Abstract
The gut microbiota undergoes rapid changes during infancy in response to early-life exposures. We have investigated how the infant gut bacterial community matures over time and how exposures such as human milk and antibiotic treatment alter gut microbiota development. We used the LonGP program to create predictive models to determine the contribution of exposures on infant gut bacterial abundances from one month to two years of age. These models indicate that infant antibiotic use, human milk intake, maternal pre-pregnancy BMI, and sample shipping time were associated with changes in gut microbiome composition. In most infants, Bacteroides, Lachnospiraceae unclassified, Faecalibacterium, Akkermansia, and Phascolarctobacterium abundance increased rapidly after 6 months, while Escherichia, Bifidobacterium, Veillonella, and Streptococcus decreased in abundance over time. Individual, time-varying, random effects explained most of the variation in the LonGP models. Multivariate association with linear models (MaAsLin) displayed partial agreement with LonGP in the predicted trajectories over time and in relation to significant factors such as human milk intake. Multiple factors influence the dynamic changes in bacterial composition of the infant gut. Within-individual differences dominate the temporal variations in the infant gut microbiome, suggesting individual temporal variability is an important feature to consider in studies with a longitudinal sampling design.