Synthetic ecology of the human gut microbiota

Network reconstructions are a common denominator in systems biology. Bottom-up metabolic network reconstructions have been developed over the last 10 years. These reconstructions represent structured knowledge bases that abstract pertinent information on the biochemical transformations taking place within specific target organisms. The conversion of a reconstruction into a mathematical format facilitates a myriad of computational biological studies, including evaluation of network content, hypothesis testing and generation, analysis of phenotypic characteristics and metabolic engineering. To date, genome-scale metabolic reconstructions for more than 30 organisms have been published and this number is expected to increase rapidly. However, these reconstructions differ in quality and coverage that may minimize their predictive potential and use as knowledge bases. Here we present a comprehensive protocol describing each step necessary to build a high-quality genome-scale metabolic reconstruction, as well as the common trials and tribulations. Therefore, this protocol provides a helpful manual for all stages of the reconstruction process.

Population stratification is a useful approach towards a better understanding of complex biological problems in human health and well-being. The proposal that such stratification applies to the human gut microbiome, in the form of distinct community composition types, termed “enterotypes”, was met with both excitement and controversy. In view of accumulated data and re-analyses since the original work, we revisit the enterotype concept, discuss different methods of dividing up the landscape of possible microbiome configurations, and put these concepts into a functional, ecological and medical context. As enterotypes are of use in describing the gut microbial community landscape and may become relevant in clinical practice, we aim to reconcile differing views and encourage a balanced application of the concept.

A large set of microbial metabolic models (AGORA) could be applied to better understand the functions of the human gut microbiome.