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Published in final edited form as: Parasite Immunol. 2020 May 3;42(9):e12721. doi: 10.1111/pim.12721

Preconception helminth infection alters offspring microbiota and immune subsets in a mouse model

Donald D Nyangahu 1,2,#,*, Matthew Darby 1, Enock Havyarimana 1, Bryan P Brown 3, William Horsnell 1,4, Heather B Jaspan 1,2,3,*
PMCID: PMC7423732  NIHMSID: NIHMS1591001  PMID: 32277499

Abstract

AIMS

Both maternal microbiota and helminth infection may alter offspring immunity but the relationship between these is underexplored. We hypothesized that maternal helminth exposure prior to pregnancy has lasting consequences on offspring intestinal microbiota and consequent immunity.

METHODS

Female BALB/c adult mice were infected with 500L3 Nippostrongylus brasiliensis (N.b). Infection was cleared by Ivermectin treatment and mice mated three weeks post infection (NbM). Control mice were not infected but were exposed to Ivermectin (NvM). We analyzed maternal gut microbiota during pregnancy, breastmilk microbiota as well as offspring fecal microbiota and immunity two weeks after delivery.

RESULTS

During pregnancy, NbM displayed significantly altered stool bacterial communities (R2=0.242; p=0.001), with increased abundance of Enterococcaceae versus NvM. Similarly, we observed a profound impact on breastmilk microbiota in NbM vs NvM. Moreover, NbM pups showed significantly altered gut microbial communities at 14 days of age versus those born to NvM with increased relative abundance of Coriobacteriaceae and Micrococcaceae. These changes were associated with alterations in pup immunity including increased frequencies and numbers of activated CD4 T cells (CD4+CD44hi) in NbM offspring spleens.

CONCLUSIONS

Taken together, we show that preconception helminth infections impact offspring immunity possibly through alteration of maternal and offspring microbiota.

Background

Various factors influence gut colonisation in infants, most of which are maternally-derived (Mulligan & Friedman, 2017; Tanaka & Nakayama, 2017). Maternal health status impacts offspring microbiome, for example, diversified meconium microbiota has been reported among neonates born to diabetic mothers (Hu et al., 2013). Intestinal helminths infect an estimated two billion people worldwide (Woodburn et al., 2009) and increased susceptibility to helminth infections during pregnancy has been reported (Yatich et al., 2009). Maternal helminth infection is known to alter offspring immunity. In some instances, infants born to helminth infected mothers have diminished humoral responses to vaccination (Malhotra et al., 2015; Ondigo et al., 2018). On the other hand, maternal helminth infection can protect offspring from atopic disease (Straubinger et al., 2014) and asthma (Zaiss et al., 2015) in rodent models. Indeed albendazole treatment during pregnancy increases the risk of eczema in human infants (Mpairwe et al., 2011).

Intestinal helminths have been shown to impact the gut microbiome (Gaze et al., 2012; Reynolds et al., 2014; Walk et al., 2010). Complex interactions occur between gut microbiota and helminths which result in profound effects on host immunity, including changes in host ability to control parasitic infection (Holzscheiter et al., 2014), susceptibility to autoimmune disease (Girgis et al., 2013; Hayes et al., 2010) and restoration of mucosal barrier function (Broadhurst et al., 2012).

Postnatally, diet is likely the greatest determinant of infant gut microbiota (Mackie, Sghir, & Gaskins, 1999; Pannaraj et al., 2017). Breast milk provides the first source of postnatal nutrition in infants and may lead to transfer of bacteria and/ or human milk oligosaccharides, which are thought to be key in development of intestinal immune homeostasis (Beattie & Weaver, 2011; Pannaraj et al., 2017). Furthermore, breast milk helps to shape immune development in infants, such as via transfer of tolerance-inducing antigens that lead to protection against asthma (Verhasselt et al., 2008). We recently showed that preconception helminth infection leads to long lasting helminth immunity in offspring which is transferred during nursing (Darby et al., 2019). Interestingly, the protection was driven by transferred pathogen-specific CD4 T cells and not maternal immunoglobulin (Darby et al., 2019). Whether an altered maternal microbiota could play an additional role in immune education in offspring is unexplored. In the present study, we investigated the effects of preconception maternal helminth infections on offspring using a mouse model of Nippostrongylus brasiliensis (N.b). Specifically, we examined the impact of preconception helminth infection on maternal gut and breast milk microbiota and infant microbiota and immunity. We hypothesized that, at least in part, the influence of helminth infection on the composition of the maternal microbiome influences the developing infant gut bacterial composition and immunity.

