Evidence map›Paper›PMID 42397708›Full record

ArticleGut microbes2026

Genome-scale metabolic models predict diet- and lifestyle-driven shifts of ecological interactions in the gut microbiome.

Georgios Marinos, Karlis Arturs Moors, Kristina Schlicht, Malte Rühlemann, Silvio Waschina, Wolfgang Lieb, Andre Franke, Matthias Laudes, Mathieu Groussin, Mathilde Poyet and 2 more

Abstract read
In one paragraph

Article in Gut microbes, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors.

Georgios MarinosResearch Group Medical Systems Biology, Institute of Experimental Medicine, University Hospital Schleswig-Holstein Campus Kiel, Kiel University, Kiel, Schleswig-Holstein, Germany.ORCID 0000-0002-6443-7696
Karlis Arturs MoorsResearch Group Medical Systems Biology, Institute of Experimental Medicine, University Hospital Schleswig-Holstein Campus Kiel, Kiel University, Kiel, Schleswig-Holstein, Germany.ORCID 0000-0001-6529-2970
Kristina SchlichtResearch Group Medical Systems Biology, Institute of Experimental Medicine, University Hospital Schleswig-Holstein Campus Kiel, Kiel University, Kiel, Schleswig-Holstein, Germany.ORCID 0000-0003-0281-5142
Malte RühlemannInstitute of Clinical Molecular Biology, University Hospital Schleswig-Holstein Campus Kiel, Kiel University, Kiel, Schleswig-Holstein, Germany.ORCID 0000-0002-0685-0052
Silvio WaschinaNutriinformatics, Institute of Human Nutrition and Food Science, Kiel University, Kiel, Schleswig-Holstein, Germany.ORCID 0000-0002-6290-3593
Wolfgang LiebInstitute of Epidemiology, Kiel, Kiel University, Kiel, Schleswig-Holstein, Germany.ORCID 0000-0003-2544-4460
Andre FrankeInstitute of Clinical Molecular Biology, University Hospital Schleswig-Holstein Campus Kiel, Kiel University, Kiel, Schleswig-Holstein, Germany.ORCID 0000-0003-1530-5811
Matthias LaudesInstitute of Diabetes and Clinical Metabolic Research, University Hospital Schleswig-Holstein Campus Kiel, Kiel, Schleswig-Holstein, Germany.ORCID 0000-0002-7846-955X
Mathieu GroussinInstitute of Clinical Molecular Biology, University Hospital Schleswig-Holstein Campus Kiel, Kiel University, Kiel, Schleswig-Holstein, Germany.ORCID 0000-0002-0942-7217
Mathilde PoyetInstitute of Experimental Medicine, University Hospital Schleswig-Holstein Campus Kiel, Kiel University, Kiel, Schleswig-Holstein, Germany.ORCID 0000-0001-6905-9017
Christoph KaletaResearch Group Medical Systems Biology, Institute of Experimental Medicine, University Hospital Schleswig-Holstein Campus Kiel, Kiel University, Kiel, Schleswig-Holstein, Germany.ORCID 0000-0001-8004-9514
A Samer KadibalbanResearch Group Medical Systems Biology, Institute of Experimental Medicine, University Hospital Schleswig-Holstein Campus Kiel, Kiel University, Kiel, Schleswig-Holstein, Germany.ORCID 0009-0001-9726-543X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Microbiomes and their host environments form complex, interconnected ecosystems. The microbial species within a microbiome, on the one hand, compete for resources, while on the other hand, they exchange vital metabolites to support their survival. These interactions are influenced by the microbial genetic repertoire, environmental conditions, and availability of nutrients. We developed EcoGS (http://www.github.com/KaletaLab/EcoGS), a metabolic modeling tool designed to predict the ecological interactions between pairs of microbes. Applying EcoGS to the microbiomes of two distinct human cohorts revealed a shift from collaborative to exploitative ecological interactions associated with increased dietary intake of simple sugars (glucose and fructose) in diabetic individuals and those living industrialized lifestyles. On the other hand, the consumption of cobalamin (vitamin B12), phylloquinone (vitamin K1), and biotin (vitamin B7), among other compounds, was associated with increased collaboration in the gut microbiome. We conclude that the abundance of simple sugars as an energy source reduces the necessity for microbes to cooperate, thereby increasing competition and hostility among microbiome members. Moreover, our study proposes multiple compounds, such as urate, deoxyadenosine, deoxyguanosine, and hypoxanthine, for in vitro validation tests as dietary interventions that have the potential to restore the ecological balance within the community. EcoGS serves as a valuable tool for exploring microbiome dynamics and their connections to environmental changes and disease.

Indexed as

BacteriaDietGastrointestinal MicrobiomeLife StyleMicrobial InteractionsHumansModels, Biologicalcommunity modelingecological interactionsFlux balance analysismicrobial ecologymicrobiomenutrition

Identifiers

PMID42397708
PMCPMC13336287

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Registered trials

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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 OpenQuestion graph.