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Appl Environ Microbiol. 2006 Jun;72(6):4302-12.

Potential of a 16S rRNA-based taxonomic microarray for analyzing the rhizosphere effects of maize on Agrobacterium spp. and bacterial communities.

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  • 1UMR CNRS 5557/USC INRA 1193 Ecologie Microbienne, Universit├ę Claude Bernard (Lyon 1), 43 bd du 11 Novembre 1918, F-69622 Villeurbanne Cedex, France.


Bacterial diversity is central to ecosystem sustainability and soil biological function, for which the role of roots is important. The high-throughput analysis potential of taxonomic microarray should match the breadth of bacterial diversity. Here, the power of this technology was evidenced through methodological verifications and analysis of maize rhizosphere effect based on a 16S rRNA-based microarray developed from the prototype of H. Sanguin et al. (Environ. Microbiol. 8:289-307, 2006). The current probe set was composed of 170 probes (41 new probes in this work) that targeted essentially the Proteobacteria. Cloning and sequencing of 16S rRNA amplicons were carried out on maize rhizosphere and bulk soil DNA. All tested clones that had a perfect match with corresponding probes were positive in the hybridization experiment. The hierarchically nested probes were reliable, but the level of taxonomic identification was variable, depending on the probe set specificity. The comparison of experimental and theoretical hybridizations revealed 0.91% false positives and 0.81% false negatives. The microarray detection threshold was estimated at 0.03% of a given DNA type based on DNA spiking experiments. A comparison of the maize rhizosphere and bulk soil hybridization results showed a significant rhizosphere effect, with a higher predominance of Agrobacterium spp. in the rhizosphere, as well as a lower prevalence of Acidobacteria, Bacteroidetes, Verrucomicrobia, and Planctomycetes, a new taxon of interest in soil. In addition, well-known taxonomic groups such as Sphingomonas spp., Rhizobiaceae, and Actinobacteria were identified in both microbial habitats with strong hybridization signals. The taxonomic microarray developed in the present study was able to discriminate and characterize bacterial community composition in related biological samples, offering extensive possibilities for systematic exploration of bacterial diversity in ecosystems.

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