Abstract
Immunoglobulin A (IgA), the major class of antibody secreted by the gut mucosa, is an important contributor to gut barrier function1,2,3. The repertoire of IgA bound to gut bacteria reflects both T-cell-dependent and -independent pathways4,5, plus glycans present on the antibody’s secretory component6. Human gut bacterial taxa targeted by IgA in the setting of barrier dysfunction are capable of producing intestinal pathology when isolated and transferred to gnotobiotic mice7,8. A complex reorientation of gut immunity occurs as infants transition from passively acquired IgA present in breast milk to host-derived IgA9,10,11. How IgA responses co-develop with assembly of the microbiota during this period remains poorly understood. Here, we (1) identify a set of age-discriminatory bacterial taxa whose representations define a program of microbiota assembly and maturation during the first 2 postnatal years that is shared across 40 healthy twin pairs in the USA; (2) describe a pattern of progression of gut mucosal IgA responses to bacterial members of the microbiota that is highly distinctive for family members (twin pairs) during the first several postnatal months then generalizes across pairs in the second year; and (3) assess the effects of zygosity, birth mode, and breast feeding. Age-associated differences in these IgA responses can be recapitulated in young germ-free mice, colonized with faecal microbiota obtained from two twin pairs at 6 and 18 months of age, and fed a sequence of human diets that simulate the transition from milk feeding to complementary foods. Most of these responses were robust to diet, suggesting that ‘intrinsic’ properties of community members play a dominant role in dictating IgA responses. The approach described can be used to define gut mucosal immune development in health and disease states and to help discover ways of repairing or preventing perturbations in this facet of host immunity.
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Acknowledgements
We thank D. O’Donnell, M. Karlsson, J. Serugo, and S. Wagoner for help with gnotobiotic husbandry; S. Deng, J. Guruge, J. Hoisington-Lopez and M. Meier for technical assistance; G. Dantas for help with maintaining our archive of de-identified human samples; and N. Griffin for comments about facets of the data analysis. This work was supported by grants from the National Institutes of Health (DK30292, DK052574), the Children’s Discovery Institute, the Bill & Melinda Gates Foundation, and the Crohn’s and Colitis Foundation of America. J.D.P. is a member of the Washington University Medical Scientist Training Program (National Institutes of Health GM007200).
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Contributions
B.B.W., P.I.T., M.I. and G.D. designed, enrolled and collected specimens from participants in the twin study. J.D.P. performed BugFACS and 16S rRNA analyses on human faecal samples. J.D.P. and J.I.G. designed the gnotobiotic mouse experiments; J.D.P. and Y.P. performed these experiments. J.D.P., A.L.K., L.V.B., Y.P., and J.I.G. analysed the data. J.D.P. and J.I.G. wrote the paper.
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J.I.G. is co-founder of Matatu, Inc., a company characterizing the role of diet-by-microbiota interactions in animal health. The other authors declare that they have no competing interests.
Additional information
16S rRNA sequences in raw format before post-processing and data analysis have been deposited at the European Nucleotide Archive under project PRJEB11697.
Extended data figures and tables
Extended Data Figure 1 Method used for OTU consolidation.
a, OTU consolidation was performed to limit pseudo-duplication of taxa. ‘Counts’ on the y axis refer to the number of OTU–OTU correlations falling within a given range of Spearman’s correlation values shown on the x axis (n = 341,640 OTU–OTU comparisons; see Methods for details). b, A subset of the matrix used to derive the distribution shown in a illustrates how OTUs within a single family-level taxon are consolidated. In this example, three clusters composed of OTUs with Spearman’s correlation coefficients of >0.7 are identified and the abundances of their constituent OTUs are summed. Each OTU cluster is assigned an identifier number with the prefix ‘C.’ and given a consensus taxonomic assignment (see Supplementary Table 5). Note that the OTUs used to generate a given ‘consolidated OTU’ shared 99.3 ± 0.4% (mean ± s.d.) nucleotide sequence identity in their V4-16S rRNA nucleotide sequences.
Extended Data Figure 2 Modelling development of the gut microbiota during the first 24 months of life in healthy twins.
a, To estimate the number of OTUs needed to maximize predictive accuracy, OTUs were iteratively added to a series of RF models, starting with the OTU with the highest feature importance score and adding additional OTUs in order of decreasing feature importance. To evaluate performance of the model, members of the 40 twin cohort were randomly assigned to ‘training’, ‘co-twin of training’, and ‘test’ sets (red, green, and blue, respectively) ten times, and the Spearman’s correlation coefficient and adjusted r2 of a linear model were calculated for a given model size (n = 10 models for each data point, mean ± s.e.m. values are plotted). The dashed vertical line indicates performance of a 25 OTU model across the three different sets. b, Predicted age was calculated for all faecal microbiota samples with a sparse 25 OTU RF-generated model. Chronological versus model-predicted age is plotted for each of the three data subsets (n = 1,477 faecal samples). The inset shows mean ± s.d. values for predicted microbiota age of samples in each monthly age bin. c, Heatmap of mean abundances over the first 24 months of life for the 25 OTUs used to generate the sparse model. Taxa are normalized by row, with hierarchical clustering (complete linkage; n = 1,477 faecal samples).
Extended Data Figure 3 Similarity of faecal microbiota composition within and between twin pairs.
Similarity in composition of the faecal microbiota within and between twin pairs was analysed with unweighted UniFrac distance calculated before OTU consolidation. Statistical significance was evaluated with the paired Wilcoxon test for twin–twin versus twin–unrelated comparisons. Mean values + s.e.m. are plotted (n = 205 paired comparisons). ***P < 0.001. The results indicate that the overall phylogenetic composition of the faecal microbiota is more similar in infants/children sharing a common living environment and genetic background than between unrelated individuals; this is apparent as early as the first month of life and does not change significantly over the ensuing 23 months.
