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

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.

Metagenomic analysis of the bacterial community associated with the taproot of sugar beet.

We analyzed a metagenome of the bacterial community associated with the taproot of sugar beet (Beta vulgaris L.) in order to investigate the genes involved in plant growth-promoting traits (PGPTs), namely 1-aminocyclopropane-1-carboxylic acid (ACC) deaminase, indole acetic acid (IAA), N2 fixation, phosphate solubilization, pyrroloquinoline quinone, siderophores, and plant disease suppression as well as methanol, sucrose, and betaine utilization. The most frequently detected gene among the PGPT categories encoded ß-1,3-glucanase (18 per 10(5) reads), which plays a role in the suppression of plant diseases. Genes involved in phosphate solubilization (e.g., for quinoprotein glucose dehydrogenase), methanol utilization (e.g., for methanol dehydrogenase), siderophore production (e.g. isochorismate pyruvate lyase), and ACC deaminase were also abundant. These results suggested that such PGPTs are crucially involved in supporting the growth of sugar beet. In contrast, genes for IAA production (iaaM and ipdC) were less abundant (~1 per 10(5) reads). N2 fixation genes (nifHDK) were not detected; bacterial N2 -fixing activity was not observed in the (15)N2 -feeding experiment. An analysis of nitrogen metabolism suggested that the sugar beet microbiome mainly utilized ammonium and nitroalkane as nitrogen sources. Thus, N2 fixation and IAA production did not appear to contribute to sugar beet growth. Taxonomic assignment of this metagenome revealed the high abundance of Mesorhizobium, Bradyrhizobium, and Streptomyces, suggesting that these genera have ecologically important roles in the taproot of sugar beet. Bradyrhizobium-assigned reads in particular were found in almost all categories of dominant PGPTs with high abundance. The present study revealed the characteristic functional genes in the taproot-associated microbiome of sugar beet, and suggest the opportunity to select sugar beet growth-promoting bacteria.

An assessment of the diversity of culturable bacteria from main root of sugar beet.

The partial sequences of the 16S rRNA genes of 531 bacteria isolated from the main root of the sugar beet (Beta vulgaris L.) were determined and subsequently grouped into 155 operational taxonomic units by clustering analysis (≥99% identity). The most abundant phylum was Proteobacteria (72.5-77.2%), followed by Actinobacteria (9.8-16.6%) and Bacteroidetes (4.3-15.4%). Alphaproteobacteria (46.7-64.8%) was the most dominant class within Proteobacteria. Four strains belonging to Verrucomicrobia were also isolated. Phylogenetic analysis revealed that the Verrucomicrobia bacterial strains were closely related to Haloferula or Verrucomicrobium.