Analysis of patients with colorectal cancer shows a specific increase in serum anti-ING1 autoantibody levels.

Colorectal cancer (CRC) is the third most prevalent cancer in the world, yet the sensitivity and specificity of biomarkers for CRC diagnosis are insufficient. In the present study, we performed a protein microarray screening method to identify antibody markers for CRC. Inhibitor of growth family 1 (ING1) was identified as a candidate tumor antigen for CRC using protein microarrays (ProtoArray). Subsequent amplified luminescence proximity homogeneous assay-linked immunosorbent assay using recombinant ING1 protein showed that the serum levels of anti-ING1 antibodies were increased not only in patients with CRC but also in those with esophageal cancer (EC), gastric cancer (GC), breast cancer (BrC), and pancreatic cancer (PC) compared with those of healthy donors (HDs). Antibodies against the ING1 amino acids between 239 and 253 were present at significantly higher levels in patients with CRC than in those with EC, GC, BrC, or PC. Anti-ING1 antibody levels were significantly higher in the patients with CRC at any stages than in the HDs. Immunohistochemical staining revealed higher expression of ING1 protein in CRC cells than in the adjacent normal tissues. In luciferase reporter assays using a CRC cell line, ING1 augmented p53-mediated NOXA promoter activity but attenuated p53-stimulated Bax, p21, and PUMA promoter activities. Consequently, serum anti-ING1 antibodies can be used for sensitive and specific diagnoses of CRC.

Systematic identification of the interventional mechanism of Qingfei Xiaoyan Wan (QFXYW) in treatment of the cytokine storm in acute lung injury using transcriptomics-based system pharmacological analyses.

CONTEXT: Acute lung injury (ALI) is a complex, severe inflammation disease with high mortality, and there is no specific and effective treatment for ALI. Qingfei Xiaoyan Wan (QFXYW) has been widely used to treat lung-related diseases for centuries. OBJECTIVE: This study evaluates the potential effects and elucidates the therapeutic mechanism of QFXYW against LPS induced ALI in mice. MATERIALS AND METHODS: BALB/c Mice in each group were first orally administered medicines (0.9% saline solution for the control group, 0.5 mg/kg Dexamethasone, or 1.3, 2.6, 5.2 g/kg QFXYW), after 4 h, the groups were injected LPS (1.0 mg/kg) to induce ALI, then the same medicines were administered repeatedly. The transcriptomics-based system pharmacological analyses were applied to screen the hub genes, RT-PCR, ELISA, and protein array assay was applied to verify the predicted hub genes and key pathways. RESULTS: QFXYW significantly decreased the number of leukocytes from (6.34 ± 0.51) × 105/mL to (4.01 ± 0.11) × 105/mL, accompanied by the neutrophil from (1.41 ± 0.19) × 105/mL to (0.77 ± 0.10) × 105/mL in bronchoalveolar lavage fluid (BALF). Based on Degree of node connection (Degree) and BottleNeck (BN), important parameters of network topology, the protein-protein interaction (PPI) network screened hub genes, including IL-6, TNF-α, CCL2, TLR2, CXCL1, and MMP-9. The results of RT-PCR, ELISA, and protein chip assay revealed that QFXYW could effectively inhibit ALI via multiple key targets and the cytokine-cytokine signalling pathway. CONCLUSIONS: This study showed that QFXYW decreased the number of leukocytes and neutrophils by attenuating inflammatory response, which provides an important basis for the use of QFXYW in the treatment of ALI.

Protein Expression Profiles among Lichen Sclerosus Urethral Strictures-Can Urethroplasty Success be Predicted?

