ReviewArchives of microbiology2026
Microbiome-metabolite signaling networks in gastrointestinal disease: systems biology, network rewiring, and precision therapeutics.
Review in Archives of microbiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The gastrointestinal tract operates as a highly integrated, multi-layer signaling ecosystem in which microbial communities, metabolite flux, epithelial receptors, immune circuits, and neuroendocrine pathways form a coordinated regulatory network rather than isolated biological compartments. The Microbiome-Metabolite Signaling Network (MMSN) framework conceptualizes gastrointestinal homeostasis and disease as emergent properties of dynamic cross-layer interactions. This review explores the framework principally on inflammatory bowel disease and irritable bowel syndrome as representative gastrointestinal disorders, drawing on other conditions only for illustrative contrast. Within this architecture, microbiota-derived metabolites including short-chain fatty acids, bile acid derivatives, and tryptophan catabolites serve as biochemical intermediaries that relay ecological signals to host receptor systems such as GPR41/43, FXR, TGR5, the aryl hydrocarbon receptor, and innate immune sensors. These receptor-mediated inputs converge on intracellular signaling hubs, including NF-κB, STAT3, inflammasomes, and neuroimmune mediators, which act as high-centrality nodes governing epithelial integrity, cytokine gradients, metabolic coordination, and visceral sensitivity. Signaling hubs are mechanistic convergence nodes that integrate diverse upstream perturbations into coordinated inflammatory or regulatory outputs. In contrast, network fragility denotes the loss of redundancy, modularity, and buffering capacity, predisposing the system to nonlinear amplification and pathological attractor states. Gastrointestinal disorders are therefore more accurately interpreted as manifestations of network rewiring characterized by hub centralization, metabolite imbalance, and strengthened inter-module coupling rather than simple microbial compositional shifts. This review explains the clinical heterogeneity, fluctuating disease trajectories, and variable therapeutic responsiveness. A network-based translational strategy emphasizes hub stabilization, metabolite recalibration, and restoration of distributed connectivity, shifting precision therapeutics toward topology-informed intervention. Integration of microbiology, immunology, neuroscience, systems biology, and computational medicine establishes a pathway toward predictive, mechanistically grounded gastrointestinal network care.
Indexed as
Identifiers
42440156What 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.