Organization and operation of metabolic pathways in complex bacterial communities

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The nascent field of metagenomics, driven by innovations in high-throughput sequencing, has profoundly transformed our understanding of complex microbial communities (microbiomes). However, while much interest has focused on community composition, much less is known concerning the interactions and co-dependencies within these communities. Identifying and characterizing these relationships is key if we are to fully exploit emerging opportunities for metagenomics applications in biotechnology industries such as bioremediation and biofuels. Bioremediation involves the application of microbes to decontaminate sites polluted with toxic hydrocarbons such as benzene and offers an economically viable alternative to more traditional decontamination methods. In Canada alone, the market for the remediation of contaminated soil is thought to be worth $30 billion. However, while benzene degrading bacteria naturally present in soil, offer a potential route for bioremediation, they have been found challenging to culture outside more complex mixed cultures. Consequently there is an emerging paradigm that benzene degrading bacteria may be critically dependent on members of their microbiome to provide essential metabolic functions. Here we propose a program of research aimed at elucidating how metabolic activities are organized and operate within the context of complex microbial communities. Focusing on an experimentally amenable benzene degrading community, we will exploit this knowledge to yield insights into community perturbations that offer improved strategies for bioremediation. Although ambitious, this work builds on established successes in genome annotation, metabolic modeling and metagenomics. For example, in previous work, we have performed systematic surveys of the metabolic capacities for a variety of organisms and adopted sophisticated mathematical modeling frameworks to identify major routes of metabolic flux. In complementary work, we are developing innovative software tools and pipelines for elucidating microbial community function from meta-transcriptomic datasets. We propose two major objaectives: OBJECTIVE 1 Survey metagenomic datasets to identify metabolic co-dependencies with complex communities. We will first construct computational pipelines that derive robust metabolic reconstructions from metagenomic datasets generated through next generation sequencing technology. At the same time, integration of taxonomic information will allow enzymatic functions to be ascribed to specific taxa. Applying this pipeline to metagenomic datasets, we will characterize the partitioning of metabolic functions across a variety of microbiomes of increasing complexity. This survey will yield a first global view of the organization and operation of metabolic pathways across microbiomes. OBJECTIVE 2 Metabolic reconstruction and analysis of a benzene degrading community. To yield more mechanistic insights into the organization of metabolism within a microbiome, we will focus on a well characterized benzene degrading community. Metagenomic and metatranscriptomic datasets will be generated and processed to derive a detailed metabolic reconstruction of the community. Constraints based modeling will then systematically explore pathway fluxes between taxa and examine the impact of introducing additional species on community structure. Predictions from these analyses will be tested using an established in vivo model. In addition to deriving a more complete understanding of a community with bioremediation potential, we expect this interdisciplinary approach will lay the foundation for new fast-track strategies capable of characterizing the metabolic potential of any microbiome.