The genetic diversity among strains in a worldwide collection of Ralstonia solanacearum, causal agent of bacterial wilt, was assessed by using three different molecular methods. PCR-RFLP analysis of the hrp gene region was extended from previous studies to include additional strains and showed that five amplicons were produced not only with all R. solanacearum strains but also with strains of the closely related bacteria Pseudomonas syzygii and the blood disease bacterium (BDB). However, the three bacterial taxa could be discriminated by specific restriction profiles. The PCR-RFLP clustering, which agreed with the biovar classification and the geographical origin of strains, was confirmed by AFLP. Moreover, AFLP permitted very fine discrimination between different isolates and was able to differentiate strains that were not distinguishable by PCR-RFLP. AFLP and PCR-RFLP analyses confirmed the results of previous investigations which split the species into two divisions, but revealed a further subdivision. This observation was further supported by 16S rRNA sequence data, which grouped biovar 1 strains originating from the southern part of Africa.

Ralstonia solanacearum is a known bacterial pathogen of eucalypt and potato plants in Africa. A survey was undertaken to detect this pathogen in eucalypt plantations in South Africa, the Democratic Republic of Congo, and Uganda. Numerous bacterial strains were isolated from trees with symptoms typical of bacterial wilt, but only seven were positively identified as R. solanacearum. A polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) technique, based on the hrp (hypersensitive response and pathogenicity) gene region was used to determine and group the biovars of these R. solanacearum strains. The eucalypt isolates and one potato isolate formed a biovar 3 cluster, whereas the two other potato isolates formed a cluster that corresponded to biovar 2. Amplified fragment length polymorphism (AFLP) analysis confirmed these clusters. Therefore, PCR-RFLP can be used as a reliable diagnostic technique to enable researchers to rapidly identify the pathogen.