Bacterioplankton in the Chesapeake Bay: Genetic diversity, population dynamics and community proteomics
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Although the ecosystem of the Chesapeake Bay has been studied extensively, little is known about the genetic diversity, population dynamics and metabolic activity of bacterioplankton living in the Bay. In this study, clone libraries containing the rRNA operon (16S rRNA-ITS-23S rRNA) were constructed from samples collected from the Chesapeake Bay to study spatial and temporal dynamics of estuarine bacterioplankton. Major bacterial groups changed dramatically between cold and warm seasons. In the summer, Alpha- and Gammaproteobacteria, Bacteroidetes (Flavobacterium-Bacteroidetes-Cytophaga), Cyanobacteria and Actinobacteria were the dominant groups while in the winter, Alpha- and Betaproteobacteria, and Actinobacteria were commonly found. Clone library analysis also revealed dramatic shifts in bacterial species composition between seasons. Unique SAR11, SAR86, and Roseobacter clades were discovered in the Chesapeake Bay, suggesting the ecological adaptation of organisms endemic to the Bay or perhaps, large temperate estuaries. The bacterioplankton populations were monitored from 2002 to 2004 by denaturing gradient gel electrophoresis (DGGE) of PCR-amplified 16S rRNA gene fragments. Remarkable seasonal shifts and repeatable annual patterns were identified. Temporal variation of bacterial communities was best explained by the change of chlorophyll a (Chl a) and water temperature, while other factors such as dissolved oxygen, ammonia, nitrite and nitrate, and viral abundance also contributed to the seasonal succession of bacterial populations. In order to understand ecological functions of microbes living in the natural environment, a community-based proteomic approach was developed. Typically, a few hundred-protein spots were visualized based on two-dimensional gel electrophoresis (2-DGE) from Chesapeake Bay microbial communities (0.2 to 3.0 µm filtered fractions). Distinct seasonal patterns and noticeable spatial variations of Chesapeake Bay metaproteomes were observed and the metaproteomic patterns correlated with genetic fingerprints based on 16S rRNA-DGGE. Six protein spots were characterized by LC-MS/MS and three of them were most closely related to the genes in the Sargasso Sea metagenomic database. We proved for the first time that metaproteomics could be applied to a complex marine microbial community. Our results indicate that community proteomics has great potential to unveil novel microgeochemical functions and to link microbial functions to their population structures.