The extent of bacterial diversity in activated sludge

FIGUEROLA, ELM; ERIJMAN, L

Universidad Nacional de La Plata

Congreso; Segundo Congreso Argentino de Microbiología General; 2005

Sociedad Argentina de Microbiología General (SAMIGE)

Nonparametric and parametric estimators have been applied recently to analyze bacterial diversity in natural and engineered environments. In both cases, estimates were obtained with clone abundance from clone libraries and extrapolated to the larger samples. However, it is widely known that the abundance of PCR-amplified genes does not reflect the relative abundance of template DNA because of the several biases introduced during the amplification of rDNAs by PCR. The use of models of species abundance, which provide a more comprehensive description of the species diversity in a community, are additionally hindered because the lack of large datasets of bacterial diversity data to support their application. We propose a novel strategy based on the full-cycle rRNA approach, to describe the richness of bacterial populations present in activated sludge, circumventing the limitations of PCR-based analysis. DNA was isolated from sludge taken from the aeration basin of a full-scale industrial treatment plant receiving pretreated wastewater of an oil refinery. A total of 139 16S rRNA gene clones were sequenced for phylogenetic analysis and assigned to 46 OTUs. We have used eleven rRNA-targeted oligonucleotide probes for semi-quantitative fluorescence in situ hybridization analysis, specific for OTUs represented by at least five clones in the library, nine of which were designed in this study. The selected OTUs, which belonged to the classes Alpha and Beta of the Proteobacteria, and to different members of the phylum Acidobacteria, accounted for 63 + 3 % of the DAPI-stained cells. Other bacteria in the sludge, determined using phylum-level probes were Actinobacteria, Verrucomicrobia, Bacteroidetes and Firmicutes, each one represented with a single clone in the library, and Deltaproteobacteria and Planctomycetes, for which representative clones were not found in the 16S rRNA gene clone library. Due to the limited amount of data, none of the species abundance models fit optimally the abundance distribution. However, using FISH data to fit species abundance models shows promise for estimating total richness, because it displays the actual distribution of bacterial populations in a sample.