A microfluidics-based in vitro model of the gastrointestinal human–microbe interface
Changes in the human gastrointestinal microbiome are associated with several diseases. To infer causality, experiments in representative models are essential, but widely used animal models exhibit limitations. Here we present a modular, microfluidics-based model (HuMiX, human-microbial crosstalk), which allows co-culture of human and microbial cells under conditions representative of the gastrointestinal human-microbe interface. We demonstrate the ability of HuMiX to recapitulate in vivo transcriptional, metabolic and immunological responses in human intestinal epithelial cells following their co-culture with the commensal Lactobacillus rhamnosus GG (LGG) grown under anaerobic conditions. In addition, we show that the co-culture of human epithelial cells with the obligate anaerobe Bacteroides caccae and LGG results in a transcriptional response, which is distinct from that of a co-culture solely comprising LGG. HuMiX facilitates investigations of host-microbe molecular interactions and provides insights into a range of fundamental research questions linking the gastrointestinal microbiome to human health and disease. ; We thank the scientists and technical staff of the Luxembourg Centre for Systems Biomedicine and Center for Applied Nanobioscience and Medicine, particularly Matthew Barrett and Brett Duane for their excellent technical assistance and engineering support. We are grateful to Francois Bernardin, Nathalie Nicot and Laurent Vallar for the microarray analysis; Aidos Baumuratov for imaging support; Linda Wampach for HuMiX illustrations; and Anna Heintz-Buschart for fruitful discussions. This work was supported by an ATTRACT programme grant (ATTRACT/A09/03), a CORE programme grant (CORE/11/BM/1186762), a European Union Joint Programming in Neurodegenerative Diseases grant (INTER/JPND/12/01) and a Proof-of-Concept grant (PoC-15/11014639) to P.W., Accompany Measures mobility grant (12/AM2c/05) to P.W. and P.S., an INTER mobility grant to P.S. (INTER/14/7516918), and an Aide a la Formation Recherche (AFR) postdoctoral grant (AFR/PDR 2013-1/BM/5821107) as well as a CORE programme grant (CORE/14/BM/8066232) to J.V.F., all funded by the Luxembourg National Research Fund (FNR). This work was further supported by a grant attributed to C.S.-D. by the 'Fondation Recherche sur le SIDA du Luxembourg'. Bioinformatics analyses presented in this paper were carried out in part using the HPC facilities of the University of Luxembourg (http://hpc.uni.lu). ; This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.