RT Journal Article
T1 Prediction of degradation pathways of phenolic compounds in the human gut microbiota through enzyme promiscuity methods.
A1 Balzerani, Francesco
A1 Hinojosa-Nogueira, Daniel
A1 Cendoya, Xabier
A1 Blasco, Telmo
A1 Perez-Burillo, Sergio
A1 Apaolaza, Iñigo
A1 Francino, M Pilar
A1 Rufian-Henares, Jose Angel
A1 Planes, Francisco J
K1 Physiology
K1 Biochemical networks
K1 Computational biology and bioinformatics
AB The relevance of phenolic compounds in the human diet has increased in recent years, particularly due to their role as natural antioxidants and chemopreventive agents in different diseases. In the human body, phenolic compounds are mainly metabolized by the gut microbiota; however, their metabolism is not well represented in public databases and existing reconstructions. In a previous work, using different sources of knowledge, bioinformatic and modelling tools, we developed AGREDA, an extended metabolic network more amenable to analyze the interaction of the human gut microbiota with diet. Despite the substantial improvement achieved by AGREDA, it was not sufficient to represent the diverse metabolic space of phenolic compounds. In this article, we make use of an enzyme promiscuity approach to complete further the metabolism of phenolic compounds in the human gut microbiota. In particular, we apply RetroPath RL, a previously developed approach based on Monte Carlo Tree Search strategy reinforcement learning, in order to predict the degradation pathways of compounds present in Phenol-Explorer, the largest database of phenolic compounds in the literature. Reactions predicted by RetroPath RL were integrated with AGREDA, leading to a more complete version of the human gut microbiota metabolic network. We assess the impact of our improvements in the metabolic processing of various foods, finding previously undetected connections with output microbial metabolites. By means of untargeted metabolomics data, we present in vitro experimental validation for output microbial metabolites released in the fermentation of lentils with feces of children representing different clinical conditions.
PB Nature Publishing Group
YR 2022
FD 2022-06-20
LK http://hdl.handle.net/10668/19563
UL http://hdl.handle.net/10668/19563
LA en
NO Balzerani F, Hinojosa-Nogueira D, Cendoya X, Blasco T, Pérez-Burillo S, Apaolaza I, et al. Prediction of degradation pathways of phenolic compounds in the human gut microbiota through enzyme promiscuity methods. NPJ Syst Biol Appl. 2022 Jul 12;8(1):24.
NO This work was funded by the European Union’s Horizon 2020 research and innovation programme through the STANCE4HEALTH project (Grant No. 816303); the Basque Government with the grant promoting doctoral theses to young predoctoral researchers [grant PRE_2017.1.0327 to X.C.].
DS RISalud
RD Apr 6, 2025