Materials and methods

Ethics statement

All animal experiments were carried out in strict accordance with protocol 012/054 approved by the Faculty of Health Sciences Animal Ethics Committee from the University of Cape Town.

Mouse experimental design

BALB/c mice were kept under specific pathogen free conditions (light/dark cycles of 12h) in ventilated cages equipped with standard bedding, filter tops, environmental enrichment and fed standard diet and autoclaved water ad libitum.

Female BALB/c mice were injected with 500 L3 N. b larvae subcutaneously in 200μl of 0.9% NaCl using a 21G needle ensuring the larvae were in suspension at the time the syringe was filled. The infection was then treated after 7 days with Ivermectin (10mg/ml) in drinking water for 7 days. One week after Ivermectin treatment (three weeks post N.b infection), mice were mated. Mice that were previously infected with N.b are designated as NbM while the control dams are NvM.

For mating, ten nine-week-old female mice were used per experiment. For breeding, two dams were housed in a single cage with a male for seven days after which the male was removed. Control BALB/c mice were not infected but were treated with ivermectin and mated simultaneously alongside the previously infected (PI) mice. Pregnant dams were separated into individual cages prior to delivery. Maternal fecal samples for microbiome analysis were collected between day 15 and 19 of gestation from the individually housed pregnant dams.

Females gave birth approximately 21 days post fertilisation and the pups were culled to 4–5 pups per mother and monitored daily for 14 days. We used pups from a single mother (4–5) per group per experiment. For litter swap experiments, pups born to NvM dams were swapped to be fostered by NbM dams and vice versa three days after delivery (3 pups per group). All experiments were repeated with different mothers (from a different litter) and their litters (3–5 pups) and results analysed together. Pups were sacrificed by cervical dislocation after inhalation of halothane at day 14 of age. Pups born to NbM are designated as NbM pups while those born to NvM are NvM pups. Pups born to NbM dams but nursed by NvM mothers are designated as NbMNvM pups while those born to NvM dams and nursed by NbM mothers are designated NvMNbM pups. Fecal samples were collected from pups’ colons and breast milk samples from pups’ stomachs for microbiome analysis at necropsy. Spleens were collected for immune analysis. All animal experiments were performed in accordance with protocols approved by the Institutional animal ethics committee, University of Cape Town.

Sample preparation and DNA extraction

Fecal samples from the cage (mothers) and colons (pups), and breast milk from the pups stomach were collected and stored at −20° C. 1 ml of sterile PBS was added to the breast milk pellet and homogenized. Samples were then spun at 3500rpm for 10 minutes and the aqueous phase isolated. This was used for downstream DNA extraction. We included an additional enzymatic lysis procedure (Yuan et al., 2012) before using the Powersoil Isolation Kit (Mo Bio Laboratories) for DNA extractions from both stool and breast milk. Briefly, 50μl lysozyme (10mg/ml, Sigma-Aldrich), 6μl mutanolysin (25KU/ml, Sigma-Aldrich), and 3μl lysostaphin (4000U/ml, Sigma-Aldrich) were added to 100μl aliquot of cell suspension followed by incubation for 1 hour at 37° C. The lysate was then subjected to further DNA isolation and purification using the Powersoil DNA Isolation Kit (Mo Bio Laboratories) as per the manufacturers instructions. The final DNA concentration was determined by the Quanti-It picogreen dsDNA HS assay kit (Invitrogen, UK).

16S rRNA deep sequencing and analysis

Deep sequencing of the V6 hypervariable region of the 16S rRNA gene was performed on fecal and breast milk samples. Extracted DNA was used for library preparation as previously described (Arthur et al., 2012). Briefly, the hypervariable V6 region of the 16S rRNA gene was amplified via PCR in two steps: The first PCR added the Illumina paired-end sequencing adaptors alongside 4–6 nucleotide barcode sequence using modified 16SrDNA-V6 specific primers (Arthur et al., 2012). The second PCR added flow cell complementary primers at the 5’ end and Illumina paired-end sequencing adapters at the 3’ end (Arthur et al., 2012; Mottawea et al., 2016). The resulting PCR amplicons were purified using the Qiagen 96-well purification kit (Qiagen, CA), the amplicon concentration was determined using the Quanti-It dsDNA BR assay (Invitrogen, UK), and 50 ng from each reaction was pooled into a single tube. Pooled DNA was run on a 1.5% agarose gel and visualized, and the 330-bp band was carefully cut out of the gel and purified using a gel purification kit (Qiagen, CA). The final DNA concentration was determined and the library sequenced at the Centre for Applied Genomics at the Hospital for Sick Children in Toronto, Canada on the Illumina HiSeq 2000 platform with 100bp PE reads.

