Nonenzymatic Electrochemical Sensor with Ratiometric Signal Output for Selective Determination of Superoxide Anion in Rat Brain

There is still an urgent need to develop reliable analytical methods of O₂^•- in vivo for deeply elucidating the roles of O₂^•- playing in the brain. Herein, a nonenzymatic electrochemical sensor with ratiometric signal output was developed for an in vivo analysis of O₂^•- in the rat brain. Diphenylphosphonate-2-naphthol ester (ND) was designed and synthesized as a specific recognition molecule for the selective determination of O₂^•-. An anodic peak ascribed to the oxidation of 2-naphthol was generated via the nucleophilic substitution between ND and O₂^•- and was increased with the increasing concentration of O₂^•-. Meanwhile, the inner reference of methylene blue (MB) was co-assembled at the electrode surface to enhance the determination accuracy of O₂^•-. The anodic peak current ratio between 2-naphthol and MB exhibited a good linear relationship with the concentration of O₂^•- from 2 to 200 μM. Because of the stable molecule character of ND and its specific reaction with O₂^•-, the developed electrochemical sensor demonstrated excellent selectivity toward various potential interferences in the brain and good stability even after storage for 7 days. Accordingly, the present electrochemical sensor with high selectivity, high stability, and high accuracy was successfully exploited in monitoring the levels of O₂^•- in the rat brain and that of the diabetic model followed by cerebral ischemia.

Optimizing Mass Spectrometry Analyses: A Tailored Review on the Utility of Design of Experiments

Mass spectrometry (MS) has emerged as a tool that can analyze nearly all classes of molecules, with its scope rapidly expanding in the areas of post-translational modifications, MS instrumentation, and many others. Yet integration of novel analyte preparatory and purification methods with existing or novel mass spectrometers can introduce new challenges for MS sensitivity. The mechanisms that govern detection by MS are particularly complex and interdependent, including ionization efficiency, ion suppression, and transmission. Performance of both off-line and MS methods can be optimized separately or, when appropriate, simultaneously through statistical designs, broadly referred to as "design of experiments" (DOE). The following review provides a tutorial-like guide into the selection of DOE for MS experiments, the practices for modeling and optimization of response variables, and the available software tools that support DOE implementation in any laboratory. This review comes 3 years after the latest DOE review (Hibbert DB, 2012), which provided a comprehensive overview on the types of designs available and their statistical construction. Since that time, new classes of DOE, such as the definitive screening design, have emerged and new calls have been made for mass spectrometrists to adopt the practice. Rather than exhaustively cover all possible designs, we have highlighted the three most practical DOE classes available to mass spectrometrists. This review further differentiates itself by providing expert recommendations for experimental setup and defining DOE entirely in the context of three case-studies that highlight the utility of different designs to achieve different goals. A step-by-step tutorial is also provided.

Application of GC-MS coupled with chemometrics for scanning serum metabolic biomarkers from renal fibrosis rat

Renal interstitial fibrosis closely relates to chronic kidney disease and is regarded as the final common pathway in most cases of end-stage renal disease. Metabolomic biomarkers can facilitate early diagnosis and allow better understanding of the pathogenesis underlying renal fibrosis. Gas chromatography-mass spectrometry (GC/MS) is one of the most promising techniques for identification of metabolites. However, the existence of the background, baseline offset, and overlapping peaks makes accurate identification of the metabolites unachievable. In this study, GC/MS coupled with chemometric methods was successfully developed to accurately identify and seek metabolic biomarkers for rats with renal fibrosis. By using these methods, seventy-six metabolites from rat serum were accurately identified and five metabolites (i.e., urea, ornithine, citric acid, galactose, and cholesterol) may be useful as potential biomarkers for renal fibrosis.

Optimisation of the synthesis of vancomycin-selective molecularly imprinted polymer nanoparticles using automatic photoreactor

A novel optimized protocol for solid-state synthesis of molecularly imprinted polymer nanoparticles (nanoMIPs) with specificity for antibiotic vancomycin is described. The experimental objective was optimization of the synthesis parameters (factors) affecting the yield of obtained nanoparticles which have been synthesized using the first prototype of an automated solid-phase synthesizer. Applications of experimental design (or design of experiments) in optimization of nanoMIP yield were carried out using MODDE 9.0 software. The factors chosen in the model were the amount of functional monomers in the polymerization mixture, irradiation time, temperature during polymerization, and elution temperature. In general, it could be concluded that the irradiation time is the most important and the temperature was the least important factor which influences the yield of nanoparticles. Overall, the response surface methodology proved to be an effective tool in reducing time required for optimization of complex experimental conditions.

