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Gut-on-Chip Models for Host–Microbiome Studies: A Systematic Review

Sep 2026 · Microorganisms · Vol 14 · 0 citations · 73 references
Medicine

TL;DR

This systematic review provides a comprehensive overview of available GoC technology used in host–microbe research, including their structural and cellular components, highlighting the potential of GoC models to support biotic characterization and preclinical evaluation while underscoring the need for further validation and standardization.

Abstract

As a central regulator of nutrient absorption, immune homeostasis and overall health, the gastrointestinal tract has become a major focus of biomedical research. However, developing in vitro models that accurately reproduce human gastrointestinal architecture and physiological conditions remains a major challenge. Gut-on-chip (GoC) systems, which integrate microfluidics with cell cultures, have emerged as a promising solution in the past decade. By recreating dynamic microenvironments that incorporate fluid flow, peristalsis-like mechanical stimulation and co-culture with microorganisms, GoC systems enable more physiologically relevant investigation of host–microbe and host–microbiome interactions. This systematic review provides a comprehensive overview of available GoC technology used in host–microbe research, including their structural and cellular components. A systematic search of PubMed, Embase and Google Scholar databases up to May 2026 identified forty-eight studies evaluating interactions between the host and probiotic strains, postbiotics, commensal microorganisms, pathogenic bacteria, fungi, viruses, or faecal-derived microbiota using GoCs. Common features, distinctive characteristics and application for modelling host–microbiome interactions and pathogenic infections are summarized. The available literature is characterized by heterogeneous study designs, variable microbiome compositions and analytical approaches, and limited cross-platform standardization, which should be considered when interpreting findings. Lastly, current limitations and future perspectives are discussed, highlighting the potential of GoC models to support biotic characterization and preclinical evaluation while underscoring the need for further validation and standardization.

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