Longitudinal flux balance analyses of a patient with Crohn’s disease highlight microbiome metabolic alterations

Abstract

Inflammatory bowel diseases (IBD) are characterised by episodic inflammation of the gastrointestinal tract. Gut microbial dysbiosis characterises the pathoetiology, but its role remains understudied. We report the first use of constraint-based microbial community modelling on a single individual with IBD, covering seven dates over 16 months, enabling us to identify a number of time-correlated microbial species and metabolites. We find that the individual's dynamical microbial ecology in the disease state drives time-varying in silico overproduction, compared to healthy controls, of more than 24 biologically important metabolites, including oxygen, methane, thiamine, formaldehyde, trimethylamine N-oxide, folic acid, serotonin, histamine, and tryptamine. A number of these metabolites may yield new biomarkers of disease progression. The microbe-metabolite contribution analysis revealed that some genus Dialister species changed metabolic pathways according to the disease phases. At the first time point, characterised by the highest levels of blood and faecal inflammation biomarkers, they produced L-serine or formate. The production of the compounds, through a cascade effect, was mediated by the interaction with pathogenic Escherichia coli strains and Desulfovibrio piger. We integrated the microbial community metabolic models of each time point with a male whole-body, organ-resolved model of human metabolism to track the metabolic consequences of dysbiosis at different body sites. The presence of D. piger in the gut microbiome influenced the sulphur metabolism with a domino effect affecting the liver. These results underline the importance of tracking an individual's gut microbiome along a time course, creating a new analysis framework for self-quantified medicine.

APOLLO: A genome-scale metabolic reconstruction resource of 247,092 diverse human microbes spanning multiple continents, age groups, and body sites

“…Such simulations may provide mechanistic insights into the known association between Westernised diets and lifestyles, and a loss in gut microbiome compositional and functional diversity (Sonnenburg and Sonnenburg, 2019). As a follow-up, personalised microbial community models could be integrated with whole-body models of human metabolism, which could then be contextualised with dietary information and metadata, including sex, weight, and height (Basile et al, 2022; Thiele et al, 2020). Hence, differences in microbiome structure and function by country of origin, age, and sex could be modelled as well as changes in host-microbiome co-metabolism.…”

More is Different: Metabolic Modeling of Diverse Microbial Communities

“…Dynamic FBA methods have become popular approaches by which to simulate this full trajectory from a set of initial conditions, to the steady-state, and then a subsequent return to the stationary phase if the system lacks a constant supply of nutrients ( Fig. 2B ) ( 26 – 29 ). Alternative dynamical approaches also include individual-based dynamic FBA models, in which single organisms or cells are modeled on a two-dimensional or three-dimensional grid with a discrete time-stepping scheme, continually updating the concentrations of extracellular metabolites and the taxon abundances in time and space ( 30 , 31 ).…”