Verticillium wilt caused by Verticillium dahliae is a common soil-borne disease worldwide, affecting many economically important crop species. Soil microbes can influence plant disease development. We investigated rhizosphere and endosphere microbiomes in relation to cotton cultivars with differential susceptibility to Verticillium wilt. Soil samples from nine cotton cultivars were assessed for the density of V. dahliae microsclerotia; plants were assessed for disease development. We used amplicon sequencing to profile both bacterial and fungal communities. Unlike wilt severity, wilt inoculum density did not differ significantly among resistant and susceptible cultivars. Overall, there were no significant association of alpha diversity indices with wilt susceptibility. In contrast, there were clear differences in the overall rhizosphere and endosphere microbial communities, particularly bacteria, between resistant and susceptible cultivars. Many rhizosphere and endosphere microbial groups differed in their relative abundance between resistant and susceptible cultivars. These operational taxonomic units included several well-known taxonomy groups containing beneficial microbes, such as Bacillales, Pseudomonadales, Rhizobiales, and Trichoderma, which were higher in their relative abundance in resistant cultivars. Greenhouse studies with sterilized soil supported that beneficial microbes in the rhizosphere contribute to reduced wilt development. These findings suggested that specific rhizosphere and endosphere microbes may contribute to cotton resistance to V. dahliae.

Using biological control agents (BCAs) is an essential component of integrated pest and diseases management. Despite much research on biocontrol of plant diseases, success in field crops has been limited with most successes being achieved in greenhouse cultivation. This lack of success is often attributed to the complex ecological processes involved in biocontrol. We used next generation sequencing (NGS) technology to study environmental fate of Bacillus subtilis, a widely used BCA, focusing on its dispersal aspect in open field and under protection. The dispersal of B. subtilis was very limited, particularly under protection. The reduction in the BCA population size was relatively small within 8 days; indeed, no overall reduction in the relative abundance was observed under the protected condition. These results suggested that limited dispersal is probably the main reason for its variable (and often low) control efficacy under field conditions. Thus to increase biocontrol efficacy, it is necessary to frequently apply this BCA with the application interval depending on the growth rate of target host tissues. Phyllosphere microbiota differed significantly between plants grown in open field and under protection but were not greatly affected by the introduced BCA.

Quantification of Verticillium dahliae microsclerotia is an important component of wilt management on a range of crops. Estimation of microsclerotia by dry or wet sieving and plating of soil samples on semiselective medium is a commonly used technique but this method is resource-intensive. We developed a new molecular quantification method based on Synergy Brands (SYBR) Green real-time quantitative polymerase chain reaction of wet-sieving samples (wet-sieving qPCR). This method can detect V. dahliae microsclerotia as low as 0.5 CFU g(-1) of soil. There was a high correlation (r=0.98) between the estimates of conventional plating analysis and the new wet-sieving qPCR method for 40 soil samples. To estimate the inoculum threshold for cotton wilt, >400 soil samples were taken from the rhizosphere of individual plants with or without visual wilt symptoms in experimental and commercial cotton fields at the boll-forming stage. Wilt inoculum was estimated using the wet-sieving qPCR method and related to wilt development. The estimated inoculum threshold varied with cultivar, ranging from 4.0 and 7.0 CFU g(-1) of soil for susceptible and resistant cultivars, respectively. In addition, there was an overall relationship of wilt incidence with inoculum density across 31 commercial fields where a single composite soil sample was taken at each field, with an estimated inoculum threshold of 11 CFU g(-1) of soil. These results suggest that wilt risk can be predicted from the estimated soil inoculum density using the new wet-sieving qPCR method. We recommend the use of 4.0 and 7.0 CFU g(-1) as an inoculum threshold on susceptible and resistant cultivars, respectively, in practical risk prediction schemes.