Spectrometric studies on stability of tenuazonic acid (TeA) solution in organic solvents

The stability of tenuazonic acid solution at different temperatures and storage times was studied using methanol, methanol-water (8:2 v/v), benzene and benzene-acetonitrile (98:2 v/v) as solvents. Solutions were analysed by a spectrometric method TeA U.V.-spectrum was recorded. Results indicated that the optimum temperature for long-time storage period of tenuazonic acid solution in any solvent assayed is -20°C. Benzene and benzene-acetonitrile (98:2 v/v) could be advised to make tenuazonic acid solution which will be stored less than 2 months at 4°C. Methanol and methanolwater (8:2 v/v) are not recommended because a low stability of TeA solution in this solvents.     

DNA Base Pair Resolution Measurements Using Resonance Energy Transfer Efficiency in Lanthanide Doped Nanoparticles

Lanthanide-doped nanoparticles are of considerable interest for biodetection and bioimaging techniques thanks to their unique chemical and optical properties. As a sensitive luminescence material, they can be used as (bio) probes in Förster Resonance Energy Transfer (FRET) where trivalent lanthanide ions (La³⁺) act as energy donors. In this paper we present an efficient method to transfer ultrasmall (ca. 8 nm) NaYF₄ nanoparticles dispersed in organic solvent to an aqueous solution via oxidation of the oleic acid ligand. Nanoparticles were then functionalized with single strand DNA oligomers (ssDNA) by inducing covalent bonds between surface carboxylic groups and a 5’ amine modified-ssDNA. Hybridization with the 5’ fluorophore (Cy5) modified complementary ssDNA strand demonstrated the specificity of binding and allowed the fine control over the distance between Eu³⁺ ions doped nanoparticle and the fluorophore by varying the number of the dsDNA base pairs. First, our results confirmed nonradiative resonance energy transfer and demonstrate the dependence of its efficiency on the distance between the donor (Eu³⁺) and the acceptor (Cy5) with sensitivity at a nanometre scale.     

Effect of exogenous circulating anti-bPL antibodies on bovine placental lactogen measurements in foetal samples

Background  

The involvement of placental lactogen (PL) in the regulation of foetal growth has been investigated in different species by in vivo immunomodulation techniques. However, when circulating antibodies are present together with the hormone, the procedure for hormonal measurement becomes considerably complex. The aim of this study was the immunoneutralization of bovine placental lactogen (bPL) concentrations in bovine foetal circulation by direct infusion of rabbit anti-bPL purified immunoglobulins (IgG) via a foetal catheter (in vivo study). The ability of a RIA based on guinea pig anti-bPL antiserum, for the measurement of bPL concentrations in samples containing exogenous rabbit anti-bPL immunoglobulins, was also analyzed in in vitro and in vivo conditions.     

Characterisation of Peptide Microarrays for Studying Antibody-Antigen Binding Using Surface Plasmon Resonance Imagery

Background

Non-specific binding to biosensor surfaces is a major obstacle to quantitative analysis of selective retention of analytes at immobilized target molecules. Although a range of chemical antifouling monolayers has been developed to address this problem, many macromolecular interactions still remain refractory to analysis due to the prevalent high degree of non-specific binding. We describe how we use the dynamic process of the formation of self assembling monolayers and optimise physical and chemical properties thus reducing considerably non-specific binding and allowing analysis of specific binding of analytes to immobilized target molecules.

Methodology/Principal Findings

We illustrate this approach by the production of specific protein arrays for the analysis of interactions between the 65kDa isoform of human glutamate decarboxylase (GAD65) and a human monoclonal antibody. Our data illustrate that we have effectively eliminated non-specific interactions with the surface containing the immobilised GAD65 molecules. The findings have several implications. First, this approach obviates the dubious process of background subtraction and gives access to more accurate kinetic and equilibrium values that are no longer contaminated by multiphase non-specific binding. Second, an enhanced signal to noise ratio increases not only the sensitivity but also confidence in the use of SPR to generate kinetic constants that may then be inserted into van''t Hoff type analyses to provide comparative ΔG, ΔS and ΔH values, making this an efficient, rapid and competitive alternative to ITC measurements used in drug and macromolecular-interaction mechanistic studies. Third, the accuracy of the measurements allows the application of more intricate interaction models than simple Langmuir monophasic binding.

Conclusions

The detection and measurement of antibody binding by the type 1 diabetes autoantigen GAD65 represents an example of an antibody-antigen interaction where good structural, mechanistic and immunological data are available. Using SPRi we were able to characterise the kinetics of the interaction in greater detail than ELISA/RIA methods. Furthermore, our data indicate that SPRi is well suited to a multiplexed immunoassay using GAD65 proteins, and may be applicable to other biomarkers.     

