Fully Automated Tracking Of Chloroplasts
In Elodea Leaf Cells From 4D Image Data
Johannes Zimmermann 1, Florian Leiss 1, Frank Sieckmann
2
– 1Definiens AG Munich, Germany, 2Leica Microsystems CMS GmbH, Mannheim, Germany
Introduction
Fully automated tracking of moving 3D structures in living cells represents several
challenges that are typical to the analysis of biological image data. Taking 4D image
data from chloroplasts in living Elodea leaf cells as an example we demonstrate
new approaches to meet these challenges (Figure 1). Chloroplasts are surprisingly
dynamic organelles: They move extensively throughout cells, they regularly split or
fuse and their shape changes constantly. A more detailed understanding of chloroand fusion. We use the SP5 confocal microscope (Leica Microsystems CMS GmbH)
Methods
plasts and background noise. Autoadaptive strategies are used to compute suitable
thresholds. A second challenge is the detection of individual chloroplasts and their
separation from other chloroplasts in the immediate vicinity. We detect potential
chloroplast seeds and employ local thresholds and shape criteria to successively grow
these seeds while keeping them separated from adjacent chloroplast seeds (Figure 2).
Chloroplasts are detected in 3D to allow volume measurements and the assessment
of shape parameters. The third challenge is the tracking of chloroplasts over time.
Individual chloroplasts need to be followed throughout the 4D data set in order to
Fig 1 Representative section of the original 4D data stack (left panel) and 3D reconstruction of a single time point (right panel). Choloroplasts are shown in green, the cell wall in red or dark green
from the close spatial proximity of chloroplasts, morphological similarities between
neighbor in the next time frame and successively increase the search range to ensure
optimal linking (Figure 3).
Conclusions
We demonstrate that fully automated tracking of chloroplasts in Elodea leaf cells
biological image analysis tasks.
Literature
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Fig 2 Intermediate steps of the analyis are represented to illustrate main strategies
Fig 3 Illustration of the approach for choroplast tracking. Chloroplasts are linked to their closest neigbour in the next time
frame. The search range is successively increased.
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