Title: Developing a systems biology framework to engineer anaerobic gut fungi
Modern biotechnology increasingly seeks to leverage consortia-based approaches for bioprocesses due to the reduced metabolic burden and expanded metabolic capability of these systems compared to monocultures. Indeed, nature seems to favor these complex, multi-member, often functionally redundant, systems. The rumen microbiome, which is composed of an incredibly complex web of interacting microbes, excels at the breakdown of recalcitrant plant biomass. This characteristic is ripe for biotechnological exploitation, with the eventual goal of bio-converting crude lignocellulose into valuable chemicals using microbial consortia. Fundamental to this endeavor is understanding the role anaerobic gut fungi, native to the rumen microbiome, play in this system.
Anaerobic gut fungi, from the phylum Neocallimastigomycota, are a clade of early diverging, obligately anaerobic fungi that specialize in lignocellulosic plant biomass breakdown. Here, I will show how multi-omic datasets can be used to broaden our understanding of these fungi both in isolation, as well as in consortia.
By leveraging the high-quality genome of an anerobic gut fungus, I have developed the first genome-scale metabolic model of an anaerobic gut fungus. The model captures key aspects of its primary metabolism and reveals new metabolic capabilities present in the energy generating organelles of anaerobic gut fungi. Further, coupling the model with flux balance analysis provides a route to predict growth rates and intra-cellular metabolic fluxes in silico. These simulations can be used to systematically find metabolic connection points for model-based consortia design, as well as highlight understudied aspects of gut fungal metabolism that require further investigation.
I will also demonstrate how a data-rich metagenomic analysis has elucidated key design rules that shape rumen microbiome communities, and how this ties in with metabolic modeling. Finally, I will introduce a custom-built automated batch reactor system that can be used to non-invasively probe the growth rate of anaerobes in high resolution.