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

Author:

Davis Birch William A.1ORCID,Moura Ines B.2ORCID,Ewin Duncan J.2ORCID,Wilcox Mark H.23ORCID,Buckley Anthony M.24ORCID,Culmer Peter R.1ORCID,Kapur Nikil1ORCID

Affiliation:

1. School of Mechanical Engineering University of Leeds Woodhouse Lane Leeds LS2 9JT UK

2. Healthcare‐Associated Infections Group Leeds Institute of Medical Research, Faculty of Medicine and Health, University of Leeds Leeds LS2 9JT UK

3. Microbiology Leeds Teaching Hospitals NHS Trust, Old Medical School, Leeds General Infirmary Leeds LS1 3EX UK

4. Microbiome and Nutritional Science Group, Faculty of Food Science and Nutrition, School of Food Science University of Leeds Leeds LS2 9JT UK

Abstract

AbstractIn 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.

Publisher

Wiley

Subject

Applied Microbiology and Biotechnology,Biochemistry,Bioengineering,Biotechnology

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