Gene expression profiling of ACSA-2 and GLAST positive astrocytes of the neonatal cerebellum was performed to investigate the transcriptome of the identified subpopulations. Therefore, ACSA-2+/GLAST-, ACSA-2+/GLAST+/- and ACSA-2-/GLAST+ cells were isolated based on the established protocols by magnetic cell separation (Supplementary Fig. 11). The purities between the biological triplicates were comparable as analyzed by marker co-stainings. ACSA-2+/GLAST- cells were enriched to 70% (± 5%), ACSA-2+/GLAST+/- to 87% (± 7%) and ACSA-2-/GLAST+ cells to 75% (± 5%). The cDNA microarray was processed as described in chapter 2.5.5. In the first step, the gene expression profile over all genes was investigated for all sample groups. In an unsupervised hierarchical clustering the gene expression of each group was compared with the gene expression of another group using correlation matrix (Fig. 3.37). This analysis was chosen to quantify the similarity between the three populations of the cerebellum. In the correlation matrix, low gene expression levels are indicated by black color and high gene expression levels is indicated by red color. As seen in Figure 3.37 gene expression levels were similar between sample groups. In addition, the pairwise distance analysis revealed that ACSA-2+/GLAST+ samples presented an intermediate group between ACSA-2+/GLAST- and ACSA-2-/GLAST+ samples. However, ACSA-2+/GLAST+ samples were closer related to ACSA-2+/GLAST- samples than to ACSA-2-/GLAST+ as shown in
Figure 3.37.
Figure 3.37: Sample clustering.
In the first step, the unprocessed data set was clustered according to the samples groups. This clustering was visualized using MeV. Correlation coefficients are indicated by their color from black (0) to red (1.0). Replicates for each sample group clustered together, indicating a specific expression profile within one group. Sample labeling according to Supplementary Fig. 12.
Results
As mentioned before,
ACSA-2+/GLAST- cells contribute to the ACSA-2+/GLAST+/- sample set. Therefore, in subsequent analysis the
ACSA-2+/GLAST- sample set and theACSA-2+/GLAST- sample set were compaired against each other to identify the highest
discriminatory regulated genes. The total number of genes addressed by the microarray were 55681. As visualized by a Volcano plot the data set was reduced to 91 candidates overexpressed in the ACSA-2-/GLAST+ group and 380 candidates overexpressed in the ACSA-2+/GLAST- usingstringent filtering ((Fig. 3.38 a) Gene lists are given in AppendixII).
Figure 3.38: Volcano plot of preselected genes.
The Volcano plot is a tool to visualize fold change and p-values of genes as scatter plot.
In total 5581 genes were addressed by the array (a). Normalized gene samples with a p-value less than 0.05 (Tukey’s range test) and less than one outlier per sample group are shown in b. By furtherprocessing the data set was grouped into genes with a fold change of 2/-2 and 4/-4 corresponding to a log_2 ratio of 2/-2 (b,c). Genes with log_2 ratios of 2/-2 were considered in subsequent analysis All Volcano plots were generated in Prism.
In subsequent steps both gene lists were used to identify bias towards biological processes and pathways (Table 6). Genes were categorized to gene ontology families by their gene identifier. However, gene ontology listing is not redundant and genes can therefore be categorized into different gene ontology families. Functional classes such as ‘receptor signaling’, ‘cellular import and export’ as well as ‘intracellular trafficking’ and ‘proliferation’ were significantly upregulated in the ACSA-2+/GLAST- sample sets and were not identified in
the ACSA-2-/GLAST+ samples (Table 6). The ‘receptor signaling’ cluster comprised several
solute carrier transporter which are important for the uptake of biologically active compounds and metabolites 233. This suggests that ACSA-2+/GLAST- cells already acquired a certain
function and show less plasticity. Families such as ‘development’, ‘cell differentiation/migration’ or ‘extracellular matrix proteins’ were found in both gene groups. However, single genes were never identified in both sample groups as shown by Venn diagrams.
