AME 22:103-110 (2000)  -  doi:10.3354/ame022103

Improvements in image analysis and fluorescence microscopy to discriminate and enumerate bacteria and viruses in aquatic samples

Alexander Shopov, Samanthia C. Williams, Peter G. Verity*

Skidaway Institute of Oceanography, 10 Ocean Science Circle, Savannah, Georgia 31411, USA
*Corresponding author. E-mail:

ABSTRACT: Commercial image analysis software includes functions for image filtering and segmentation, but few packages contain automated cell counting routines. Software capable of performing object enumeration functions adequately when samples contain brightly illuminated particles on a dark, even background. However, although current sample preparation protocols for aquatic bacteria and virus samples conceptually yield images ideal for such analysis, the reality can be quite different. Coastal and estuarine waters, in particular, contain considerable particulate organic matter which, when stained for epifluorescent microscopy, produces images incorporating numerous particles of different size, color, and optical density. We have modified an earlier automated image analysis protocol, in order to discriminate and analyze suspended cells based on size and optical density parameters, as well as cells associated with detrital matter. For the enumeration of free bacteria versus bacteria attached to detritus, this approach employs a color segmentation algorithm to create an alpha-channel mask of the detritus. This mask can then be used as a template over the original image, permitting enumeration of both free bacteria and attached bacteria. This software protocol can be used in conjunction with specific staining protocols to evaluate relationships among bacteria, viruses, and detritus in aquatic samples.


KEY WORDS: Image analysis · Bacteria · Viruses · Detritus · Microscopy


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