1887

Abstract

Nodule isolates from 11 species of wild legumes in north-western China were characterized by numerical taxonomy, PCR-based 16S rRNA gene RFLP and sequence analyses, DNA-DNA hybridization, restriction patterns of and genes, and symbiotic properties. Based on the results of numerical taxonomy, most of the 35 new isolates were grouped into five clusters (clusters 7, 9, 12, 14 and 15). Clusters 7 and 12 were identified as and , respectively, based on their high DNA homologies with the reference strains for these species, their 16S rRNA gene analysis and their phenotypic features. Results of 16S rDNA PCR-RFLP analysis showed that cluster 9 belonged to . Clusters 14 and 15 were identified as based on their moderately slow-growing, acid-producing characters and the high similarity of their 16S rDNA PCR-RFLP patterns to those of species. These two clusters were genomic species distinct from all described species based on analysis of DNA relatedness within this genus. The isolates in cluster 12 () failed to nodulate their original host and other selected hosts and they did not hybridize to gene probes. The possibility of opportunistic nodulation of these isolates is discussed. Identical restriction patterns were obtained in the gene hybridization studies from the three isolates within cluster 15, which were isolated from the same host species. The isolates from different host plants in each of clusters 9 and 14 produced different RFLP patterns, but similar RFLP patterns appeared (one band for each isolate). Different patterns were observed among different clusters from both the and gene hybridization studies. Cross-nodulation was recorded among the isolates and the host plants in the same cluster and promiscuous properties were found among some of the hosts tested.

Loading

Article metrics loading...

/content/journal/ijsem/10.1099/00207713-49-4-1457
1999-10-01
2019-11-18
Loading full text...

Full text loading...

http://instance.metastore.ingenta.com/content/journal/ijsem/10.1099/00207713-49-4-1457
Loading

Most Cited This Month

This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error