MiGut: A scalable in vitro platform for simulating the human gut microbiome—Development, validation and simulation of antibiotic‐induced dysbiosis

• Published in: Microbial biotechnology Vol. 16; no. 6; pp. 1312 - 1324
• Main Authors: Davis Birch, William A., Moura, Ines B., Ewin, Duncan J., Wilcox, Mark H., Buckley, Anthony M., Culmer, Peter R., Kapur, Nikil
• Format: Journal Article
• Language: English
• Published: United States John Wiley & Sons, Inc 01.06.2023; John Wiley and Sons Inc; Wiley
• Subjects: Animal models; Animals; Anti-Bacterial Agents - adverse effects; Antibiotics; Bacteria - genetics; Cause-effect relationships; Colon; Complexity; Digestive system; Dysbacteriosis; Dysbiosis - chemically induced; Dysbiosis - microbiology; Gastrointestinal Microbiome; Humans; In vivo methods and tests; Intestinal microflora; Longitudinal studies; Microbiomes; Microbiota; Pathogenesis; Physiology; Potassium
• DOI: 10.1111/1751-7915.14259
• ISSN: 1751-7915

In vitro models of the human colon have been used extensively in understanding the human gut microbiome (GM) and evaluating how internal and external factors affect the residing bacterial populations. Such models have been shown to be highly predictive of in vivo outcomes and have a number of advantages over animal models. The complexity required by in vitro models to closely mimic the physiology of the colon poses practical limits on their scalability. The scalable Mini Gut (MiGut) platform presented in this paper allows considerable expansion of model replicates and enables complex study design, without compromising on in vivo reflectiveness as is often the case with other model systems. MiGut has been benchmarked against a validated gut model in a demanding 9‐week study. MiGut showed excellent repeatability between model replicates and results were consistent with those of the benchmark system. The novel technology presented in this paper makes it conceivable that tens of models could be run simultaneously, allowing complex microbiome‐xenobiotic interactions to be explored in far greater detail, with minimal added resources or complexity. This platform expands the capacity to generate clinically relevant data to support our understanding of the cause‐effect relationships that govern the GM. In vitro models of the human colon have been used extensively in developing an understanding of the human gut microbiome, but current technologies are extremely complex and have limited throughput. MiGut is a novel platform which addresses these shortcomings, allowing for considerable expansion of model runs without compromising on in vivo reflectiveness. The technology has been validated in a demanding 9‐week study where dysbiosis was simulated in vitro and has been benchmarked against a previously validated and extremely well understood triple‐stage gut model system.