Apolipoprotein B-48: comparison of fasting concentrations measured in normolipidaemic individuals using SDS-PAGE, immunoblotting and ELISA

Raised levels of chylomicrons and chylomicron remnants, which circulate following a meal, have been implicated in the development of atherosclerosis. Apolipoprotein (apo) B-48 is exclusively associated with chylomicron particles and provides a specific direct measurement of the number of intestinally derived lipoproteins in the circulation. The quantification of apo B-48 in biological samples is difficult due to the very low concentration in plasma, structural similarity to the N-terminal 48% of apo B-100 and lack of an appropriate standard for apo B-48. Sodium dodecyl sulphate polyacrylamide gel electrophoresis (SDS-PAGE), followed by coomassie blue staining, has been used for many years to measure apo B-48 levels in triacylglycerol (TAG)-rich lipoprotein samples. The raising of antiserum to apo B-48 has led to development of more sensitive and specific methods including immunoblotting and enzyme-linked immunosorbant assays (ELISAs). This has enabled direct measurement of apo B-48 in plasma without the need for separation into TAG-rich lipoproteins. A high degree of variability was observed in the apo B-48 concentrations reported in the literature both within and between the SDS-PAGE, immunoblotting and ELISA methods. (C) 2004 Elsevier Ireland Ltd. All rights reserved.

Anionic metabolic profiling of urine from antibiotic-treated rats by capillary electrophoresis–mass spectrometry

A recently developed capillary electrophoresis (CE)-negative-ionisation mass spectrometry (MS) method was used to profile anionic metabolites in a microbial-host co-metabolism study. Urine samples from rats receiving antibiotics (penicillin G and streptomycin sulfate) for 0, 4, or 8 days were analysed. A quality control sample was measured repeatedly to monitor the performance of the applied CE-MS method. After peak alignment, relative standard deviations (RSDs) for migration time of five representative compounds were below 0.4 %, whereas RSDs for peak area were 7.9–13.5 %. Using univariate and principal component analysis of obtained urinary metabolic profiles, groups of rats receiving different antibiotic treatment could be distinguished based on 17 discriminatory compounds, of which 15 were downregulated and 2 were upregulated upon treatment. Eleven compounds remained down- or upregulated after discontinuation of the antibiotics administration, whereas a recovery effect was observed for others. Based on accurate mass, nine compounds were putatively identified; these included the microbial-mammalian co-metabolites hippuric acid and indoxyl sulfate. Some discriminatory compounds were also observed by other analytical techniques, but CE-MS uniquely revealed ten metabolites modulated by antibiotic exposure, including aconitic acid and an oxocholic acid. This clearly demonstrates the added value of CE-MS for nontargeted profiling of small anionic metabolites in biological samples.

Error, reproducibility and sensitivity: a pipeline for data processing of Agilent oligonucleotide expression arrays

Background: Expression microarrays are increasingly used to obtain large scale transcriptomic information on a wide range of biological samples. Nevertheless, there is still much debate on the best ways to process data, to design experiments and analyse the output. Furthermore, many of the more sophisticated mathematical approaches to data analysis in the literature remain inaccessible to much of the biological research community. In this study we examine ways of extracting and analysing a large data set obtained using the Agilent long oligonucleotide transcriptomics platform, applied to a set of human macrophage and dendritic cell samples. Results: We describe and validate a series of data extraction, transformation and normalisation steps which are implemented via a new R function. Analysis of replicate normalised reference data demonstrate that intrarray variability is small (only around 2 of the mean log signal), while interarray variability from replicate array measurements has a standard deviation (SD) of around 0.5 log(2) units (6 of mean). The common practise of working with ratios of Cy5/Cy3 signal offers little further improvement in terms of reducing error. Comparison to expression data obtained using Arabidopsis samples demonstrates that the large number of genes in each sample showing a low level of transcription reflect the real complexity of the cellular transcriptome. Multidimensional scaling is used to show that the processed data identifies an underlying structure which reflect some of the key biological variables which define the data set. This structure is robust, allowing reliable comparison of samples collected over a number of years and collected by a variety of operators. Conclusions: This study outlines a robust and easily implemented pipeline for extracting, transforming normalising and visualising transcriptomic array data from Agilent expression platform. The analysis is used to obtain quantitative estimates of the SD arising from experimental (non biological) intra- and interarray variability, and for a lower threshold for determining whether an individual gene is expressed. The study provides a reliable basis for further more extensive studies of the systems biology of eukaryotic cells.

