Infant gut and breast milk have high levels of ARGs and MGEs

Infant gut microbiomes had higher abundances of ARGs and MGEs than the gut microbiomes of their mothers (p < 0.05, negative binomial generalized linear models (GLMs) and Tukey’s post hoc test) (Fig. 1c, d, Supplementary Tables 1&2). This was apparent even though the infants had not been exposed to antibiotics during their life. However, the diversity of the MGEs and ARGs did not significantly differ between the two groups despite that the taxonomic diversity was significantly lower in infants (p < 0.05, analysis of variance (ANOVA) and Tukey’s post hoc test, Fig. 1a, b and Supplementary Fig. 1, Supplementary Tables 3–6). The observation that infants have higher ARG abundances compared to adults has been made previously8, but similar studies on the MGE abundance in the infant gut have not been conducted.

Fig. 1 Simpson diversity of ARGs and MGEs and their relative sum abundances. a ARG diversity. b MGE diversity. c ARG sum relative abundances. d MGE sum relative abundances. The relative sum abundances are calculated per copy of 16S rRNA gene and normalized by gene lengths. Each colored point represents one sample. Predicted mean and standard error from the negative binomial GLM is drawn in black. Sample names are as follows: Inf_1M = 1-month-old infants, Inf_6M = 6-month-old infants, Mot_32W = mother fecal samples gestational week 32, Mot_1M = mother fecal samples one month postpartum, Milk_CL = colostrum or milk produced within 7 days after delivery, Milk_1M = milk 1 month postpartum. Each sample type has an n of 16. In boxplots a and b, the lower hinge represents 25% quantile, upper hinge 75% quantile and center line the median. Notches are calculated with the formula median ± 1.58 * interquartile range/sqrt(n). Negative binomial general linearized models (GLMs) were used to predict the means and standard errors (SEs) of the relative sum abundances in different sample types. The notches in c and d represent SEs and means are represented as black points Full size image

The relative abundances of ARGs were similar in breast milk and fecal samples from 6-month-old infants and mothers (p > 0.05, negative binomial GLMs and Tukey’s post hoc test, Fig. 1c and d, Supplementary Table 1). Breast milk had the lowest microbial diversity of all sample types (p < 0.05, (ANOVA) and Tukey’s post hoc test, Supplementary Fig. 1, Supplementary Tables 3&4). MGEs were significantly more abundant in breast milk than in mothers’ feces (p < 0.05, negative binomial GLMs and Tukey’s post hoc test, Fig. 1b, Supplementary Table 2). However, due to the lower sequencing depth in breast milk compared to feces, there is uncertainty in the exact estimates of both the relative abundance and diversity, which should be noted.

Principal coordinates analysis (PCoA) was done to cluster samples using relative abundance (Fig. 2, Supplementary Tables 6&7) and presence–absence data (Supplementary Fig. 2, Supplementary Tables 6&7) on the microbiomes, resistomes and MGEs. Breast milk harbored a microbial community, resistome and MGE profile distinct from the gut (ADONIS, Benjamini & Hochberg method adjusted p-value < 0.05, Fig. 2a–d and Supplementary Fig. 2, Supplementary Tables 7&8). Breast milk was overall more similar to the infant than maternal gut. We observed that infants and mothers had differences not only in their microbial community and resistome composition which have been observed previously7,8, but also in their MGE composition (ADONIS, Benjamini & Hochberg method adjusted p-value < 0.05, Fig. 2a–d and Supplementary Fig. 2, Supplementary Table 7). Characterization of the MGEs was enabled by using a custom MGE database (Materials and methods).

Fig. 2 PCoA of microbiomes, resistomes, and MGEs using relative abundance. a Species level taxonomic identification done based on single copy marker genes with Metaphlan244. b Taxonomic profiling based on 16S rRNA reads retrieved using Metaxa241. c Resistome profiles based on reads mapped against an ARG database and normalized to 16S rRNA gene reads and gene lengths. d MGE profiles based on read mapping against a custom MGE database. Horn-Morisita similarity indexes were used to calculate between sample overlap for the ordinations. The confidence ellipses are drawn with confidence level of 0.90. Sample names are as follows: Inf_1M = 1-month-old infants, Inf_6M = 6-month-old infants, Mot_32W = mother fecal samples gestational week 32, Mot_1M = mother fecal samples 1 month postpartum, Milk_CL = colostrum or milk produced within 7 days after delivery, Milk_1M = milk 1 month postpartum. The significances and R2-values of differences between samples are represented in Supplementary Tables 6 and 7 Full size image