An ultrasonication-assisted extraction and derivatization protocol for GC/TOFMS-based metabolite profiling

Conventional chemical derivatization of metabolites in biological specimens is time-consuming, which limits the throughput and efficiency of metabolite profiling using a gas chromatography/time-of-flight mass spectrometry (GC/TOFMS) platform. We report an ultrasonication-assisted protocol which reduces the derivatization time from hours to about 30 min and significantly enhances the derivatization efficiency prior to a GC/TOFMS analysis. The protocol was evaluated using 40 compounds representing different classes of human metabolites, and demonstrated good analytical precision and accuracy. In comparison with the conventional method, the new protocol was able to increase the intensity of most of the identified peaks (71.0%) in the GC/TOFMS chromatograms of human serum samples. The detected compounds with increased intensity include most amino acids, keto-containing organic acids, carbonyl-containing carbohydrates, and unsaturated fatty acids. We applied this protocol in a metabolomic study of human serum samples obtained from 34 patients diagnosed with hypertension and 29 age- and gender-matched healthy subjects. Metabolite markers associated with hypertension, including glucosamine, D-sorbitol, 1-stearoylglycerol, and homocysteine, were identified and validated by statistical methods and use of reference standards. Our work highlights the potential of this novel approach for the large-scale metabolite profiling of samples generated from plant, animal, and clinical and epidemiological studies.

Systems level studies of mammalian metabolomes: the roles of mass spectrometry and nuclear magnetic resonance spectroscopy

The study of biological systems in a holistic manner (systems biology) is increasingly being viewed as a necessity to provide qualitative and quantitative descriptions of the emergent properties of the complete system. Systems biology performs studies focussed on the complex interactions of system components; emphasising the whole system rather than the individual parts. Many perturbations to mammalian systems (diet, disease, drugs) are multi-factorial and the study of small parts of the system is insufficient to understand the complete phenotypic changes induced. Metabolomics is one functional level tool being employed to investigate the complex interactions of metabolites with other metabolites (metabolism) but also the regulatory role metabolites provide through interaction with genes, transcripts and proteins (e.g. allosteric regulation). Technological developments are the driving force behind advances in scientific knowledge. Recent advances in the two analytical platforms of mass spectrometry (MS) and nuclear magnetic resonance (NMR) spectroscopy have driven forward the discipline of metabolomics. In this critical review, an introduction to metabolites, metabolomes, metabolomics and the role of MS and NMR spectroscopy will be provided. The applications of metabolomics in mammalian systems biology for the study of the health-disease continuum, drug efficacy and toxicity and dietary effects on mammalian health will be reviewed. The current limitations and future goals of metabolomics in systems biology will also be discussed (374 references).

An optimized procedure for metabonomic analysis of rat liver tissue using gas chromatography/time-of-flight mass spectrometry

In this paper, we present a tissue metabonomic method with an optimized extraction procedure followed by instrumental analysis with gas chromatography/time-of-flight mass spectrometry (GC/TOFMS) and spectral data analysis with multivariate statistics. Metabolite extractions were carried out using three solvents: chloroform, methanol, and water, with design of experiment (DOE) theory and multivariate statistical analysis. A two-step metabolite extraction procedure was optimized using a mixed solvent of chloroform-methanol-water (1:2:1, v/v/v) and then followed by methanol alone. This approach was subsequently validated using standard compounds and liver tissues. Calibration curves were obtained in the range of 0.50-125.0mug/mL for standards and 0.02-0.25g/mL acceptable for liver tissue samples. For most of the metabolites investigated, relative standard deviations (RSD) were below 10% within a day (reproducibility) and below 15% within a week (stability). Rat liver tissues of carbon tetrachloride-induced acute liver injury models (n=10) and healthy control rats (n=10) were analyzed which demonstrated the applicability of the developed procedure for the tissue metabonomic study.

Metabolite analysis of human fecal water by gas chromatography/mass spectrometry with ethyl chloroformate derivatization

Fecal water is a complex mixture of various metabolites with a wide range of physicochemical properties and boiling points. The analytical method developed here provides a qualitative and quantitative gas chromatography/mass spectrometry (GC/MS) analysis, with high sensitivity and efficiency, coupled with derivatization of ethyl chloroformate in aqueous medium. The water/ethanol/pyridine ratio was optimized to 12:6:1, and a two-step derivatization with an initial pH regulation of 0.1M sodium bicarbonate was developed. The deionized water exhibited better extraction efficiency for fecal water compounds than did acidified and alkalized water. Furthermore, more amino acids were extracted from frozen fecal samples than from fresh samples based on multivariate statistical analysis and univariate statistical validation on GC/MS data. Method validation by 34 reference standards and fecal water samples showed a correlation coefficient higher than 0.99 for each of the standards, and the limit of detection (LOD) was from 10 to 500pg on-column for most of the standards. The analytical equipment exhibited excellent repeatability, with the relative standard deviation (RSD) lower than 4% for standards and lower than 7% for fecal water. The derivatization method also demonstrated good repeatability, with the RSD lower than 6.4% for standards (except 3,4-dihydroxyphenylacetic acid) and lower than 10% for fecal water (except dicarboxylic acids). The qualitative means by searching the electron impact (EI) mass spectral database, chemical ionization (CI) mass spectra validation, and reference standards comparison totally identified and structurally confirmed 73 compounds, and the fecal water compounds of healthy humans were also quantified. This protocol shows a promising application in metabolome analysis based on human fecal water samples.