PURPOSE: Urethroplasty of lichen sclerosus strictures has a significantly higher failure rate than strictures due to other causes. We sought to determine predictors of urethroplasty failure in men with lichen sclerosus urethral stricture disease by evaluating protein expression profiles. MATERIALS AND METHODS: Urethral tissue was excised from patients with lichen sclerosus who were undergoing urethroplasty of urethral stricture disease at a single institution. A tissue microarray was created with cores from each sample. Immunohistochemistry was performed to compare protein expression related to inflammation, cell cycle disruption, oxidative stress, hormone receptor status and infection. Stricture recurrence was defined by the need for a subsequent unanticipated procedure for urethral stricture disease. RESULTS: We evaluated 50 men with lichen sclerosus urethral stricture disease, including 31 with successful reconstruction and 19 with recurrent stricture. Recurrent strictures expressed lower levels of several inflammatory markers and had a lower Ki-67 mitotic index and significantly higher vascular endothelial growth factor levels than nonrecurrent strictures. CONCLUSIONS: To our knowledge this is the first study to use tissue protein expression to identify risk factors for urethroplasty failure among men with lichen sclerosus urethral stricture disease. Our findings suggest that recurrent lichen sclerosus strictures demonstrate a suppressed inflammatory response, a decreased cell turnover rate, and poor oxygenation and nutrient delivery. Prospective studies are needed to clarify the role of these pathways in the pathophysiology of lichen sclerosus urethral stricture disease, determine whether preoperative biopsy can predict urethroplasty success, help counsel patients and develop future treatments.

Chemoradiotherapy response prediction model by proteomic expressional profiling in patients with locally advanced cervical cancer.

OBJECTIVE: Resistance to chemo-radiation therapy is a substantial obstacle that compromises treatment of advanced cervical cancer. The objective of this study was to investigate if a proteomic panel associated with radioresistance could predict survival of patients with locally advanced cervical cancer. METHODS: A total of 181 frozen tissue samples were prospectively obtained from patients with locally advanced cervical cancer before chemoradiation. Expression levels of 22 total and phosphorylated proteins were evaluated using well-based reverse phase protein arrays. Selected proteins were validated with western blotting analysis and immunohistochemistry. Performances of models were internally and externally validated. RESULTS: Unsupervised clustering stratified patients into three major groups with different overall survival (OS, P = 0.001) and progression-free survival (PFS, P = 0.003) based on detection of BCL2, HER2, CD133, CAIX, and ERCC1. Reverse-phase protein array results significantly correlated with western blotting results (R2 = 0.856). The C-index of model was higher than clinical model in the prediction of OS (C-index: 0.86 and 0.62, respectively) and PFS (C-index: 0.82 and 0.64, respectively). The Kaplan-Meier survival curve showed a dose-dependent prognostic significance of risk score for PFS and OS. Multivariable Cox proportional hazard model confirmed that the risk score was an independent predictor of PFS (HR: 1.6; 95% CI: 1.4-1.9; P < 0.001) and OS (HR: 2.1; 95% CI: 1.7-2.5; P < 0.001). CONCLUSION: A proteomic panel of BCL2, HER2, CD133, CAIX, and ERCC1 independently predicted survival in locally advanced cervical cancer patients. This prediction model can help identify chemoradiation responsive tumors and improve prediction for clinical outcome of cervical cancer patients.

A liquid biomarker signature of inflammatory proteins accurately predicts early pancreatic cancer progression during FOLFIRINOX chemotherapy.

BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) is often treated with FOLFIRINOX, a chemotherapy associated with high toxicity rates and variable efficacy. Therefore, it is crucial to identify patients at risk of early progression during treatment. This study aims to explore the potential of a multi-omics biomarker for predicting early PDAC progression by employing an in-depth mathematical modeling approach. METHODS: Blood samples were collected from 58 PDAC patients undergoing FOLFIRINOX before and after the first cycle. These samples underwent gene (GEP) and inflammatory protein expression profiling (IPEP). We explored the predictive potential of exclusively IPEP through Stepwise (Backward) Multivariate Logistic Regression modeling. Additionally, we integrated GEP and IPEP using Bayesian Kernel Regression modeling, aiming to enhance predictive performance. Ultimately, the FOLFIRINOX IPEP (FFX-IPEP) signature was developed. RESULTS: Our findings revealed that proteins exhibited superior predictive accuracy than genes. Consequently, the FFX-IPEP signature consisted of six proteins: AMN, BANK1, IL1RL2, ITGB6, MYO9B, and PRSS8. The signature effectively identified patients transitioning from disease control to progression early during FOLFIRINOX, achieving remarkable predictive accuracy with an AUC of 0.89 in an independent test set. Importantly, the FFX-IPEP signature outperformed the conventional CA19-9 tumor marker. CONCLUSIONS: Our six-protein FFX-IPEP signature holds solid potential as a liquid biomarker for the early prediction of PDAC progression during toxic FOLFIRINOX chemotherapy. Further validation in an external cohort is crucial to confirm the utility of the FFX-IPEP signature. Future studies should expand to predict progression under different chemotherapies to enhance the guidance of personalized treatment selection in PDAC.

