Drivers of infant gut microbiota

Gut microbiota is influenced by mode of delivery and gestational age

The structure of the infant gut microbiota is clearly affected by mode of delivery (Fig. 1, Additional file 1: Table S4). The results demonstrate that there was a significant difference in microbiota composition at genus level across the four different groups from week 1 to week 24, when analysed by Spearman distance matrix and visualised by principal coordinates analysis (PcoA). At 1 week of age, the microbiota composition of the FT-CS group was significantly different from that of both PT-CS and FT-SVD groups (p values <0.001). PT-CS and FT-SVD were also distinct from one another (p < 0.001). The low number of PT-SVD infants (n = 4) did not permit significant testing at this time point, but it is worth noting that this microbiota cluster is situated between the PT-CS and FT-SVD groups. At 4 weeks of age, FT-CS microbiota was significantly different to all other groups (p < 0.001). The PT infant microbiota mainly separated across the x-axis. At 8 weeks of age, the FT-CS group is distinct from both PT-CS and FT-SVD (p < 0.001), separated on both axes. The FT-SVD and PT-CS are also distinct (p < 0.001); all three groups have significantly different microbiota composition at 8 weeks of age. By 24 weeks, there were no significant differences between PT-CS and FT-CS microbiota, while FT-CS and FT-SVD microbiota were still significantly different (p < 0.01). At this time point, mode of delivery remains influential while differences due to gestational age have been eliminated. At all time points, there was wide diversity of individual population structures within each group, showing the heterogeneous composition of the developing infant gut microbiota.

Fig. 1 Birth mode and gestation age both significantly affect the composition of the infant gut microbiota to 24 weeks of age. Principal coordinates analysis (PCoAs) on Spearman distance matrices of samples at each of four time points (weeks 1, 4, 8 and 24) revealed significant differences between the groups. Significance was calculated using permutational multivariate analysis of variance (PerMANOVA, Additional file 1: Table S3). *p < 0.05; **p < 0.01; ***p < 0.001 Full size image

Distinctive metabolomic profiles are associated with microbiota profiles

Co-inertia analysis of the week 4 microbiota data at the OTU level and the metabolomic dataset showed that there was a significant (p < 0.05) amount of co-variation in the two datasets (Fig. 2). There was little separation observed between FT birth modes (FT-CS and FT-SVD); however, the PT-CS samples separated distinctly from the FT samples. The co-inertia analysis showed that there were greater differences between the group microbiota profiles than between the group metabolomic profiles. These differences are evident where the FT metabolomic baricentres are overlaid while there is a separation between the microbiota baricentres. The PT-SVD metabolomic and microbiota baricentres were relatively distant from one another, but this separation may be due to the low number of samples in each of these groups. The compounds associated with the PT-FT split are from multiple different sources and were represented by a diverse selection of metabolites (Additional file 3: Figure S1, Additional file 1: Table S5). Annotated metabolites were grouped based on their origin and chemical character: (i) amino acids and metabolites; (ii) carboxylic acids and phenolic acids and their metabolites; (iii) vitamins and their metabolites; (iv) drugs and their metabolites; (v) carnitines; (vi) indole metabolites; and (vii) fatty acids and their metabolites (see Additional file 1: Tables S5 and S6). Urea and its associated metabolite derivatives were situated in the centre of the metabolite cluster, suggesting it is abundant in both groups, providing confidence in our classifications.

