From meta-omics to causality: experimental models for human microbiome research

Abstract

Large-scale 'meta-omic' projects are greatly advancing our knowledge of the human microbiome and its specific role in governing health and disease states. A myriad of ongoing studies aim at identifying links between microbial community disequilibria (dysbiosis) and human diseases. However, due to the inherent complexity and heterogeneity of the human microbiome, cross-sectional, case-control and longitudinal studies may not have enough statistical power to allow causation to be deduced from patterns of association between variables in high-resolution omic datasets. Therefore, to move beyond reliance on the empirical method, experiments are critical. For these, robust experimental models are required that allow the systematic manipulation of variables to test the multitude of hypotheses, which arise from high-throughput molecular studies. Particularly promising in this respect are microfluidics-based in vitro co-culture systems, which allow high-throughput first-pass experiments aimed at proving cause-and-effect relationships prior to testing of hypotheses in animal models. This review focuses on widely used in vivo, in vitro, ex vivo and in silico approaches to study host-microbial community interactions. Such systems, either used in isolation or in a combinatory experimental approach, will allow systematic investigations of the impact of microbes on the health and disease of the human host. All the currently available models present pros and cons, which are described and discussed. Moreover, suggestions are made on how to develop future experimental models that not only allow the study of host-microbiota interactions but are also amenable to high-throughput experimentation.

Figure 1

From association to causality. (A) Functional co-occurrence networks, established by the analysis of human microbial communities from healthy and diseased cohorts by meta-omic approaches are crucial to define dysbiotic states and to correlate individual microbial community members with disease. (B) In order to gain detailed information about microbial compositional changes and their associated impact on disease, high-throughput in vitro experimental systems are essential. In vitro co-culture approaches allow the confirmation or the rejection of hypotheses resulting from meta-omic data. (C) In order to causally link changes in microbial community structure or in their associated biomolecular patterns with specific diseases, gnotobiotic animal models are indispensable for in vivo validation. In all panels, triangles represent different biomolecules whereas color-coded circles represent different microbial taxa.

Figure 2

Conceptualization of an idealized in vitro gastrointestinal experimental model. An idealized in vitro co-culture model may include three distinct culture chambers, namely microbial, human epithelial and human immune cell culture chambers, each separated by semipermeable membranes allowing molecular cross-talk between the different contingents while preventing microbes from rapidly overtaking human cells due to pronounced differences in their respective growth rates. Furthermore, an idealized gastrointestinal in vitro model should reflect the biogeographical distribution of the gastrointestinal microbiota. Such a model should allow the culture of representative microbial communities for the individual sections of the gastrointestinal tract (GIT) including stomach, small intestine, ascending colon, transverse colon and descending colon. All the individual compartments should be connected in series and allow modulation of their respective environmental factors including pH, fluid retention times, growth medium and other physiological factors such as mucin (in green in the microbial chamber) compositions, which actively interact and alter the microbial communities. To represent the GIT in the most realistic way, the microbial growth chamber needs to be depleted of oxygen, which could be achieved by flushing this chamber with anaerobic microbial medium, whereas the human cell chambers need to be flushed with oxygenated medium. Finally, an idealized GIT in vitro model suitable for microbiome research must support high-throughput omic analyses and, thus, needs to allow probing of the individual contingents to perform dedicated analyses on the different cell contingents following a particular experimental regime and to relate particular measurements back to the cell populations of origin.