After demultiplexing the raw reads using in-house scripts based on respective sample barcodes, primers preceding the 16S rRNA amplicon reads were removed by cutadapt (default parameters) (Martin, 2011). Trimmed sequences were then imported into R and processed using the DADA2 (v1.12.1) pipeline (Callahan et al., 2016). Briefly, the pipeline performs quality check prior to data analysis. After quality check, the pipeline performs quality trimming and filtering, dereplicates sequences, learns errors rates, removes sequences potentially containing errors, merges paired-end reads, constructs amplicon sequence variant (ASV) abundance table, removes chimeric sequences and runs taxonomic assignment of ASV’s using Silva (v132 release) reference database (Quast et al., 2013). The pipeline detected 8.2% of all sequences as chimeric and were removed from the the dataset. Downstream analysis was then done using phyloseq (McMurdie & Holmes, 2013) and DeSeq2 (Love et al., 2014), alongside other R packages. Rarefaction plots for the ASV abundance dataset showed sufficient depth for sample comparison (Fig. S5, S6 & S7). Due to the compositional nature of microbiome data, data was normalized by centred log ratio (clr) prior to plotting the euclidean distance Principal Component Analysis and alpha diversity plots. Principal Component Analysis plots were tested using Permutational multivariate analysis of variance (PERMANOVA) and homogeneity of group dispersion (PERMDISP) (Anderson, 2017) while differences in microbial diversity was tested by the welch t-test. Network analysis was done using the plot_net function in phyloseq with default parameters. Differential abundance testing was done using DeSeq2; the log fold change was set to 0 and the p-value threshold at 0.05. Output p values are adjusted for multiple comparisons by Benjamini-Hochberg correction (Love et al., 2014) and adjusted p values less than 0.05 were considered statistically significant.

Cell and Tissue processing

Spleens were isolated aseptically and resuspended in Iscove’s Modified Eagle Medium (IMDM) (Invitrogen) supplemented with 10% heat inactivated fetal bovine serum (FBS) and 100U/ml penicillin G and 100μg/ml streptomycin. Single cell suspensions were achieved by passing spleens through a 40μm nylon cell strainer (Becton Dickson, NJ) using a 2ml syringe plunger. Cells were then spun at 1200rpm for five minutes, media discarded, and the red blood cells lysed. Cells were pelleted again and resuspended. Viability was determined by using trypan blue and cells counted using the Neubauer chamber. Cells were then reconstituted to a working concentration of 107 cells/ml for culture and flow cytometry.

Flow cytometry

Splenic lymphocytes were characterized by flow cytometry. Single cells were stained at 2 ×106 cells per well in a 96 well V bottomed plate with anti-CD3 Alexa 700 (BD, clone 500A2), anti-CD4 PerCPCy5.5 (BD, clone RM4–5), anti-CD19 PECy7 (BD, clone 6D5), anti-CD44 FITC (BD, clone IM7), anti-CD62L V450 (BD, clone MEL-14) and anti-FOXP3 APC (BD, clone MF23). 50μl of the antibody master mix prepared in MACS buffer was added per well in all staining procedures. Cells were acquired on an LSRII (Becton Dickinson) and analysed by FlowJo (Tree Star, Ashland) software.

Statistical analysis

Two way associations were explored using the Mann-Whitney test for non-parametric data. All statistical analysis were two tailed and p values less than 0.05 were considered statistically significant.

