Department of Bioengineering, University of Illinois Urbana-Champaign, Urbana, United States; Carl R. Woese Institute for Genomic Biology, University of Illinois Urbana-Champaign, Urbana, United States; College of Food Science and Nutritional Engineering, China Agricultural University, Beijing, China
Yongping Xin
Department of Bioengineering, University of Illinois Urbana-Champaign, Urbana, United States; Carl R. Woese Institute for Genomic Biology, University of Illinois Urbana-Champaign, Urbana, United States
Department of Bioengineering, University of Illinois Urbana-Champaign, Urbana, United States; Carl R. Woese Institute for Genomic Biology, University of Illinois Urbana-Champaign, Urbana, United States; Department of Physics, University of Illinois Urbana-Champaign, Urbana, United States; Center for Biophysics and Quantitative Biology, University of Illinois Urbana-Champaign, Urbana, United States; National Center for Supercomputing Applications, Urbana, United States
One defining goal of microbiome research is to uncover mechanistic causation that dictates the emergence of structural and functional traits of microbiomes. However, the extraordinary degree of ecosystem complexity has hampered the realization of the goal. Here, we developed a systematic, complexity-reducing strategy to mechanistically elucidate the compositional and metabolic characteristics of microbiome by using the kombucha tea microbiome as an example. The strategy centered around a two-species core that was abstracted from but recapitulated the native counterpart. The core was convergent in its composition, coordinated on temporal metabolic patterns, and capable for pellicle formation. Controlled fermentations uncovered the drivers of these characteristics, which were also demonstrated translatable to provide insights into the properties of communities with increased complexity and altered conditions. This work unravels the pattern and process underlying the kombucha tea microbiome, providing a potential conceptual framework for mechanistic investigation of microbiome behaviors.