The predictive capability of the retention time prediction model based on quantitative structure-retention relationships (QSRR) was tested. QSRR model was derived with the use of set of peptides identified with the highest scores and originated from 8 known proteins annotated as model ones. The predictive ability of the QSRR model was verified with the use of a <i>Bacillus subtilis</i> proteome digest after separation and identification of the peptides by LC-ESI-MS/MS. That ability was tested with three sets of testing peptides assigned to the proteins identified with different levels of confidence. First, the set of peptides identified with the highest scores achieved in the search were considered. Hence, proteins identified on the basis of more than one peptide were taken into account. Furthermore, proteins identified on the basis of just one peptide were also considered and, depending on the possessed scores, both above and below the assumed threshold, were analyzed in two separated sets. The QSRR approach was applied as the additional constraint in proteomic research verifying results of MS/MS ion search and confirming the correctness of the peptides identifications along with the indication of the potential false positives.

Katarzyna Macur

Tomasz B&#x105;czek

Roman Kaliszan

Caterina Temporini

Federica Corana

Gabriella Massolini

Jolanta Grzenkowicz-Wydra

Micha&#x142; Obuchowski

Correctness of Protein Identifications of <i>Bacillus subtilis</i> Proteome with the Indication on Potential False Positive Peptides Supported by Predictions of Their Retention Times

Protein profiling using SELDI-TOF-MS has gained over the past few years an increasing interest in the field of biomarker discovery. The technology presents great potential if some parameters, such as sample handling, SELDI settings, and data analysis, are strictly controlled. Practical considerations to set up a robust and sensitive strategy for biomarker discovery are presented. This paper also reviews biological fluids generally available including a description of their peculiar properties and the preanalytical challenges inherent to sample collection and storage. Finally, some new insights for biomarker identification and validation challenges are provided.

Muriel De Bock

Dominique de Seny

Marie-Alice Meuwis

Jean-Paul Chapelle

Edouard Louis

Michel Malaise

Marie-Paule Merville

Marianne Fillet

Challenges for Biomarker Discovery in Body Fluids Using SELDI-TOF-MS

Contrarily to the general believe, many biologically active proteins lack stable tertiary and/or secondary structure under physiological conditions in vitro. These intrinsically disordered proteins (IDPs) are highly abundant in nature and many of them are associated with various human diseases. The functional repertoire of IDPs complements the functions of ordered proteins. Since IDPs constitute a significant portion of any given proteome, they can be combined in an unfoldome; which is a portion of the proteome including all IDPs (also known as natively unfolded proteins, therefore, unfoldome), and describing their functions, structures, interactions, evolution, and so forth. Amino acid sequence and compositions of IDPs are very different from those of ordered proteins, making possible reliable identification of IDPs at the proteome level by various computational means. Furthermore, IDPs possess a number of unique structural properties and are characterized by a peculiar conformational behavior, including their high stability against low pH and high temperature and their structural indifference toward the unfolding by strong denaturants. These peculiarities were shown to be useful for elaboration of the experimental techniques for the large-scale identification of IDPs in various organisms. Some of the computational and experimental tools for the unfoldome discovery are discussed in this review.

Vladimir N. Uversky

The Mysterious Unfoldome: Structureless, Underappreciated, Yet Vital Part of Any Given Proteome

In order to study the differential protein expression in complex biological samples, strategies for rapid, highly reproducible and accurate quantification are necessary. Isotope labeling and fluorescent labeling techniques have been widely used in quantitative proteomics research. However, researchers are increasingly turning to label-free shotgun proteomics techniques for faster, cleaner, and simpler results. Mass spectrometry-based label-free quantitative proteomics falls into two general categories. In the first are the measurements of changes in chromatographic ion intensity such as peptide peak areas or peak heights. The second is based on the spectral counting of identified proteins. In this paper, we will discuss the technologies of these label-free quantitative methods, statistics, available computational software, and their applications in complex proteomics studies.

