Quantitative iTRAQ-Based Proteomic Identification of Candidate Biomarkers for Diabetic Nephropathy in Plasma of Type 1 Diabetic Patients

# The Author(s) 2010. This article is published with open access at Springerlink.com Introduction As part of a clinical proteomics programme focused on diabetes and its complications, it was our goal to investigate the proteome of plasma in order to find improved candidate biomarkers to predict diabetic nephropathy. Methods Proteins derived from plasma from a crosssectiona

Characterization of a caspase-3-substrate kinome using an N- and C-terminally tagged protein kinase library produced by a cell-free system

Caspase-3 (CASP3) cleaves many proteins including protein kinases (PKs). Understanding the relationship(s) between CASP3 and its PK substrates is necessary to delineate the apoptosis signaling cascades that are controlled by CASP3 activity. We report herein the characterization of a CASP3-substrate kinome using a simple cell-free system to synthesize a library that contained 304 PKs tagged at their N- and C-termini (NCtagged PKs) and a luminescence assay to report CASP3 cleavage events. Forty-three PKs, including 30 newly identified PKs, were found to be CASP3 substrates, and 28 cleavage sites in 23 PKs were determined. Interestingly, 16 out of the 23 PKs have cleavage sites within 60 residues of their N- or C-termini. Furthermore, 29 of the PKs were cleaved in apoptotic cells, including five that were cleaved near their termini in vitro. In total, approximately 14% of the PKs tested were CASP3 substrates, suggesting that CASP3 cleavage of PKs may be a signature event in apoptotic-signaling cascades. This proteolytic assay method would identify other protease substrates

Characterization of a caspase-3-substrate kinome using an N- and C-terminally tagged protein kinase library produced by a cell-free system

Caspase-3 (CASP3) cleaves many proteins including protein kinases (PKs). Understanding the relationship(s) between CASP3 and its PK substrates is necessary to delineate the apoptosis signaling cascades that are controlled by CASP3 activity. We report herein the characterization of a CASP3-substrate kinome using a simple cell-free system to synthesize a library that contained 304 PKs tagged at their N- and C-termini (NCtagged PKs) and a luminescence assay to report CASP3 cleavage events. Forty-three PKs, including 30 newly identified PKs, were found to be CASP3 substrates, and 28 cleavage sites in 23 PKs were determined. Interestingly, 16 out of the 23 PKs have cleavage sites within 60 residues of their N- or C-termini. Furthermore, 29 of the PKs were cleaved in apoptotic cells, including five that were cleaved near their termini in vitro. In total, approximately 14% of the PKs tested were CASP3 substrates, suggesting that CASP3 cleavage of PKs may be a signature event in apoptotic-signaling cascades. This proteolytic assay method would identify other protease substrates

Quantitative Mass Spectrometry Analysis Using PAcIFIC for the Identification of Plasma Diagnostic Biomarkers for Abdominal Aortic Aneurysm

BACKGROUND: Abdominal aortic aneurysm (AAA) is characterized by increased aortic vessel wall diameter (>1.5 times normal) and loss of parallelism. This disease is responsible for 1-4% mortality occurring on rupture in males older than 65 years. Due to its asymptomatic nature, proteomic techniques were used to search for diagnostic biomarkers that might allow surgical intervention under nonlife threatening conditions. METHODOLOGY/PRINCIPAL FINDINGS: Pooled human plasma samples of 17 AAA and 17 control patients were depleted of the most abundant proteins and compared using a data-independent shotgun proteomic strategy, Precursor Acquisition Independent From Ion Count (PAcIFIC), combined with spectral counting and isobaric tandem mass tags. Both quantitative methods collectively identified 80 proteins as statistically differentially abundant between AAA and control patients. Among differentially abundant proteins, a subgroup of 19 was selected according to Gene Ontology classification and implication in AAA for verification by Western blot (WB) in the same 34 individual plasma samples that comprised the pools. From the 19 proteins, 12 were detected by WB. Five of them were verified to be differentially up-regulated in individual plasma of AAA patients: adiponectin, extracellular superoxide dismutase, protein AMBP, kallistatin and carboxypeptidase B2. CONCLUSIONS/SIGNIFICANCE: Plasma depletion of high abundance proteins combined with quantitative PAcIFIC analysis offered an efficient and sensitive tool for the screening of new potential biomarkers of AAA. However, WB analysis to verify the 19 PAcIFIC identified proteins of interest proved inconclusive save for five proteins. We discuss these five in terms of their potential relevance as biological markers for use in AAA screening of population at risk

Analysis of mass spectrometry data from the secretome of an explant model of articular cartilage exposed to pro-inflammatory and anti-inflammatory stimuli using machine learning

Background: Osteoarthritis (OA) is an inflammatory disease of synovial joints involving the loss and degeneration of articular cartilage. The gold standard for evaluating cartilage loss in OA is the measurement of joint space width on standard radiographs. However, in most cases the diagnosis is made well after the onset of the disease, when the symptoms are well established. Identification of early biomarkers of OA can facilitate earlier diagnosis, improve disease monitoring and predict responses to therapeutic interventions. Methods: This study describes the bioinformatic analysis of data generated from high throughput proteomics for identification of potential biomarkers of OA. The mass spectrometry data was generated using a canine explant model of articular cartilage treated with the pro-inflammatory cytokine interleukin 1 β (IL-1β). The bioinformatics analysis involved the application of machine learning and network analysis to the proteomic mass spectrometry data. A rule based machine learning technique, BioHEL, was used to create a model that classified the samples into their relevant treatment groups by identifying those proteins that separated samples into their respective groups. The proteins identified were considered to be potential biomarkers. Protein networks were also generated; from these networks, proteins pivotal to the classification were identified. Results: BioHEL correctly classified eighteen out of twenty-three samples, giving a classification accuracy of 78.3% for the dataset. The dataset included the four classes of control, IL-1β, carprofen, and IL-1β and carprofen together. This exceeded the other machine learners that were used for a comparison, on the same dataset, with the exception of another rule-based method, JRip, which performed equally well. The proteins that were most frequently used in rules generated by BioHEL were found to include a number of relevant proteins including matrix metalloproteinase 3, interleukin 8 and matrix gla protein. Conclusions: Using this protocol, combining an in vitro model of OA with bioinformatics analysis, a number of relevant extracellular matrix proteins were identified, thereby supporting the application of these bioinformatics tools for analysis of proteomic data from in vitro models of cartilage degradation