Fig. 2 Co-inertia analysis of urine-derived metabolomic and 16S rRNA gut microbiota data from stool. Microbiota data was scalar normalised and logged. Microbiota is represented by circles and the metabolomic samples are represented by squares. Four groups are visualised; preterm-Caesarean section (blue), preterm-spontaneous vaginal delivery (orange), full-term Caesarean section (red) and full-term spontaneous vaginal delivery (green). Small objects represent the individual samples and large objects represent the barycentre of the group. Analysis shows that the co-variance between the microbiota and metabolomics dataset splits the preterm infants from the full-terms. Metabolites associated with this split are highlighted in Additional file 3: Figure S1 and Additional file 1: Table S4 Full size image

We found a number of paracetamol metabolites to be significantly higher in PT infants, as well as several different vitamins and their metabolites such as riboflavin, CECH—a tocopherol metabolite or pyridoxic acid (Additional file 1: Table S5). These metabolites may be due to altered medical treatment of PT infants. Among endogenous metabolites found to be statistically significant, two families could be easily identified: tryptophan and tyrosine. Metabolites belonging to tryptophan pathway were kynurenine, indoxyl sulphate, indole acetic acid, while those belonging to tyrosine were acetylphenylalanine, acetyl tyrosine and hydroxyphenylalanine sulphate.

The accurate mass and fragmentation pattern of a number of features that were elevated in the urine of the PT group were consistent with bile acids; all of them conjugated to glycine. We found glycocholic acid, one sulphate conjugate of chenodeoxyglycocholic acid (or its isomer glycoursodeoxycholic acid) and three atypical bile acids (Additional file 1: Table S5).

Among small carboxylic acids we found succinic acid and its derivatives are statistically lower in PT, while several metabolites of glutamic acid were found at higher levels.

Finally, a number of fatty acids were found to be statistically higher in PT-CS infants. Most of them were found as dicarboxylic species, with different hydroxylation patterns and with different saturation levels; moreover, some were found as glucuronide conjugates.

Differentially abundant taxa drive microbiota clustering over time

The abundance of genera can also be represented by a heat plot of hierarchically clustered samples (Fig. 3), which helps classify differentially abundant taxa. Many of the samples cluster by time point, where week 1 and week 24 in particular show relatively tight clusters. Weeks 4 and 8 show some variation, which is possibly due to the inclusion of FT and PT infants, whereas PT infants are slightly older, due to the time point of sampling. Very few genera are present at high abundance at week 1, as bacterial diversity is lowest at this time point. The genera that are abundant at week 1 decrease in relative abundance by week 24 (branch 1), as other genera begin to emerge at detectable levels as the infants age (branch 2). This trend is visible through week 8, when another cluster of genera begins to emerge (branch 3). By week 24, the genera that were most abundant at week 1 have markedly reduced in proportion (branch 1). Genera on branch 2 have low relative abundances, whereas genera on branch 3 are found to be quite highly abundant. Within this third branch we find genera that are core to enterotypes, such as Prevotella, Blautia and Ruminococcus. Once Bifidobacterium emerged (at week 1 for some samples, and by week 4 for others), their abundances appear to remain relatively stable, at least to 24 weeks of age.

Fig. 3 Infants separate temporally and into three distinct clusters based on differentially abundant taxa. The three clusters may indicate the beginning of an enterotype-based microbiota profile as early as 24 weeks of age. Only those genera (side) that are present in at least 10% of samples (top) are shown. Samples are highlighted by the time point at which they were obtained Full size image

Breastfeeding influences the gut microbiota of CS infants

We collected categorical metadata on how long each infant was breastfed. Three categories were recorded: between 1 and 2 months, between 2 and 4 months, and greater than 4 months. We used PerMANOVA to compare the microbiota of infants in these categories, and also examined the birth mode effect separately (Additional file 1: Table S7). No differences were detected between the microbiota composition of infants who were breastfed for 1 to 2 months and those breastfed for 2 to 4 months. However, comparing infants breastfed for less than 4 months and those for longer than 4 months revealed a significant difference for FT-CS but not FT-SVD (Fig. 4). Five genera were significantly more abundant in infants that were breastfed for longer and four genera were more abundant in infants that were breastfed for a shorter duration (Additional file 1: Table S8). Bifidobacterium was not found to significantly differ in abundance based on duration of breastfeeding (also tested with Wilcoxon Rank Sum test; data not shown).

