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Several studies have shown that in addition to its role as a survival factor and tumor promoting agent, AKT is also able to exhibit pro-apoptotic effects under diverse conditions, including oxidative stress, cytokine stimulation and exposure to cytotoxic chemicals like staurosporine, methotrexate, docetaxel and etoposide. Moreover, phosphorylation of second mitochondria-derived activator of caspases (SMAC) by AKT promotes caspase-3 activation during etoposide-induced apoptosis in HeLa cells. Our data show that injection of pristane into the peritoneum induces apoptosis-mediated cell death of peritoneal exudate cells (PECs), as evidenced by the increased number of annexin V+ peritoneal cells and their increased levels of cleaved/active caspase-3. Indeed, the higher levels of activated caspase-3 protein in WT PECs, particularly at 2-weeks post pristane treatment, are indicative of a higher rate of apoptosis compared to Cd38¿/¿ cells. In contrast, no differences were observed in the levels of MCL-1, an anti-apoptotic protein and member of the BCL2 family. Furthermore, kinases ERK1/2 and AKT showed distinct activation kinetics in pristane-elicited PECs. Interestingly, caspase-3 activation followed similar kinetics to AKT activation in both WT and Cd38¿/¿ PECs, while ERK activation correlated with increased levels of MCL-1. In summary our data strongly suggest that in the pristane-induced lupus model AKT activation is associated with apoptotic signals and not with survival signals. Further studies, however, are required to identify specific pro- and anti-apoptotic target proteins that are phosphorylated by ERK or AKT following pristane treatment, and that regulate the apoptotic process.

Background: Intraperitoneal injection of pristane to C57BL6/J WT mice provokes a strong inflammatory reaction with a massive influx of pro-inflammatory Ly6Chi monocytes and neutrophils to the peritoneum that ends up in overt autoimmunity (a murine lupus model of systemic lupus erythematosus (SLE) human disease). The inflammation is milder in CD38-deficient (Cd38-/-) and in double-deficient (Cd38-/- Art2-/-) mice, while it is similar to WT in Art2-deficient (Art2-/-) mice, which suggests an important role of CD38 on the onset of the disease. The aim of this work has been to isolate exosomes from peritoneal exudates (PE-EXO) of mice treated with pristane and to identify/quantify the proteins by mass spectrometry. Functional analyses were performed in silico with the use of FunRich and ClueGO software. Methods: Two types of PE-EXOs (Fr5-10 and Fr11-12) were isolated from pristane-treated mice by qEV size exclusion column methodology. Protein extracts were analyzed by LC-MS/MS. Protein identification was performed with ProteinScape 4.0 (Bruker) and MASCOT data searching using Swiss-Prot database. For relative quantification the emPAI-based method was used. The functional enrichment analysis was based on the latest publicly available data from multiple annotation and ontology resources that can be automatically accessed through FunRich and ClueGO. Results: Gene Ontology (GO) enrichment analyses of Fr5-10 and Fr11-12 PE-EXOs with FunRich showed that 65-75% of the identified proteins clustered in the GO term extracellular vesicular exosomes, while the comparative analyses with CluGO showed that these PE-EXOs were functionally quite distinct. Thus, Fr5-10 PE-EXOs were enriched in terms such as ¿regulation of myeloid leukocyte mediated immunity¿, ¿positive regulation of adaptive immune response¿, while Fr11-12 exosomes were enriched in terms such as ¿complement activation¿, and ¿regulation of humoral immune response¿. Interestingly the predominance of given GO terms in Fr5-10 vs Fr11-12 PE-EXOs seemed to vary with the extent of the inflammatory reaction to pristane, suggesting that these exosomes are representative of the distinct inflammatory cells that are recruited to the peritoneum. Conclusions: Proteomics with the help of appropriate bioinformatics tools such as ClueGO visualizes GO terms and pathways as networks, and groups them based on their biological role. This may contribute to a better diagnosis/prognosis of autoimmune diseases such as lupus. Keywords: exosomes; inflammation; lupus; bioinformatics; gene ontology; omics data analysis; biological networks.

