Community Analysis-based Screening of Plant Growth-promoting Bacteria for Sugar Beet.

Abstract

Clone libraries of bacterial 16S rRNA genes (a total of 1,980 clones) were constructed from the leaf blades, petioles, taproots, and lateral roots of sugar beet (Beta vulgaris L.) grown under different fertilization conditions. A principal coordinate analysis revealed that the structures of bacterial communities in above- and underground tissues were largely separated by PC1 (44.5%). The bacterial communities of above-ground tissues (leaf blades and petioles) were more tightly clustered regardless of differences in the tissue types and fertilization conditions than those of below-ground tissues (taproots and lateral roots). The bacterial communities of below-ground tissues were largely separated by PC2 (26.0%). To survey plant growth-promoting bacteria (PGPBs), isolate collections (a total of 665 isolates) were constructed from the lateral roots. As candidate PGPBs, 44 isolates were selected via clustering analyses with the combined 16S rRNA gene sequence data of clone libraries and isolate collections. The results of inoculation tests using sugar beet seedlings showed that eight isolates exhibited growth-promoting effects on the seedlings. Among them, seven isolates belonging to seven genera (Asticcacaulis, Mesorhizobium, Nocardioides, Sphingobium, Sphingomonas, Sphingopyxis, and Polaromonas) were newly identified as PGPBs for sugar beet at the genus level, and two isolates belonging to two genera (Asticcacaulis and Polaromonas) were revealed to exert growth-promoting effects on the plant at the genus level for the first time. These results suggest that a community analysis-based selection strategy will facilitate the isolation of novel PGPBs and extend the potential for the development of novel biofertilizers.