Fig. 4 Breastfeeding duration influences the gut microbiota of C-section infants but not naturally delivered infants at 24 weeks of age. a Caesarean section, full-term infants. b Naturally delivered full-term infants. In blue are infants that were breastfed for less than 4 months (i.e. between 1 and 2 months, or between 2 and 4 months). In red are infants that were breastfed for longer than 4 months. The vast majority of infants in the cohort were breastfed for 1 month Full size image

Twins have more similar gut microbiota than unrelated infants

There were ten sets of twins and one set of triplets within the cohort. Twenty one of these 23 infants were in the PT-CS category; we therefore focussed only on these infants. Using t tests with Monte-Carlo permutations, we determined that at week 1, twins’ microbiota were more similar within twin pairs than between non-twin pairs (Spearman distance test: p < 0.001). This is also true at weeks 4, 8 and 24 (p < 0.001 at each time point) (Additional file 4: Figure S2).

Gut microbiota of preterm infants is influenced by post-birth age

For the week 1 time point, all infants were approximately 1 week post-birth (range 6 to 8 days). However, at other time points, PT infants were chronologically older than FT infants, as the samples for these time points were collected at weeks post due date rather than post-birth. This was to ensure all infants were the same post-conceptional age when sampled, as this was previously postulated to have the greatest effect on the establishment of the microbiota [15]. Infants were assigned to groups depending on how many weeks premature they were at birth (4, 5, 6, 7, 8, 9 or 12 weeks). We found that at 1 week of age, when all PT infants are the same post-birth age, no significant difference or trends were apparent. At predicted due dates, three comparisons showed significant differences, with a further seven showing a trend for differences (Additional file 1: Table S9).

Description of the infant gut microbiota

Differential abundance at phylum and genus level in infant groups

We utilised DESeq2 in order to identify bacteria responsible for the microbiota separation of the different groups at phylum and genus levels. The main differences are outlined below, with a full list of all differentially abundant genera available in Additional file 1: Tables S10–S17).

Phylum level

Using relative abundance of phyla from the rarefied dataset, we determined the major bacterial phyla in the different infant groups (Fig. 5). A clear distinction is apparent between the different infant groups at 1 week of age. The FT-SVD infants have a relatively consistent microbiota composition from 1 to 24 weeks of age. The dominant phylum throughout this period is the Actinobacteria (mainly comprised of the genus Bifidobacterium). FT-CS infants initially had a higher relative proportion of Firmicutes at 1 week of age compared to FT-SVD (p < 0.05) and less Actinobacteria (p < 0.001). At 4 weeks of age, Actinobacteria (p < 0.01) and Bacteroidetes (p < 0.001) were more abundant in FT-SVD infants, again with Firmicutes less abundant (p < 0.01). Within the FT-CS group, Actinobacteria significantly increased in relative abundance from 1 to 4 weeks of age (p < 0.001). Bacteroidetes increased significantly in proportion from week 4 to week 8 (p < 0.05) and again from week 8 to week 24 (p < 0.001). Thus, the FT-CS microbiota progressed over time to one which is similar to the FT-SVD infants with no differences at phylum level at either 8 weeks or 24 weeks of age.

Fig. 5 Naturally delivered infant microbiota remains stable at phylum level from 1 to 24 weeks of age, while C-section delivered infants progress to a similar microbiota profile over time. There is no shift in the FT-SVD infant composition from 1 to 24 weeks of age. FT-CS progresses by increasing the relative abundance of Actinobacteria (p < 0.001) and Bacteroidetes (p < 0.001) and decreasing the relative abundance of Firmicutes (p < 0.05) over the same period. PT-CS infants initially have a higher abundance of Proteobacteria compared to the FT groups (p < 0.001). Between week 1 and week 4 the Proteobacteria and Firmicutes abundance decreased (p < 0.001 and p < 0.01, respectively). No significant differences were recorded after week 4. The PT-SVD group had low subject numbers (n = 4), hindering significant associations, resulting in no significant changes being observed. Showing phyla found at >1% average in total population. Phyla found at <1% were grouped as ‘other’ Full size image

The most pronounced difference between the FT-CS infant gut and the PT-CS gut is evident at 1 week of age when there is a significantly higher proportion of Proteobacteria in PT infants (p < 0.001). The PT-CS group also harbours an initially high relative proportion of Firmicutes at week 1 before becoming dominated by both Actinobacteria and Firmicutes from weeks 4 to 24.

