VOLUM OMAGIAL - Facultatea de Ştiinţe ale Naturii şi Ştiinţe Agricole

Simona Ghiţă et al. / Ovidius University Annals, Biology-Ecology Series 14: 127-137 (2010)
cell). Means of each column and the unit of measure
(pixels or micrometers) are presented in the end of
the file.
Image acquisition—Images for analysis were
done with a Canon digital camera. Brightness and
contrast were adjusted for the first image and kept
unchanged throughout the image acquisition
procedure. The images (1600 by 1200 pixels, 256
dpi) were acquired at 50x magnification and stored as
543-KB JPG files. Additional images acquired at
100x magnification were used to verify that
measurements of individual filaments/ bacteria were
independent of magnification
a) Acridin-orange stained filamentous
cyanobacteria isolated from mesothermal sulfurous
spring were analysed using Image J software for
distinguish heterocystous cells. First of all, the
original RGB image (Figure 10 A) were transformed
into 32-bit images, then we adjust the
brightness/contrast and also applied smooth or find
edges (Figure 10 B) option from processing images.
The same image were analysed with CellC software
(Fig. 10 C) to count the cells from filamentous
cyanobacteria or to measure the size of each cells.
A B
C
Fig 10. A – digital image of heterocystous
cyanobacteria isolated from sulphurous mesothermal
spring Obanul Mare (Mangalia) stained with AO; B –
find edges of panel A using ImageJ software; C- total
count analysis of panel A using CellC software (48
cells counted from cyanobacteria’s filaments).
Validation of any count were done using
manual count.
ImageJ software were used for
automated measuring cell’s length (µm), using a
133
calibrated eyepiece graticule as reference (Ardelean
et al, 2009).
Digital images from AO staining filaments of
cyanobacteria in microcosm were treated with ImageJ
to distinguish the heterocystous cell.
Fig 11. Cyanobacteria with heterocyst presence in
microcosm 2; AO staining (arrow indicate heterocyst
cell present in samples of microcosm supplemented
with gasoline).
To avoid uncertain estimates of filament length
and width, the number of filaments presented in one
image should not be too high. Extreme filament
densities would undoubtedly increase filament
overlap and lead to uncertain measurements unless
samples are diluted (Almesjö & Rolff, 2007).
We use a blue light epifluorescence filter set to
visualize AO-stained bacteria (N-400FL type). AO
stains both DNA and RNA so is used for the
enumeration of total bacteria.
In figure 12 A we present only an example of
digital analysis of fig.7 b: first, we adjust
contrast/brightness of digital image, then analyse
measure of graticula presented in fig. 7b and set the
calibration bar to determine correctly the length of
each bacteria treated with nalidixic acid. In B is
presented image analysis using CellC software.
A B
Fig 12. Image analysis program Image J (A) and
CellC (B) from microcosm 2, elongated cells at time
T4 (8hours)
b) DAPI were used to view filamentous
cyanobacteria isolated from mesothermal sulfurous