DISSERTATION RESEARCH: A trait-based approach for understanding the relationship between microbial community assembly and metabolic function

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Bacteria compose the majority of the planetary biodiversity and inhabit almost every corner of our planet. Bacteria are the engines that drive Earth's biogeochemical cycles and help to sustain life. Scientific papers are published daily on what types of bacteria live in every imaginable ecosystem. Scientists have found patterns of bacteria community composition in relation to environmental (e.g. temperature, pH, etc.) or host (e.g. disease history, cancer state, etc.) characteristics, but the underlying reasons for the observed patterns remain unclear. Connecting these patterns to a general conceptual framework of how microbes interact with each other and their environment will help scientists to better manage microbes in systems that directly affect people such as human pathogens and wastewater treatment plants. This research will be a step towards addressing this gap in knowledge by adapting frameworks developed in plant systems based on functional characteristics (traits) to microbial ecology, allowing examination of connections between lake bacterial diversity and ecosystems processes using a mechanistic approach. A computational workflow of this project's analysis will be publicly available and used to create open access online educational tools to aid in teaching computational analyses, scientific reproducibility, and programming literacy. Finally, this workflow will be put together to teach a half day workshop at the Ecological Society of America conference. This research examines how the relationship between bacterial diversity and secondary productivity is constrained by the traits that determine community assembly. Through a comparative genomic analysis of published and newly reconstructed bacterial genomes from environmental genomic data, this project will identify DNA-inferred (a) response traits that control the differences in bacterial community composition and (b) effect traits that determine the presence or absence of a diversity-productivity relationship. The identified genes and inferred traits will help expand current understanding of how bacterial community assembly and processes affect ecosystem function. This understanding will improve linkages between microbial community and ecosystem ecology principles.