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Table 6: Pathway families
In the ACSA-2
-/GLAST
+sample set
CXCR4, which was shown to control migration of the cerebellar development at embryonic stage was identified 233. Besides, different genes ofthe Wnt pathway such as Frizzled-1 or Wif1 but also fgf8 were identified (Fig. 3.39). Fgf8 is important for the development of the cerebellum 234. The members of the Wnt family are also important for development but furthermore for the regulation of cell fate and proliferation as well as for migration 235. In addition, members of the sonic hedgehog family including Gli1 the
hedgehog interacting protein (hhip) and patched homologue 2 (Ptch2) were significantly upregulated. Also Hes5, reflecting Notch signaling activity in the progenitor pool was identified 236. However, Hes5 was rather weak expressed in 2 from 3 samples of the
ACSA-2-/GLAST+ sample set. All three pathways, SHH, Wnt and Notch are described to
influence cell fate specification 237. The enrichment of these genes suggests that ACSA-2-
/GLAST+ are at an early developmental state. To address this further, stem cell factors such as Nestin (Nes) 70 were investigated and revealed to be significantly upregulated in the
ACSA-2-/GLAST+ sample set. In addition, upregulation of the Lgr5 gene was detected. The
Lgr5 protein is reported to be expressed by distinct stem or progenitor cells in various tissues 238,239. Common stem cell factors known to be expressed by embryonic stem cells (Klf-
4, Nanog, Sox-2 240) were suppressed in the ACSA-2-/GLAST+ samples. This indicates that ACSA-2-/GLAST+ are restricted stem cells.
The sample set was further investigated for the expression of Parvalbumin, a marker for interneurons, 241 which was seen to be expressed by the ACSA-2-/GLAST+ transplants, as shown in chapter 3.6.4. In correlation to the transplantation experiment the expression of Pvlb
Results
was significantly upregulated in the ACSA-2-/GLAST+ sample set. In addition, pancreas
transcription factor 1 subunit alpha (Ptf1a), which is specifically expressed on VZ derived cells and important for the generation of interneurons was upregulated on ACSA-2-/GLAST+ cells 242. Furthermore, Ascl1 (Mash1), which is predominat expressed by cells of the
prospective white matter cells was upregulated in the ACSA-2-/GLAST+ sample set 243
(Fig. 3.39 b). As reported by Leto et al. prospective white matter cells compose a defined neurogenic niche in the cerebellum 244. In contrast, the ACSA-2-/GLAST+ sample set did not show an enrichment for serotonergic or domaminergic neurons marked by Nk2-2, PTEN, or
OTX-2, Lmx1a 240,245 (Fig. 3.39 c). Furthermore, the GAD1 gene encoding the GAD67
transporter and doublecortin (Dcx) a microtubule-associated protein expressed by interneurons of the SVZ/RMS were suppressed in the ACSA-2-/GLAST+ sample set. This indicates that ACSA-2-/GLAST+ cells are primed to differentiate into GABAergic interneurons. The oligodendrocyte specific gene Mbp was further identified and differentiation into oligodendrocytes was seen in the transplantation experiment (Supplementary Fig. 15). In addition, the glial marker Tenascin C, which is reported to be expressed by radial glia and Bergmann glia of the cerebellum was enriched in the ACSA-2-/GLAST+ sample set 246. GFAP
was weak expressed in the ACSA-2-/GLAST+ sample set. In summary, this analysis indicates
that a specification of t he ACSA-2-/GLAST+ cells towards a GABAergic cell type as well as to a glia cell type is favoured. Based on the transplantation experiment and the gene expression profiling it is likely that prospectic white matter cells can be characterized by the absence of ACSA-2expression and the prescence of GLASTexpression.
Results
Figure 3.39: Clustering of genes upregulated in the ACSA-2-/GLAST+ sample set.