Differences in the resistome compositions between adults and infants and gut and breast milk were also seen in ARG and MGE classes (Fig. 3a, b). Tetracycline resistance genes were the most abundant resistance class in mothers’ feces and also prevalent in infants, which is typical for gut microbiota10,23,24. Interestingly, all resistance gene classes except tetracycline, MLSB (macrolide-lincosamide-streptogramin B) and trimethoprim resistance were more abundant in infants compared to mothers (negative binomial GLM, Tukey’s post hoc test, adjusted p-value < 0.05). The colistin resistance gene class including the pmr and mobile mcr gene families was among the 12 most abundant classes and abundant especially in infants. Nonetheless, we did not detect any mobile colistin resistance genes. Transposases constituted the most common MGE class in all samples (Fig. 3). The higher abundance of ARGs and MGEs including conjugative plasmids and transposons in the infant gut (Figs. 1c, d and 3a, b) indicates that there is a higher potential for antibiotic resistance and horizontal gene transfer than in the adult gut.

Fig. 3 Abundant bacteria, ARGs, and MGEs in breast milk and infants’ and mothers’ gut. a Most abundant resistance classes b Most abundant MGE classes. c Most abundant genera based on Metaphlan244 taxonomy profiling. d Most abundant classes based on Metaphlan244 taxonomy profiling. ARG and MGE sum abundances are normalized to 16S rRNA gene as in Fig. 1 and depicted on the y-axis in a and b. The mean relative abundances for taxa, expressed as percentages, are depicted on the y-axis in c and d. Sample names are as follows: Inf_1M = 1-month-old infants, Inf_6M = 6-month-old infants, Mot_32W = mother fecal samples gestational week 32, Mot_1M = mother fecal samples 1 month postpartum, Milk_CL = colostrum or milk produced within 7 days after delivery, Milk_1M = milk 1 month postpartum Full size image

Gammaproteobacteria and Bacilli were more common in infants than in mothers while mothers had more Clostridia, Bacteroides and Verrumicrobiae (Fig. 3d). On class level, Actinobacteria was most abundant in fecal samples and Bacilli in milk samples. The most abundant genus in feces of infants and mothers was Bifidobacterium and genus Streptococcus in breast milk (Fig. 3c). Genera which were significantly different (DESeq2, negative binomial GLMs, Wald’s test, p < 0.05) between infants and mothers and 1- and 6-month-old infants using DESeq225 analysis are depicted in Supplementary Fig. 3 and Supplementary Fig. 4.

Infant gut resistomes are linked to microbiome composition

The microbial community composition structured the resistome and MGE composition in the fecal microbiome of infants and mothers and in breast milk. The resistome, MGE and microbial community distance matrices correlated significantly with each other (Mantel’s test, cor ≥ 0.5 and p ≤ 0.001 for all pairwise correlations). The correlation between microbial community structure and ARGs suggests that the phylogenetic composition at least partially governs the resistome and mobilome composition in the gut microbiome of infants and mothers and in breast milk, similar to what has been seen in soil habitats26. Interestingly, there also seems to be an association between the microbial community and MGEs. However, MGEs did not show correlation patterns with any specific taxa on species, genus, and class levels (Supplementary Data 4).

On the other hand, strong correlations between taxa, such as Escherichia coli and Gammaproteobacteria, and the total sum of ARG abundances were observed in the infants at both 1 and 6 months of age (negative binomial GLMs, Benjamini & Hochberg method adjusted p-value < 0.05, Supplementary Data 4). E. coli best predicted the ARG abundances in infants (model validation with χ2-test p < 0.05, negative binomial GLM, estimate = 0.062, p = 6.87e−07). This confirms the existing hypothesis that Gammaproteobacteria contribute to high resistance load in infants7,11 and most likely harbor the majority of the most abundant ARGs. Infants had more Gammaproteobacteria, including E. coli, than the mothers (Fig. 3 and Supplementary Fig. 1). Gammaproteobacteria and Enterobacteriaceae blooms have been linked to increased rates of horizontal gene transfer between opportunistic pathogens and commensals during states of gut microbiota dysbiosis27, suggesting that there might be elevated rates of gene transfer in the infant gut with high abundances of Enterobacteriaceae. This could further promote the spread of ARGs in the infant gut. However, breastfeeding might be beneficial in reducing the ARG load, as breast milk has been shown to decrease the abundance of Enterobacteriaceae and E. coli in the infant gut28,29.

