Changes in bacterioplankton metabolic capabilities along a salinity gradient in the York River estuary, Virginia, USA

Citation
Ge. Schultz et H. Ducklow, Changes in bacterioplankton metabolic capabilities along a salinity gradient in the York River estuary, Virginia, USA, AQUAT MIC E, 22(2), 2000, pp. 163-174
Citations number
55
Categorie Soggetti
Aquatic Sciences
Journal title
AQUATIC MICROBIAL ECOLOGY
ISSN journal
09483055 → ACNP
Volume
22
Issue
2
Year of publication
2000
Pages
163 - 174
Database
ISI
SICI code
0948-3055(20000908)22:2<163:CIBMCA>2.0.ZU;2-7
Abstract
Changes in metabolic capabilities of bacterial communities along the estuar ine salinity gradient may affect the extent of organic matter processing an d bacterial growth and accumulation during transit through the system; As p art of a larger study of estuarine microbial processes, we attempted to qua ntify differences in bacterial community structure using Biolog plates. Bio log GN plates (Biolog, Inc., Hayward, CA, USA) were used to determine diffe rences in bacterioplankton community metabolic potential. Biolog GN micropl ates are 96-well microtiter plates in which each well contains an individua l carbon source as well the redox dye tetrazolium violet. As bacteria grow and oxidize each substrate, a purple color is formed that can be quantified spectrophotometrically. The resultant patterns are a function of the origi nal community inoculated into the sample wells. Samples were taken weekly f rom May 1997 through May 1998 at a fixed location. Samples were also collec ted bi-monthly from July 1997 through May 1998 at 6 stations located along the salinity gradient. Principal component analysis shows clear differences in the patterns of community metabolic capabilities along the salinity gra dient. Bacterial communities were separated by both temperature and salinit y. Rates of color development mimicked the pattern of a strong landward gra dient in specific growth rates. Biolog analysis is shown to be a powerful t ool for identifying shifts in bacterial community composition in space and time, and provides a useful guide for deeper analysis of bulk property data .