Table 1.
Effect of PPA and BA on neurotransmitter related gene expression in PC12 cells.
Figure 1.
PPA activates the transcription of TH gene in CREB-dependant manner.
Plasmid constructs with wild type (WT) rat TH promoter (−773/+27 bp) driving the expression of luciferase reporter gene or having a G-to A transition mutation in the CRE promoter element (mCRE) were electroporated in PC12 cells pre-treated for one day with increasing concentrations of PPA (0.1 to 10 mM, Fig. 1A)). The same doses of PPA were given immediately after electroporation for additional 24 hours, when changes in reporter gene activity were determined. In the second set of experiments (Figure 1B), PC12 cells were co-transfected with combination of wt TH promoter construct and plasmids expressing wild type or dominant negative CREB mutants (binding-defective K-CREB or phosphorylation-defective 133CREB). To half of the cultures, 10 mM PPA was given 1 day before and immediately after electroporation for additional 24 h (black bars). Controls received vehicle 24 hrs before and immediately after electroporation (open bars). The values shown are means ± SEM from three experiments. The luciferase activities (RLU/s/µg protein) are expressed as fold stimulation relative to control cells co-transfected with the same plasmids but not treated with PPA. *P<0.05 (PPA vs. vehicle treated; **P<0.002 (wt vs. mutant constructs).
Figure 2.
PPA induces accumulation of TH mRNA and TH protein in vitro.
PC12 cells were treated with SCFA: propionic acid (PPA, 1 mM), butyric acid (BA, 1 mM) or valproic acid (VPA, 0.1 mM). At indicated times (48 hrs) total RNA or total cell lysates (0, 24, 48 and 72 hrs) were prepared and subjected to Northern (A) or Western blot analyses (B, PPA and BA). The data on Fig. 2A are presented as mean ± SEM value relative to the mRNA levels in control, vehicle treated cells. 18S rRNA was used as a house keeping gene for normalization of data. *P<0.05 SCFA vs. vehicle treated. For Western blotting (2B) cells were lysed after indicated incubation times and equal amounts of proteins were subjected to analyses using TH-specific antibody as described in Experimental procedures. Membranes were re-probed with β-actin specific antibody as loading control. The autoradiographs were analyzed by densitometry. Values are presented as the ratio of TH to that of beta-actin as fold difference from control, vehicle- treated cells. N = 6–8 independent samples per group, and the experiment was repeated twice with similar results [63].
Figure 3.
Differential gene expression profiles evoked by SCFA in PC12 cells.
Total RNA was isolated from PC12 cells following 48 hrs exposures to BA (6 mM), PPA (10 mM) or vehicle and subjected to microarray analysis. Genes that changed two-fold or greater in SCFA-treated groups (*p<0.05) compared to the control (vehicle treated PC12 cells) group were imported into MetaCore GeneGo for comparison analyses. Differentially expressed unique (1599 for BA and 355 for PPA experimental group) and common for both groups genes (1010) were identified. Fisher's exact test p-value was <2.2e-16.
Table 2.
Comparison analysis of differentially expressed genes triggered by PPA and BA in PC12 cells: Top 10 most affected common genes.
Table 3.
Examples of common genes which were affected more by PPA.
Table 4.
Common genes oppositionally affected by PPA and BA.
Table 5.
Gene ontology annotation analysis: Oxidative stress.
Table 6.
Gene ontology annotation analysis: Dopamine & serotonin pathways.
Table 7.
Gene ontology annotation analysis: Fatty acid metabolism.
Table 8.
Gene ontology annotation analysis: GAP junction proteins.
Table 9.
Most relevant biological networks identified for common genes.
Figure 4.
Enrichment analysis of differentially expressed genes: distribution by gene ontology (GO) processes.
Differentially expressed genes in BA and PPA groups (t-test compared to control group p<0.01) were subjected to enrichment analysis (which consists of matching gene IDs for the common, similar and unique sets of the uploaded files with gene IDs in functional ontologies in MetaCore). The figure illustrates the distribution by GO processes. The gene content is aligned between all uploaded files. The set of common gene IDs is marked as blue and white stripes. The unique genes for the files are marked as colored bars (BA - orange; PPA- blue). The sorting was done by common gene IDs; p-value was set for 0.05; both signals (induced and repressed) were included. The data shown are for sorting method “similarity by”. The degree of “relevance” to different categories for the uploaded datasets is defined by p values, so that the lower p-value gets higher priority. The top 10 processes are listed based on their −log (p-value).
Table 10.
SCFA alter the expression of genes implicated in ASD in human and animal studies.