Systematic interrogation of the distinct metabolic potential in gut microbiomes of inflammatory bowel disease patients with dysbiosis

Heinken, Almut; Thiele, Ines

doi:10.1101/640649

Cited by 2 publications

(1 citation statement)

References 58 publications

(95 reference statements)

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“…For this study we rely on its predecessor due to its extensive application and validation in the field (63,(127)(128)(129). While the development of GEMs, as a technology, is ongoing, they are ideally placed for analyses such as the one we perform here, where we granularly inspect cellular metabolism and inter-strain interactions for community design, difficult to perform through alternative modalities.…”

Section: Discussionmentioning

confidence: 99%

Genome scale metabolic modelling of human gut microbes to inform rational community design

Ortiz,

McClure,

Holmes

et al. 2024

Preprint

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BackgroundThe human gut microbiome plays a pivotal role in health and disease, influenced significantly by diet, particularly through the intake of digestion-resistant carbohydrates (DRCs). Emerging evidence underscores the potential of DRC supplementation in modulating the gut microbiome towards health-promoting metabolic outputs, notably through the fermentation of DRCs into short-chain fatty acids (SCFAs) including butyrate. However, the effectiveness of such interventions is hindered by the inherent complexity of microbial communities and the variable functional capacity of microbiomes across individuals. Improved understanding of gut ecology is necessary to move past interventions with transient benefits.ResultsThis study leverages genome-scale metabolic models (GEMs) to characterise the metabolic capabilities of 598 stable human gut colonising strains from the AGORA database. We infer the strains’ abilities to utilize dietary carbohydrates of varying complexities and produce metabolites that mediate interactions with other microbes and the host.Our analysis reveals a stratified functional landscape where prominent bacterial families show predispositions towards primary or secondary degrader roles based on their carbohydrate utilisation capabilities. Further, we identify metabolite production profiles that exceed phylogenetic variation in our sample. These results offer a comprehensive functional mapping of carbohydrate metabolism across a wide array of gut microbes, shedding light on the complex trophic networks underpinning the gut ecosystem.Supporting DRC-based interventions with rationally designed microbial communities can better guarantee the delivery of the intended health-promoting metabolic outputs. Applying our functional assessment, and principles of reverse ecology and network analysis, we propose a novel framework for the rational design gut microbial communities, where trophic networks are optimised to produce target metabolites from selected DRCs. Our results further suggest that this framework can predict resilient minimal communities, an important trait in the constantly changing human gut nutritional environment.ConclusionOur work provides novel insights into gut microbial ecology as well as intervention and consortia design. The identified metabolic capabilities of individual strains inform the rational design of a purpose-based microbial community to optimise butyrate production from inulin degradation. The framework we propose herein sets a foundation for future efforts aimed at the rational design of interventions that target the human gut microbiome to improve health.

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Section: Discussionmentioning

confidence: 99%

Genome scale metabolic modelling of human gut microbes to inform rational community design

Ortiz,

McClure,

Holmes

et al. 2024

Preprint

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MMINT: a Metabolic Model Interactive Network Tool for the exploration and comparative visualisation of metabolic networks

Molina Ortiz,

Morgan,

Paten

et al. 2024

Preprint

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Genome-scale metabolic models (GEMs) are essential tools in systems and synthetic biology, enabling the mathematical simulation of metabolic pathways encoded in genomes to predict phenotypes. The complexity of GEMs, however, can often limit the interpretation and comparison of their outputs. Here, we present MMINT (Metabolic Modelling Interactive Network Tool), designed to facilitate the exploration and comparison of metabolic networks. MMINT employs GEM networks and flux solutions derived from Constraint Based Analysis (e.g. Flux Balance Analysis) to create interactive visualizations. This tool allows for seamless toggling of source and target metabolites, network decluttering, enabling exploration and comparison of flux solutions by highlighting similarities and differences between metabolic states, which enhances the identification of mechanistic drivers of phenotypes. We demonstrate MMINT’s capabilities using thePyrococcus furiosusGEM, showcasing its application in distinguishing the metabolic drivers of acetate- and ethanol-producing phenotypes. By providing an intuitive and responsive model-exploration experience, MMINT addresses the need for a tool that simplifies the interpretation of GEM outputs and supports the discovery of novel metabolic engineering strategies. MMINT is available athttps://doi.org/10.6084/m9.figshare.26409328Graphical abstractMMINT functionalities provide an intuitive and responsive model-exploration experience, enabling flux solution comparison and the identification of metabolic drivers of phenotypes

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Systematic interrogation of the distinct metabolic potential in gut microbiomes of inflammatory bowel disease patients with dysbiosis

Cited by 2 publications

References 58 publications

Genome scale metabolic modelling of human gut microbes to inform rational community design

Genome scale metabolic modelling of human gut microbes to inform rational community design

MMINT: a Metabolic Model Interactive Network Tool for the exploration and comparative visualisation of metabolic networks

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