Identification of proteins related to the stress response in Enterococcus faecalis V583 caused by bovine bile.

Background: Enterococcus faecalis is an opportunistic pathogen and one of the most important causes of hospital infections. Bile acids are a major stress factor bacteria have to cope with in order to colonize and survive in the gastro-intestinal tract. The aim of this study was to investigate the effects of bile acids on the intracellular proteome of E.

Proteome changes in bovine longissimus thoracis muscle during the first 48 h postmortem: shifts in energy status and myofibrillar stability.

Changes in the insoluble protein fraction of bovine longissimus thoracis muscle from eight Norwegian Red (NRF) dual-purpose young bulls during the first 48 h postmortem were investigated by two-dimensional gel electrophoresis (2DE) and matrix-assisted laser desorption ionization-time of flight tandem mass spectrometry (MALDI-TOF MS/MS). Significant changes were observed in a total of 35 proteins, and of those, 26 were identified and divided into three different groups: metabolic enzymes, cellular defense/stress proteins, and structural proteins, according to their predicted function. The majority of the metabolic enzymes identified are involved in the energy metabolism of the cell, while the cellular defense/stress proteins can be related to regulation and stabilization of the myofibrillar proteins.

Improved dynamic range of protein quantification in silver-stained gels by modelling gel images over time.

Silver staining is a commonly used protein stain to visualise proteins separated by 2-DE. Despite this, the technique suffers from a limited dynamic range, making the simultaneous quantification of high- and low-abundant proteins difficult. In this paper we take advantage of the fact that silver staining is not an end-point stain by photographing the gels during development.

Combination of statistical approaches for analysis of 2-DE data gives complementary results.

Five methods for finding significant changes in proteome data have been used to analyze a two-dimensional gel electrophoresis data set. We used both univariate (ANOVA) and multivariate (Partial Least Squares with jackknife, Cross Model Validation, Power-PLS and CovProc) methods. The gels were taken from a time-series experiment exploring the changes in metabolic enzymes in bovine muscle at five time-points after slaughter.

An improved pixel-based approach for analyzing images in two-dimensional gel electrophoresis.

An improved pixel-based approach for analyzing 2-DE images is presented. The key feature of the method is to create a mask based on all gels in the experiment using image morphology, followed by multivariate analysis on the pixel level. The method reduces the impact of noise and background by identifying regions in the image where protein spots are present, but make no assumption on individual spot boundaries for isolated spots.

A new method for assigning common spot boundaries for multiple gels in two-dimensional gel electrophoresis.

The benefits of defining common spot boundaries when several gels from 2-DE are compared and analyzed have lately been stressed by both commercial software producers and users of this software. Though the importance of common spot boundaries is clearly stated, few reports exist that target this issue explicitly. In this study a method for defining common spots boundaries is developed, called the spot density method.

Two-dimensional LC-MS/MS in detection of peptides in hypothalamus of the rat subjected to hypoxic stress.

A capillary 2-D LC method coupled with IT MS has been used for separation and identification of peptides in rat hypothalamus. Animals of two different age groups (8 and 50 wk) were exposed to two different rates of CO(2 )in inhaled air to investigate the influence of different hypoxia/hypercapnia levels and their stress-related factor on the peptide excretion. Peptide compounds were fractionated (strong cation exchange chromatography), trapped, and separated (RP chromatography), and MS/MS mass spectra were used for identification.

Application of proteomics to understand the molecular mechanisms behind meat quality.

The proteome is expressed from the genome, influenced by environmental and processing conditions, and can be seen as the molecular link between the genome and the functional quality characteristics of the meat. In contrast to traditional biochemical methods where one protein is studied at a time, several hundred proteins can be studied simultaneously. Proteomics is a promising and powerful tool in meat science and this is reflected by the increasing number of studies emerging in the literature using proteomics as the key tool to unleash the molecular mechanisms behind different genetic backgrounds or processing techniques of meat.

Pixel-based analysis of multiple images for the identification of changes: a novel approach applied to unravel proteome patterns [corrected] of 2-D electrophoresis gel images.

A novel approach for revealing patterns of proteome variation among series of 2-DE gel images is presented. The approach utilises image alignment to ensure that each pixel represents the same information across all gels. Gel images are normalised, and background corrected, followed by unfolding of the images to 1-D pixel vectors and analysing pixel vectors by multivariate data modelling.

Multivariate analysis of 2-DE protein patterns--practical approaches.

Practical approaches to the use of multivariate data analysis of 2-DE protein patterns are demonstrated by three independent strategies for the image analysis and the multivariate analysis on the same set of 2-DE data. Four wheat varieties were selected on the basis of their baking quality. Two of the varieties were of strong baking quality and hard wheat kernel and two were of weak baking quality and soft kernel.

Challenges related to analysis of protein spot volumes from two-dimensional gel electrophoresis as revealed by replicate gels.

Assumptions that need to be considered prior to statistical analysis of protein spot volumes from two-dimensional gel electrophoresis (2-DE) data are studied using replicate gels of the same sample. The most important observation is that the data tables of protein spot volumes from 2-DE images contain a large number of missing values, which are not consistent with the presence or absence of the proteins. This implies both loss of information and problems for the subsequent statistical analysis.