Novel Genes and Metabolite Trends in Bifidobacterium longum subsp. infantis Bi-26 Metabolism of Human Milk Oligosaccharide 2'-fucosyllactose.
Bryan ZabelChristian Clement YdePaige RoosJørn MarcussenHenrik Max JensenKrista SalliJohanna HirvonenArthur C OuwehandWesley MorovicPublished in: Scientific reports (2019)
Human milk oligosaccharides (HMOs) function as prebiotics for beneficial bacteria in the developing gut, often dominated by Bifidobacterium spp. To understand the relationship between bifidobacteria utilizing HMOs and how the metabolites that are produced could affect the host, we analyzed the metabolism of HMO 2'-fucosyllactose (2'-FL) in Bifidobacterium longum subsp. infantis Bi-26. RNA-seq and metabolite analysis (NMR/GCMS) was performed on samples at early (A600 = 0.25), mid-log (0.5-0.7) and late-log phases (1.0-2.0) of growth. Transcriptomic analysis revealed many gene clusters including three novel ABC-type sugar transport clusters to be upregulated in Bi-26 involved in processing of 2'-FL along with metabolism of its monomers glucose, fucose and galactose. Metabolite data confirmed the production of formate, acetate, 1,2-propanediol, lactate and cleaving of fucose from 2'-FL. The formation of acetate, formate, and lactate showed how the cell uses metabolites during fermentation to produce higher levels of ATP (mid-log compared to other stages) or generate cofactors to balance redox. We concluded that 2'-FL metabolism is a complex process involving multiple gene clusters, that produce a more diverse metabolite profile compared to lactose. These results provide valuable insight on the mode-of-action of 2'-FL utilization by Bifidobacterium longum subsp. infantis Bi-26.
Keyphrases
- human milk
- low birth weight
- single cell
- rna seq
- genome wide
- preterm infants
- ms ms
- genome wide identification
- copy number
- preterm birth
- magnetic resonance
- cell therapy
- stem cells
- blood glucose
- blood pressure
- metabolic syndrome
- saccharomyces cerevisiae
- skeletal muscle
- type diabetes
- gene expression
- mass spectrometry
- data analysis
- genetic diversity