Metabolic model predictions enable targeted microbiome manipulation through precision prebiotics.
Caenorhabditis elegans
Ochrobactrum vermis MYb71
Pseudomonas lurida MYb11
flux balance analysis
genome-scale metabolic models
nutritional supplements
serine
Journal
bioRxiv : the preprint server for biology
Titre abrégé: bioRxiv
Pays: United States
ID NLM: 101680187
Informations de publication
Date de publication:
18 Feb 2023
18 Feb 2023
Historique:
pubmed:
25
2
2023
medline:
25
2
2023
entrez:
24
2
2023
Statut:
epublish
Résumé
The microbiome is increasingly receiving attention as an important modulator of host health and disease. However, while numerous mechanisms through which the microbiome influences its host have been identified, there is still a lack of approaches that allow to specifically modulate the abundance of individual microbes or microbial functions of interest. Moreover, current approaches for microbiome manipulation such as fecal transfers often entail a non-specific transfer of entire microbial communities with potentially unwanted side effects. To overcome this limitation, we here propose the concept of precision prebiotics that specifically modulate the abundance of a microbiome member species of interest. In a first step, we show that defining precision prebiotics by compounds that are only taken up by the target species but no other species in a community is usually not possible due to overlapping metabolic niches. Subsequently, we present a metabolic modeling network framework that allows us to define precision prebiotics for a two-member
Identifiants
pubmed: 36824941
doi: 10.1101/2023.02.17.528811
pmc: PMC9949166
pii:
doi:
Types de publication
Preprint
Langues
eng
Déclaration de conflit d'intérêts
Conflicts of Interest None to declare