Results

Preconception helminth infections impact maternal gut microbiota during pregnancy

To investigate the impact of resolved preconception maternal helminth infections on gut composition during pregnancy, we collected fecal samples from pregnant NbM or NvM dams at day 16–19 of gestation for sequencing (Fig. 1A). After filtering and removal of nonbacterial sequences, there was an average of 273,392 reads per sample. Pregnant NbM showed a trend towards higher microbial diversity compared to pregnant NvM (Fig. 1B). We observed significant differences in clustering by PCA of Euclidean distances between Pregnant NbM vs NvM dams (R2=0.242, Adonis p=0.001, Fig. 1C). We also confirmed by the dispersion test that the significance was not as a result of within group differences but rather a difference in the clustering between the two experimental groups (permutest p = 0.079). Next, we tested differential abundance between the two groups by DESeq2 (Fig. 1D). At the order level, Sphingobacteriales, Bacillales and Burkholderiales were significantly enriched in pregnant NbM vs pregnant NvM (Fig. S1). At the family level, Sphingobacteriaceae, Aerococcaceae, Enterococcaceae and Alcaligenaceae were significantly more abundant in Pregnant NbM vs Pregnant NvM (adj p = 0.024, 0.008, 0.001 and 0.002 respectively, Fig. 1D). Prevotellaceae and Bacteroidaceae were at significantly lower abundance in Pregnant NbM vs NvM dams (adj p =0.006 and 0.008, Fig. 1D).

Figure 1: Preconception helminth infection impacts maternal microbiota during pregnancy.

Figure 1:

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(A) Experimental setup. Adult female mice were infected subcutaneously with 500L3 N. brasiliensis. Infection was cleared 7 days after by oral treatment with Ivermectin for 7 days. Mice were mated 3 weeks post-infection. Fecal samples were collected from dams 16 days after mating for microbiome analysis. (B) Shannon alpha diversity of maternal intestinal microbiota. (C) Principal Coordinate Analysis of maternal gut microbiota based on Euclidean metric. (D) Differentially abundant bacteria at order level. Results are combined from two independent experiments. n=3–4 mice per group per experiment

Although it has been shown that N. brasiliensis infection clears naturally from an immunocompetent host 9–10 days after inoculation (Finkelman et al., 1997), we confirmed this scenario in our model in a time course experiment. Consistent with published data, we did not detect any worms in the intestines of N.b infected mice by day 12 (Fig. S2A) and there were no eggs in stool by day 10 post-infection (Fig. S2B). Together, our data shows that resolved helminth infections prior to conception impact the gut microbial composition during pregnancy.

Preconception helminth infections impacts maternal breastmilk microbiota

We have previously shown that alterations in maternal gut microbiota during gestation have an influence on breastmilk microbiota (Nyangahu et al., 2018). We next asked whether the helminth-bacterial interactions in the gut could impact breastmilk microbiota. We collected breastmilk pellets from the stomachs of 14 day old pups, as previously described (Nyangahu et al., 2018), due to difficulty in obtaining breastmilk directly from the mother (Fig 2A). Pups are still only fed breastmilk at 14 days of age and are not yet coprophagic or feeding independently. A total of 132 taxa remained after filtering and merging at the lowest taxonomic annotation. We found no significant differences in alpha diversity between breastmilk microbiota from NbM vs NvM (Fig. 2B). However, we observed a significant difference in clustering by PCA analysis between breastmilk from NvM vs NbM dams (R2 = 0.216, p = 0.001, Fig. 2C). The difference was not as a result of dispersion within the group (permutest p = 0.62). Furthermore, we observed significant differences in composition of bacteria between NbM and NvM breastmilk. Differential abundance testing by DeSeq2 showed Pseudomonadaceae and Enterobacteriaceae to be significantly more abundant in breastmilk from NbM compared to breastmilk from NvM (Fig 2D, adj p =0.0047 and 4.1e-05 respectively). Aerococcaceae, Corynebacteriaceae and Bacillaceae were significantly less abundant in NbM vs NvM breastmilk (Fig 2D, adj p < 0.0001 for all comparisons). Overall, maternal helminth infection prior to pregnancy significantly impacted on extraintestinal microbiota and led to significant differences in breastmilk microbiota between the previously infected and uninfected dams.

Figure 2: Preconception helminth infections impacts breastmilk microbiota.

Figure 2:

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(A) Experimental setup. Adult female mice were infected subcutaneously with 500L3 N. brasiliensis. Infection was cleared 7 days after by oral treatment with Ivermectin for 7 days. Mice were mated 3 weeks post-infection. Breastmilk pellets were collected from pups’ stomachs at day 14 for microbiome analysis. (B) Shannon alpha diversity of breastmilk pellet microbiota. (C) Principal Coordinate Analysis of breastmilk microbiota based on Euclidean distance. (D) Differentially abundant bacteria at order level. Results are combined from two independent experiments. n=3–4 mothers used per group per experiment. Since samples were collected from pups stomach’s, 5 pups per group per experiment were used.