Genus level

The infant gut is dynamic and a number of genera demonstrate significant abundance differences between groups (Fig. 6 and Additional file 1: Table S10–S13) and within groups at different ages (Additional file 1: Table S14–S17). We identified genera which were differentially abundant in at least two of the groups and thus found 21 genera that had dissimilar abundances at week 1, 41 genera at week 4, 39 genera at week 8 and 25 genera at week 24 (Additional file 1: Tables S10–S13). Some of the significant changes are described below.

Fig. 6 Comparison of the microbiota composition of infants born by different birth modes and gestation duration at the same age across four time points from 1 week to 24 weeks of age. The most pronounced differences are evident at week 1 of age, with the microbiota composition becoming increasingly uniform over time to 24 weeks. Showing genera found at >1% average in total population. Genera found at <1% were grouped as ‘other’ Full size image

As expected, Bifidobacterium were found to be a major component of the infant gut. Bacteroides and Clostridia were also important contributors to the gut microbiota composition. Despite the apparently large difference in the average proportion of Bifidobacterium at week 1 between FT-CS and FT-SVD (19 vs 48%), this difference is not statistically significant, due to the high inter-individual variation between infants at this early age. There was no statistically significant difference in the relative proportion of Bifidobacterium between these two birth modes at any time point. Bacteroides was found to be significantly more abundant in FT-SVD infants compared to FT-CS at both 1 and 4 weeks of age (p < 0.001), but not at later time points. Parabacteroides were also significantly more abundant at 4 weeks of age in FT-SVD than FT-CS (p < 0.001). We also observed that PT-CS had a higher relative proportion of Bacteroides at 4 weeks of age compared to FT-CS. Clostridium sensu stricto is significantly more abundant in FT-CS when compared to FT-SVD at week 1 (p < 0.001). At this time point, it is also more abundant in PT-CS than PT-SVD (p < 0.01) but, as for Bacteroides, no differences were observed at the later time points.

We noted very little development of the FT-SVD microbiota composition at genus level throughout the 24 week period studied (Fig. 6, Additional file 1: Table S16). From week 1 to 4 to 8, no genus was found to be significantly altered in relative proportion. From week 8 to week 24, only Blautia (p < 0.05), and Subdoligranulum (p < 0.01; representing a very low proportion of the overall microbiota composition) were found to significantly change in abundance. Contrastingly, there were 12 and 16 genera that showed significantly altered relative proportions between week 1 and week 4 for FT-CS (Additional file 1: Table S14) and PT-CS (Additional file 1: Table S15) respectively, indicating a high level of microbiota change in the early life of these infants. Sampling of subsequent time points does not demonstrate this level of compositional change indicating a stabilisation of the infant gut microbiota. The statistical analysis of PT-SVD gut microbiota development was hindered by low subject numbers, but notwithstanding this limitation, we observed a number of significant changes between week 8 and week 24, with relatively few changes at earlier time points (Additional file 1: Table S17).

Co-abundance analysis is a useful way to reveal higher-level constraints and associations in microbiota composition [32]. We therefore examined the relationship between abundances of genera. Given that many genera appeared or increased in abundance over the time period assessed within this study we expected numerous positive correlations. We therefore tested whether any genera were negatively correlated. Of 12,090 correlations tested, after adjusting for multiple testing, 16 were significant negative correlations (Additional file 1: Table S18). Fourteen of these significant negative correlations involved Bifidobacterium.

