The human microbiome comprises multiple species in co-existence with known ecological drivers serving to shape the diversity and makeup of the community. Devoid of immune contributions, it is possible to maintain a gut microflora from different species in vitro using bioreactors. The precise effects of chemical stressors and antibiotic effector molecules on population diversity as well as network connectivity are poorly understood. Having established controlled bioreactors under microaerobic to aerobic conditions, we aim to test the effects of long-term exposure to stressors, on gut microbiota dynamics. This is compared with simulations of a mathematical model of multispecies competition in order to identify factors that increase community robustness and reduces the risk for gut dysbiosis. To map changes in the microbial composition of the community, we will generate amplicon libraries of the small subunit 16s rRNA of prokaryotes and 18s rRNA of eukaryote microorganisms before, during and after stressor application to reactors run in triplicate at flow rates equivalent to precise portions of the human gut. These amplicons will be sequenced, and analyzed using mostly open source software on datasets while networks will be assessed using Random Matrix Theory (RMT)-based methods.