Retinol-binding protein 4 and its potential roles in hypercholesterolemia revealed by proteomics

Effects of hypercholesterolemia on alterations of serum proteins have not been fully elucidated. Herein, using two-dimensional gel electrophoresis (2-DE) in conjunction with LC-MS searching has successfully been carried out to investigate the change of protein expression profiles as consequences of raised blood cholesterol at different levels (normal group: total cholesterol < 200 mg/dL; borderline high group: total cholesterol 200-239 mg/dL; and high group: total cholesterol ≥ 240 mg/dL) (n = 45). Results revealed that down-regulation of retinol-binding protein 4 (RBP4) (-2.26 fold), transthyretin (-1.25 fold) and gelsolin (-1.47 fold) was observed in the high group. Meanwhile, the other proteins such as haptoglobin, complement factor B and CD5 antigen-like protein were upregulated upto +3.24, +1.96 and +2.04 fold, respectively. Confirmation by Western blotting revealed a significant reduction of RBP4 (approximately 50 %) in individual samples derived from the high group. Presumptive conclusion can be drawn that down-regulation of RBP4 might be attributable to the inflammation of adipocytes caused by the release of proinflammatory cytokines (e.g. tumor necrosis factor α and interleukin-1β) from adipose tissues. Moreover, the decrease of transthyretin might also be taken into accounts since it is known that the transthyretin usually forms complex with RBP4 to prevent glomerular filtration and excretion through the kidney. The suppressing effect on RBP4 should be potentiated by the increase of complement factor B and CD5 antigen-like protein, which rendered the adipose tissues to overwhelm the liberation of RBP4 to blood circulation by metabolic and inflammatory processes. Such inflammation could further modulate the induction of cytokine release (e.g. IL-6 and IL-1β), resulting in the synthesis of acute phase protein, in particular, haptoglobin and Creactive proteins from hepatocytes. However, the mechanism of gelsolin reduction remains unclear. Among these differentially expressed proteins, the RBP4 has been proposed as a major linkage between hypercholesterolemia, adipose tissues, liver and kidney, which is believed to be a potential biomarker for metabolic and cardiovascular disorders associated with dyslipidemia in the future

Proteomic alterations of Escherichia coli by paraquat

Paraquat (PQ; a widely used herbicide) exerts its harmful effect to human, mammals and microorganisms upon intracellular conversion to superoxide radical. Cellular responses against toxic paraquat remain not fully understood, especially on the adaptive metabolic changes as a consequence of oxidative burden. In this study, alterations of metabolic processes of Escherichia coli (E. coli) by paraquat were systematically investigated by two-dimensional gel electrophoresis (2-DE) in conjunction with peptide mass fingerprinting (PMF). In host cells, the first line mechanism was scrutinized by a remarkable induction of endogenous superoxide dismutase (E. coli SOD). The second line involved in the metabolic adaptation and compensation for energy production by up- or down-regulation of the enzymes implicated in glycolysis and tricarboxylic acid cycle. Notably, down-regulation of aconitase enzyme and changes of enzyme isoform from the acidic (pI~5.29) to the higher basidic form (pI~5.59) were detected. Meanwhile, up-regulation of fumarase approximately 4-5 folds were observed. Importantly, overexpression of human manganese superoxide dismutase (human Mn-SOD) in E. coli cells could in turn down-regulate the expression of fumarase enzyme. This observation was not found when the cells expressing human catalase were tested. Other mechanisms such as changes of purine nucleoside phosphorylase and protein transporters (D-ribose-binding protein and oligopeptide binding protein) were also accounted. However, among all the differentially expressed proteins, the fumarase enzyme is evidenced to be a major target responsible for superoxide-generating paraquat, which may further be applied as a potential biomarker for paraquat toxicity in the future

Quantitative population-health relationship (QPHR) for assessing metabolic syndrome

Background: Metabolic syndrome (MS) is a condition that predisposes individuals to the development of cardiovascular diseases and type 2 diabetes mellitus. Methods: A cross-sectional investigation of 15,365 participants residing in metropolitan Bangkok who had received an annual health checkup in 2007 was used in this study. Individuals were classified as MS or non-MS according to the International Diabetes Federation criteria using BMI cutoff of ≥ 25 kg/m2 plus two or more MS components. This study explores the utility of quantitative population-health relationship (QPHR) for predicting MS status as well as discovers variables that frequently occur together. The former was achieved by decision tree (DT) analysis, artificial neural network (ANN), support vector machine (SVM) and principal component analysis (PCA) while the latter was obtained by association analysis(AA). Results: DT outperformed both ANN and SVM in MS classification as deduced from its accuracy value of 99 % as compared to accuracies of 98 % and 91 % for ANN and SVM, respectively. Furthermore, PCA was able to effectively classify individuals as MS and non-MS as observed from the scores plot. Moreover, AA was employed to analyze individuals with MS in order to elucidate pertinent rule from MS components that occur frequently together, which included TG+BP, BP+FPG and TG+FPG where TG, BP and FPG corresponds to triglyceride, blood pressure and fasting plasma glucose, respectively. Conclusion: QPHR was demonstrated to be useful in predicting the MS status of individuals from an urban Thai population. Rules obtained from AA analysis provided general guidelines (i.e. co-occurrences of TG, BP and FPG) that may be used in the prevention of MS in at risk individuals