Improving the default data analysis workflow for large autoimmune biomarker discovery studies with ProtoArrays.

Contemporary protein microarrays such as the ProtoArray® are used for autoimmune antibody screening studies to discover biomarker panels. For ProtoArray data analysis, the software Prospector and a default workflow are suggested by the manufacturer. While analyzing a large data set of a discovery study for diagnostic biomarkers of the Parkinson's disease (ParkCHIP), we have revealed the need for distinct improvements of the suggested workflow concerning raw data acquisition, normalization and preselection method availability, batch effects, feature selection, and feature validation. In this work, appropriate improvements of the default workflow are proposed. It is shown that completely automatic data acquisition as a batch, a re-implementation of Prospector's pre-selection method, multivariate or hybrid feature selection, and validation of the selected protein panel using an independent test set define in combination an improved workflow for large studies.

Role of Serum Inflammatory Cytokines in Sepsis Rats Following BMSCs Transplantation: Protein Microarray Analysis.

Bone marrow stromal cells (BMSCs) have emerged as a potential therapy for sepsis, yet the underlying mechanisms remain unclear. In this study, we investigated the effects of BMSCs on serum inflammatory cytokines in a rat model of lipopolysaccharide (LPS)-induced sepsis. Sepsis was induced by intravenous injection of LPS, followed by transplantation of BMSCs. We monitored survival rates for 72 h and evaluated organ functions, histopathological changes, and cytokines expression. Sepsis rats showed decreased levels of white blood cells, platelets, lymphocyte ratio, and oxygen partial pressure, along with increased levels of neutrophil ratio, carbon dioxide partial pressure, lactic acid, alanine aminotransferase, and aspartate aminotransferase. Histologically, lung, intestine, and liver tissues exhibited congestion, edema, and infiltration of inflammatory cells. However, after BMSCs treatment, there was improvement in organ functions, histopathological injuries, and survival rates. Protein microarray analysis revealed significant changes in the expression of 12 out of 34 inflammatory cytokines. These findings were confirmed by enzyme-linked immunosorbent assay. Pro-inflammatory factors, such as interleukin-1ß (IL-1ß), IL-1α, tumor necrosis factor-α (TNF-α), tissue inhibitor of metal protease 1 (TIMP-1), matrix metalloproteinase 8 (MMP-8), Leptin, and L-selectin were upregulated in sepsis, whereas anti-inflammatory and growth factors, including IL-4, ß-nerve growth factor (ß-NGF), ciliary neurotrophic factor (CNTF), interferon γ (IFN-γ), and Activin A were downregulated. BMSCs transplantation led to a decrease in pro-inflammatory cytokines and an increase in anti-inflammatory and growth factors. We summarized relevant molecular signaling pathways that resulted from cytokines in BMSCs for treating sepsis. Our results illustrated that BMSCs could promote tissue repair and improve organ functions and survival rates in sepsis through modulating cytokine networks.

Identification of Novel Plasma Biomarkers for Abdominal Aortic Aneurysm by Protein Array Analysis.

