Pathway analysis of the significantly lesion- vs. sham-regulated genes in aged and young animals.

<p>Pathway analysis at different time points was done using the Ingenuity curated database of gene interactions of over 23,900 human, rat, and mouse genes. In this analysis, genes were tested for significant association in specific cell functional or signaling pathways versus random chance association in a total of gene interactions using right-tailed Fisher's exact test (Ingenuity Systems). Significance was assessed by testing the number of genes that were regulated by sprouting neurons in a specific pathway versus total number of genes in this database for that pathway (blue columns). The red line in the left graph indicates the threshold for a significant association, the −log (0.05). For example, if the pathway has a <i>P-score</i> of 10, the odds of this pathway being generated at random are less than 1 out of 10¹⁰.</p

Enriched biological processes of significantly lesion-regulated genes in young and aged animals.

<p>Enriched biological processes of significantly lesion-regulated genes in young and aged animals during the acute, subacute and chronic stages of SCI determined by DAVID (D), ErmineJ (Roc, receiver-operator curves, Cor, correlation resampling). In contrast to DAVID, which analyses only significantly regulated genes that have passed a defined cut-off, ErmineJ considers the entire dataset with the advantage not to be biased by cut-offs.</p

Global cluster of all 27,342 genes.

<p>Clustering of genes across all samples using the self-organizing maps. We assigned the following labels to the emerged clusters (i) genes whose expression was consistently different between aged and young animals (age-specific) and (ii) genes whose expression changed over time (time-specific) as well as (iii) genes whose expression differed between distinct treatment conditions (treatment-specific). Condition trees (average linkage hierarchical clustering of conditions at different time points) demonstrated that treatment-specific changes override the age-specific gene expression at 35 dpo (right panel, up and down, respectively). SY = sham young, AY = AST young, LY = lesioned young, SO = sham old, LO = lesioned old, AO = AST old.</p

Validation of the expression of selected transcripts by qRT-PCR.

<p>Validation of changes in mRNA expression by quantitative real-time RT-PCR (qRT-PCR) for genes representative of expression patterns of young animals at 35 dpo identified by the GeneChip analysis (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0049812#pone-0049812-g005" target="_blank">Fig. 5</a>). mRNA expression levels (mean fold change ± standard error, n = 3–4 animals) relative to young sham animals determined with microarray and by qRT-PCR. Microarray values are given as ratios relative to normalization and RMA levels derived from Genespring. qRT-PCR values are ratios relative to ornithine decarboxylase 1 (ODC, houskeeping gene) expression. For all genes measured, qRT-PCR corroborated the rank order of magnitude of expression observed with microarrays. Abbrevations: Kruppel-like factor 7 (Klf7), integrin beta 7 (Intb7), complement component 1 q subcomponent, B chain (C1qb), hemoglobin beta (Hbb), Sh, sham; ls, lesion.</p>*<p>p<0.05,</p>**<p>p<0.01,</p>***<p>p<0.001,</p><p>n.s., not significant (student's <i>t</i>-test).</p

Aging changes the cortical expression of genes that are relevant to SCI.

<p>(<b>A</b>) Variance analysis of the total data set indicated that, in total, 11,361 out of 21,798 genes were significantly regulated either by time point, age or treatment. Among them 2,617 genes were regulated by age when the data were pooled over time points and treatment conditions. (<b>B</b>) Expression patterns of the age-specific genes revealed that these genes are constantly and conversely either up- or down-regulated at old <i>vs</i> young age. (<b>C</b>) Biological processes such as neurogenesis, cell adhesion and axon function, besides others, were over-represented among these age-specific genes (<b>D</b>) Genes representing the axonogenesis/axon guidance group are depicted with the respective expression profiles.</p

Mining the Secretome of C2C12 Muscle Cells: Data Dependent Experimental Approach To Analyze Protein Secretion Using Label-Free Quantification and Peptide Based Analysis

Secretome analysis faces several challenges including detection of low abundant proteins and the discrimination of bona fide secreted proteins from false-positive identifications stemming from cell leakage or serum. Here, we developed a two-step secretomics approach and applied it to the analysis of secreted proteins of C2C12 skeletal muscle cells since the skeletal muscle has been identified as an important endocrine organ secreting myokines as signaling molecules. First, we compared culture supernatants with corresponding cell lysates by mass spectrometry-based proteomics and label-free quantification. We identified 672 protein groups as candidate secreted proteins due to their higher abundance in the secretome. On the basis of Brefeldin A mediated blocking of classical secretory processes, we estimated a sensitivity of >80% for the detection of classical secreted proteins for our experimental approach. In the second step, the peptide level information was integrated with UniProt based protein information employing the newly developed bioinformatics tool “Lysate and Secretome Peptide Feature Plotter” (LSPFP) to detect proteolytic protein processing events that might occur during secretion. Concerning the proof of concept, we identified truncations of the cytoplasmic part of the protein Plexin-B2. Our workflow provides an efficient combination of experimental workflow and data analysis to identify putative secreted and proteolytic processed proteins