Rapid coupling of Surface Plasmon Resonance (SPR and SPRi) and ProteinChip based mass spectrometry for the identification of proteins in nucleoprotein interactions

We compared coupling approaches of SPR to LC-MS and ProteinChip-based mass spectrometry (SELDI) as a means of identifying proteins captured on DNA surfaces. The approach we outline has the potential to allow multiple, quantitative analysis of macromolecular interactions followed by rapid mass spectrometry identification of retained material.     

The N terminus of the serpin, tengpin, functions to trap the metastable native state

Serpins fold to a metastable native state and are susceptible to undergoing spontaneous conformational change to more stable conformers, such as the latent form. We investigated conformational change in tengpin, an unusual prokaryotic serpin from the extremophile Thermoanaerobacter tengcongensis. In addition to the serpin domain, tengpin contains a functionally uncharacterized 56-amino-acid amino-terminal region. Deletion of this domain creates a variant--tengpinDelta51--which folds past the native state and readily adopts the latent conformation. Analysis of crystal structures together with mutagenesis studies show that the N terminus of tengpin protects a hydrophobic patch in the serpin domain and functions to trap tengpin in its native metastable state. A 13-amino-acid peptide derived from the N terminus is able to mimick the role of the N terminus in stabilizing the native state of tengpinDelta51. Therefore, the function of the N terminus in tengpin resembles protein cofactors that prevent mammalian serpins from spontaneously adopting the latent conformation.     

Relationship of aerobic and anaerobic parameters with 400 m front crawl swimming performance

The aims of the present study were to investigate the relationship of aerobic and anaerobic parameters with 400 m performance, and establish which variable better explains long distance performance in swimming. Twenty-two swimmers (19.1±1.5 years, height 173.9±10.0 cm, body mass 71.2±10.2 kg; 76.6±5.3% of 400 m world record) underwent a lactate minimum test to determine lactate minimum speed (LMS) (i.e., aerobic capacity index). Moreover, the swimmers performed a 400 m maximal effort to determine mean speed (S400m), peak oxygen uptake (V.O2PEAK) and total anaerobic contribution (C_ANA). The C_ANA was assumed as the sum of alactic and lactic contributions. Physiological parameters of 400 m were determined using the backward extrapolation technique (V.O2PEAK and alactic contributions of C_ANA) and blood lactate concentration analysis (lactic anaerobic contributions of C_ANA). The Pearson correlation test and backward multiple regression analysis were used to verify the possible correlations between the physiological indices (predictor factors) and S400m (independent variable) (p < 0.05). Values are presented as mean ± standard deviation. Significant correlations were observed between S400m (1.4±0.1 m·s^-1) and LMS (1.3±0.1 m·s^-1; r = 0.80), V.O2PEAK (4.5±3.9 L·min^-1; r = 0.72) and C_ANA (4.7±1.5 L·O₂; r= 0.44). The best model constructed using multiple regression analysis demonstrated that LMS and V.O2PEAK explained 85% of the 400 m performance variance. When backward multiple regression analysis was performed, C_ANA lost significance. Thus, the results demonstrated that both aerobic parameters (capacity and power) can be used to predict 400 m swimming performance.     

Synthesis and evaluation of a bimodal CXCR4 antagonistic peptide

The antagonistic Ac-TZ14011 peptide, which binds to the chemokine receptor 4, has been labeled with a multifunctional single attachment point reagent that contains a DTPA chelate and a fluorescent dye with Cy5.5 spectral properties. Flow cytometry and confocal microscopy showed that the bimodal labeled peptide gave a specific receptor binding that is similar to monofunctionalized peptide derivatives. Therefore, the newly developed bimodal peptide derivative can be used in multimodal imaging applications.     

A computational investigation of kinetoplastid trans-splicing

Trans-splicing is an unusual process in which two separate RNA strands are spliced together to yield a mature mRNA. We present a novel computational approach which has an overall accuracy of 82% and can predict 92% of known trans-splicing sites. We have applied our method to chromosomes 1 and 3 of Leishmania major, with high-confidence predictions for 85% and 88% of annotated genes respectively. We suggest some extensions of our method to other systems.     

Using co-occurrence network structure to extract synonymous gene and protein names from MEDLINE abstracts

Background  

Text-mining can assist biomedical researchers in reducing information overload by extracting useful knowledge from large collections of text. We developed a novel text-mining method based on analyzing the network structure created by symbol co-occurrences as a way to extend the capabilities of knowledge extraction. The method was applied to the task of automatic gene and protein name synonym extraction.