Purification of (Ca2+-Mg2+)-ATPase from rat liver plasma membranes

The Ca2+-stimulated, Mg2+-dependent ATPase from rat liver plasma membranes was solubilized using the detergent polyoxyethylene 9 lauryl ether and purified by column chromatography using Polybuffer Exchanger 94, concanavalin A-Sepharose 4B, and Sephadex G-200. The molecular weight of the enzyme, estimated by gel filtration in the presence of the detergent on a Sephadex G-200 column, was 200,000 +/- 15,000. The enzyme was purified at least 300-fold from rat liver plasma membranes and had a specific activity of 19.7 mumol/mg/min. Polyacrylamide gel electrophoresis under nondenaturing conditions of the purified enzyme indicated that the enzymatic activity correlated with the major protein band. In sodium dodecyl sulfate-polyacrylamide gel electrophoresis, one major band in the molecular weight range of 70,000 +/- 5,000 was seen. The isoelectric point of the purified enzyme was 6.9 +/- 0.2 as determined by analytical isoelectric focusing. The enzyme was activated by Ca2+ with an apparent half-saturation constant of 87 +/- 2 nM for Ca2+. Calmodulin and trifluoperazine at the concentration of 1 microgram/ml and 100 microM, respectively, had no effect on the enzymatic activity.     

Synthesis of a new carrier for immunization: polytuftsin. Two examples of its use with peptides selected in the hepatitis B surface antigen

Sequential poly(Arg-Thr-Lys-Pro) consisting mainly of the repeat of tuftsin Thr-Lys-Pro-Arg was synthesized by condensing the p-nitrophenyl ester of Arg(HCl)-Thr-Lys-(2-Cl-Z)-Pro in the presence of HOBt. Two haptenic sequences of the Pre-S region of hepatitis B virus antigen (10-26 and 39-55) were prepared by solid phase and coupled to polytuftsin via glutaraldehyde. The peptides, either free or coupled to polytuftsin, were administrated to mice and the antisera were assayed by ELISA. Coupling the peptides to the polypeptide significantly improved the anti-peptide antibody titer in Freund complete adjuvant or in NaCl 0.9%. Cross-reaction between antibodies induced by the peptides and the native protein was also improved. Polytuftsin alone is very poorly immunogenic.     

State-of-the art data normalization methods improve NMR-based metabolomic analysis

Extracting biomedical information from large metabolomic datasets by multivariate data analysis is of considerable complexity. Common challenges include among others screening for differentially produced metabolites, estimation of fold changes, and sample classification. Prior to these analysis steps, it is important to minimize contributions from unwanted biases and experimental variance. This is the goal of data preprocessing. In this work, different data normalization methods were compared systematically employing two different datasets generated by means of nuclear magnetic resonance (NMR) spectroscopy. To this end, two different types of normalization methods were used, one aiming to remove unwanted sample-to-sample variation while the other adjusts the variance of the different metabolites by variable scaling and variance stabilization methods. The impact of all methods tested on sample classification was evaluated on urinary NMR fingerprints obtained from healthy volunteers and patients suffering from autosomal polycystic kidney disease (ADPKD). Performance in terms of screening for differentially produced metabolites was investigated on a dataset following a Latin-square design, where varied amounts of 8 different metabolites were spiked into a human urine matrix while keeping the total spike-in amount constant. In addition, specific tests were conducted to systematically investigate the influence of the different preprocessing methods on the structure of the analyzed data. In conclusion, preprocessing methods originally developed for DNA microarray analysis, in particular, Quantile and Cubic-Spline Normalization, performed best in reducing bias, accurately detecting fold changes, and classifying samples.

     

Plasma Biomarkers Discriminate Clinical Forms of Multiple Sclerosis

Multiple sclerosis, the most common cause of neurological disability in young population after trauma, represents a significant public health burden. Current challenges associated with management of multiple sclerosis (MS) patients stem from the lack of biomarkers that might enable stratification of the different clinical forms of MS and thus prompt treatment for those patients with progressive MS, for whom there is currently no therapy available. In the present work we analyzed a set of thirty different plasma cytokines, chemokines and growth factors present in circulation of 129 MS patients with different clinical forms (relapsing remitting, secondary progressive and primary progressive MS) and 53 healthy controls, across two independent cohorts. The set of plasma analytes was quantified with Luminex xMAP technology and their predictive power regarding clinical outcome was evaluated both individually using ROC curves and in combination using logistic regression analysis. Our results from two independent cohorts of MS patients demonstrate that the divergent clinical and histology-based MS forms are associated with distinct profiles of circulating plasma protein biomarkers, with distinct signatures being composed of chemokines and growth/angiogenic factors. With this work, we propose that an evaluation of a set of 4 circulating biomarkers (HGF, Eotaxin/CCL11, EGF and MIP-1β/CCL4) in MS patients might serve as an effective tool in the diagnosis and more personalized therapeutic targeting of MS patients.