How microbial communities contrast with respect to taxonomic and functional composition within and between soil ecosystems remains an unresolved question that is central to modeling soil functioning and services. This is especially relevant for remote, northern latitude soils, which are challenging to sample and are also thought to be more vulnerable to climate change compared to temperate soils. While several soil metagenomes from various soil habitats have recently become available, their analysis is limited by the high complexity of these datasets, which typically prevents robust assembly and population binning analyses, and the methods available such as the analysis of 16S rRNA gene sequences, which offer limited resolution. The team proposes to develop new approaches to enable the analysis of soil microbial communities at the important level of ecosystem functioning, i.e., the individual population level. In particular, they will advance and optimize the read recruitment plots in order to provide key information for assessing the diversity and function of a population. The resulting information will allow researchers to identify which populations are widespread within specific soil ecosystems and thus, establish them as model organisms for studying carbon cycling within the corresponding ecosystems, and reveal what gene functions are differentially abundant and thus, selected by different ecosystems.
Proposer: Kostas Konstantinidis, Georgia Institute of Technology
Proposal: Assessing Microbiomes at the Individual Population Level: Tool Development and Applications to Soil Carbon Cycling