Dynamic changes in bacterial community structure are associated with distinct priming effect patterns

Abstract

The addition of residues (maize straw) to soil stimulates microbial activity and significantly changes the decomposition rates of soil organic matter (SOM), which is referred to as priming effects (PEs). PE patterns are influenced by microorganisms utilising various substrates. However, the varied functional traits of keystone taxa and structure traits of the bacterial community associated with the PEs patterns remain elusive. Therefore, we established a microcosm by adding C4 maize residue (C4 plants have a different 13C signature than C3 plants) to C3 soil amended for 120 d to observe the dynamics of PEs. High-throughput sequencing techniques were used to detect the succession of bacteria; keystone taxa were identified using network analysis. Negative PE (early stage) and positive PE (late stage) were observed during residue decomposition. At the end of the incubation, residue with N resulted in a positive PE, while residue alone had a minimal effect on the decomposition of native SOC. Furthermore, the bacterial community structure displayed distinct successions during residue decomposition. Correspondingly, network analysis revealed differences in the keystone taxa between the early and late stages. Bacillus, Streptomyces, Arthrobacter, and Agromyces were the keystone taxa during the early stage, whereas BD2-11 terrestrial, Bacteroidales, Sphingomonadaceae, and Xanthomonadales were the keystone taxa at the late stage. These putative keystone taxa have different functional traits as drivers of community function, thus linking them to either negative or positive PE. In addition, network modules of bacterial communities differed in the early versus late stages and showed different module-trait relationships during PE. Therefore, the different modules are aggregated in response to distinct PE patterns. This study provides deeper insights into the network structure of bacterial community corresponding to PE patterns and highlights the importance of keystone taxa in PE.