bioRxivMicrobiology
Breastmilk-promoted bifidobacteria produce aromatic lactic acids in the infant gut
M. F. Laursen, M. Sakanaka, N. von Burg, U. Mörbe, D. Andersen, J. M. Moll, C. T. Pekmez, A. Rivollier, K. F. Michaelsen, C. Molgaard, M. V. Lind, L. O. Dragsted, T. Katayama, H. L. Frandsen, A. M. Vinggaard, M. I. Bahl, S. Brix, W. Agace, T. R. Licht, H. M. Roager
Abstract
Breastfeeding profoundly shapes the infant gut microbiota, which is critical for early life immune development. However, few breastmilk-dependent microbial metabolites mediating host-microbiota interactions are currently known. We here demonstrate that breastmilk-promoted Bifidobacterium species convert aromatic amino acids (tryptophan, phenylalanine and tyrosine) into their respective aromatic lactic acids (indolelactate, phenyllactate and 4-hydroxyphenyllactate) via a previously unrecognised aromatic lactate dehydrogenase. By longitudinal profiling of the gut microbiota composition and metabolome of stool samples of infants obtained from birth until 6 months of age, we show that stool concentrations of aromatic lactic acids are determined by the abundance of human milk oligosaccharide degrading Bifidobacterium species containing the aromatic lactate dehydrogenase. We demonstrate that stool concentrations of Bifidobacterium-derived indolelactate, the most abundant aromatic lactic acid in vivo, are associated with the capacity of infant stool samples to activate the aryl hydrocarbon receptor (AhR), a receptor important for controlling intestinal homeostasis and immune responses. Finally, we show that indolelactate modulates ex vivo immune responses of human CD4+ T-cells and monocytes in a dose-dependent manner by acting as an agonist of both, the AhR and hydroxycarboxylic acid receptor 3 (HCAR3). Our findings reveal that breastmilk-promoted Bifidobacterium produce aromatic lactic acids in the gut of infants and suggest that these microbial metabolites may impact immune function in early life.
- organism: human
- assay: metabolomics
- research focus: host-pathogen & immune response
- approach: statistical model
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