Wenhong Zhu

Jeffrey W. Smith

Chun-Ming Huang

Mass Spectrometry-Based Label-Free Quantitative Proteomics

Currently no specific biomarkers exist for the screening of pregnancies at risk for down syndrome (DS). Since a quantitative proteomic approach with isobaric labelling (iTRAQ) has recently been suggested to be highly suitable for the discovery of novel plasma biomarkers, we have now used this method to examine for potential quantitative changes in the plasma proteome of the pregnancies bearing DS fetuses in comparison to normal healthy babies. In our study, we used plasma from six women with DS pregnancies and six with uncomplicated pregnancies care were taken to match cases and controls for gestational and maternal age, as
these could be a confounder. In our quantitative proteomics analysis we were able to detect 178 proteins using iTRAQ
labelling in conjunction with 4800 MALDI TOF/TOF. Amongst these we observed changes in <svg style="vertical-align:-2.29482pt;width:8.8500004px;" id="M1" height="13.425" version="1.1" viewBox="0 0 8.8500004 13.425" width="8.8500004"  xmlns="http://www.w3.org/2000/svg">
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		</g>
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</svg>HCG, a known screening marker for DS, indicating that our assay was functional. We found a number of elevated proteins Ig lambda chain C region, serum amyloid P-component, amyloid beta A4, and under expressed proteins like gamma-actin and titin in DS pregnancies. These proteins are also found in the sera of patients with Alzheimer disease, which share similar pathologies of DS. Our study therefore indicates that the iTRAQ labelling approach may be indeed useful for the detection of novel biomarkers.

Varaprasad Kolla

Paul Jenö

Suzette Moes

Sevgi Tercanli

Olav Lapaire

Mahesh Choolani

Sinuhe Hahn

Quantitative Proteomics Analysis of Maternal Plasma in Down Syndrome Pregnancies Using Isobaric Tagging Reagent (iTRAQ)

Human blood plasma contains a plethora of proteins, encompassing not only proteins that have plasma-based functionalities, but also possibly every other form of low concentrated human proteins. As it circulates through the tissues, the plasma picks up proteins that are released from their origin due to physiological events such as tissue remodeling and cell death. Specific disease processes or tumors are often characterized by plasma &#x201C;signatures,&#x201D; which may become obvious via changes in the plasma proteome profile, for example, through over expression of proteins. However, the wide dynamic range of proteins present in plasma makes their analysis very challenging, because high-abundance proteins tend to mask those of lower abundance. In the present study, we used a strategy combining iTRAQ as a reagent which improved the peptide ionization and peptide OFFGEL fractionation that has already been shown, in our previous research, to improve the proteome coverage of cellular extracts.  Two prefractioning methods were compared: immunodepletion and a bead-based library of combinatorial hexapeptide technology. Our data suggested that both methods were complementary, with regard to the number of identified proteins. iTRAQ labelling, in association with OFFGEL fractionation, allowed more than 300 different proteins to be characterized from 400&#x2009;<svg     style="vertical-align:-3.56265pt;width:9.5625px;" id="M1" height="12.175" version="1.1" viewBox="0 0 9.5625 12.175" width="9.5625"  xmlns:xlink="http://www.w3.org/1999/xlink" xmlns="http://www.w3.org/2000/svg">
	
		
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</svg>g of plasma proteins.

Emilie Ernoult

Anthony Bourreau

Erick Gamelin

Catherine Guette

A Proteomic Approach for Plasma Biomarker Discovery with iTRAQ Labelling and OFFGEL  Fractionation

The human placenta is a difficult tissue to work with using proteomic technology since it contains large amounts of lipids and glycogen. Both lipids and glycogen are known to interfere with the first step in the two-dimensional polyacrylamide gel electrophoresis (2D-PAGE), the isoelectric focusing. In order to gain the best possible protein separation on 2D-PAGE, an optimized sample preparation protocol for placental proteins was developed. Two different buffers, urea/CHAPS and Hepes, were used for solubilization in combination with six different precipitation methods. The removal of glycogen from the samples by centrifugation was crucial for the final proteome maps. Solubilization with urea/CHAPS in combination with dichloromethane/methanol or acidified acetone proved to be the best precipitation procedures. When applied to clinical placenta samples apolipoprotein A1 was found to be accumulated in the preeclamptic placenta, where it may either have a nutritional effect or act as a modifier of signal transduction.

Magnus Centlow

Stefan R. Hansson

Charlotte Welinder

Differential Proteome Analysis of the Preeclamptic Placenta Using Optimized Protein Extraction

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BioMed Research International

Proteomics

Proteomics

Articles

Correctness of Protein Identifications of Bacillus subtilis Proteome with the Indication on Potential False Positive Peptides Supported by Predictions of Their Retention Times

Challenges for Biomarker Discovery in Body Fluids Using SELDI-TOF-MS

The Mysterious Unfoldome: Structureless, Underappreciated, Yet Vital Part of Any Given Proteome

Mass Spectrometry-Based Label-Free Quantitative Proteomics

Quantitative Proteomics Analysis of Maternal Plasma in Down Syndrome Pregnancies Using Isobaric Tagging Reagent (iTRAQ)

A Proteomic Approach for Plasma Biomarker Discovery with iTRAQ Labelling and OFFGEL Fractionation

Differential Proteome Analysis of the Preeclamptic Placenta Using Optimized Protein Extraction