Abdominal aortic aneurysm (AAA) is a potentially life-threatening disease that is common in the aging population. Currently, there are no approved diagnostic biomarkers or therapeutic drugs for AAA. We aimed to identify novel plasma biomarkers or potential therapeutic targets for AAA using a high-throughput protein array-based method. Proteomics expression profiles were investigated in plasma from AAA patients and healthy controls (HC) using 440-cytokine protein array analysis. Several promising biomarkers were further validated in independent cohorts using enzyme-linked immunosorbent assay (ELISA). Thirty-nine differentially expressed plasma proteins were identified between AAA and HC. Legumain (LGMN) was significantly higher in AAA patients and was validated in another large cohort. Additionally, "AAA without diabetes" (AAN) patients and "AAA complicated with type 2 diabetes mellitus" (AAM) patients had different cytokine expression patterns in their plasma, and nine plasma proteins were differentially expressed among the AAN, AAM, and HC subjects. Delta-like protein 1 (DLL1), receptor tyrosine-protein kinase erbB-3 (ERBB3), and dipeptidyl peptidase 4 (DPPIV) were significantly higher in AAM than in AAN. This study identified several promising plasma biomarkers of AAA. Their role as therapeutic targets for AAA warrants further investigation.

Sodium danshensu attenuates cerebral ischemia-reperfusion injury by targeting AKT1.

The beneficial properties of Sodium Danshensu (SDSS) for controlling cerebral ischemia and reperfusion injury (CIRI) are elucidated here both in vivo and in vitro. SDSS administration significantly improved the viability of P12 cells, reduced lactate dehydrogenase (LDH) leakage, and decreased the apoptosis rate following exposure to an oxygen-glucose deprivation/reoxygenation (OGD) environment. In addition, the results of a HuprotTM human protein microarray and network pharmacology indicated that AKT1 is one of the main targets of SDSS. Moreover, functional experiments showed that SDSS intervention markedly increased the phosphorylation level of AKT1 and its downstream regulator, mTOR. The binding sites of SDSS to AKT1 protein were confirmed by Autodock software and a surface plasmon resonance experiment, the result of which imply that SDSS targets to the PH domain of AKT1 at ASN-53, ARG-86, and LYS-14 residues. Furthermore, knockdown of AKT1 significantly abolished the role of SDSS in protecting cells from apoptosis and necrosis. Finally, we investigated the curative effect of SDSS in a rat model of CIRI. The results suggest that administration of SDSS significantly reduces CIRI-induced necrosis and apoptosis in brain samples by activating AKT1 protein. In conclusion, SDSS exerts its positive role in alleviating CIRI by binding to the PH domain of AKT1 protein, further resulting in AKT1 activation.

Reverse-Phase Protein Array: Technology, Application, Data Processing, and Integration.

Reverse-phase protein array (RPPA) is a high-throughput antibody-based targeted proteomics platform that can quantify hundreds of proteins in thousands of samples derived from tissue or cell lysates, serum, plasma, or other body fluids. Protein samples are robotically arrayed as microspots on nitrocellulose-coated glass slides. Each slide is probed with a specific antibody that can detect levels of total protein expression or post-translational modifications, such as phosphorylation as a measure of protein activity. Here we describe workflow protocols and software tools that we have developed and optimized for RPPA in a core facility setting that includes sample preparation, microarray mapping and printing of protein samples, antibody labeling, slide scanning, image analysis, data normalization and quality control, data reporting, statistical analysis, and management of data. Our RPPA platform currently analyzes ∼240 validated antibodies that primarily detect proteins in signaling pathways and cellular processes that are important in cancer biology. This is a robust technology that has proven to be of value for both validation and discovery proteomic research and integration with other omics data sets.

Reverse-Phase Protein Array: Technology, Application, Data Processing, and Integration.

