Endocrinol. 2018;9:716.

    Article  Google Scholar 

  11. Savage JH, Lee-Sarwar KA, Sordillo JE, Lange NE, Zhou Y, O’Connor GT, et al. Diet during pregnancy and infancy and the infant intestinal microbiome. J Pediatr. 2018;203:47-54.e4.

    Article  Google Scholar 

  12. Robinson LN, Rollo ME, Watson J, Burrows TL, Collins CE. Relationships between dietary intakes of children and their parents: a cross-sectional, secondary analysis of families participating in the Family Diet Quality Study. J Hum Nutr Diet. 2015;28(5):443–51.

    CAS  Article  Google Scholar 

  13. Robson SM, Couch SC, Peugh JL, Glanz K, Zhou C, Sallis JF, et al. Parent diet quality and energy intake are related to child diet quality and energy intake. J Acad Nutr Diet. 2016;116(6):984–90.

    Article  Google Scholar 

  14. Vepsäläinen H, Nevalainen J, Fogelholm M, Korkalo L, Roos E, Ray C, et al. Like parent, like child? Dietary resemblance in families. Int J Behav Nutr Phys Act. 2018;15(1):62.

    Article  Google Scholar 

  15. Bogl LH, Silventoinen K, Hebestreit A, Intemann T, Williams G, Michels N, et al. Familial resemblance in dietary intakes of children, adolescents, and parents: does dietary quality play a role? Nutrients. 2017;9(8):892.

    Article  Google Scholar 

  16. Leigh SJ, Kendig MD, Morris MJ. Palatable western-style cafeteria diet as a reliable method for modeling diet-induced obesity in rodents. J Vis Exp. 2019(153).

  17. Tajaddini A, Kendig MD, Prates KV, Westbrook RF, Morris MJ. Male rat offspring are more impacted by maternal obesity induced by cafeteria diet than females-additive effect of postweaning diet. Int J Mol Sci. 2022;23(3):1442.

    CAS  Article  Google Scholar 

  18. Caporaso JG, Lauber CL, Walters WA, Berg-Lyons D, Lozupone CA, Turnbaugh PJ, et al. Global patterns of 16S rRNA diversity at a depth of millions of sequences per sample. In Proceedings of the National Academy of Sciences of the United States of America. 2011;108 Suppl 1(Suppl 1):4516–22.

  19. Schloss PD, Westcott SL, Ryabin T, Hall JR, Hartmann M, Hollister EB, et al. Introducing mothur: open-source, platform-independent, community-supported software for describing and comparing microbial communities. Appl Environ Microbiol. 2009;75(23):7537–41.

    CAS  Article  Google Scholar 

  20. Kozich JJ, Westcott SL, Baxter NT, Highlander SK, Schloss PD. Development of a dual-index sequencing strategy and curation pipeline for analyzing amplicon sequence data on the MiSeq Illumina sequencing platform. Appl Environ Microbiol. 2013;79(17):5112–20.

    CAS  Article  Google Scholar 

  21. Clarke KR. Non-parametric multivariate analyses of changes in community structure. Aust J Ecol. 1993;18(1):117–43.

    Article  Google Scholar 

  22. Segata N, Izard J, Waldron L, Gevers D, Miropolsky L, Garrett WS, et al. Metagenomic biomarker discovery and explanation. Genome Biol. 2011;12(6):R60.

    Article  Google Scholar 

  23. Jalili V, Afgan E, Gu Q, Clements D, Blankenberg D, Goecks J, et al. The Galaxy platform for accessible, reproducible and collaborative biomedical analyses: 2020 update. Nucleic Acids Res. 2020;48(W1):W395-w402.

    CAS  Article  Google Scholar 

  24. McMurdie PJ, Holmes S. phyloseq: an R package for reproducible interactive analysis and graphics of microbiome census data. PLoS ONE. 2013;8(4): e61217.

    CAS  Article  Google Scholar 

  25. Love MI, Huber W, Anders S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 2014;15(12):550.

    Article  Google Scholar 

  26. Knights D, Kuczynski J, Charlson ES, Zaneveld J, Mozer MC, Collman RG, et al. Bayesian community-wide culture-independent microbial source tracking. Nat Methods. 2011;8(9):761–3.

    CAS  Article  Google Scholar 

  27. Feng K, Zhang Z, Cai W, Liu W, Xu M, Yin H, et al. Biodiversity and species competition regulate the resilience of microbial biofilm community. Mol Ecol. 2017;26(21):6170–82.

    Article  Google Scholar 

  28. Raipuria M, Bahari H, Morris MJ. Effects of maternal diet and exercise during pregnancy on glucose metabolism in skeletal muscle and fat of weanling rats. PLoS ONE. 2015;10(4): e0120980.