Extended Data Figure 4 Feeding status and microbiota composition during the first year of life.
a, The proportion of all feedings on the day of faecal sampling that consisted of either formula or breast milk (n = 746 observations). b, Microbiota age, defined by the sparse RF-derived model, compared for participants that were predominantly breast fed (≥50% of milk feeding) or predominantly formula fed across different age bins. Mean values + s.e.m. are plotted (n = 681 faecal samples). *P < 0.05; **P < 0.01; ***P < 0.001 (Mann–Whitney U-test). c, Aggregate percentage relative abundance of age-discriminatory bifidobacteria included in the sparse RF-derived model; differences in their representation in the faecal microbiota as a function of breast or formula feeding evaluated in each age bin are shown. Horizontal lines within each column represent the median values; the horizontal dashed line represents the lower limit of detection. *P < 0.05; **P < 0.01; ***P < 0.001 (Mann–Whitney U-test comparing samples obtained from breast versus formula fed individuals; n = 681 faecal samples).
Extended Data Figure 5 Further characterization of IgA responses to members of the microbiota in the USA twin cohort.
a. Evidence that IgA indices are independent of relative abundance. IgA indices for all OTUs are plotted against their relative abundance in the ‘input fraction’ for all infant/child, maternal, and gnotobiotic mouse faecal samples analysed by BugFACS (n = 22,713 comparisons). b, Mean IgA indices ± s.e.m. for two OTUs whose IgA targeting varied significantly with age across all 80 individuals in the twin birth cohort (FDR-corrected Kruskal–Wallis test, P < 0.05). c, Variance of IgA indices as a function of age. A total of 26 OTUs were detected in at least two individuals in all of the age bins surveyed. The variance in their IgA indices was then calculated and the non-parametric repeated-measures Friedman test was used to test for statistical significance (P < 0.0001). Mean values + s.e.m. are plotted.
Extended Data Figure 6 Specificity of targeting and temporal variation in the prevalence of IgA-targeted or non-targeted taxa.
Specificity values from the indicator species analysis were calculated across all time points for the 30 OTUs identified as consistently IgA-targeted or non-targeted in Fig. 1a. Prevalence of the taxa, defined as detection in either the IgA+ or IgA− fraction, was plotted against the percentage of samples in which a given taxon had a positive or negative IgA index (n = 4,186 IgA index values analysed). The results reveal a group of OTUs that increased in prevalence over the course of the first 2 years of postnatal life and had very high ‘specificity’ for either the IgA+ or IgA− fraction (that is, across the population of faecal samples, most 16S rRNA reads for a given OTU were detected in one of the two fractions). This group included R. torques OTU C.6 and C. nexile OTU 4436046 that were IgA targeted in the majority of twins (when they are detectable in their microbiota), as well as Ruminococcus sp. ce2 OTU C.39 which was IgA− in most of the children. A second group of OTUs became more prevalent with age but members had a much weaker, albeit statistically significant, association with one or the other sorted fraction (for example, R. gnavus OTU C.4 and B. vulgatus OTU C.15). A third group of OTUs were highly specific for a given sorted fraction but were only detected in a minority (≤20%) of children. This last group included two strongly IgA-targeted OTUs assigned to A. muciniphila (OTU 588471 and OTU 4306262). Intriguingly, these two OTUs co-occurred just once among the 176 BugFACS samples in which A. muciniphila was detected (P < 0.0001, χ2 test).
Extended Data Figure 7 Effects of diet on gut mucosal IgA responses to members of the microbiota.
The analysis was constrained to those faecal samples where a diet history had been collected within 10 days of procuring the specimens (n = 276). After FDR correction with the Benjamini–Hochberg procedure, IgA targeting of 2 of the 30 taxa identified in Fig. 1a varied significantly as a function of breast versus formula feeding. Each circle represents results from a given faecal sample. Samples are colour-coded on the basis of the type of milk diet being consumed by the donor at the time of faecal sampling. Horizontal lines in each column represent mean values. *P < 0.05 (Mann–Whitney U-test of the differences between breast and formula fed).
Extended Data Figure 8 Diet-dependent changes in composition of the faecal microbiota of gnotobiotic mice.
Indicator species analysis was used to identify taxa from the RF-derived model of gut microbiota maturation whose abundances varied consistently by diet treatments (n = 9,999 permutations with ‘mouse’ as the grouping variable). The top 60 ranked OTUs in the model (on the basis of their feature importance scores) were included in the analysis; those OTUs with statistically significant diet-dependent partitioning (P < 0.05) after FDR correction and with an indicator value >0.5 are shown, ranked from highest to lowest indicator value for infant formula-discriminatory (upper portion of figure) and ‘infant formula plus fruits and vegetables’-discriminatory (lower portion of figure) (see Supplementary Table 19 for results of the indicator species analysis). Mean values for relative abundances in the faecal microbiota at each time point are plotted ± s.d.
Extended Data Figure 9 Similarity in IgA responses as a function of microbiota donor, twin pair, and time after transplantation.
Pearson’s correlation coefficients were calculated with IgA index data from all faecal samples collected from gnotobiotic mice that had been analysed by BugFACS. Mean values ± s.d. are shown for the indicated comparisons. ****P < 0.0001; **P < 0.01; *P < 0.05 (Kruskal–Wallis test with Dunn’s correction for multiple comparisons; n = 5,029 total comparisons).
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Planer, J., Peng, Y., Kau, A. et al. Development of the gut microbiota and mucosal IgA responses in twins and gnotobiotic mice. Nature 534, 263–266 (2016). https://doi.org/10.1038/nature17940
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DOI: https://doi.org/10.1038/nature17940
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