Despite the fact that breast milk had similar total relative abundances of ARGs to fecal samples, the abundant taxa in breast milk samples were negatively correlated with the total relative ARG abundances in infants (negative binomial GLMs, Benjamini & Hochberg method adjusted p-value < 0.05, Supplementary Data 4). We observed that of all the genera, Bifidobacterium had the strongest negative correlation with ARG abundance in infants (Supplementary Data 4). Bifidobacterium was too rare to detect in the breast milk samples using metagenomics. Previous studies using 16S rRNA gene amplicon sequencing, which enables more sensitive characterization of taxonomic information, have reported that the abundance of Bifidobacterium in breast milk ranges from undetectable to 1.3%15,30,31. Even though Bidifobacterium is a minor member of the breast milk microbial community, the abundance of this genus increases in the infant gut as a consequence of breastfeeding and human milk oligosaccharides14 and it was the most dominant genus in the infant gut (Fig. 3c). Our results indicate that colonization by Bifidobacterium might be beneficial for reducing the resistance gene load in the infant gut.

Infants’ ARGs and MGEs resemble those of their mothers

Infants shared 40% of their ARG and 37% of their MGE types in their guts with their mothers and correspondingly, 20 and 12% with breast milk (Supplementary Fig. 5). Of the ARGs detected in breast milk, 70 and 46% overlapped between infant and maternal gut, respectively. It is likely that some of the genes shared between breast milk and infant gut are directly transferred via breastfeeding to the gut by shared species, as 76% of the species found in breast milk were also detected in the infant gut. This indicates that while several genes are common between mothers and infants, some ARGs and MGEs might be acquired by the infant from other maternal body sites such as the skin and mouth or from the urogenital tract. Some of the bacteria are likely also acquired from non-maternal sources as has been suggested previously8.

The infant gut microbial community, resistome and MGE compositions were significantly more similar to each infant’s own mother’s gut microbiota than to unrelated women (ANOVA, family, p < 0.05, Fig. 4a–f for microbiota, resistomes, and MGEs, respectively). The results indicate similarity of microbial community composition, ARGs and MGEs between related mothers and infants. Previous studies have not been able to pinpoint that infants share significantly more ARGs with their mothers than with unrelated adults possibly due to small set of subjects or methodological challenges8,12. Our results suggest that maternal ARGs and MGEs have significant effects on the resistome and MGE composition of the infant gut and that there likely is transfer of some of these genes between mothers and infants.

Fig. 4 Dissimilarities of infant and mothers’ gut microbiota, resistomes, and MGEs. a Dissimilarity of microbial community on species level between infants and mothers using Metaphlan244 species classifications. b Dissimilarity of microbial communities in infants and mothers using DNA sequence profiles calculated based on kmer profiles. c Dissimilarity of resistomes between infants and mothers using gene type annotations. d Dissimilarity between resistomes using DNA sequence profiles of genes calculated based on kmer profiles. e Dissimilarity of MGEs between infants and mothers using gene type annotations. f Dissimilarity between MGEs using DNA sequence profiles of genes calculated based on kmer profiles. Dissimilarities between related and unrelated infant-mother pairs were compared. Type notion indicates that mothers and infants are significantly different from each other, family indicates that infant’s feces are more similar to mother’s feces than to that of unrelated women, same type vs. same family indicates that infants are more similar to each other than to their own mothers. Significance of differences was tested using ANOVA between the similarity indexes in the comparisons and p-values < 0.05 are indicated in the figures. The density plot depicts where comparisons between sample pairs are located on the dissimilarity scale. The higher the density is at a given dissimilarity, the more pairwise comparisons have the given dissimilarity value. Density of the samples is plotted on the y-axis and the x-axis depicts the between sample Jaccard similarity index of species, ARGs and MGEs shared between sample types using presence–absence data or DNA sequence profiles based on kmers calculated with sourmash56. DNA sequence profiles provide a way to compare DNA sequence signatures of samples with each other and does not rely on species or gene annotations. The x-axis ranges from 0 (no dissimilarity, i.e., completely similar) to 1 (complete dissimilarity) Full size image

