16S rRNA gene sequencing data from: Breastmilk IgG engages the neonatal immune system to instruct immune responses to gut antigens

Maternal antibodies fundamentally regulate gut immunity in the developing infant, yet the mechanisms underlying this process remain elusive. Here, we show that maternal IgG, ingested in the first week of life, restrains microbiota-dependent adaptive immune responses weeks later, following weaning. Antibodies are key regulators of gut microbiota diversity and composition, prompting us to explore whether alterations in microbiome assembly correlated with immune dysregulation in maternal antibody-deficient offspring. 16S rRNA gene sequencing of ileal and colonic contents did not reveal substantial differences in the diversity of microbes in each sample (alpha diversity) nor between-group distances (beta diversity) between age-matched offspring of µMT+/- or µMT-/- littermate dams and B6 sires. However, the abundance of a small subset of taxa differed significantly between p7 offspring of µMT+/- and µMT-/- dams, and this variation increased with age. Thus, the absence of all breastmilk antibodies correlates with minor alterations in the assembly of the postnatal microbiome. Analysis of p20 progeny of µMT-/- dams and B6 sires fed sIgG or BSA during the first week of life similarly failed to reveal significant differences in alpha or beta diversity as a function of feeding. Instead, litter was a driving factor. Indeed, the provision of IgG resulted in the differential abundance of only a single ileal taxon and two colonic taxa, which were distinct from those identified in p21 offspring of µMT+/- and µMT-/- dams. The similarity in microbiota community structure between IgG and BSA-fed littermates indicates that breastmilk IgG does not significantly alter the composition of the developing microbiome.

Methods
Amplification and MiSeq Illumina Sequencing of the V4 region of the 16S gene was performed by the Alkek Center for Metagenomics and Microbiome Research (CMMR) at Baylor College of Medicine. Reads were demultiplexed, trimmed and quality checked with bbduk. Paired-end reads were then merged using bbmap and run through the MaLiAmPi workflow to generate Amplicon Sequence Variants (ASVs) using DADA2. The Bayesian classifier Pplacer was used to estimate taxonomic classification of ASVs using phylogenetic placement with a likelihood cutoff of 90%. Alpha diversity estimates were generated by MaLiAmPi and Bray-Curtis dissimilarity was calculated using the R package vegan (v2.6-4) to determine beta diversity estimates. A pseudocount was applied prior to calculating differences in the relative abundance of taxonomic groups and ASVs with fewer than 10 reads across all samples were removed from the dataset. Differential abundance was determined using DESeq2, and data was normalized using the “poscounts” size estimator.