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MicroDE Report Summary

Project ID: 336355
Funded under: FP7-IDEAS-ERC
Country: Norway

Mid-Term Report Summary - MICRODE (Interpreting the irrecoverable microbiota in digestive ecosystems)

Plant biomass provides a giant potential source of energy and valuable products and is thought to play a major role in a future “bio-based economy”. Unfortunately, this enormous resource remains largely untapped, due to the recalcitrance of lignocellulosic biomass and a lack of understanding how this recalcitrance can be overcome. Microbial communities are renowned for the influences they exert in plant biomass conversion, especially in mammalian health and nutrition as well as industrial applications. In particular, anaerobic biomass conversion by microbial communities has been heavily scrutinized in order to improve knowledge in both bio-ethanol and bio-methane production. Technical issues still restrict biofuel technologies, many of which are generated by a paucity in information concerning how microbes and their enzymes interact with plant cell walls and how these biomass-converting communities maintain stability. Compounding these difficulties is the “cultivability bottleneck”. The microbes that harbor the answers to these questions are largely irrecoverable in isolate form, which restricts access to their genetic and metabolic machinery. The MicroDE project addresses these issues by applying a combination of predictive genome-reconstruction, functional “omic” technologies, isolation strategies, bioinformatics and protein biochemistry in order to generate insight into diverse uncultured microbial lineages. The microbial populations targeted with this strategy include those that harbor core enzyme systems for biomass degradation as well as those they exert influence in community stability.

Key results include reporting the discovery of a novel uncultured bacterium (unFirm_1) in commercial biogas reactors that recycle municipal waste into bio-methane. Importantly, unFirm_1 is proposed to perform a key metabolic step that maintains stability in biogas microbiomes, whereby it syntrophically oxidizes acetate to hydrogen and carbon dioxide, which methanogens then covert to methane. Broader comparisons suggest that unFirm_1 is a key mediator towards the successful long-term stable operation of biogas production using plant biomass and protein-rich wastes. The MircoDE project has also initiated biochemical characterization of novel enzymatic capabilities of Candidatus genera that originate from the cow rumen and biogas reactors that operate on lignocellulosic biomass. Complementing the culture-independent aspects of the MicroDE project, we have also focussed on enigmatic bacterial isolates that are known to degrade recalcitrant plant biomass but for which no mechanisms have been elucidated. We have demonstrated the first illustration of a detailed genetic and functional analysis of a Bacteroidetes-affiliated Polysaccharide utilization loci (PULs) that targets an insoluble crystalline polysaccharide (chitin). The studied PUL is atypical, by relying on a powerful secreted multimodular chitinase, rather than cell surface-anchored enzymes. By combining reverse genetics to map essential PUL genes, structural studies on outer membrane chitin-binding proteins, and enzymology we provide insight into the mechanisms employed by Bacteroidetes to degrade recalcitrant polysaccharides and reveal important novel aspects of the PUL paradigm. We have also generated novel insight into how a famous, yet poorly understood cellulolytic rumen bacteria (Fibrobacter succinogenes), which produces enzyme-enriched outer membrane vesicles that have broad plant biomass degrading capabilities. The MicroDE project has also dedicated resources towards improving methods that are used for meta-omic and bioinformatics approaches. This includes the development of hybrid sequencing approaches that takes advantage of long-read technologies to assemble and taxonomically assign difficult populations. Via collaboration the project has also contributed towards development of computational methods that predict various phenotypic traits in uncultured genomes.

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