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Proteomic Patterns (proteomic + pattern)

Distribution by Scientific Domains

Chemistry	80%

Selected Abstracts

Proteomic patterns for classification of ovarian cancer and CTCL serum samples utilizing peak pairs indicative of post-translational modifications

PROTEINS: STRUCTURE, FUNCTION AND BIOINFORMATICS, Issue 22 2007
Chenwei Liu
Abstract Proteomic patterns as a potential diagnostic technology has been well established for several cancer conditions and other diseases. The use of machine learning techniques such as decision trees, neural networks, genetic algorithms, and other methods has been the basis for pattern determination. Cancer is known to involve signaling pathways that are regulated through PTM of proteins. These modifications are also detectable with high confidence using high-resolution MS. We generated data using a prOTOFÔ mass spectrometer on two sets of patient samples: ovarian cancer and cutaneous t-cell lymphoma (CTCL) with matched normal samples for each disease. Using the knowledge of mass shifts caused by common modifications, we built models using peak pairs and compared this to a conventional technique using individual peaks. The results for each disease showed that a small number of peak pairs gave classification equal to or better than the conventional technique that used multiple individual peaks. This simple peak picking technique could be used to guide identification of important peak pairs involved in the disease process. [source]

Response of Listeria monocytogenes to liquid smoke

JOURNAL OF APPLIED MICROBIOLOGY, Issue 6 2008
M. Guilbaud
Abstract Aims:, To investigate the effect of liquid smoke on growth, survival, proteomic pattern and haemolytic potential of Listeria monocytogenes. Methods and Results:, Growth and survival curves were recorded in brain,heart infusion broth supplemented with three concentrations of liquid smoke. L. monocytogenes growth was inhibited in the presence of 15 ,g ml,1 phenol while a rapid decrease in cell viability occurred in the presence of 30 ,g ml,1 phenol. The proteome of L. monocytogenes cytosoluble proteins was slightly modified after 2-h incubation with 30 ,g ml,1 phenol but no protein already characterized in response to other known stresses was induced, except the protease ClpP. Liquid smoke inhibited the haemolytic potential without affecting hly gene expression, showing a potential inhibition of protein activity or stability. Conclusions:, The presence of liquid smoke in a rich medium strongly affected growth and survival of L. monocytogenes. Brief smoke stress affected the metabolic pathways and inhibited the haemolytic activity of L. monocytogenes. Significance and Impact of Study:, This study is a first step in the investigation of the influence of a smoked product on L. monocytogenes strains. [source]

Processing and classification of protein mass spectra

MASS SPECTROMETRY REVIEWS, Issue 3 2006
Melanie Hilario
Abstract Among the many applications of mass spectrometry, biomarker pattern discovery from protein mass spectra has aroused considerable interest in the past few years. While research efforts have raised hopes of early and less invasive diagnosis, they have also brought to light the many issues to be tackled before mass-spectra-based proteomic patterns become routine clinical tools. Known issues cover the entire pipeline leading from sample collection through mass spectrometry analytics to biomarker pattern extraction, validation, and interpretation. This study focuses on the data-analytical phase, which takes as input mass spectra of biological specimens and discovers patterns of peak masses and intensities that discriminate between different pathological states. We survey current work and investigate computational issues concerning the different stages of the knowledge discovery process: exploratory analysis, quality control, and diverse transforms of mass spectra, followed by further dimensionality reduction, classification, and model evaluation. We conclude after a brief discussion of the critical biomedical task of analyzing discovered discriminatory patterns to identify their component proteins as well as interpret and validate their biological implications. © 2006 Wiley Periodicals, Inc., Mass Spec Rev 25:409,449, 2006 [source]

Mass spectrometry for the detection of differentially expressed proteins: a comparison of surface-enhanced laser desorption/ionization and capillary electrophoresis/mass spectrometry

RAPID COMMUNICATIONS IN MASS SPECTROMETRY, Issue 2 2004
Nils v. Neuhoff
The discovery of biomarkers is currently attracting much interest as it harbors great potential for the diagnosis and monitoring of human diseases. Here we have used two advanced mass spectroscopy based technologies, surface enhanced laser desorption ionization (SELDI-MS) and capillary electrophoresis/mass spectrometry (CE/MS), to obtain proteomic patterns of urine samples from patients suffering from membranous glomerulonephritis (MGN) and healthy volunteers. The results indicate that CE/MS analysis is able to display a rich and complex pattern of polypeptides with high resolution and high mass accuracy. In order to analyze these patterns, the MosaiqueVisu software was developed for peak identification, deconvolution and the display of refined maps in a three-dimensional format. The polypeptide profiles obtained with SELDI-MS from the same samples are much sparser and show lower resolution and mass accuracy. The SELDI-MS profiles are further heavily dependent on analyte concentration. SELDI-MS analysis identified three differentially expressed polypeptides, which are potential biomarkers that can distinguish healthy donors from patients with MGN. In contrast, approximately 200 potential biomarkers could be identified by CE/MS. Thus, while SELDI-MS is easy to use and requires very little sample, CE/MS generates much richer data sets that enable an in-depth analysis. Copyright © 2003 John Wiley & Sons, Ltd. [source]