When we compared the infant gut to breast milk, we observed that the infant gut MGE type and DNA sequence profile compositions were more similar to those of each infant’s own mother’s breast milk than to milk from unrelated mothers (ANOVA, family, p < 0.05, Fig. 5e, f), indicating that MGEs are shared between mothers and infants also via breast milk. Correspondingly, the mothers’ breast milk MGE DNA sequence profiles were more similar to DNA profiles of the mother’s own feces than to the fecal DNA profiles of other mothers (ANOVA, individual, p < 0.05, Supplementary Fig. 6). The similarities of MGEs in the gut and breast milk of related mothers and infants (ANOVA, family, p < 0.05, Fig. 5e, f) and breast milk and feces from the same mother (ANOVA, individual, p < 0.05, Supplementary Fig. 6) were observed despite the vastly different conditions in gut and breast milk. Interestingly, the sharing of MGE types and nucleotide profiles between gut and breast milk was not reflected in the taxonomic compositions and resistomes (ANOVA, family, p > 0.05, Fig. 5a–d and individual, ANOVA, p > 0.05 Supplementary Fig. 6d, e). However, this might be due to limitations in the sequencing of breast milk microbial DNA resulting in a lower sequencing depth, making it more difficult to observe sharing of low-abundant species and genes.

Fig. 5 Dissimilarities of infant gut and breast milk microbiota, resistomes, and MGEs. a Dissimilarity of microbial communities using Metaxa245 taxonomy profiles based on 16S rRNA genes between breast milk and infant feces. b Dissimilarity of microbial communities in infants and breast milk using DNA sequence profiles calculated based on kmers. c Dissimilarity of resistomes of breast milk and infant’s feces. d Similarity of resistomes between breast milk and mother’s feces. e Dissimilarity of MGEs between breast milk and infants’ feces. f Dissimilarity of MGEs between breast milk and mothers’ feces. Dissimilarities between related and unrelated infant-mother pairs were compared. Notion type indicates that breast milk and feces are significantly different from each other, family indicates that mother’s breast milk is more similar to related infant’s feces than to unrelated infant’s feces, type vs. family indicates that breast milk samples are more similar to each other than to feces samples from the infant from the same family, family vs. type indicates that breast milk and feces samples are more similar to samples from family members than to a sample of the same type. Significance of differences was tested using ANOVA between the similarity indexes in the comparisons and p-values < 0.05 are indicated in the figures. The density plot depicts where comparisons between sample pairs are located on the dissimilarity scale. The higher the density is at a given dissimilarity, the more pairwise comparisons have the given dissimilarity value. Density of the samples is plotted on the y-axis and the x-axis depicts the between sample Jaccard dissimilarity index of species, ARGs and MGEs shared between sample types using presence–absence data or DNA sequence profiles based on kmers calculated with sourmash56. DNA sequence profiles provide a way to compare DNA sequence signatures of samples with each other and does not rely on species or gene annotations. The x-axis ranges from 0 (no dissimilarity) to 1 (complete dissimilarity) Full size image

Overall, the infant microbial communities, resistomes and MGEs on species and gene type level were more similar to other infants than to those of their mothers (ANOVA, same type vs. same family, p < 0.05, Fig. 4a, c, e). This is likely due to differences in the gut environmental conditions between infants and their mothers being reflected in the microbiome and, by consequence, also the resistome, as it seems that phylogeny is a major determinant of the gut resistome. However, on DNA sequence profile level, the infant total microbial communities were significantly more similar to their own mothers than to other infants (ANOVA, same family vs. same type, p < 0.05, Fig. 4b). This result suggests that the signature of microbial strains transmitted from mothers is more pronounced than the signature related to infancy or adulthood, despite there being differences in the microbial community composition between infants and mothers (ANOVA, type, p < 0.05, Fig. 4a, b).

We observed that there were no significant differences in the similarity of infants and their mothers in their microbial community, resistome or MGEs in relation to sampling time overlap versus different sampling times (ANOVA, p > 0.05, Supplementary Fig. 7) suggesting that the familial signature is stable for several months. This might be the result of a constant transmission between family members or due to stabilization of strains and genes in the infant gut. Correspondingly, the infant microbial community, resistome and MGE compositions were significantly more similar to their own than to an infant of the same age (ANOVA, p < 0.05, Supplementary Fig. 6) suggesting that the signature of each infant is more pronounced than the signature related to the infant’s age. The results indicate that the transmission signature of each family or individual, which was observed in the microbiomes, resistomes, and MGEs, is persistent.

Since half of the mothers received IAP antibiotics, we investigated whether the antibiotics had an effect on how similar the mothers’ and infants’ microbiomes, resistomes, and MGEs were. We did not observe any differences in similarities between related infants and mothers in microbial communities, ARGs, and MGEs based on antibiotic treatment (Supplementary Fig. 8). However, IAP group’s mothers and infants shared significantly less species than the control group (ANOVA, p < 0.05, Supplementary Fig. 8).