Fractional order and non-linear system identification algorithms for biomedical applications

We discuss the modelling of dielectric responses of amorphous biological samples. Such samples are commonly encountered in impedance spectroscopy studies as well as in UV, IR, optical and THz transient spectroscopy experiments and in pump-probe studies. In many occasions, the samples may display quenched absorption bands. A systems identification framework may be developed to provide parsimonious representations of such responses. To achieve this, it is appropriate to augment the standard models found in the identification literature to incorporate fractional order dynamics. Extensions of models using the forward shift operator, state space models as well as their non-linear Hammerstein-Wiener counterpart models are highlighted. We also discuss the need to extend the theory of electromagnetically excited networks which can account for fractional order behaviour in the non-linear regime by incorporating nonlinear elements to account for the observed non-linearities. The proposed approach leads to the development of a range of new chemometrics tools for biomedical data analysis and classification.

Simple method for sub-diffraction resolution imaging of cellular structures on standard confocal microscopes by three-photon absorption of quantum dots

This study describes a simple technique that improves a recently developed 3D sub-diffraction imaging method based on three-photon absorption of commercially available quantum dots. The method combines imaging of biological samples via tri-exciton generation in quantum dots with deconvolution and spectral multiplexing, resulting in a novel approach for multi-color imaging of even thick biological samples at a 1.4 to 1.9-fold better spatial resolution. This approach is realized on a conventional confocal microscope equipped with standard continuous-wave lasers. We demonstrate the potential of multi-color tri-exciton imaging of quantum dots combined with deconvolution on viral vesicles in lentivirally transduced cells as well as intermediate filaments in three-dimensional clusters of mouse-derived neural stem cells (neurospheres) and dense microtubuli arrays in myotubes formed by stacks of differentiated C2C12 myoblasts.

Coupling liquid MALDI MS to liquid chromatography

Matrix-assisted laser desorption/ionisation (MALDI) coupled with time-of-flight (TOF) mass spectrometry (MS) is a powerful tool for the analysis of biological samples, and nanoflow high-performance liquid chromatography (nanoHPLC) is a useful separation technique for the analysis of complex proteomics samples. The off-line combination of MALDI and nanoHPLC has been extensively investigated and straightforward techniques have been developed, focussing particularly on automated MALDI sample preparation that yields sensitive and reproducible spectra. Normally conventional solid MALDI matrices such as α-cyano-4-hydroxycinnamic acid (CHCA) are used for sample preparation. However, they have limited usefulness in quantitative measurements and automated data acquisition because of the formation of heterogeneous crystals, resulting in highly variable ion yields and desorption/ ionization characteristics. Glycerol-based liquid support matrices (LSM) have been proposed as an alternative to the traditional solid matrices as they provide increased shot-to-shot reproducibility, leading to prolonged and stable ion signals and therefore better results. This chapter focuses on the integration of the liquid LSM MALDI matrices into the LC-MALDI MS/MS approach in identifying complex and large proteomes. The interface between LC and MALDI consists of a robotic spotter, which fractionates the eluent from the LC column into nanoliter volumes, and co-spots simultaneously the liquid matrix with the eluent fractions onto a MALDI target plate via sheath flow. The efficiency of this method is demonstrated through the analysis of trypsin digests of both bovine serum albumin (BSA) and Lactobacillus plantarum WCFS1 proteins.

Biological and chemical assessment of zinc ageing in field soils

As zinc (Zn) is both an essential trace element and potential toxicant, the effects of Zn fixation in soil are of practical significance. Soil samples from four field sites amended with ZnSO4 were used to investigate ageing of soluble Zn under field conditions over a 2-year period. Lability of Zn measured using 65Zn radioisotope dilution showed a significant decrease over time and hence evidence of Zn fixation in three of the four soils. However, 0.01 M CaCl2 extractions and toxicity measurements using a genetically modified lux-marked bacterial biosensor did not indicate a decrease in soluble/bioavailable Zn over time. This was attributed to the strong regulatory effect of abiotic properties such as pH on these latter measurements. These results also showed that Zn ageing occurred immediately after Zn spiking, emphasising the need to incubate freshly spiked soils before ecotoxicity assessments. Ageing effects were detected in Zn-amended field soils using 65Zn isotopic dilution as a measure of lability, but not with either CaCl2 extractions or a lux-marked bacterial biosensor.

Using near infrared reflectance spectroscopy (NIRS) to predict the biological parameters of maize silage

The microbial fermentability, ruminal degradability and digestibility of 48 maize silages were determined using in vitro gas production (GP), in situ degradability and in vitro digestibility procedures. The silages were produced from forage maize harvested throughout the summer of 1998, and represent a wide range of physiological maturities. Large variations among samples were observed for all biological parameters, with the exception of in vitro digestibility and the asymptote of in vitro GP. The potential of near infrared reflectance spectroscopy (NIRS) to predict the biological parameters measured was determined by regression of the biological data against the respective spectral profile. NIRS demonstrated only a moderate ability (R-2 > 0.60-0.80) to predict in vitro digestibility, modelled kinetics of gas production (excluding the asymptote of gas production) and the modelled ruminally soluble dry matter (DM) fraction. Calibration statistics for remaining biological parameters were unacceptably poor (R-2 = 0.60). (C) 2004 Elsevier B.V. All rights reserved.