ABSTRACT
Soil microbial communities act on important environmental processes, being sensitive to the application of wastes, mainly those potential contaminants, such as tannery sludge. Due to the microbiome complexity, graph-theoretical approaches have been applied to represent model microbial communities interactions and identify important taxa, mainly in contaminated soils. Herein, we performed network and statistical analyses into microbial 16S rRNA gene sequencing data from soil samples with the application of different levels of composted tannery sludge (CTS) to assess the most connected nodes and the nodes that act as bridges to identify key microbes within each community. The network analysis revealed hubs belonging to Proteobacteria in soil with lower CTS rates, while active degraders of recalcitrant and pollutant chemical hubs belonging to Proteobacteria and Actinobacteria were found in soils under the highest CTS rates. The majority of classified connectors belonged to Actinobacteria, but similarly to hubs taxa, they shifted from metabolic functional profile to taxa with abilities to degrade toxic compounds, revealing a soil perturbation with the CTS application on community organization, which also impacted the community modularity. Members of Actinobacteria and Acidobacteria were identified as both hub and connector suggesting their role as keystone groups. Thus, these results offered us interesting insights about crucial taxa, their response to environmental alterations, and possible implications for the ecosystem.