Roles of kininogen-1, basement membrane specific heparan sulfate proteoglycan core protein, and roundabout homolog 4 as potential urinary protein biomarkers in diabetic nephropathy

Diabetic nephropathy, a major complication of diabetes mellitus (DM), is increasing worldwide and the large majority of patients have type 2 DM. Microalbuminuria has been used as a diagnostic marker of diabetic nephro­pathy. But owing to its insufficient sensitivity and specificity, other biomarkers are being sought. In addition, the pathophysiology of diabetic nephropathy is not fully understood and declines in renal function occur even without microalbuminuria. In this study, we investigated urinary proteins from three study groups (controls, and type 2 diabetic subjects with or without microalbuminuria). Non-targeted label-free Nano-LC QTOF analysis was conducted to discover underlying mechanisms and protein networks, and targeted label-free Nano-LC QTOF with SWATH was performed to qualify discovered protein candidates. Twenty-eight proteins were identified as candidates and functionally analyzed via String DB, gene ontology and pathway analysis. Four predictive mechanisms were analyzed: i) response to stimulus, ii) platelet activation, signaling and aggregation, iii) ECM-receptor interaction, and iv) angiogenesis. These mechanisms can provoke kidney dysfunction in type 2 diabetic patients via endothelial cell damage and glomerulus structural alteration. Based on these analyses, three proteins (kininogen-1, basement membrane-specific heparan sulfate proteoglycan core protein, and roundabout homolog 4) were proposed for further study as potential biomarkers. Our findings provide insights that may improve methods for both prevention and diagnosis of diabetic nephropathy

PyBact

PyBact is a software written in Python for bacterial identification. The code simulates the predefined behavior of bacterial species by generating a simulated data set based on the frequency table of biochemical tests from diagnostic microbiology textbook. The generated data was used for predictive model construction by machine learning approaches and results indicated that the classifiers could accurately predict its respective bacterial class with accuracy in excess of 99 %

Paper-based acetylcholinesterase inhibition assay combining a wet system for organophosphate and carbamate pesticides detection

A dramatic increase in pesticide usage in agriculture highlights the need for on-site monitoring for public health and safety. Here, a paper-based sensor combined with a wet system was developed for the simple and rapid screening of organophosphate (OP) and carbamate (CM) pesticides based on the inhibition of acetylcholinesterase (AChE). The paper-based sensor was designed as a foldable device consisting of a cover and detection sheets pre-prepared with indoxyl acetate and AChE, respectively. The paper-based sensor requires only the incubation of a sample on the test zone for 10 minutes, followed by closing of the foldable sheet to initiate the enzymatic reaction. Importantly, the buffer loading hole was additionally designed on the cover sheet to facilitate the interaction of the coated substrate and the immobilized enzyme. This subsequently facilitates the mixing of indoxyl acetate with AChE, resulting in the improved analytical performance of the sensor. The absence or decrease in blue color produced by the AChE hydrolysis of indoxyl acetate can be observed in the presence of OPs and CMs. Under optimized conditions and using image analysis, the limit of detection (LOD) of carbofuran, dichlorvos, carbaryl, paraoxon, and pirimicarb are 0.003, 0.3, 0.5, 0.6, and 0.6 ppm, respectively. The assay could be applied to determine OP and CM residues in spiked food samples. Visual interpretation of the color signal was clearly observed at the concentration of 5 mg/kg. Furthermore, a self-contained sample pre-concentration approach greatly enhanced the detection sensitivity. The paper-based device developed here is low-cost, requires minimal reagents and is easy to handle. As such, it would be practically useful for pesticide screening by non-professional end-users

Construction of chimeric antibody binding green fluorescent protein for clinical application

