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1. Introduction
2. Our individual responses to diet are governed, in part, by our unique microbiome
3. The microbiome influences responses to diet
4. Translating microbiome composition into ecosystem function
5. Over the last century, we have gained extensive knowledge of biochemistry and metabolism
6. What’s the best measure of metabolic function?
7. Community-scale metabolic modeling for precision microbiome-mediated medicine
8. Flux Balance Analysis (FBA)
9. MIcrobial COMmunity (MICOM )
10. More is different: cooperative tradeoff Flux Balance Analysis (ctFBA)
11. MICOM enables exploration of taxon-taxon interactions in complex communities
12. Translational potential: Clostridioides difficile
13. Validation: in vitro engraftment prediction
14. Validation: in vivo engraftment prediction
15. Metabolic plasticity across environmental contexts
16. Towards precision probiotic cocktail design to prevent or reverse C. difficile colonization
17. Translational potential: short chain fatty acid
18. Butyrate: A key cardiometabolic molecule you might not know about
19. Model validation: poop soup experiments
20. Predicting personalized SCFA (butyrate and propionate) production in humans
21. Blood-based clinical chemistries associated with butyrate predictions in the human cohort
22. Using MICOM to simulate personalized effects of diet shifts and pre/probiotic co-interventions
23. Co-intervention outcomes among high-fiber diet non-responders and regressors
24. How to improve MCMMs predictive capacity to move towards translational applications?
25. Data-driven dietary intake assessments
26. Metagenomic estimation of dietary intake (MEDI)
27. MEDI controls for false positives and false negatives
28. Phylogenetically related organisms have similar nutrient contents
29. Estimating dietary intake directly from metagenomic data in infants
30. Estimating dietary intake directly from metagenomic data in adults
31. Validating food intake predictions in controlled feeding study
32. Validating nutrient intake predictions in controlled feeding study - micronutrients
33. Estimating dietary intake directly from meta-genomic data that lack questionnaire data
34. Converting dietary intake into nutritional intake METACARDIS
35. MEDI-inferred nutritional intake could be leveraged to improve MICOM predictions
36. Thank you and acknowledgements
37. Financial disclosures

Topics Covered

• Computational modeling
• Gut-microbiome interaction
• Microbiome and nutrition metabolism
• Diet and metabolic disorders
• Personalized medicine
• Dietary tests
• Dietary assessment

Links

Series:

• Introduction to Computational Biology

Categories:

• Microbiology

External Links

• Slide 6- The Journey of a Metabolite

Talk Citation

Gibbons, S. (2025, December 31). Microbial community-scale metabolic modeling and precision nutrition [Video file]. In The Biomedical & Life Sciences Collection, Henry Stewart Talks. Retrieved December 31, 2025, from https://doi.org/10.69645/HDXY1129.
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Publication History

• Published on December 31, 2025

Financial Disclosures

• Dr. Sean Gibbons is a paid member of the Thorne scientific advisory board. Thorne was not involved in any of the work presented in this talk.