摘要
Pollution has a considerable effect on biological communities, in terms of size and diversity of the populations. Yet, the precise consequences of human activity on microbial communities in the marine environment are poorly understood. Therefore, in an ongoing collaborative research programme between Heriot-Watt University and the Ocean University of Qingdao, bacteria were isolated in 1999 and 2000 from marine sediment, seawater, seaweed, fish and shellfish, taken from locations in Shandong Province adjacent to Qingdao. Sampling locations were comprised of industrial and aquacultural sites and a clean, control site. In order to analyse microbial diversity, a polyphasic approach was adopted for characterisation of these isolates, specifically through examination of key phenotypic traits, i.e. using Biolog GN MicroPlate TM profiles, bacterial whole cell protein profiles and 16S and 23S rRNA gene sequences. These techniques yielded complex taxonomic data, which were subjected to statistical and cluster analyses. The application of these methods to studies of microbial communities is discussed.
Pollution has a considerable effect on biological communities, in terms of size and diversity of the populations. Yet, the precise consequences of human activity on microbial communities in the marine environment are poorly understood. Therefore, in an ongoing collaborative research programme between Heriot-Watt University and the Ocean University of Qingdao, bacteria were isolated in 1999 and 2000 from marine sediment, seawater, seaweed, fish and shellfish, taken from locations in Shandong Province adjacent to Qingdao. Sampling locations were comprised of industrial and aquacultural sites and a clean, control site. In order to analyse microbial diversity, a polyphasic approach was adopted for characterisation of these isolates, specifically through examination of key phenotypic traits, i.e. using Biolog GN MicroPlate TM profiles, bacterial whole cell protein profiles and 16S and 23S rRNA gene sequences. These techniques yielded complex taxonomic data, which were subjected to statistical and cluster analyses. The application of these methods to studies of microbial communities is discussed.
