The bifidogenic effect of 2 fucosyllactose is driven by age-specific bifidobacterium species, demonstrating age as an important factor for gut microbiome targeted precision medicine

Authors: Firrman, Jenni; DEYAERT, STEF - Cryptobiotix; Mahalak, Karley; Liu, Lin; BAUDOT, AURELIEN - Cryptobiotix; JOOSSENS, MARIE - Cryptobiotix; POPPE, JONAS - Cryptobiotix; CAMERON, SIMON - Queens University - United Kingdom; VAN DEN ABBEELE, PIETER - Cryptobiotix

Submitted to: Microbiome
Publication Type: Review Article
Publication Acceptance Date: 12/29/2024
Publication Date: 12/31/2024
Citation: Firrman, J., Deyaert, S., Mahalak, K.K., Liu, L.S., Baudot, A., Joossens, M., Poppe, J., Cameron, S., Van Den Abbeele, P. 2024. The bifidogenic effect of 2 fucosyllactose is driven by age-specific bifidobacterium species, demonstrating age as an important factor for gut microbiome targeted precision medicine. Microbiome. https://doi.org/10.3390/nu17010151.
DOI: https://doi.org/10.3390/nu17010151

Interpretive Summary: Each person has a large community of bacteria in their colon, known as the gut microbiota, that aids in digestion of food and release byproducts that can be used by the human cells. Different food components called prebiotics have been identified that serve as a source of food for the healthy bacteria and, therefore, enhance human health via the gut microbiota. However, as humans age their biology changes and so does the gut microbiota. These age-dependent changes may affect how prebiotics work, yet age is rarely considered in prebiotic studies. This gap in knowledge was addressed in this study by comparing the gut microbiota of humans from six age groups, spanning infancy to older adults. The results showed that the gut microbiota between age groups were very different, particularly between infants and toddlers and older age groups. Importantly, the gut microbiota from different age groups responded to prebiotic treatment in a unique manner, clearly showing that a person’s age affects the outcome of prebiotic treatment. In conclusion, the results of this study provided evidence that age is an important factor that needs to be considered when designing or testing prebiotic treatments.

Technical Abstract: Background: The human gut microbiota develops in concordance with its host over a lifetime, resulting in age-related shifts in community structure and metabolic function. Little is known about whether these changes impact the community’s response to microbiome-targeted therapeutics. Providing critical information on this subject, faecal microbiomes of subjects from six age groups, spanning from infancy to 70-year-old adults (n = 6 per age group) were harvested. The responses of these divergent communities to treatment with the human milk oligosaccharide 2’-fucosyllactose (2’FL), fructo-oligosaccharides (FOS) and lactose was investigated using the ex vivo SIFR® technology that employs bioreactor fermentation and is validated to be predictive of clinical findings. Additionally, it was evaluated whether combining faecal microbiomes of a given age group into a single pooled microbiome produced similar results as the individual microbiomes. Results: First, marked age-dependent changes in community structure were identified. Bifidobacterium levels strongly declined as age increased and Bifidobacterium species composition was age-dependent: B. longum, B. catenulatum/pseudocatenulatum and B. adolescentis were most prevalent for breastfed infants, toddlers/children and adults, respectively. Metabolomic analyses (LA-REIMS) demonstrated that these age-dependent differences particularly impacted treatment effects of 2’FL (more than FOS/lactose). Further analysis revealed that while 2’FL enhanced production of short chain fatty acids (SCFAs) and exerted potent bifidogenic effects, regardless of age, the specific Bifidobacterium species enhanced by 2’FL, as well as subsequent cross-feeding interactions, were highly age-dependent. Furthermore, single pooled microbiomes produced results that were indicative of the average treatment response for each age group. Nevertheless, pooled microbiomes had an artificially high diversity, thus overestimating treatment responses (especially for infants), did not recapitulate interindividual variation, and disallowed for the correlative analysis required to unravel mechanistic actions. Conclusion: Age is an important factor in shaping the gut microbiome, with the dominant taxa and their metabolites changing over a lifetime. This divergence affects the response of the microbiota to therapeutics, demonstrated in this study using 2’FL. These results evidence the importance of screening across multiple age groups separately to provide granularity of how therapeutics impact the microbiome and consequently human health.