Reverse-phase protein array (RPPA) is a high-throughput antibody-based targeted proteomics platform that can quantify hundreds of proteins in thousands of samples derived from tissue or cell lysates, serum, plasma, or other body fluids. Protein samples are robotically arrayed as microspots on nitrocellulose-coated glass slides. Each slide is probed with a specific antibody that can detect levels of total protein expression or post-translational modifications, such as phosphorylation as a measure of protein activity. Here we describe workflow protocols and software tools that we have developed and optimized for RPPA in a core facility setting that includes sample preparation, microarray mapping and printing of protein samples, antibody labeling, slide scanning, image analysis, data normalization and quality control, data reporting, statistical analysis, and management of data. Our RPPA platform currently analyzes ∼240 validated antibodies that primarily detect proteins in signaling pathways and cellular processes that are important in cancer biology. This is a robust technology that has proven to be of value for both validation and discovery proteomic research and integration with other omics data sets.

A descriptive analysis of non-human leukocyte antigens present in renal transplant donor-recipient pairs.

INTRODUCTION: End stage renal disease (ESRD) is the irreversible deterioration of renal function requiring renal replacement therapy by dialysis or transplant. Human leucocyte antigens (HLA) have been well examined however research still is required into the non-HLA antibodies. Antibody mediated rejection (AMR) can be seen in the absence of HLA antibodies on biopsies of patients who have received identical transplants; anti-endothelial cell antibodies may explain this. Investigation into endothelial cell antigens on donor and recipient endothelium may elucidate and stratify the degree of risk of any given transplant and may guide towards the best matched donor. METHODS: Protein array analysis was carried out on 8 patient pairs using nitro-cellulose membranes and biotinylated detection antibodies. The fluorescence emitted was captured by X-Ray film and results were recorded with ImageJ software. A fold increase of more than 2 was considered to be positive. RESULTS: 11 proteins identified had a fold increase of increase ≥2 and were present in ≥2 patient pairs which may point to potential clinical utility. Nectin2/CD112 may be measured in order analyse graft survival time in transplant recipients. Prognosticating renal failure has clinical importance and potential markers that have been identified to aid which include MEPE, CRELD2, and TIMP-4. Novel pharmacological therapies for specific biomarkers identified in this study include JAM-A, E-Selectin, CD147, Galectin-3, JAM-C, PAR-1, and TNFR2. CONCLUSION: Protein analysis showed differences in expression of antigens between patients with and without Chronic Kidney Disease (CKD). This information could be used at the matching stage of renal transplantation and also in the treatment of rejection episodes. The results highlight biomarkers that potentially prognosticate and pharmacological therapies that may ameliorate kidney disease and rejection in ESRD and transplant recipients.

Protein Expression of Cyclin B1, Transferrin Receptor, and Fibronectin Is Correlated with the Prognosis of Adrenal Cortical Carcinoma.

BACKGROUND: Adrenal cortical carcinoma (ACC) is a rare cancer with a variable prognosis. Several prognostic factors of ACC have been previously reported, but a proteomic analysis has not yet been performed. This study aimed to investigate prognostic biomarkers for ACC using a proteomic approach. METHODS: We used reverse-phase protein array data from The Cancer Proteome Atlas, and identified differentially expressed proteins in metastatic ACCs. Multivariate Cox regression analysis adjusted by age and staging was used for survival analysis, and the C-index and category-free net reclassification improvement (cfNRI) were utilized to evaluate additive prognostic value. RESULTS: In 46 patients with ACC, cyclin B1, transferrin receptor (TfR1), and fibronectin were significantly overexpressed in patients with distant metastasis. In multivariate models, high expression of cyclin B1 and TfR1 was significantly associated with mortality (hazard ratio [HR], 6.13; 95% confidence interval [CI], 1.02 to 36.7; and HR, 6.59; 95% CI, 1.14 to 38.2; respectively), whereas high fibronectin expression was not (HR, 3.92; 95% CI, 0.75 to 20.4). Combinations of high cyclin B1/high TfR1, high cyclin B1/high fibronectin, and high TfR1/high fibronectin were strongly associated with mortality ([HR, 13.72; 95% CI, 1.89 to 99.66], [HR, 9.22; 95% CI, 1.34 to 63.55], and [HR, 18.59; 95% CI, 2.54 to 135.88], respectively). In reclassification analyses, cyclin B1, TfR1, fibronectin, and combinations thereof improved the prognostic performance (C-index, 0.78 to 0.82-0.86; cfNRI, all P values <0.05). CONCLUSION: In ACC patients, the overexpression of cyclin B1, TfR1, and fibronectin and combinations thereof were associated with poor prognosis.

