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Objective: Proper characterization of hydatid cyst fluid (HCF) is useful for diagnostic and follow up purposes of cystic echinococcosis/hydatidosis, which is an important zoonotic disease. In this regard, proteomics methods are very helpful. The present study was conducted to compare three protein extraction methods for HCF collected from sheep liver hydatid cysts including, trichloracetic acid (TCA)/Acetone precipitation, TCA/Acetone along with dialysis, and combination of 2-D Clean-up Kit and dialysis followed by two-dimensional electrophoresis (2-DE), to achieve better resolution in the proteomic characterization of HCF proteins., Results: The 2-DE of TCA/Acetone products showed a lot of smears in the background of gels; TCA/Acetone with dialysis showed greatly reduced smears while the 2-D Clean-up Kit together with dialysis showed sharp spots and least smears. Three-dimensional images of separated spots created by Progenesis SameSpots software showed the best result was achieved by 2-D Clean-up Kit and dialysis.

Background: Cystic echinococcosis (CE) is one of the most important parasitic zoonosis in the world. Post-surgery follow up in CE patients is an important non-solved problem up to now. Therefore, the investigations on this problematic issue would be very applicable in the view of CE clinical treatment. Methods: A total of 24 confirmed liver CE patients sera including eight sera before surgery (BS), eight sera three months post-surgery (3MPS), and eight sera six months postsurgery (6MPS) were used in the present study. Proteomics methods including 2DE and LC-MS/MS were performed on the specimens followed by bioinformatics analysis such as Gene Ontology (GO) and Protein-Protein Interaction (PPI) network analysis. Results: A total of 235 proteins were detected of which 12 differentially expressed proteins (DEP) were identified by LC-MS/MS in all sera. The proteins were presented in BS and suppressed after surgery as follows: HPX, SERPINA1, SERPINC1, CP, HBD, and HBA2. Comparisons of the protein expression in sera of patients BS, 3MPS, and 6MPS revealed that GC, IGJ, AHSG, CD5L, FGG, and APOC3 have been overexpressed in 3MPS and 6MPS. PPI network analysis demonstrated that SERPINC1 and AHSG with more connection in the network could be considered as hub proteins and potential prognostic biomarkers in response to surgical treatment of liver CE. Conclusion: Application of proteomics methods on patient's sera could be used as a novel biomarker tool for following-up liver CE patients. In this regards, proteomics and, application of bioinformatics analysis including GO and PPI showed that SERPINC1, AHSG and HPX are of more value as a potential follow up biomarkers in response to surgical treatment. [ABSTRACT FROM AUTHOR]

Aim: Detection of protein expression changes in human cystic echinococcosis sera by 2D gel electrophoresis. Background: Diagnosis and successful treatment of cystic echinococcosis (CE) is a major challenge, up to now. Identification of related expressed proteins using proteomics tools and bioinformatics analysis of patients' sera have not been investigated, so far. Methods: Sera from eight confirmed CE patients and three healthy controls were collected, tested by 2-DE for total protein separation of serum and analyzed using proteomics and bioinformatics methods. The gels were stained by Coomassie blue followed by scan imaging of the gels. The protein spots in each gel were analyzed using progenesis same spots software. Proteins names were obtained from TagIdent server. Results: A total of 263 protein spots with different expression were detected in both normal and diseased samples. Comparison between diseased and normal gels showed the expression of 45 up-regulated protein spots with fold≥2 in diseased gel of which 10 were new proteins with statistical difference by normal gel (p-value<0.05). On the other hand, the expression of 50 down-regulated protein spots were observed of which 11 proteins have been suppressed. Clustering of all detected sera proteins (263) using correlation analysis, divided the proteins into 2 clusters based on up-regulated and down-regulated expression of proteins. Clustering results were approved by principal component analysis (PCA). Conclusion: Significant protein expression changes in human CE sera which is demonstrable by application of proteomics and bioinformatics analysis makes it an impressing tool for diagnosis of CE patients. [ABSTRACT FROM AUTHOR]