Abstract
Soil contains a diverse community of organisms; these can include archaea, fungi, viruses, and bacteria. In situ identification of soil microorganisms is challenging. The use of genome-centric metagenomics enables the assembly and identification of microbial populations, allowing the categorization and exploration of potential functions living in the complex soil environment. However, the heterogeneity of the soil-inhabiting microbes poses a tremendous challenge, with their functions left unknown, and difficult to culture in lab settings. In this study, using genome assembling strategies from both field core samples and enriched monolith samples, we assembled 679 highly complete metagenome-assembled genomes (MAGs). The ability to identify these MAGs from samples across a precipitation gradient in the state of Kansas (USA) provided insights into the impact of precipitation levels on soil microbial populations. Metabolite modeling of the MAGs revealed that more than 80% of the microbial populations possessed carbohydrate-active enzymes, capable of breaking down chitin and starch.