Comparison of metabolic capabilities across life history strategies of soil bacteria

Background/Question/Methods

Recent work by many scientists argues for the application of life history theory developed in macroorganisms to microbial ecology. Because life history theory explicitly considers the physiologic constraints imposed on organisms by their genetic potential, it can be a powerful conceptual framework for generalizing across the diversity of microorganisms. While recent application of single-gene based molecular approaches to bacterial communities have yielded insight into shifts in community membership along ecological gradients in soils, sediments, and water, still greater insight into community function can be gained by holistic consideration of entire genomes. This insight can be achieved by creating and refining a metabolic network, or map of all possible biochemical reactions occurring within an organism. Flux-balance analysis is a mathematical approach based on biotic and physicochemical constraints that can then be applied to determine movement of molecules through this map. This allows predictions of which biochemical reactions can be mediated by an organism and which are essential for it to grow. Using publicly-available genomic data, this project addresses two questions: Are there patterns in functional genome allocation strategies (a proxy for life history strategy) across soil bacteria? and Are these patterns reflective of differences in the metabolic capabilities of these organisms?

Results/Conclusions

Non-metric multidimensional scaling analysis paired with hierarchical clustering analysis of reveals four distinct clusters of functional genome allocation strategies found in soil heterotrophic bacteria. Non-significant Mantel tests suggest that these patterns in whole genome allocation to different functional groups of genes cannot be explained by evolutionary history (measured as phylogenetic distance based on 16S ribosomal sequence data) alone. Metabolic network reconstruction and flux balance analysis results demonstrate differences in metabolic capabilities among these genome allocation strategy groups. Taken together, these results suggest that differences in functional genome allocation strategies of organisms may have effects on ecosystem processes such as carbon degradation and soil respiration rates. Further adaptation of these methods to metagenomes could allow generation of testable predictions at a scale measurable in natural ecosystems and provide insight into the functional role of natural communities.