Helminth infections prior to pregnancy impact offspring intestinal microbiota.

Maternal infections have been shown to impact gut microbiota in infants (Bender et al., 2016), and maternal gut microbes are more persistent in the infant gut compared to microbes from other sources (Ferretti et al., 2018). We next asked whether previous helminth infections in dams impact gut microbiota in their offspring. At 14 days of age, before onset of coprophagy, we removed stools from the pup colons at sacrifice and compared stool microbiota in pups born to NbM versus pups to NvM. Samples had an average of 294,863 reads per sample after filtering, and 63 ASVs. Pups born to NbM had significantly higher alpha diversity compared to those born to NvM (p = 0.00503, Fig. 3A). There was significantly distinct clustering based on maternal helminth infection (R2=0.18, p=0.004, Fig. 3B). Moreover, NbM pups had significantly higher abundance of taxa in the family Erysipelotrichaceae, Coriobacteriaceae and Micrococcaceae compared to NvM pups (adj p = 0.0357, 0.0090 and 0.00071 respectively, Fig. 3D). Clostridiaceae and Enterobacteriaceae were significantly less abundant in NbM pups (adj p= 0.0061 and 0.0331, Fig. 3D).

Figure 3: Preconception helminth infections alters offspring gut microbiota.

Figure 3:

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(A) Experimental setup. Adult female mice were infected subcutaneously with 500L3 N. brasiliensis. Infection was cleared 7 days after by oral treatment with Ivermectin for 7 days. Mice were mated 3 weeks post-infection. Fecal pellets were collected from pups’ colons at day 14 for microbiome analysis. (B) Shannon alpha diversity of pups’ gut microbiota. (C) Principal Coordinate Analysis of pups’ intestinal microbiota by Euclidean distance. (D) Differential abundance of taxa at the Order level. Results are combined from two independent experiments. n=4–5 pups per group per experiment. *p<0.05, **p<0.01, ***p<0.001.

To test whether changes in offspring microbiota occurred in utero, while nursing or during both phases, we included litter swap experiments. Pups born to NbM mothers were swapped and fostered by NvM dams (NbMNvM pups) while those born to NvM mothers were swapped and fostered by NbM dams (NvMNbM pups). NbMNvM and NvMNbM pups clustered distinctly from each other. NvMNbM pups clustered amongst the NvM pups, but NbMNvM pup stool communities were distinct from NbM pups (Fig. 4A). Also, we observed significantly lower microbial diversity in both NvMNbM and NbMNvM pups vs NbM pups (p=0.0131 and 0.0001699 respectively; Fig. 4B). All pup gut microbiota was distinct when examined against breastmilk microbiota by PCoA (Fig. S3A). We found no evidence of association by network analysis between pup gut and breastmilk microbiota regardless of infection status (Fig. S3B). As expected, the maternal gut microbiota, breastmilk microbiota and offspring gut microbiota clustered distinctly based on site (Fig. S3A). Together, these data show that changes in offspring gut microbiota begin in utero and continue during breastfeeding, but that there is not a direct transfer of microbes between breastmilk and offspring gut.

Figure 4: Microbiota programming in pups begins in utero and continues during nursing.

Figure 4:

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Litter swap experiments where pups born to naïve mothers were fostered by previously infected mothers (NvMNbM pups) and vice versa (NbMNvM pups) beginning 3 days after delivery, and their stool microbiota compared with that of pup groups that were not swapped (NvM and NbM pups). (A) Principal Component Analysis by Euclidean distance of pup stool microbiota at day 14 of life. (B) Microbial diversity by Shannon metric. n= 3–5 per group per experiment. Data are combined from two independent experiments. *p<0.05, **p<0.01, ***p<0.001.