IAP and terminating breastfeeding increase ARGs and MGEs

We studied the possible contribution of breastfeeding duration and intrapartum antibiotic prophylaxis (IAP) on the development of the infant gut microbiome, resistome, and MGEs. Termination of all breastfeeding before 6 months of age, which is the recommended duration of exclusive breastfeeding according to the World Health Organization32, was associated with an enrichment of several ARGs and MGEs in infants (negative binomial GLMs, Wald’s test, DESeq2, adjusted p-value < 0.05, Fig. 6a, b), while no significant differences in the taxonomic composition or total relative sum abundance of ARGs and MGEs were detected. The enriched genes included genes conferring resistance to aminoglycoside, sulphonamide, and tetracycline as well as integrases, plasmid markers, and transposases (Fig. 6a, b, negative binomial GLMs, Wald’s test, DESeq2, adjusted p-value < 0.05). The results suggest that early termination of breastfeeding might have negative health effects for infants due to an increased resistance potential of the gut microbiota against certain antibiotics, and, thus, increasing the likelihood of selecting for antibiotic resistant opportunistic pathogens able to cause infections under the right circumstances.

Fig. 6 Differentially abundant ARGs and MGEs in 6-month-old infants. a MGEs differentially abundant due to breastfeeding in 6-month-old infants compared to non-breastfed infants. b ARGs differentially abundant in breastfed infants at 6 months, c ARGs differentially abundant in 1-month-old infants due to IAP. d ARGs differentially abundant in 6-month-old infants due to IAP. e MGEs differentially abundant due to IAP in 1-month-old infants. f MGEs differentially abundant due to IAP in 6-month-old infants. Genes that have negative fold changes are more abundant in the non-breastfed and IAP groups. Sizes depict the number of samples each gene was found in (n = 1–10), color represents ARG or MGE class. The y-axis shows log2 fold changes and the x-axis denotes gene names Full size image

Antibiotic treatment of mothers during delivery (IAP) had a modest but statistically significant effect on the composition of the gut microbiota of 1-month-old infants (ADONIS, R2 = 0.13, p = 0.048), but not on the resistome or MGE composition. The abundance of horizontally transferrable ARGs and MGEs was significantly increased in the IAP group compared to the control group still 6 months after the antibiotic prophylaxis (negative binomial GLMs, p = 5.34e−03 and p = 1.34e−03, respectively). No significant changes were observed in the abundance of ARGs in the infants between the IAP and control groups or in the abundance and composition of the microbiome, ARGs and MGEs in probiotic and placebo groups. Infants in the IAP group also had a larger number of enriched ARGs and MGEs than infants in the control group (negative binomial GLMs, Wald’s test, DESeq2, adjusted p-value < 0.05, Fig. 6c–f). The effect of IAP on the infants persisted for 6 months, even though no significant trends for increase in the ARG or MGE loads were observed in the mothers.

Sharing of strains and MGEs containing ARGs

The presence of MGEs carrying ARGs shared among mother-infant pairs was investigated. All together 86 contigs containing an ARG and an MGE were assembled from the samples (Supplementary Data 5). Of those contigs, 26 contigs with the same arrangement of genes in the contigs were shared between a related mother-infant pair the most common contig being the Tn916 transposon with a tetM resistance gene. This suggests that the MGEs containing ARGs are shared between family members. Nearly all of the mobile ARG contig types were found in more than one infant-mother pair, indicating that the MGE types which could be assembled from the dataset are common in the gut and that the identified types are widely spread. However, the analysis was done based on gene annotations only, and cannot distinguish between nucleotide level variants of the genetic elements due to the technical challenge of short read assembly of low abundance genes in varying genetic contexts, such as ARGs from diverse environments33,34,35.

We studied whether mothers and infants shared strains of the species, which were linked to antibiotic resistance using Strainphlan50. E. coli was the only species which shared strains between the guts of infants and their mothers and the sharing was observed only in one mother-infant pair. This suggests that infants do not generally acquire the E. coli strains from their mother or that the maternal strains come from other body sites. The investigation of contigs revealed that several of the assembled mobile ARG containing contigs had their best taxonomic hit to Escherichia or Klebsiella (Supplementary Data 5), indicating that many ARGs carried by E. coli in the infant gut are mobile. It has been previously observed that Enterobacteriaceae in infants born in hospitals are likely to be acquired from the hospital environment22,36, which might partly explain the observed correlation of E. coli with high ARG abundance in the infant gut.