Data analysis

4.12.1 Double-staining in sections

Vibratome sections were analysed at a two-channel confocal laser-scanning microscope (CLSM) using 10x to 63x objectives. Single optical section images (thickness 1-10µm) and maximum intensity images (thickness 10-150µm) were derived.

4.12.2 Triple-staining in cell cultures

Acutely dissociated cells were analysed using a fluorescence microscope with 63x oil objective. Quantitative analysis was performed by counting 50 cells of 10 to 15 different optical fields per coverslip that were chosen stochastically throughout the entire surface of the coverslip. In each field, the proportion of single-, double - and triple-labelled cells was determined. To evaluate the proportion of immunoreactive cells at a given stage, 100 phase bright cells of about 10 different optical fields per coverslip were analysed for their immunoreactivity.

20 different combinations of triple-stainings were used to examine and quantify the cell types detected by RC2-, GLAST- and BLBP-immunoreactivity. First we combined the RC2-, GLAST- or BLBP-antisera each in combination with cell type markers such as ß-tubulin-III- and/or Ki67- and/or nestin- and/or BrdU-staining. For example, the most frequently used combinations were RC2/ß-tub-III/Ki67; RC2/nest/Ki67; RC2/ß-tub -III/nest; GLAST/ß-tub-III/Ki67; GLAST/nest/Ki67; GLAST/ß-tub-III/nest; BLBP/ß-tub-III/nest; BLBP/ß-tub-III/BrdU; BLBP/nest/TEC3. These stainings revealed that almost all RC2-, GLAST- or BLBP-immunoreactive cells are precursor cells (see results). Combinations of two marker antigens (RC2/GLAST; RC2/BLBP; GLAST/BLBP) with Ki67- or nestin- or BrdU-staining further confirmed this. Since almost all RC2-, GLAST- and BLBP-immunoreactive cells were precursors, we could then use RC2/GLAST/BLBP-triple -labelling to quantify the contribution of the subtypes characterized by their antigenic profile to the progenitor pool (Fig. 5.4). Since our data have a standard error of the mean around 4 (Table 5.1), we excluded populations smaller than 5% for Figure 5.4.

Since these triple -stainings revealed which marker populations co-exist at a given time, we could use the stainings with two markers and Ki67 or nestin described

antigens, the size of the Ki67-only population in Fig. 5.4. For example, at E14 GLAST and BLBP were subpopulations of the RC2-immunoreactive precursors and therefore the proportion of RC2-negative, Ki67-positive cells was a direct measure of the Ki67- only population at this stage. In E16-18 cortex and E18 GE GLAST was contained in the largest population of precursors, comprising the RC2- and/or BLBP-positive cells. The Ki67-only fraction could therefore be evaluated as the Ki67-positive cells that are GLAST-negative. For the E16 GE, we used the triple -staining of RC2/GLAST/Ki67 to detect the fraction of Ki67-positive cells that were neither GLAST- nor RC2- immunoreactive.

4.12.3 Clonal analysis

For cell fate analysis in FACS- or retrovirus-experiments, clones were analysed for their composition of neurons, astrocytes, oligodendrocytes and precursor cells. Clones are discrete clusters of cells, derived from a single progenitor. The percentage of pure neuronal, pure non-neuronal and mixed clones was calculated per coverslip. Clones from sorted cells were detected by labelling with the antibodies M2 (mouse precursors and glial cells) and M6 (mouse neurons), detecting all mouse cells on the rat feeder layer (Malatesta et al. 2000). BAG-infected clones were detected by anti-ß-gal immunohistochemistry (see as well Table 4.2). M2M6 or anti-ß-gal respectively were combined with cell type specific markers like anti-ß-tubulin-III for neurons, anti-GFAP for astrocytes or anti-nestin for precursor cells (see as well Table 4.2). Clones were analysed at 40x magnification. The probability of clonal superimposition was calculated as described in Williams et al. (1991), e.g. for coverslips containing a maximum of 65 clones the probability was calculated to be 0.07, for those with 25 clones 0.02. The mean number of clones per coverslip obtained in our experiments was 32±2.

4.12.4 Analysis of the orientation of cell division

The analysis of the orientation of cell division at the ventricular surface was performed by different DNA-labelling methods (DAPI, PI or Yo-Pro-1-iodide staining). The plane of division respective to the ventricular surface was analysed: angles from 90-60° were interpreted as vertical, 60-30° as oblique and 30-0° as horizontal divisions. Sections were analysed at the fluorescence microscope or by CLSM.

4.12.5 3D-analysis of DiI-labelled ventricular zone cells

For examination of the morphology of ventricular zone precursor cells by ventricular DiI-labelling, injected brains were cut with a vibratome at 150µm thickness and slices were mounted in AquaPoly/Mount mounting medium. Sections were analysed immediately after cutting by CLSM, as after cutting DiI started to leak out from damaged labelled cells, resulting in high background fluorescence already after 1-2 days. Series of =1µm thick single optical section images (SOSI) were taken through the entire slice (stack of up to 200 SOSI). SOSI-stacks were reconstructed to 3D-images using Imaris™-Program. The analysis of the labelled cells then was performed using CorelPhotopoint, which allowed rota tion of the 3D-image step by step with an angle of about 5°. Only cells, where the soma and the entire process were discernable were taken into account for the analysis. Visualization of mitotic figures in DiI-labelled sections was performed by counterstaining with Yo -Pro-1- Iodide free floating.

4.12.6 Statistics

For all data sets, the arithmetic average ? ? ? n i i x n x 1 1

was calculated and the

standard deviation 1 ) ( 1 2 ? ? ?

?

and the standard error of the mean

n s

SEM ?

were computed. Error bars depict the SEM. The Student’s t-test was used to examine whether data sets differed significantly. Data were considered as significant with p<0.05 and as highly significant with p<0.01. Calculations of the arithmetic average, the standard deviation, the standard error of the mean were performed with Microsoft Excel. The significance of the obtained data was tested using the program Statistics W1.59.

4.13 Material