Omics Reveals Microbial Dark Matter In Soil.

Climate change has unknown consequences for the vast reserves of terrestrial carbon that are currently sequestered in soil. For example, warming is resulting in thaw of permafrost soil in the arctic thus increasing the accessibility of the previously frozen carbon pools to microbial degradation and greenhouse gas emission. Also, changes in precipitation patterns in the North American Great Prairie have unknown consequences on soil carbon reserves. In order to understand soil carbon sources and sinks as a result of climate change it is imperative to understand how microorganisms metabolize and cycle soil carbon. However, study of soil microorganisms is challenging due to the high soil microbial diversity and complexity of the soil matrix. In addition, the majority of soil microorganisms (>90%) have never been cultivated and their properties are unknown; thus analogous to Earths dark matter. To address this challenge we developed molecular approaches (omics) that bypass the necessity for cultivation to gain an understanding of the soil microbial community structure and function. For example, we used a combination of deep sequencing of 16S rRNA genes (microbiomics), total DNA sequencing (metagenomics), total RNA sequencing (metatranscriptomics) and shotgun community proteomics (metaproteomics) to determine the impact of permafrost thaw on soil microbial communities and functions in Alaska. We used the same combination of multi-omics tools to study native prairie soils. In Alaska, we looked at a site undergoing a natural thaw transition and thaw due to fire, as well as a transect across a site with permafrost deformations, known as polygons. In all cases there were dramatic changes in microbial community composition and function with thaw. Also in the prairie we developed a new set of tools to enable us to tackle the high microbial complexity and to simultaneously determine gene abundance and expression. The results of these studies indicate that soil microbial communities are responsive to climate change and that some key processes, including carbon cycling and greenhouse gas emissions, are altered as a result. Eventually these data should be used to better inform climate models.