The use of PCR based community profiling techniques to determine change in community structure and qPCR quantification of potato pathogens in soil under different temperature-moisture conditions over time

Abstract

Monitoring of pathogens levels in soil is an important tool for disease management and understanding pathogen ecology. Rapid pathogen detection methods that can quantify the pathogen are desired for routine pathogen detection. Rhizoctonia solani (R. solani), a soil borne pathogen that has 13 anastomosis groups (AGs) of which AG3-PT is the group frequently associated with disease in potatoes. A qPCR method described by Woodhall et al., (2013) was used to detect the quantity of R. solani in soil from a diseased potato field, kept under different moisture-temperature conditions in the greenhouse for 18 weeks. Another problematic pathogen in all the potato growing regions of the world is Pectobacterium, and in South Africa Pectobacterium carotovorum subsp. brasiliensis (Pcb) is the main causal agent for blackleg and tuber soft rot on potatoes. Using primers and probes designed by Woodhall (unpublished), a qPCR assay was designed for Pcb, and was used to detect Pcb in soil from a diseased field. Results showed that the qPCR protocols for R. solani and Pcb were able to detect very low quantities of the pathogens in the soil. ANOVA analysis for R. solani and Pcb showed that there was no statistical difference in the quantities of pathogens detected for the different moisture temperature combinations over time. However, at optimum growth temperatures (20oC) for R. solani and Pcb, more quantities of the pathogens were detected. Terminal restriction fragment length polymorphism was used to monitor change in microbial community structure for the soil under different moisture temperature combinations over 18 weeks. T-RFLP analysis results showed a dominant OTU of 71 base pairs that was present in all soil samples from the different moisture temperature combinations for all sampling times.