Preconception helminth infections impact offspring immunity

Next, we asked whether previous helminth infection of dams impacts inherent offspring immunity. We analyzed immune subsets in the spleens of NbM pups versus NvM pups at 14 days postpartum. Pups born to NbM had significantly higher splenic cell counts versus pups born from NvM (Fig. 5A). We used flow cytometry to characterize immune subsets in the spleen (Gating strategy, Fig. S4). We observed significantly higher frequencies and numbers of total activated CD4 T cells (CD4+CD44hi) in NbM pups (Figs. 5B, C). While there was no difference in B cell frequency, total numbers of B cells were significantly elevated in NbM pups compared to NvM pups (Figs. 5D, E). Similarly, we found no difference in frequencies of T regulatory cells but cell numbers were significantly higher in NbM pups (Figs. 5F, G).

Figure 5: Preconception helminth infections impacts offspring inherent immunity.

Figure 5:

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Splenicimmunity was analyzed at 14 days in NvM or NbM pups. (A) Total cell count in spleen. (B-C) Frequency and numbers of total activated CD4 T cells (CD4+CD44hi). (D-E) Frequency andnumbers of B cells (CD19+B220+) (F-G) Frequency and numbers of T regulatory cells(CD4+FOXP3+). (H) Differentially abundant taxa in high vs low groups. Binarization was donearound the median frequency of total activated CD4 T cells. Results representative of twoindependent experiments. n=6–7 pups per group. *p<0.05, **p<0.01, ***p<0.001.

To assess the association between the microbiota at day 14 in pups and immunity in the corresponding pups, we binarized the CD4+CD44hi frequencies into high or low around the median frequency. Most of the samples making up the “low” category were those from NvM pups and vice versa (Table S1). We used DeSeq2 to determine differentially abundant bacteria between the high vs low groups. Coprobacter, Clostridium_IV and Gordonibacter were significantly differentially abundant in the high category vs low (adj p =0.00013, 0.0334 and 0.0334 respectively). Taken together, our data shows that preconception helminth infections impact offspring intestinal microbiota which may in turn influence offspring developing immunity.

Discussion

The gut microbiota plays a significant role in health, including the development and maturation of the immune system (Round & Mazmanian, 2009; Round & Palm, 2018). Some pathogens, for example helminths, inhabit the same niche as our gut microbiota, thereby possibly impacting gut composition. Indeed helminths have been shown to alter microbiota in both murine models (Rausch et al., 2013; Walk et al., 2010) and humans (Cooper et al., 2013; Giacomin et al., 2015; Lee et al., 2014). Moreover, altered microbiota can be sufficient to modulate host susceptibility to disease, for example to allergic asthma (Zaiss et al., 2015).

Here, we investigated the impact of preconception helminth infection on maternal gut and breastmilk microbiota and its effect on offspring intestinal microbiota and immunity. We showed that N.b-induced changes in gut microbiota three weeks prior to mating persist during pregnancy. In addition, we found that resolved helminth infections prior to pregnancy impacted bacterial communities in maternal breastmilk. However, since breastmilk was collected from pups’ stomach, we cannot rule out the possibility of its contamination with gastric contents; thus the breastmilk data should be interpreted with caution. Importantly, most prior studies have examined the impact of active helminth infections on gut microbiota, while here, we studied the effects of a cleared helminth infection. Host treatment with Ivermectin clears the helminth infection, yet the consequences of the infection on the gut bacterial composition persisted long past clearance of the pathogen. Our results of an altered gut microbiota in previously infected dams even after the parasite has cleared from the host are consistent with the findings of a recent human study in Kenya (Easton et al., 2019). Following Albendazole therapy and clearance of soil-transmitted helminths, there were significant increases in proportion of the microbiota made up of Clostridiales and reduction in Enterobacteriales (Easton et al., 2019). Similarly, in mice 11 days post N.b infection, when the worm has naturally cleared, changes in microbiota were still evident (Fricke et al., 2015). Fricke et al. observed increased relative abundance of Lactobacillaceae and Coriobacteriacea and reduced Clostridiaceae (Fricke et al., 2015). We report increased abundance of Sphingobacteriaceae, Alcaligenaceae and Enterococcaceae in stool and increased abundance of Enterobacteriaceae in breastmilk. These differences could be due to the fact that we analyzed microbiota during pregnancy while Fricke and colleagues characterized microbiota in non-pregnant dams. Moreover, the same authors observed that N. brasiliensis infection led to a reduction in the abundance of segmented filamentous bacteria (SFB). We did not detect the SFB bacteria in either our control and experimental mice. It is worth mentioning that Fricke et al. used SFB colonized mice in their experiments, our study used Jackson mice which are not colonized with SFB. NbM dams exhibited significantly reduced abundance of Prevotellaceae and Bacteroidaceae in their gut during pregnancy compared to NvM. However, Rausch et al. observed increased abundance of colonic Enterobacteriaceae, Bacteroides and Prevotella with no impact on Lactobacilli or Clostridia following infection of mice with Heligmosomoides polygyrus bakeri (H. p. bakeri) compared to uninfected controls. Microbial analysis was done 14 days post infection at the acute adult stage of the parasite (Rausch et al., 2013). Inconsistencies in results could be due to differences in the infecting helminth as well as the timing of microbiome analysis. Indeed, pregnancy has previously been associated with a changing gut microbiome (Koren et al., 2012). From the first trimester onwards to the third, the gut microbiota changes dramatically and is characterized by increased abundance of Actinobacteria and Proteobacteria in humans (Koren et al., 2012). The gut microbiota during pregnancy is influenced not only by internal host factors but also by external factors, mainly diet (Gohir et al., 2015). We also analyzed the microbiota after clearing the helminth infection while Rausch studied the microbiota during active helminth infection (acute adult stage of the parasite).