Data set was preprocessed using quantil normalization. Samples were compared using ANOVA. Samples with a p-value less than 0.05 (Tukey’s range test), less than one outlier per sample group, a log_2 ratio of (2/-2) were considered for this analyses. Samples of ACSA-2+/GLAST- (A+/G-), ACSA-2+ /GLAST+ (A+/G+), ACSA-2-/GLAST+ (A-/G+) were
visualized using MeV. Correlation co-efficients are indicated by their color from blue (-6) to yellow (+3) (a). Data was further illustrated as bar diagrams. Triplicates of normalized log_2 intensities are indicated as Mean ± SD (b).
In the ACSA-2+/GLAST- sample set several genes of extracellular matrix epitopes such as Gjb2, Gjb6, Gja1 encoding connexin 26, 30 and 43 were found. All of these hemichannels are reported to be only expressed by astrocytes 247. Besides, tetraspanin (CD82) and vitronectin
(VTN) that promote cell adhesion were identified in the ACSA-2+/GLAST- sample set (Fig.
3.40). Furthermore, genes of the slit family, which interact with ligands expressed by neurons, were upregulated in the ACSA-2+/GLAST- samples. These genes were Slit1 and Slitrk1.
Besides, the gene of the astrocyte specific markers glial fibrillary acidic protein (GFAP) (Supplementary Figure 16) and VCAM-1 (CD106) as well as the oligodendrocyte specific basic-loop-helix transcription factors Olig1 and Olig2 were upregulated in the ACSA- 2+/GLAST- samples (Fig. 3.40). In contrast, the neuronal gene Ptf1a was not expressed and
Nestin was suppressed in the ACSA-2+/GLAST- sample set (compare Fig. 3.39). As shown in
Table 6, genes coding for different receptors were enriched in the ACSA-2+/GLAST- data set.
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enriched in the ACSA-2+/GLAST- samples: Slc32a1 a vesicular inhibitory amino acid
transporter, Slc6a11 encoding GAT-3, and the Slc6a12 a neurotransmitter transporter Slc6a12 and Slc6a13, which correspond to solute carriers and indicate members of receptor signaling pathway family.
Figure 3.40: Clustering of genes upregulated in the ACSA-2+/GLAST- sample set.
Data set was preprocessed using quantil normalization. Samples were compared using ANOVA.
Normalized gene samples with a p-value less than 0.05 (Tukey’s range test), less than one outlier per sample group, a log_2 ratio of (2/-2) were considered for this analyses. Pathways were identified using MetaCore. Samples of ACSA-2+/GLAST- (A+/G-), ACSA-2+/GLAST+
(A+/G+), ACSA-2-/GLAST+ (A-/G+) were visualized using MeV. Correlation coefficients are indicated by color from blue (-6) to yellow (3) (a). Data further illustrated using bar diagrams. Triplicates of normalized log_2 intensities are indicated as Mean ± SD (b).
Results
Genes such as Sox-2 and or PDGFR did not reveal significant differences between the tested samples (Supplementary Figure 17). Furthermore, ATOH1 (Math-1), Zic1, Tbr2 248,249, specific markers for granule cells of the cerebellum, showed low levels of gene expression in the tested samples. This indicates a low percentage of granule cell contaminations in ACSA-2+/GLAST-, ACSA-2+/GLAST+ and ACSA-2-/GLAST+ samples of the cerebellum. In
summary, this transcriptome analysis supports the differences between ACSA-2+/GLAST- cells
and ACSA-2+/GLAST- cells seen in the transplantation experiment. The gene expression profiling showed a close lineage relationship between ACSA-2+/GLAST- and ACSA-
2+/GLAST+ cells. ACSA-2-/GLAST+ were enriched for stem cell factors and genes of
GABAergic phenotype indicating higher plasticity. In contrast, ACSA-2+/GLAST- showed an
enrichment of cell adhesion and cell matrix proteins indicating a lower plasticity and more tissue integrated phenotype.
Discussion