Francino, M.P. (M. Pilar)
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- BN-BacArena: Bayesian network extension of BacArena for the dynamic simulation of microbial communities(Oxford University Press, 2024) Balzerani, F. (Francesco); Valcárcel-García, L.V. (Luis Vitores); Blasco, T. (Telmo); Larrañaga, P. (Pedro); Rufián-Henares, J.Á. (Ángel José); Francino, M.P. (M. Pilar); Planes-Pedreño, F.J. (Francisco Javier); Bielza, C. (Concha); Pérez-Burillo, S. (Sergio)Motivation: Simulating gut microbial dynamics is extremely challenging. Several computational tools, notably the widely used BacArena, enable modeling of dynamic changes in the microbial environment. These methods, however, do not comprehensively account for microbe–microbe stimulant or inhibitory effects or for nutrient–microbe inhibitory effects, typically observed in different compounds present in the daily diet. Results: Here, we present BN-BacArena, an extension of BacArena consisting on the incorporation within the native computational framework of a Bayesian network model that accounts for microbe–microbe and nutrient–microbe interactions. Using in vitro experiments, 16S rRNA gene sequencing data and nutritional composition of 55 foods, the output Bayesian network showed 23 significant nutrient–bacteria interactions, suggesting the importance of compounds such as polyols, ascorbic acid, polyphenols and other phytochemicals, and 40 bacteria–bacteria significant relationships. With test data, BN-BacArena demonstrates a statistically significant improvement over BacArena to predict the time-dependent relative abundance of bacterial species involved in the gut microbiota upon different nutritional interventions. As a result, BN-BacArena opens new avenues for the dynamic modeling and simulation of the human gut microbiota metabolism.
- Adaptation of the human gut microbiota metabolic network during the first year after birth(Frontiers Media SA, 2019) Vallès, Y. (Yvonne); Fuertes, A. (Alvaro); Rufián-Henares, J.Á. (Ángel José); Francino, M.P. (M. Pilar); Planes-Pedreño, F.J. (Francisco Javier); Apaolaza-Emparanza, I.(Iñigo); Pérez-Burillo, S. (Sergio)Predicting the metabolic behavior of the human gut microbiota in different contexts is one of the most promising areas of constraint-based modeling. Recently, we presented a supra-organismal approach to build context-specific metabolic networks of bacterial communities using functional and taxonomic assignments of meta-omics data. In this work, this algorithm is applied to elucidate the metabolic changes induced over the first year after birth in the gut microbiota of a cohort of Spanish infants. We used metagenomics data of fecal samples and nutritional data of 13 infants at five time points. The resulting networks for each time point were analyzed, finding significant alterations once solid food is introduced in the diet. Our work shows that solid food leads to a different pattern of output metabolites that can be potentially released from the gut microbiota to the host. Experimental validation is presented for ferulate, a neuroprotective metabolite involved in the gut-brain axis.