An in vitro analysis of how lactose modifies the gut microbiota structure and function of adults in a donor-independent manner

Front Nutr. 2023 Jan 26:9:1040744. doi: 10.3389/fnut.2022.1040744. eCollection 2022.

Abstract

Introduction: Following consumption of milk, lactose, a disaccharide of glucose and galactose, is hydrolyzed and absorbed in the upper gastrointestinal tract. However, hydrolysis and absorption are not always absolute, and some lactose will enter the colon where the gut microbiota is able to hydrolyze lactose and produce metabolic byproducts.

Methods: Here, the impact of lactose on the gut microbiota of healthy adults was examined, using a short-term, in vitro strategy where fecal samples harvested from 18 donors were cultured anaerobically with and without lactose. The data were compiled to identify donor-independent responses to lactose treatment.

Results and discussion: Metagenomic sequencing found that the addition of lactose decreased richness and evenness, while enhancing prevalence of the β-galactosidase gene. Taxonomically, lactose treatment decreased relative abundance of Bacteroidaceae and increased lactic acid bacteria, Lactobacillaceae, Enterococcaceae, and Streptococcaceae, and the probiotic Bifidobacterium. This corresponded with an increased abundance of the lactate utilizers, Veillonellaceae. These structural changes coincided with increased total short-chain fatty acids (SCFAs), specifically acetate, and lactate. These results demonstrated that lactose could mediate the gut microbiota of healthy adults in a donor-independent manner, consistent with other described prebiotics, and provided insight into how dietary milk consumption may promote human health through modifications of the gut microbiome.

Keywords: Bifidobacterium; gut microbiota; lactate; lactic acid bacteria (LAB); lactose-intolerance; milk.

Grants and funding

This work was supported by the in-house Project 8072-41000-108-00D, “In vitro Human Gut System: Interactions Between Diet, Food Processing, and Microbiota”. This research used resources provided by the SCINet project and the AI Center of Excellence of the USDA Agricultural Research Service, ARS project number 0500-00093-001-00-D.