Automated Microscopy

The filtration of water-samples onto track-etch membrane-filters and subsequent multiple staining, for example by fluorescence in-situ hybridization (FISH) and unspecific DNA-staining offers a fast and quantitative way to analyze microbial populations in freshwater as well as in marine environments. The most time-consuming and tedious step in this procedure is the manual evaluation of the filters by epifluorescence microscopy. To overcome this problem we created a fully automated system for image-acquisition and analysis of large numbers of samples. The core of the system is a motorized epifluorescence microscope (AxioImager.Z1, Zeiss, Germany) including a motorized stage capable of holding eight slides. The microscope was programmed with Visual Basic for Applications (VBA) included in the Zeiss software AxioVision. With an object oriented programming approach, following a widely used software-engineering standard, the rational unified process, we developed a user-friendly system for high-throughput analysis of multiple stained microscopic preparations. The system is able to process up to eight microscopic slides with filter pieces without user-interaction beyond loading the stage and setting initial parameters. The filter-pieces on the slides are automatically recognized by the system and a number of fields for image acquisition specified by the user are equally distributed on each filter-piece. The user can chose up to three fluorescence channels in which he wants to acquire images for each field. Additionally, bright field image stacks may be taken to evaluate microautoradiography preparations. After automated image acquisition and image quality check, a set of image analysis routines can be used for the evaluation of different kind of experiments (single-, double-, triple-staining and microautoradiography). Moreover, cell volumes can be calculated and a morphological classification can be done automatically. Finally, a report is generated and detected cells are annotated in the images giving the user full transparency on the counting routines. This automated system shortens the time of an entire experiment by a factor of about 5. We are confident that this new system will on one hand simplify, and on the other hand allows the creation of larger sets of data in future ecological studies.

Planktothrix Quantification

The filamentous cyanobacterium Planktothrix rubescens is a highly interesting organism and of prime importance in the context of microbial ecology and drinking water quality control. It produces a variety of potent toxins that may threaten animal and human health and by its ability to form massive blooms in some freshwaters it can easily dominate the entire bacterioplankon in an aquatic system. Although the abundance of this organism is generally low compared to bacterial abundance, it can overwhelm bacterial biomass by its large cell size. P. rubescens filaments are about 5 – 8 micrometer in diameter and up to several millimeters in length. The large variation in length implicates that the mere counting of filaments in a water sample is not sufficient to determine the biovolume. It is necessary to measure the length of individual filaments. This can be achieved in an automated manner by microscopy and image analysis. However, the enormous elongation of Planktothrix filaments leads to the fact that filaments on microscopic preparations often cross each other. Crossing objects are generally difficult to analyze separately by image analysis. Therefore, a computer program was developed following a model-based object-oriented image analysis approach (1). It allows for counting and sizing individual filaments on fluorescent images in a high-throughput manner. The program is freely available (see ‘software’ section). We are confident that this method allows to asses the Planktothrix distribution in the water body in higher spatial and temporal resolution and that the filament-length distribution will give further clues on the nature of this fascinating organism.

(1) Zeder M, Van den Wyngaert S, Köster O, Felder KM, Pernthaler J.
Automated quantification and sizing of unbranched filamentous cyanobacteria by model based object oriented image analysis.
Appl Environ Microbiol. 2010 Jan 4. [Epub ahead of print]