We also found that pups born to previously infected dams had altered intestinal microbiota. Maternal gut microbes have been shown to be more persistent in the infant gut compared to those from other sources (Ferretti et al., 2018). We observed significantly decreased abundance of Clostridiaceae and increased abundance of Erysipelotrichaceae and Coriobacteriaceae in NbM pups indicating that preconception helminth induced changes in microbiome are transferable. Interestingly, these same bacteria were significantly elevated in their mothers’ gut during pregnancy. This suggests that while maternal gut organisms are likely to be identified in her offspring intestinal microbiota, the trends in the offspring relative abundance may not always mirror the maternal gut.

In addition, we observed elevated total activated CD4 T cells as well as B cells in NbM pups suggesting that preconception helminth exposure impacts immune development possibly beginning in utero. Changes in gut microbiota during pregnancy may potentially impact transfer of microbiota and their byproducts at the maternal-fetal interface, via the placenta, or postpartum via breastfeeding (Nyangahu & Jaspan, 2019). Memory CD4 T cells in fetal intestines have been shown to colocalize with antigen presenting cells and produce IFN-γ, IL-2 or TNF-α promoting intestinal development (Li et al., 2019; Schreurs et al., 2019). These studies suggest immune programming might occur due to fetal meconium microbiota. On the other hand, we recently showed that NbM pups are protected against challenge and that protection was driven by maternal pathogen-specific T cells that were transferred during breastfeeding (Darby et al., 2019). Factors that could potentially influence the quality of protection conferred by breastmilk include the local microbiota.

We observed a significant impact of N.b exposure on community structure of breastmilk microbiota. Pseudomonadaceae and Enterobacteriaceae were significantly elevated in breastmilk from NbM dams while Corynebactericeae, Bacillaceae and Aerococcaceae were significantly less abundant in the same dams. Whether these changes in bacterial composition in breastmilk have any impact on offspring immune development is only speculative for now. There was no evidence of direct transfer of microbes from breastmilk to infant gut, but it is clear from the pup swap experiments that breastfeeding contributes to shaping of the infant gut microbiota.

In conclusion, we show for the first time that preconception N.b infections impact maternal gut microbiota and that helminth-induced changes in maternal microbiota may influence offspring microbiota and immune subsets. Our findings are relevant to infant immunity in helminth endemic settings.

Supplementary Material

Supp TableS1
Supp FIgS1-7

Acknowledgements

We thank the University of Cape Town ICTS high performance computing team: http://hpc.uct.ac.za for facilities that supported the bioinformatic analysis of this data.

The work presented here was supported in part by the National Institutes of Health (R01 AI120714-01A1 to H.B.J.), Poliomyelitis Research Foundation (15/16 to H.B.J), Carnegie Corporation of New York (to M.G.D.), Horizon 2020 (to W.G.C.H.), National Research Foundation (78912 to W.G.C.H. and 81578 to M.G.D.), Deutsche Forschungsgemeinschaft (LA 2746/2 to W.G.C.H.)

Footnotes

Data availability

Sequence Read Archive (SRA) accession number for the 16SrRNA sequences reported in this paper is PRJNA609138.

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