Identification of the Thioredoxin-Like 2 Autoantibody as a Specific Biomarker for Triple-Negative Breast Cancer.

Triple-negative breast cancer (TNBC) has a higher risk of death within 5 years of being diagnosed than the other forms of breast cancer. It is the second leading cause of death due to cancer among women. Currently, however, no diagnostic blood-based biomarker exists to identify the early stages of TNBC. To address this point, we utilized a human protein microarray system to identify serum autoantibodies that showed different expression patterns between TNBC and normal serum samples, and identified five autoantibodies showing TNBC-specific expression. Among them, we selected the thioredoxin-like 2 (TXNL2) autoantibody and evaluated its diagnostic relevance by dot blot analysis with the recombinant TXNL2 protein. We demonstrated that the TXNL2 autoantibody showed 2- to 6-fold higher expression in TNBC samples than in normal samples suggesting that serum TXNL2 autoantibodies are potential biomarkers for TNBC.

Investigation of Immune-Regulatory Effects of Mageumsan Hot Spring via Protein Microarray In Vitro.

BACKGROUND: Empirical evidences for efficacy of hot spring (HS) water in inflammatory skin disorders have not been substantiated with sufficient, immunological "hard evidence". Mageumsan HS water, characterized by its weakly-alkaline properties and low total dissolved solids content, has been known to alleviate various immune-inflammatory skin diseases, including atopic dermatitis (AD). OBJECTIVE: The trial attempted to quantitatively analyze in vitro expression levels of chemical mediators in cutaneous inflammation from HaCaT cell line treated with Mageumsan HS, and suggest the likely mode of action through which it exerts the apparent anti-inflammatory effects in AD. METHODS: Using membrane-based human antibody array kit, customized to include 30 different, keratinocyte-derived mediator proteins, their expression levels (including interleukin [IL]-1, IL-6, IL-8, thymic stromal lymphopoietin, thymus and activation-regulated chemokine, and granulocyte macrophage colony-stimulating factor) were assessed in vitro. Selected key proteins were further quantified with enzyme-linked immunosorbent assay. RESULTS: There was a clear pattern of overall suppression of the mediators, especially those noted for their pro-inflammatory role in AD (monocyte chemoattractant protein [MCP]-1, regulated on activation, normal T cell expressed and secreted, cutaneous T-cell-attracting chemokine, Eotaxin, and macrophage inflammatory protein-1α, etc.). Also, reduced expression of involucrin and cytokeratin 1 was also reduced in the HS-treated group. CONCLUSION: The present study has shown that Mageumsan HS water may exert its effects on inflammatory skin disorders through regulation of proinflammatory cytokines. These evidences are to be supported with further future investigations to elucidate immunological mechanism behind these beneficial effects of HS water in the chronically inflamed skin of AD.

A transcription/translation-based gene signature predicts resistance to chemotherapy in breast cancer.

Although chemotherapy is widely used to treat human cancers, most chemotherapeutic agents only benefit a small fraction of patients because of the heterogeneity of cancers. Therefore, identifying of the sensitivity of cancers toward various chemotherapies would be important for choosing of chemotherapeutic regime. In this study, a 23-gene chemoresistance signature was developed from chemoresistant breast cancers. Functions of the genes in the signature were related with transcription and translation. The signature was indicative of chemoresistance and associated with poor prognosis in multiple chemotherapeutic agents and cancer types. Furthermore, by applying computational approaches, we identified several compounds that might specifically affect the chemoresistant signature. Decitabine (DAC) was the compound most likely to target the signature. In vitro and clinical analysis confirmed effect of DAC toward both breast cancer cell lines and ovarian cancers respectively. In conclusion, our study identified a chemoresistant signature that is both predictive and prognostic, and the signature-related chemoresistance could be suppressed by DAC treatment.

