Wu Zhengzhi

Exploration of tongue coating protein based on proteomics assessment and bioinformatics analysis

Objective: To observe the coating of tongue to identify the diagnosis and explore its mechanisms at molecular level by using proteomics techniques. Method: Subjects were divided into four groups: normal thin and whitish coating group, patho-thin coating group, thick coating group and exfoliative coating group according to the presentation of the coating of tongue and with or without system organic diseases; two-dimension electrophoresis was conducted with immobilized pH gradients as first-dimension and vertical SDS-PAGES as second dimension. Proteins expressional signal were examined by sliver staining and image analysis of ImageMaster 2D Platinum software. Proteins altered in expressional level were digested by trypsin. The peptide mass fingerprint was identified by MALDI-TOF MS/MS. Result: The results of protein spots in these four groups were 1082plusmn105, 1052plusmn85, 1129plusmn98 and 1143plusmn140 respectively. According to the analysis of those selective protein spots by mass spectrometry and bioinformatics studies, 13 proteins closely related to tongue coating had been found, among which cystatin B, cytokeratin 13 and GAL7 protein were found for first time, which were closely related to the changes of tongue coating. Furthermore, there were 5 new proteins identified, which have not been recorded in the international Protein Data Bank till today, of which the biological effect needs to be further explored. Conclusion: The research method for tongue coating on the basis of proteomics and bioinformatics was feasible. The protein profile present significantly difference between patho-tongue coating and normal tongue coating. Deep research on proteomics of tongue coating may hopefully become the scientific proof and microcosmic index of clinic diagnosis of traditional Chinese medicine, evaluation of herbal pharmaceutical effect, method for screening new drugs and exploring their pharmacodynamics.

Effect of Natural Brain-Kenetine on variance of Gene expression profiles in MSC and hippocampus of AD rats analyzed by Gene chips and bioinformatics techniques

To explore the difference of gene expression in rat mesenchymal stem cell (MSC) and in the hippocampus of the Alzheimerpsilas disease (AD) model rats on Natural Brain-Kinetine by Gene chips. Methods: Rat MSC is primary cultured according to method-routie. The MSCs have two groups, the control group and treatment group without or with Natural Brain-Kinetine (NBK) respectively. MSCs gene expression is detected and analyze through the Affymetrix microarray. In addition, we analyze the gene expression in hippocampus of rats. The rats were randomly divided into 3 groups : sham group, AD model group (injected 25 mug Amyloid peptide beta1-40 in bilateral hippocampus), AD model treatment group. They were fed for 30 days with nature salt solution and Natural Brain-Kinetine respectively. Results: In MSCs, the expression of 18 genes are significantly increased (FC > 2) and lower of 28 genes (FC <-2) compared with the control group. The animal experiments show that in treatment group, there is 58 genes up regulated and 25 genes down regulated compared with the sham group, there is 15 genes up regulated and 28 genes down regulated compared with the AD model group. Those genes are possible involved the ones including cellular proliferation, cell differentiation and development, cell adhesion, nerve growth, cellular function regulation, cell signal transduction, cellular material and energy metabolism, immune response, and so on. Conclusion: We speculate that Natural Brain-Kinetine can regulate some target genes in the growth and differentiation of MSCs, and regulate hippocampus function in rats with a multi pathway to regulate the function of brains.

Preliminary studies on diagnostic cast of peptic ulcer based on saliva proteome and bioinformatics

To explore protein expression profile in peptic ulcer saliva by proteomics mass spectrum techniques, seek for specific biomarkers of peptic ulcer diagnosis. Method Peptide mass fingerprint of saliva collected from peptic ulcer patients and healthy subjects was investigated by using MALDI-TOF-MS technique after saliva sample had been treated with WCX magnetic beads. The diagnostic cast was developed based on the peptide mass fingerprint obtained from the saliva of chronic gastritis patients and healthy subjects. Result Totally 74 protein peaks were identified from the saliva of chronic gastritis patients and healthy subjects as being associated with peptic ulcer, among which 5 specific protein peaks (P<0.05) were found with statistically significant differential expression level. The 3 specific protein peaks with a mass-to-charge ratio (m/z) of 2934.36Da, 5502.38Da and 3472.94Da were used to build a predictive model for diagnosis of peptic ulcer. This predictive model has an identification rate of 88.4% and predictive ability of 80.35%. Clinical back substitution analysis indicated that this diagnostic model can discriminate chronic gastritis from controls with a precision of 88.57% (31/35), a sensitivity of 82.35% (14/17)and a specificity of 94.44% (17/18). Conclusion Saliva protein fingerprint mass spectrum from peptic ulcer was preliminarily obtained; the diagnostic cast on 2934.36Da, 5502.38Da and 3472.94Da protein peaks of protein expression mass spectrum from peptic ulcer saliva protein was developed to discriminate peptic ulcer clinically.

Application of iTRAQ quantitative proteomics in identification of serum biomarkers in breast cancer

Aim: This study aims to explore the presence of informative protein biomarkers in the human serum proteome. Patients and Methods; Serum samples collected from 20 breast cancer patients which were divided into two groups of breast cancer, and 10 health controls and 10 mammary fibroma patients were profiled using iTRAQ technology coupled with LC-ESI-QTOF-MS, and Mascot searching. Western-blotting were used for validation of the candidate biomarkers on a new group of breast cancer and healthy subjects as well as mammary fibroma patients. Results: 335 proteins were identified, and 11 proteins were associated with breast cancer, includind 1 upregulated protein and 10 downregulated proteins. Three biomarker candidates generated from iTRAQ experiments were successfully verified using Western-blotting. Conclusion: This study provided a global view of potential mechanisms and potentional biomarkers of breast cancer, and demonstrated that iTRAQ combined with LC-ESI-QTOF-MS quantitative proteomics is a powerful tool for biomarker discovery.