In vitro models of the human colon have been used extensively in developing understanding of the human gut microbiome and how internal and external factors affect the residing bacterial populations. Such models can be highly predictive of in vivo effects of antibiotics, and indeed more so than animal models. The complexity required by current in vitro models to closely mimic the physiology of the colon poses practical limits on their scalability. MiGut allows considerable expansion of model

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... , increasing the capacity to test reproducibility or parameters under investigation. The MiGut platform has been assessed against a well-studied triple-stage chemostat model in a demanding nine-week study, with exposure to multiple antibiotics inducing a state of dysbiosis in the microbiome. A good correlation is found, both between individual MiGut models and against the triple-stage chemostat. Together with high-throughput molecular techniques for sample analysis, it is now conceivable that tens of in vitro models could be run simultaneously, allowing complex microbiome-xenobiotic interactions to be explored in far greater detail. MiGut is a unique platform whereby multiple colonic models can be run simultaneously with minimal added resource and complexity to support our understanding of the cause-effect relationships that govern the gut microbiome. This model system expands the capacity to generate clinically relevant data that can optimize interventions which target the gut microbiome directly or indirectly.