Methods in molecular biology
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Protein phosphorylation plays an essential role in the regulation of various cellular functions. Dysregulation of phosphorylation is implicated in the pathogenesis of certain cancers, diabetes, cardiovascular diseases, and central nervous system disorders. As a result, protein kinases have become potential drug targets for treating a wide variety of diseases. ⋯ However, identification of bona fide kinase substrates has remained challenging, necessitating the development of new methods and techniques. The kinase assay linked phosphoproteomics (KALIP) approach integrates in vitro kinase assays with global phosphoproteomics experiments to identify the direct substrates of protein kinases. This strategy has demonstrated outstanding sensitivity and a low false-positive rate for kinase substrate screening.
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Isobaric tagging reagents have become an invaluable tool for multiplexed quantitative proteomic analysis. These reagents can label multiple, distinct peptide samples from virtually any source material (e.g., tissue, cell line, purified proteins), allowing users the opportunity to assess changes in peptide abundances across many different time points or experimental conditions. Here, we describe the application of isobaric peptide labeling, specifically 8plex isobaric tags for relative and absolute quantitation (8plex iTRAQ), for quantitative phosphoproteomic analysis of cultured cells or tissue suspensions. For this particular protocol, labeled samples are pooled, fractionated by strong cation exchange chromatography, enriched for phosphopeptides, and analyzed by tandem mass spectrometry (LC-MS/MS) for both peptide identification and quantitation.
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This chapter presents an introduction to data mining with machine learning. It gives an overview of various types of machine learning, along with some examples. It explains how to download, install, and run the WEKA data mining toolkit on a simple data set, then proceeds to explain how one might approach a bioinformatics problem. Finally, it includes a brief summary of machine learning algorithms for other types of data mining problems, and provides suggestions about where to find additional information.
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Clostridium difficile is a challenging infection that can be difficult to treat with antibiotic therapy. This chapter outlines the processing material for fecal microbiota transplantation (FMT), also known as stool transplant. ⋯ FMT uses a stool sample collected from a healthy, screened donor to restore healthy microbiota in the colon of a patient with CDI for symptom resolution. Here, we describe a rapid method for FMT preparation that uses inexpensive and disposable materials.
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In recent years, mass spectrometry-based phosphoproteomics has propelled our knowledge about the regulation of cellular pathways. Nevertheless, typically applied bottom-up strategies have several limitations. Trypsin, the preferentially used proteolytic enzyme shows impaired cleavage efficiency in the vicinity of phosphorylation sites. ⋯ To overcome these limitations, we introduce an alternative and simple approach based on the usage of the nonspecific serine protease subtilisin, which enables a fast and reproducible digestion and provides access to "hidden" areas of the proteome. Thus, in a single LC-MS experiment >1800 phosphopeptides were confidently identified and localized from 125 μg of HeLa digest, compared to >2100 sites after tryptic digestion. While the overlap was less than 20 %, subtilisin allowed the identification of many phosphorylation sites that are theoretically not accessible via tryptic digestion, thus considerably increasing the coverage of the phosphoproteome.