As a new technique for DNA fingerprinting, denaturing gradient gel electrophoresis (DGGE) can be used for microbial diversity analysis in environmental samples. In this study, PCR-DGGE was applied to analyze the microbial communities in lake sediments. Sediment samples from seven locations in three lakes were collected and their genomic DNA was directly extracted. The DNA yield of sediments of Lake Xuanwu and Lake Mochou was high (10μg/g), while that of sediments in Lake Taihu was relatively low. After DNA purification, the 16S rRNA genes (V3 to V5 region) were amplified with two universal primers (F341GC and R907). These amplified DNA fragments were separated by parallel DGGE.
The DGGE profiles indicate different bands’ patterns for different samples. There are five common bands in all lake sediment samples, which indicate that there are similarities among the populations of microorganisms that exist in all lake sediments. But, the specific bands in sediment samples indicate that the microbial communities in different lakes are different. The DGGE profiles of Lake Xuanwu and Lake Mochou are very similar and about twenty types of microorganisms are identified in the sediment samples of both lakes. These results suggest that the sediment samples of these two city lakes (Xuanwu, Mochou) have similar microbial communities. However, the DGGE profiles of sediment samples in Lake Taihu are significant different from these two lakes. Furthermore, the DGGE profiles of sediment samples in different locations in Lake Taihu are also very different, which suggests that the microbial communities in Lake Taihu are more diversified than those in Lake Xuanwu and Lake Mochou. The differences in microbial diversity may be caused by the different environmental conditions, such as redox potential, pH, and the concentrations of organic matters, etc.
Seven major bands of 16S rDNA genes fragments from DGGE profiles of sediment samples were further eluted from gel, reamplified and sequenced. The sequences of these fragments were compared with the database in GeneBank (NCBI). The results indicate that five sequences share 99%～100% homology with known sequences (Bacillus and Brevibacillus, uncultured bacteria), while the other two sequences share 96% ～ 93% homology with known sequences (Acinetobacter and Bacillus).
These results indicate that the PCR-DGGE technique combined with sequences determination is a feasible and efficient method for microbial community analysis in sediment samples.