    Article  Google Scholar 

  29. Bäckhed F, Roswall J, Peng Y, Feng Q, Jia H, Kovatcheva-Datchary P, et al. Dynamics and stabilization of the human gut microbiome during the first year of life. Cell Host Microbe. 2015;17(5):690–703.

    Article  Google Scholar 

  30. Yatsunenko T, Rey FE, Manary MJ, Trehan I, Dominguez-Bello MG, Contreras M, et al. Human gut microbiome viewed across age and geography. Nature. 2012;486(7402):222–7.

    CAS  Article  Google Scholar 

  31. Sangild PT. Gut responses to enteral nutrition in preterm infants and animals. Exp Biol Med (Maywood). 2006;231(11):1695–711.

    CAS  Article  Google Scholar 

  32. Flint HJ, Scott KP, Duncan SH, Louis P, Forano E. Microbial degradation of complex carbohydrates in the gut. Gut Microbes. 2012;3(4):289–306.

    Article  Google Scholar 

  33. Morrison DJ, Preston T. Formation of short chain fatty acids by the gut microbiota and their impact on human metabolism. Gut Microbes. 2016;7(3):189–200.

    Article  Google Scholar 

  34. Bortolin RC, Vargas AR, Gasparotto J, Chaves PR, Schnorr CE, Martinello KB, et al. A new animal diet based on human Western diet is a robust diet-induced obesity model: comparison to high-fat and cafeteria diets in term of metabolic and gut microbiota disruption. Int J Obes (Lond). 2018;42(3):525–34.

    CAS  Article  Google Scholar 

  35. Sonnenburg ED, Smits SA, Tikhonov M, Higginbottom SK, Wingreen NS, Sonnenburg JL. Diet-induced extinctions in the gut microbiota compound over generations. Nature. 2016;529(7585):212–5.

    CAS  Article  Google Scholar 

  36. Malik M, Subedi S, Marques CNH, Mahler GJ. Bacteria remediate the effects of food additives on intestinal function in an in vitro model of the gastrointestinal tract. Front Nutr. 2020;7(131).

  37. Laudisi F, Stolfi C, Monteleone G. Impact of food additives on gut homeostasis. Nutrients. 2019;11(10):2334.

    CAS  Article  Google Scholar 

  38. Lecomte V, Kaakoush NO, Maloney CA, Raipuria M, Huinao KD, Mitchell HM, et al. Changes in gut microbiota in rats fed a high fat diet correlate with obesity-associated metabolic parameters. PLoS ONE. 2015;10(5): e0126931.

    Article  Google Scholar 

  39. Yang H, Guo R, Li S, Liang F, Tian C, Zhao X, et al. Systematic analysis of gut microbiota in pregnant women and its correlations with individual heterogeneity. NPJ Biofilms Microbiomes. 2020;6(1):32.

    Article  Google Scholar 

Download references

Acknowledgements

Not applicable.

Funding

This project was supported by National Health and Medical Research Council (NHMRC) project grant funding to MJM and RFW (APP1161418).

Author information

Affiliations

Authors

Contributions

Conceptualization-MJM and RFW; Data curation-KH and NOK; Formal analysis-KH and NOK; Funding acquisition-MJM and RFW; Investigation-MDK and AT; Methodology-MJM, RFW and MDK; Project administration-MJM, RFW and MDK; Writing (original draft)-KH; Writing (review&editing)-MJM, RFW, MDK, NOK and KH. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Margaret J. Morris.

Ethics declarations

Ethics approval and consent to participate

The experimental protocol was approved by the Animal Care and Ethics Committee of the University of New South Wales (Ethics number: 19/74A) in accordance with the guidelines for the use and care of animals for scientific purposes (National Health and Medical Research Council Australia).

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Additional file 1: Figure S1

. α-diversity three-way interaction plots. Three-way interaction between maternal diets, postnatal diets and time at 7 and 14 weeks shown in A) Species Richness; B) Evenness; and C) Shannon Index.

Additional file 2: Figure S2

. β-diversity (PCO).

Additional file 3: Figure 3

. β-diversity by group. β-diversity by groups were shown, A) Mother; B) Weaner; C) 7weeks; and D) 14weeks.

Additional file 4: Figure 4

. SourceTracker analysis. Relative contributions to offspring by Chow mothers, Caf mothers and Chow fathers.

Additional file 5: Table S1

. SourceTracker analysis: Proportions of Chow and Caf mother microbial communities’ contribution to offspring gut microbial composition. Chow mothers, Caf mothers and fathers were pooled separately as environmental sources. Data are displayed as mean ± SEM.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Hasebe, K., Kendig, M.D., Kaakoush, N.O. et al. The influence of maternal unhealthy diet on maturation of offspring gut microbiota in rat. anim microbiome 4, 31 (2022). https://doi.org/10.1186/s42523-022-00185-w

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s42523-022-00185-w

Keywords

  • Gut microbiota development
  • Vertical microbiota transmission
  • Cafeteria diet
  • Maternal overnutrition