A chimeric antibody-binding green fluorescent protein (ZZGFPuv) was successfully constructed and applied as a powerful tool for immunological diagnosis. A gene encoding two repetitive sequences of Z-domain, derivative of IgG-binding B domain of staphylococcal protein A, was fused in-frame to the N-terminus of gfpuv gene. The chimeric gene was subsequently transformed and expressed in various strains of E. coli. Expression of chimeric protein in E. coli strain HB101 resulted in a protein translocation from cytoplasm to periplasmic space and cultivation medium. The chimeric ZZGFPuv could be purified using either IgG Sepharose column or immobilized metal (Cu2+) affinity chromatography. The purified protein migrated in non-denaturing SDS-PAGE as two major bands. A fluorescent band was located at 36 kDa while another band at 48 kDa exhibited non-fluorescence. The fluorescent band was isolated and assessed for IgG-binding via fluorescent emission. The lowest amount of IgG that could be detected by dot immunobinding assay was approximately 630 ng. Indirect immunofluorescent assay for a serological detection of leptospirosis was performed by using the chimeric ZZGFPuv as IgG detector. A strong fluorescent intensity as comparable to that of the fluorescein isothiocyanate (FITC) conjugated system was significantly detected. All these findings support a high feasibility to apply the chimeric Ab-binding GFP for clinical applications in the future

Development of bacterial cell-based system for intracellular antioxidant activity screening assay using green fluorescence protein (GFP) reporter

The novel bacterial cell-based assay was developed for evaluating the intracellular antioxidant activity. The genetically engineered Escherichia coli strains harboring the fusions of sodA::gfp and fumC::gfp were constructed and applied as reporters in response to cellular superoxide stress. Using this assay, twelve pure compounds and three Thai medicinal plants were investigated for intracellular antioxidant activity in comparison with conventional chemical-based assays; 2,2-diphenyl-1-picrylhydrazyl (DPPH) and superoxide dismutase (SOD) activity assays. Both strains demonstrated that quercetin and α- tocopherol exhibited the most potent and significant antioxidant activity with more than 60% reduction of intracellular superoxide. These compounds also showed high DPPH radical scavenging activity. Interestingly, gallic, caffeic and protocatechuic acids had the most significant DPPH radical scavenging and SOD-like activities but with moderate to weak intracellular antioxidant activity. Our hypothesis was that the lower intracellular antioxidant activity possibly occurs due to poor permeability of compounds into biological membrane based on their structures. Moreover, our results demonstrated that intracellular antioxidant activity of three plant extracts well correlated to results from DPPH assay. Our bacterial-based assay is simple, reproducible, very specific and applicable as an alternative screening tool for assessing the activity of compounds and plant extracts affecting cellular oxidative stress.Key words: Bacterial cell-based assay, antioxidant activity, oxidative stress, superoxide dismutase, fumarase, green fluorescence protein (GFP) reporter, plant extracts

A practical overview of quantitative structure-activity relationship

Quantitative structure-activity relationship (QSAR) modeling pertains to the construction of predictive models of biological activities as a function of structural and molecular information of a compound library. The concept of QSAR has typically been used for drug discovery and development and has gained wide applicability for correlating molecular information with not only biological activities but also with other physicochemical properties, which has therefore been termed quantitative structure-property relationship (QSPR). Typical molecular parameters that are used to account for electronic properties, hydrophobicity, steric effects, and topology can be determined empirically through experimentation or theoretically via computational chemistry. A given compilation of data sets is then subjected to data preprocessing and data modeling through the use of statistical and/or machine learning techniques. This review aims to cover the essential concepts and techniques that are relevant for performing QSAR/QSPR studies through the use of selected examples from our previous work

Synthesis and computational investigation of molecularly imprinted nanospheres for selective recognition of alpha-tocopherol succinate

Molecularly imprinted polymers (MIPs) are macromolecular matrices that can mimic the functional properties of antibodies, receptors and enzymes while possessing higher durability. As such, these polymers are interesting materials for applications in biomimetic sensor, drug synthesis, drug delivery and separation. In this study, we prepared MIPs and molecularly imprinted nanospheres (MINs) as receptors with specific recognition properties toward tocopherol succinate (TPS) in comparison to tocopherol (TP) and tocopherol nicotinate (TPN). MIPs were synthesized using methacrylic acid (MAA) as functional monomer, ethylene glycol dimethacrylate (EGDMA) as crosslinking agent and dichloromethane or acetronitrile as porogenic solvent under thermal-induced polymerization condition. Results indicated that imprinted polymers of TPS-MIP, TP-MIP and TPN-MIP all bound specifically to their template molecules at 2 folds greater than the non-imprinted polymers. The calculated binding capacity of all MIP was approximately 2 mg per gram of polymer when using the optimal rebinding solvent EtOH:H2O (3:2, v/v). Furthermore, the MINs toward TPS and TP were prepared by precipitation polymerization that yielded particles that are 200-400 nm in size. The binding capacities of MINs to their templates were greater than that of the non-imprinted nanospheres when using the optimal rebinding solvent EtOH:H2O (4:1, v/v). Computer simulation was performed to provide mechanistic insights on the binding modalities of template-monomer complexes. In conclusion, we had successful prepared MIPs and MINs for binding specifically to TP and TPS. Such MIPs and MINs have great potential for industrial and medical applications, particularly for the selective separation of TP and TPS