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Applied and Environmental Microbiology, January 2007, p. 421-431, Vol. 73, No. 2
0099-2240/07/$08.00+0     doi:10.1128/AEM.01849-06
Copyright © 2007, American Society for Microbiology. All Rights Reserved.

Longitudinal Changes in the Bacterial Community Composition of the Danube River: a Whole-River Approach ^,

Institute of Chemical Engineering, Department for Applied Biochemistry and Gene Technology, Vienna University of Technology, Getreidemarkt 166-169, 1060 Vienna, Austria,⁴ Microbial Ecology and Biogeochemistry Group, CNRS, Laboratoire d'Océanographie de Villefranche, BP 28, 06234 Villefranche-sur-Mer CEDEX, France, and Université Pierre et Marie Curie-Paris 6, Laboratoire d'Océanographie de Villefranche, BP 28, 06234 Villefranche-sur-Mer CEDEX, France,¹ Wasserkluster Lunz-Inter Universitary Cluster for Water Research Lunz, Carl Kupelwieser Promenade 5, 3293 Lunz/See, Austria,² Federal Agency for Water Management, Pollnbergstrasse 1, 3252 Petzenkirchen, Austria³

Received 4 August 2006/ Accepted 25 October 2006

The Danube River is the second longest river in Europe, and its bacterial community composition has never been studied before over its entire length. In this study, bacterial community composition was determined by denaturing gradient gel electrophoresis (DGGE) analysis of PCR-amplified portions of the bacterial 16S rRNA gene from a total of 98 stations on the Danube River (73 stations) and its major tributaries (25 stations), covering a distance of 2,581 km. Shifts in the bacterial community composition were related to changes in environmental conditions found by comparison with physicochemical parameters (e.g., temperature and concentration of nutrients) and the concentration of chlorophyll a (Chl a). In total, 43 distinct DGGE bands were detected. Sequencing of selected bands revealed that the phylotypes were associated with typical freshwater bacteria. Apparent bacterial richness in the Danube varied between 18 and 32 bands and correlated positively with the concentration of P-PO₄ (r = 0.56) and negatively with Chl a (r = –0.52). An artificial neural network-based model explained 90% of the variation of apparent bacterial richness using the concentrations of N-NO₂ and P-PO₄ and the distance to the Black Sea as input parameters. Between the cities of Budapest and Belgrade, apparent bacterial richness was significantly lower than that of other regions of the river, and Chl a showed a pronounced peak. Generally, the bacterial community composition developed gradually; however, an abrupt and clear shift was detected in the section of the phytoplankton bloom. Large impoundments did not have a discernible effect on the bacterial community of the water column. In conclusion, the riverine bacterial community was largely influenced by intrinsic factors.

Published ahead of print on 3 November 2006.

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