Background: Intraperitoneal injection of pristane to WT mice provokes a strong inflammatory reaction with a massive influx of pro-inflammatory Ly6Chi monocytes and neutrophils to the peritoneum (experimental lupus model). The inflammation is milder in CD38 deficient (Cd38-/-) mice. The aim of this work has been to isolate exosomes from peritoneal exudates (PE-EXO) of mice treated with pristane and to identify/quantify the proteins by mass spectrometry. Methods: PE-EXOs were isolated from pristane-treated mice by qEV size exclusion column methodology. Protein extracts were analyzed by LC-MS/MS and/or MALDI-TOF-MS/MS. Protein identification was performed with ProteinScape 4.0 (Bruker) and MASCOT data searching using Swiss-Prot database. For relative quantification the emPAI-based method was used. In addition to emPAI and molar fraction percentages, the fold change in the abundance of proteins identified was also calculated by dividing the molar percentage value for an individual protein in pristane-treated Cd38-/- mice with the cognate value in WT mice. The log2 value of the Cd38-/-/WT ratio was calculated and finally the absolute fold change calculated as 2log2 value. Results: Two weeks after pristane treatment 76 proteins were modulated by 1.3-fold or more in PE-EXO from Cd38-/- mice versus WT mice, representing 73% of the proteins that were common in PE-EXO from both types of mice: 26 proteins were significantly up-regulated, whereas 39 proteins were significantly down-regulated. Some of the down-modulated proteins in the Cd38-/- PE-EXOs, such as S100A9, may contribute to the migration of Ly6Chi monocytes and neutrophils to the inflamed peritoneum. Conclusions: emPAI is a reliable method for the semi-quantitative analysis of changes in protein abundance in exosomes from mice subjected to inflammatory/autoimmune challenges. These changes in protein abundance reflect the extent of the inflammatory reaction and may contribute to a better diagnosis/prognosis of autoimmune diseases such as lupus. Keywords: exosomes, inflammation, emPAI, relative quantification, expression proteomics.

The aim of this work has been to isolate exosomes from peritoneal exudates (PE-EXO) of mice with pristane-induced lupus (a murine lupus model of systemic lupus erythematosus (SLE) human autoimmune disease) to identify/quantify the proteins by mass spectrometry and to group them into functional modules. Methods: Two pools of PE-EXOs were isolated from pristane-treated mice by qEV size exclusion column methodology (Fr5-10 and Fr11-12). Protein extracts were analyzed by LC-MS/MS. MS analysis was performed using an Amazon Speed ETD de Bruker, or a Q-Exactive mass spectrometer (Thermo Scientific). Protein identification was performed with ProteinScape 4.0 (Bruker), or Proteome Discoverer (version1.4.1.14) (Thermo), and MASCOT data searching using Swiss-Prot database. For relative quantification the emPAI-based method was used. The functional enrichment analysis was based on the latest publicly available data from multiple annotation and ontology resources that can be automatically accessed through FunRich and ClueGO. Results: Gene Ontology (GO) enrichment analyses of Fr5-10 and Fr11-12 PE-EXOs with FunRich showed that 65-75% of the identified proteins clustered in the GO term ¿extracellular vesicular exosomes¿, while the ClueGO analyses showed that the proteins clustered into functionally distinct GO terms. Thus, Fr5-10 PE-EXOs were enriched in terms such as ¿regulation of myeloid leukocyte mediated immunity¿, ¿positive regulation of adaptive immune response¿, while Fr11-12 exosomes were enriched in terms such as ¿complement activation¿, and ¿regulation of humoral immune response¿. Moreover, the predominance of given GO terms in PE-EXOs seemed to vary with the extent of the inflammatory/autoimmune reaction to pristane. Conclusions: Proteomic analyses, with the help of appropriate bioinformatics tools such as ClueGO, visualize GO terms and pathways as networks, and group them based on their biological role. This approach may contribute to a better diagnosis/prognosis of autoimmune diseases such as lupus. Keywords: exosomes; inflammation; lupus; bioinformatics; gene ontology; omics data analyses; biological networks.