Network-Based Analysis for Large Soil Microbial Genomics Data

Early environmental microbe studies characterized a limited snapshot of microbial diversity. The availability of huge amount of genome sequence data from natural microbial consortia including soil environment enables integrated analysis to resolve the genetic and metabolic potential of microbial communities, to establish how functions are partitioned in and among populations, and to reveal how microbial communities evolve and adapt across multiple environments. we propose to analyze comparative microbial genomes from soil environment using network preservation analysis. The developed computational framework was able to identify functional modules and evaluate the functional roles of those modules in microbial communities as response to environmental change. We found modularized environmental adaptation among microbial communities. It is gene module instead of individual gene that serves as evolution unit in microbial communities. We demonstrate that modules with strong evidence of preservation contain ubiquitous pathways that contribute to the metabolism of major nutrient substances; while non-preserved modules include many environmentally dependent pathways that are expected to be responsive to environmental change. The developed computational framework has potential application to the study of rhizosphere bacterium and the study of plant-bacterium interactions.