The clinical performance evaluation of novel protein chips for eleven biomarkers detection and the diagnostic model study.

We aimed to develop and validate two novel protein chips, which are based on microarray chemiluminescence immunoassay and can simultaneously detected 11 biomarkers, and then to evaluate their clinical diagnostic value by comparing with the traditional methods. Protein chips were evaluated for limit of detection, specificity, common interferences, linearity, precision and accuracy. 11 biomarkers were simultaneously detected by traditional methods and protein chips in 3683 samples, which included 1723 cancer patients, 1798 benign diseases patients and 162 healthy controls. After assay validation, protein chips demonstrated high sensitivity, high specificity, good linearity, low imprecision and were free of common interferences. Compared with the traditional methods, protein chips have good correlation in the detection of all the 13 kinds of biomarkers (r≥0.935, P<0.001). For specific cancer detection, there were no statistically significant differences between the traditional method and novel protein chips, except that male protein chip showed significantly better diagnostic value on NSE detection (P=0.004) but significantly worse value on pro-GRP detection (P=0.012), female chip showed significantly better diagnostic value on pro-GRP detection (P=0.005). Furthermore, both male and female multivariate diagnostic models had significantly better diagnostic value than single detection of PGI, PG II, pro-GRP, NSE and CA125 (P<0.05). In addition, male models had significantly better diagnostic value than single CA199 and free-PSA (P<0.05), while female models observed significantly better diagnostic value than single CA724 and ß-HCG (P<0.05). For total disease or cancer detection, the AUC of multivariate logistic regression for the male and female disease detection was 0.981 (95% CI: 0.975-0.987) and 0.836 (95% CI: 0.798-0.874), respectively. While, that for total cancer detection was 0.691 (95% CI: 0.666-0.717) and 0.753 (95% CI: 0.731-0.775), respectively. The new designed protein chips are simple, multiplex and reliable clinical assays and the multi-parameter diagnostic models based on them could significantly improve their clinical performance.

A Molecular Biological and Biochemical Investigation on Mycobacterium tuberculosis MutT Protein.

BACKGROUND: Mycobacterium tuberculosis is a vicious microbe co-existing with the infected host. This pathogen exploited opportunities to spread during periods of urbanization and social upheaval, and got retreated with improved hygiene. OBJECTIVES: This investigation was designed to clone and characterize M. tuberculosis mutT gene, a homologue of a DNA repair protein in Escherichia coli. The aim was to depict the possible role of this homologue in the virulent microbe. MATERIALS AND METHODS: A DNA fragment of the mutT gene was amplified with PCR from the genomic DNA of strain H37Rv M. tuberculosis. The expression vector was transformed into E. coli strains BL21 (DE3) and MK602 (DE3) (mutT-). The protein activity assay was performed by biochemical methods. RESULTS: M. tuberculosis MutT shares 23% identity with the E. coli MutT protein. The mutT gene DNA fragment was subcloned into the expression vector pET28a(+) and the recombinant plasmid was overexpressed in E. coli. Purified and refolded M. tuberculosis MutT possesses a dGTPase activity, which is one of the most well-known preference nucleotidase activities of MutT in E. coli. This study also showed that the dGTPase activity of M. tuberculosis MutT was enhanced by magnesium and inhibited by Ni(2+) or EDTA. Endogenous MutT protein in M. tuberculosis lysate displayed a smear pattern in the Western blot, suggesting instability of this protein in the bacteria similar to the important proteins, such as P53 protein, tightly regulated by protein degradation. CONCLUSIONS: The cloned M. tuberculosis mutT gene and MutT protein were characterized. M. tuberculosis MutT has a dGTPase activity, which is one of the most well-known preference nucleotidase activities of MutT in E. coli. These findings provide further understanding about the vicious bacterium.