Diversity of the gut microbiota increases with age

Alpha diversity is a measure of the overall diversity of the community present in a sample. The alpha diversity of the infant gut microbiota was shown to be influenced by age and birth mode (Fig. 7). As measured by the Shannon index, α-diversity increases as the infant ages. However, the microbiota diversity in each group did not increase equally over the first 24 weeks of life (Fig. 7, Additional file 5: Figure S3). We observed that the groups have a different diversity relative to each other at week 24 when compared to week 1. At 1 week of age, the FT-SVD microbiota displays the highest diversity of all groups, while PT-SVD is lowest. Diversity of all four groups increases from week 1 to week 4. FT-SVD increases in diversity between 1 and 4 weeks of age (p < 0.001); then diversity reduces slightly between week 4 and week 8 (p < 0.001); before increasing again between week 8 and 24 (p < 0.001). PT-CS diversity increased from weeks 1 to 4 (p < 0.001); 4 to 8 (p < 0.001); and showed a trend toward an increase from week 8 to 24 (p < 0.1). FT-CS increased from weeks 1 to 4 (p < 0.001) and weeks 8 to 24 (p < 0.01) but not between weeks 4 and 8. The overall increase in bacterial diversity is comparable in both FT groups. PT-SVD infants microbial diversity increased between week 1 and 4 (p < 0.001) and then appears to stabilise, with no further significant increase at 24 weeks. By week 24, there are no significant differences in alpha diversity between any groups, but a trend can be observed for higher diversity in FT-CS over PT-SVD, suggesting that infants of different birth modes and term have reached an equivalent diversity state at this age.

Fig. 7 Shannon diversity of different groups of infant gut microbiota increases with age, demonstrated by separating subjects by both age and by birth mode. Significant differences between birth modes at a given time point were tested with a linear mixed effects model which adjusts for potential batch effect (sequencing run), and the age of the infants at the given time point. Comparing different time points for a given birth mode was performed with linear mixed effects models that adjust for the batch and the subjects Full size image

Correlation of bacterial culture and culture-independent data

To isolate representative strains of major taxa, we also performed bacterial culture on the infant faecal samples. Bifidobacterium and Lactobacillus bacterial populations in infant faeces were determined by plate counting (Fig. 8). We observed a significant correlation between the Bifidobacterium levels recorded by 16S analysis, and the colony forming unit (CFU) counts (ρ = 0.24; p value = 6.64e−07). Likewise, Lactobacillus counts correlated with 16S-based data (ρ = 0.21; p value = 1.96e−05).

Fig. 8 Count data showing the absolute levels of Bifidobacterium and Lactobacillus at all time points from 1 to 24 weeks of age for all four infant groups. Culture techniques were used to generate count data to verify the accuracy of the culture-independent sequencing data. Over 7000 strains of Bifidobacterium and Lactobacillus stocks were isolated and stocked in a biobank Full size image

To determine whether significant differences in Bifidobacterium or Lactobacillus counts were present between birth modes at a given time point, or between time points for a given birth mode, we applied the Wilcoxon rank sum test with Benjamini-Hochberg adjustment. Due to the high level of variation recorded, we only observed a trend for higher Bifidobacterium counts in FT-SVD over FT-CS at week 1 (Fig. 8). Bifidobacterium counts at week 1 were highest in FT-SVD (mean 7.45 log CFU/g) and lowest in PT-SVD infants (mean 2.57 log CFU/g). Bifidobacteria numbers increased across all groups from week 1 to week 4, while at week 8, counts were observed to stabilise. At week 24, numbers remained stable across all groups. Similarly, Lactobacillus was also most abundant in FT-SVD (mean 3.98 log CFU/g) and lowest in PT-CS infants (mean 1.12 log CFU/g) at week 1. Counts increased in all groups (except PT-SVD) from week 1 to week 4; from week 4 to week 8 counts were stable in the PT-CS, FT-CS and FT-SVD groups, while an increase was observed in PT-SVD infants.