Back to basics: simplifying microbial communities to decrypt complex interactions

All life on earth depends on the actions of microorganisms. For example, the digestion system of humans depends on a vital relationship with a community of microorganisms that control the breakdown of ingested food whilst forming a protective barrier against disease and infection. Microorganisms also play a central role in the turnover of biomass, be it in natural ecosystems or in the production of bioenergy. With the help of microbial communities, we can convert a wide range of plant biomass and agricultural waste into renewable fuels and bioproducts. The microbial degradation of organic matter is usually not carried out by one bacterium, but rather a complex network of microbial populations where microbes work together by performing different tasks that complement each other. Researchers who wish to study these important microorganisms and their relation to each other, encounter many technical challenges. One key bottleneck is that the vast majority of microorganisms that exist in nature cannot be grown and studied in the laboratory, which means a complete understanding of how they operate and collaborate is restricted. This project utilized recent advancements in molecular and computational technologies to create new knowledge into how microorganisms, which cannot be grown in the lab, can work together to perform important tasks in mammalian digestion as well as bio-industries. We developed methods that pieced together the DNA and proteins that are used by different microorganisms who work together in a community to convert organic material. Important fragments of DNA (called genes) and proteins were examined in detail and their suitability to industrial applications was also assessed. The "Back to Basics" project revealed exciting results that illustrated the cooperation between uncultured microbes, which play significant roles in dictating microbial conversion of biomass. We produced and analyzed several minimalistic model communities that contained the key microbial populations required to convert complex carbohydrates to useful metabolites. Using both culture-dependent and -independent approaches we revealed that key protein-degrading species that are known to numerically dominate industrial biogas plants, are in fact configured in complex populations of closely related strains that have genetically evolved via horizontal gene transfer to a plant biomass-degrading lifestyle. From the human gut, we uncovered a novel community of microbes, which work together to degrade xanthan, a commonly used dietary supplement that has hitherto believed to be resistant to microbial attack. We also uncovered that anaerobic fungi are major players in the rumen and produce many enzymes to degrade plant fiber. We further utilized novel computational approaches to demonstrate co-expression patterns between multiple strains and other specialist species, suggesting inter-population cooperation to perform critical functions (i.e. degrade complex carbohydrates) that are central to mammalian digestion as well as industrial processes such as biogas production and waste-water treatment.

One of the most significant outcomes arising from within Back2Basics, was the need (and value) of absolute quantification in meta-omics analyses, showing that it is both achievable without increasing excessively the experimental work and allows to answer questions concerning molecular level regulation and, more widely, making the samples (and different experiments) comparable. We introduced the novel concept of using the population-wide relationship (i.e. linearity) of the transcriptome and proteome as a proxy for the population activity. Moreover, when the relationships are compared among populations from the same community, the study of their trends (e.g. convergent, parallel, etc.) can identify metabolically intertwined microbes. The impact of such an approach is that it can "collapse" complex datasets into simplistic metrics in order to identify underlying community interactions and trends within "real world" microbiomes that contain huge levels of species diversity.

Microbial communities are renowned for the influences they exert in mammalian health and nutrition as well as in industrial applications. They encompass an extraordinary level of species complexity that includes symbiotic interactions between individual species including commensalism, synergism and mutualism. Our understanding of such interactions, whilst invaluable to the overall function of the community, is severely restricted due to this inherent species complexity and the fact that the majority of microbes that exist in nature cannot be cultivated. This project will address these core issues by applying a progressive interdisciplinary approach to decrypt microbial communities that perform the industrial relevant process of biomass conversion. The project aims to significantly advance our understanding of the microbial ecology of biomass turnover by capitalizing on newly created insight into synergistic interactions between uncultured microbial lineages. To achieve its objectives and building on recent innovative work by the applicant, the project will develop low-complexity biomass-degrading communities and employ predictive genome-reconstruction technologies to generate high precision genomes for all constituents. Community dynamics during biomass degradation will be visualized by mapping temporal transcriptomic and proteomic data over the lifetime of a growth cycle. Genes of interest will have their importance evaluated by reverse genetics (where possible), and suitable candidates will be characterised in detail and their pertinence to industrial applications interrogated. The project is expected to advance scientific understanding within key Norwegian research activities at the host university that all share a core reliance on conversion of plant cell wall material. Specifically, these activities entail: (1) polysaccharide converting enzymes in a biorefining context, (2) enhanced production of biogas and (3) agricultural feed production and conversion.