Mixed microbial communities play pivotal roles in governing human health and disease. Recent evidence suggests that some diseases result from microbial community disequilibria rather than being caused by single pathogenic strains. For example, the etiology of several idiopathic medical conditions, e.g. cancer, cardiovascular diseases, diabetes, diseases of the central nervous system or chronic inflammatory diseases, has recently been putatively linked to shifts in the human gastrointestinal microbiome. Causative links are difficult to ascertain because of a distinct lack of in vitro human-microbial co-culture systems in which emergent hypotheses can be tested. Here, we propose the development of a modular microfluidics-based device that will allow the partitioned cultivation of human cell lines and sampled human microbial communities while at the same time allowing molecular interactions between both contingents across a semi-permeable membrane. The device architecture will allow us to estabish in vitro models for the human proximal colon, the entire human gastrointestinal tract and human gastrointestinal tissues. Furthermore, the device may allow for the co-culture of patient-derived human cells/tissues in conjunction with their naturally coexisting mixed microbial communities.Following the establishment of the respective human-microbial gastrointestinal models, we aim to investigate a number of fundamental scientific questions pertaining to the impact of molecular interactions on human and microbial metabolism as well as functional gene expression. As a proof-of-concept of the device, we will investigate the integrative gastrointestinal digestion of certain bioactive plant compounds which is currently simulated separately or consecutively using human intestinal cell lines or microbial cultures.We will assay underlying molecular processes through a integrative systems biology approach (in particular using metabolomics, genomics and transcriptomics) as well as investigate cellular spatial arrangements by microscopy. The resulting high-resolution data will be processed, integrated and analysed using a suite of bioinformatic approaches. In particular, we aim to employ the experimental data to develop and refine integrated multi-scale models of human and microbial metabolism. These models may allow for the prediction of system-wide impacts of human and microbial molecular interactions on the pathobiology of certain diseases.