Cover crops restore declining soil properties and suppress bacterial wilt by regulating rhizosphere bacterial communities and improving soil nutrient contents.

Bacterial wilt (BW) disease causes huge economic loss. Heretofore there is no effective way to completely control BW. Here, cover crops (pea, rapeseed, and wheat) were used to restore declining soil properties and control BW. Cover crops can increase content of soil organic matter, alkali-hydrolyzable nitrogen and enzymatic activities, as well as suppress BW. Different kinds of cover crops are distinguished in recovering different soil properties. For instance, rapeseed can inhibit BW more effectively than wheat and pea, while wheat has the best effect on increasing soil organic matter, urease, and invertase. Nevertheless, pea improves catalase better than rapeseed and wheat. Moreover, relative abundance of plant-beneficial bacteria in cover crop treatments is higher than that in the control, with a negative correlation with disease index. For example, wheat has the best effect on improving the growth of plant-beneficial bacteria, followed by rapeseed. The bacteria involved in nitrogen cycling are enriched in pea treatments. However, the relative abundance of pathogen and denitrifying bacteria in cover crop treatments is lower than that in the control, with a positive correlation with disease index. The count of bacteria genes involved in nutrients cycling, antibiotics synthesis, and biodegradation of toxic compounds in cover crop treatments is higher than that in the control. Wheat includes more these genes than rapeseed and pea. Overall, cover crops can restore declining soil properties and suppress BW by increasing soil nutrients and beneficial bacteria as well as decreasing pathogen. Among all cover crops, wheat is considered as the optimal one.

Microbial Network and Soil Properties Are Changed in Bacterial Wilt-Susceptible Soil.

Bacterial wilt disease is a devastating disease of crops, which leads to huge economic loss worldwide. It is hypothesized that the occurrence of bacterial wilt may be related to changes in soil chemical properties and microbial interactions. In this study, we compared the soil chemical properties and microbial network structures of a healthy soil (HS) and a bacterial wilt-susceptible soil (BWS). The contents of available nitrogen, potassium, and phosphorus and the soil pH in the BWS were significantly lower than those in the HS. BWS showed nutrient deficiency and acidification in comparison with the HS. The structure and composition of the BWS network were quite different from those of the HS network. The BWS network had fewer modules and edges and lower connectivity than the HS network. The HS network contained more interacting species, more key microorganisms, and better high-order organization and thus was more complex and stable than the BWS network. Most nodes and module memberships were unshared by the two networks, while the ones that were shared showed different topological roles. Some generalists in the HS network became specialists in the BWS network, indicating that the topological roles of microbes were changed and key microorganisms were shifted in the BWS. In summary, the composition and structure of the microbial network of the BWS were different from that of the HS. Many microbial network connections were missing in the BWS, which most likely provided conditions leading to higher rates of bacterial wilt disease.IMPORTANCE Bacterial wilt disease is caused by the pathogen Ralstonia solanacearum and is a widespread devastating soilborne disease leading to huge economic losses worldwide. The soil microbial community is crucial to the capacity of soils to suppress soilborne diseases through complex interactions. Network analysis can effectively explore these complex interactions. In this study, we used a random matrix theory (RMT)-based network approach to investigate the changes in microbial network and associated microbial interactions in a bacterial wilt-susceptible soil (BWS) in comparison to a healthy soil (HS). We found that the structure and composition of the microbial network in BWSs were quite different from those of the HS. The BWS network had fewer modules, edges, and key microorganisms and lower connectivity than the HS network. In the BWSs, apparently the topological role of microbes was changed and key microorganisms were shifted to specialists.