ReviewNature microbiology2025
Moving from genome-scale to community-scale metabolic models for the human gut microbiome.
Review in Nature microbiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
15 citing papers in PubMed.
- Metagenome-scale modeling to assess microbiome metabolic complementarity for precision microbiota transplantation therapies.Gut microbes · 2026Article
- Keystone concept revisited: insights into microbial community dynamics and control.Nature reviews. Microbiology · 2026Review
- Dual-encoder contrastive learning accelerates enzyme discovery.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Enrichment is not necessarily recruitment in root microbiome assembly.The ISME journal · 2026Review
- Topological characteristics and longitudinal dynamics of co-abundance networks involving beneficial commensal bacteria in the pig gut microbiome and its association with average daily gain.Frontiers in microbiology · 2026Article
- BileActome reveals community-assembled bile acid metabolism in the rumen microbiome.ISME communications · 2026Article
- Grand challenge in microbiome data science: recovering the microbiome as a system.Frontiers in microbiology · 2026Article
- Precision nutrition through diet-gut microbiome interactions: Emerging insights driven by artificial intelligence, microbiome health metrics, and mechanistic modeling.Gut microbes reports · 2026Review
- SIMBA-GNN: mechanistic graph learning for microbiome prediction.NPJ systems biology and applications · 2025Article
- In Silico Prediction and In Vitro Validation of Bacterial Interactions in the Plant Rhizosphere Using a Synthetic Bacterial Community.Bio-protocol · 2025Article
- Synthetic microbial consortia based on quorum-sensing for disease therapy.Bioresources and bioprocessing · 2025Review
- In silico encounters: harnessing metabolic modelling to understand plant-microbe interactions.FEMS microbiology reviews · 2025Review
- Discovery and cultivation of prokaryotic taxa in the age of metagenomics and artificial intelligence.The ISME journal · 2025Article
- Metabolic modeling of host-microbe interactions.Computational and structural biotechnology journal · 2025Review
- Mathematical models of the colonic microbiota: an evaluation of accuracy usingFrontiers in nutrition · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
Metabolic models of individual microorganisms or small microbial consortia have become standard research tools in the bioengineering and systems biology fields. However, extending metabolic modelling to diverse microbial communities, such as those in the human gut, remains a practical challenge from both modelling and experimental validation perspectives. In complex communities, metabolic models accounting for community dynamics, or those that consider multiple objectives, may provide optimal predictions over simpler steady-state models, but require a much higher computational cost. Here we describe some of the strengths and limitations of microbial community-scale metabolic models and argue for a robust validation framework for developing personalized, mechanistic and accurate predictions of microbial community metabolic behaviours across environmental contexts. Ultimately, quantitatively accurate microbial community-scale metabolic models could aid in the design and testing of personalized prebiotic, probiotic and dietary interventions that optimize for translationally relevant outcomes.
Indexed as
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What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.