AME 36:107-115 (2004)  -  doi:10.3354/ame036107

Tools for discrimination and analysis of lake bacterioplankton subgroups measured by flow cytometry in a high-resolution depth profile

Stefan Andreatta1, Manfred M. Wallinger1, Jaume Piera2,3, Jordi Catalan2,4, Roland Psenner1, Julia S. Hofer1, Ruben Sommaruga1,*

1Institute of Zoology and Limnology, University of Innsbruck, Technikerstrasse 25, 6020 Innsbruck, Austria
2Department of Ecology, University of Barcelona Diagonal 645, 08028 Barcelona, Spain
3Present address: Department of Signal Theory and Communications, Escola Politécnica Superior de Castelldefels (EPSC), Universitat Politécnica de Catalunya, Avenida Canal Olimpic s/n, 08860 Castelldefels, Barcelona, Spain
4Present address: Limnology Unit (CSIC-UB), Centro de Estudios Avancados de Blanes (CEAB), Accés a la Cala St. Francesc 14, 17300 Blanes, Spain
*Corresponding author. Email:

ABSTRACT: A 24 m deep mesotrophic lake was sampled at 25 cm depth intervals throughout the whole water column for flow cytometric analysis of bacterioplankton, with the object of (1) assessing the suitability of image analysis algorithms to objectively discriminate bacterial subgroups in natural samples; (2) testing 2 models to evaluate the effect of changes in signal intensity versus changes in the relative abundance of the individual subgroups on bulk cell properties of the bacterial community; and (3) to examine the suitability of a numerical index for quantifying small-scale spatial variability in cell abundance. Within the heterotrophic bacterial community, 5 subgroups were detected by image analysis of DAPI fluorescence versus side scatter (SSC) histograms. On average for the whole profile, 91% (range: 86 to 94%) of all measured bacteria belonged to the 5 subgroups. Along the depth profile, abundances within these subgroups showed trends which were different from that for the bacterial community as a whole. The comparison of the 2 numerical models suggested that shifts in average DAPI and SSC signals of the whole community are better explained by changes in relative abundance within individual subgroups rather than by signal shifts within individual subgroups. Spatial variability in cell abundance for most of the heterotrophic bacterioplankton subgroups was highest in the upper 4 m of the water column, corresponding to the zone of turbulent mixing, and between 9 and 12 m, at the depth of maximum picocyanobacterial abundance. Our results show that flow cytometry in combination with image analysis of DAPI-SSC histograms at the level of bacterial subgroups allow objective assessment of the structure of the bacterial community and underpin potential sources of small-scale variability in bacterioplankton distribution.


KEY WORDS: Bacteria · Bacterial subgroups · Flow cytometry · Image analysis · Turbulence · Temperature microstructure · Lakes


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