The Zea mays mutants opaque-2 and opaque-7 disclose extensive changes in endosperm metabolism as revealed by protein, amino acid, and transcriptome-wide analyses

<p>Abstract</p> <p>Background</p> <p>The changes in storage reserve accumulation during maize (<it>Zea mays </it>L.) grain maturation are well established. However, the key molecular determinants controlling carbon flux to the grain and the partitioning of carbon to starch and protein are more elusive. The <it>Opaque-2 </it>(<it>O2</it>) gene, one of the best-characterized plant transcription factors, is a good example of the integration of carbohydrate, amino acid and storage protein metabolisms in maize endosperm development. Evidence also indicates that the <it>Opaque-7 </it>(<it>O7</it>) gene plays a role in affecting endosperm metabolism. The focus of this study was to assess the changes induced by the <it>o2 </it>and <it>o7 </it>mutations on maize endosperm metabolism by evaluating protein and amino acid composition and by transcriptome profiling, in order to investigate the functional interplay between these two genes in single and double mutants.</p> <p>Results</p> <p>We show that the overall amino acid composition of the mutants analyzed appeared similar. Each mutant had a high Lys and reduced Glx and Leu content with respect to wild type. Gene expression profiling, based on a unigene set composed of 7,250 ESTs, allowed us to identify a series of mutant-related down (17.1%) and up-regulated (3.2%) transcripts. Several differentially expressed ESTs homologous to genes encoding enzymes involved in amino acid synthesis, carbon metabolism (TCA cycle and glycolysis), in storage protein and starch metabolism, in gene transcription and translation processes, in signal transduction, and in protein, fatty acid, and lipid synthesis were identified. Our analyses demonstrate that the mutants investigated are pleiotropic and play a critical role in several endosperm-related metabolic processes. Pleiotropic effects were less evident in the <it>o7 </it>mutant, but severe in the <it>o2 </it>and <it>o2o7 </it>backgrounds, with large changes in gene expression patterns, affecting a broad range of kernel-expressed genes.</p> <p>Conclusion</p> <p>Although, by necessity, this paper is descriptive and more work is required to define gene functions and dissect the complex regulation of gene expression, the genes isolated and characterized to date give us an intriguing insight into the mechanisms underlying endosperm metabolism.</p

Deciphering the universe of RNA structures and trans RNA-RNA interactions of transcriptomes in vivo: from experimental protocols to computational analyses

The last few years have seen an explosion of experimental and computational methods for investigating RNA structures of entire transcriptomes in vivo. Very recent experimental protocols now also allow trans RNA–RNA interactions to be probed in a transcriptome-wide manner. All of the experimental strategies require comprehensive computational pipelines for analysing the raw data and converting it back into actual RNA structure features or trans RNA–RNA interactions. The overall performance of these methods thus strongly depends on the experimental and the computational protocols employed. In order to get the best out of both worlds, both aspects need to be optimised simultaneously. This review introduced the methods and proposes ideas how they could be further improved

Guidelines for management of ischaemic stroke and transient ischaemic attack 2008

This article represents the update of the European Stroke Initiative Recommendations for Stroke Management. These guidelines cover both ischaemic stroke and transient ischaemic attacks, which are now considered to be a single entity. The article covers referral and emergency management, Stroke Unit service, diagnostics, primary and secondary prevention, general stroke treatment, specific treatment including acute management, management of complications, and rehabilitation

Isoelectric focusing in immobilized pH gradients: an update.

The latest trends on isoelectric focusing (IEF) in immobilized pH gradients (IPG) are here reviewed. The major advances on IPG technologies have been made when interfacing this technique with sodium dodecyl sulfate-polyacrylamide gel electrophoresis to produce two-dimensional (2-D) maps. Previous 2-D maps were routinely performed using conventional IEF as a first dimension, which typically resulted in poor reproducibility of spot position. With IPGs, correlation between experimental and calculated protein pI values is as good as +0.01 to 0.02 pH units. A new software has also been released, permitting easy calculation and optimization of linear, concave and convex exponential gradients, even in very complex recipes utilizing all ten Immobiline chemicals. It has also been proven that IPGs can be interfaced with mass spectrometry, thus obtaining a novel 2-D map with the best of pI measurements in the first dimension coupled with the best of mass determination in the second dimension. Recently, it has been shown that IPGs can be exploited to charter forbidden grounds, with the creation of non-linear pH gradients covering the extreme alkaline pH 10-12 gradient. In such basic regions, excellent steady-state patterns of histones and subtilisin mutants have been reported. Different families of histones could be mapped not only in this pH 10-12 interval, but also in 2-D maps exploiting this very alkaline gradient in the first dimension. Although the IPG technique is now a trouble-free, user-friendly technique, some annoying artefacts, producing severe protein smears and precipitation, were very recently reported, but found to be linked to some commercial Immobiline preparations containing up to 5% oligomers. Better quality control on the part of the company producing such chemicals should eliminate even this last source of troubles