Toward protein biomarkers for allergy: CD4+ T cell proteomics in allergic and nonallergic subjects sampled in and out of pollen season.

Allergy is an immunological disorder of the upper airways, lung, skin, and the gut with a growing prevalence over the last decades in Western countries. Atopy, the genetic predisposition for allergy, is strongly dependent on familial inheritance and environmental factors. These observations call for predictive markers of progression from atopy to allergy, a prerequisite to any active intervention in neonates and children (prophylactic interventions/primary prevention) or in adults (immunomodulatory interventions/secondary prevention). In an attempt to identify early biomarkers of the "atopic march" using minimally invasive sampling, CD4+ T cells from 20 adult volunteers (10 healthy and 10 with respiratory allergies) were isolated and quantitatively analyzed and their proteomes were compared in and out of pollen season (± antigen exposure). The proteome study based on high-resolution 2D gel electrophoresis revealed three candidate protein markers that distinguish the CD4+ T cell proteomes of normal from allergic individuals when sampled out of pollen season, namely Talin 1, Nipsnap homologue 3A, and Glutamate-cysteine ligase regulatory protein. Three proteins were found differentially expressed between the CD4+ T cell proteomes of normal and allergic subjects when sampled during pollen season: carbonyl reductase, glutathione S-transferase ω 1, and 2,4-dienoyl-CoA reductase. The results were partly validated by Western blotting.

In-depth protein characterization by mass spectrometry.

Within this chapter, various techniques and instructions for characterizing primary structure of proteins are presented, whereas the focus lies on obtaining as much complete sequence information of single proteins as possible. Especially, in the area of protein production, mass spectrometry-based detailed protein characterization plays an increasing important role for quality control. In comparison to typical proteomics applications, wherein it is mostly sufficient to identify proteins by few peptides, several complementary techniques have to be applied to maximize primary structure information and analysis steps have to be specifically adopted. Starting from sample preparation down to mass spectrometry analysis and finally to data analysis, some of the techniques typically applied are outlined here in a summarizing and introductory manner.

Getting a grip on proteomics data - Proteomics Data Collection (ProDaC).

In proteomics, rapid developments in instrumentation led to the acquisition of increasingly large data sets. Correspondingly, ProDaC was founded in 2006 as a Coordination Action project within the 6th European Union Framework Programme to support data sharing and community-wide data collection. The objectives of ProDaC were the development of documentation and storage standards, setup of a standardized data submission pipeline and collection of data. Ending in March 2009, ProDaC has delivered a comprehensive toolbox of standards and computer programs to achieve these goals.

An easy-to-use Decoy Database Builder software tool, implementing different decoy strategies for false discovery rate calculation in automated MS/MS protein identifications.

One of the major challenges for large scale proteomics research is the quality evaluation of results. Protein identification from complex biological samples or experimental setups is often a manual and subjective task which lacks profound statistical evaluation. This is not feasible for high-throughput proteomic experiments which result in large datasets of thousands of peptides and proteins and their corresponding mass spectra. To improve the quality, reliability and comparability of scientific results, an estimation of the rate of erroneously identified proteins is advisable. Moreover, scientific journals increasingly stipulate that articles containing considerable MS data should be subject to stringent statistical evaluation. We present a newly developed easy-to-use software tool enabling quality evaluation by generating composite target-decoy databases usable with all relevant protein search engines. This tool, when used in conjunction with relevant statistical quality criteria, enables to reliably determine peptides and proteins of high quality, even for nonexperienced users (e.g. laboratory staff, researchers without programming knowledge). Different strategies for building decoy databases are implemented and the resulting databases are characterized and compared. The quality of protein identification in high-throughput proteomics is usually measured by the false positive rate (FPR), but it is shown that the false discovery rate (FDR) delivers a more meaningful, robust and comparable value.

Multidimensional chromatography: a powerful tool for the analysis of membrane proteins in mouse brain.

Understanding the function of membrane proteins is of fundamental importance due to their crucial roles in many cellular processes and their direct association with human disorders. However, their analysis poses a special challenge, largely due to their highly amphipathic nature. Until recently, analyses of proteomic samples mainly were performed by two-dimensional polyacrylamide gel electrophoresis (2D-PAGE), due to the unprecedented separation power of the technique. However, in conventional 2D-PAGE membrane proteins are generally underrepresented due to their tendency to precipitate during isoelectric focusing and their inefficient transfer from the first to the second dimension. As a consequence, several other separation techniques, primarily based on liquid chromatography (LC), have been employed for analysis of this group of proteins. In the present study, different LC-based methods were compared for the analysis of crude protein extracts. One- and two-dimensional high-performance liquid chromatographic (1D- and 2D-HPLC) separations of brain protein tryptic digests with a predicted concentration range of up to 5 orders of magnitude were found to be insufficient, thus making a preceding fractionation step necessary. An additional protein separation step was introduced and a 3D-PAGE-HPLC analysis was performed. The results of these experiments are compared with results of 2D-PAGE/matrix-assisted laser desorption ionization mass spectrometric (MALDI MS) analyses of the same samples. Features, challenges, advantages, and disadvantages of the respective systems are discussed. The brain (mouse and human) was chosen as the analyzed tissue as it is of high interest in medical and pharmaceutical research into neurological diseases such as multiple sclerosis, stroke, Alzheimer's disease, and Parkinson's disease. The study is part of our ongoing research aimed at identifying new biomarkers for neurodegenerative diseases.

Gaining knowledge from previously unexplained spectra-application of the PTM-Explorer software to detect PTM in HUPO BPP MS/MS data.

A novel software tool named PTM-Explorer has been applied to LC-MS/MS datasets acquired within the Human Proteome Organisation (HUPO) Brain Proteome Project (BPP). PTM-Explorer enables automatic identification of peptide MS/MS spectra that were not explained in typical sequence database searches. The main focus was detection of PTMs, but PTM-Explorer detects also unspecific peptide cleavage, mass measurement errors, experimental modifications, amino acid substitutions, transpeptidation products and unknown mass shifts. To avoid a combinatorial problem the search is restricted to a set of selected protein sequences, which stem from previous protein identifications using a common sequence database search. Prior to application to the HUPO BPP data, PTM-Explorer was evaluated on excellently manually characterized and evaluated LC-MS/MS data sets from Alpha-A-Crystallin gel spots obtained from mouse eye lens. Besides various PTMs including phosphorylation, a wealth of experimental modifications and unspecific cleavage products were successfully detected, completing the primary structure information of the measured proteins. Our results indicate that a large amount of MS/MS spectra that currently remain unidentified in standard database searches contain valuable information that can only be elucidated using suitable software tools.

Functional annotation of proteins identified in human brain during the HUPO Brain Proteome Project pilot study.

The HUPO Brain Proteome Project is an initiative coordinating proteomics studies to characterise human and mouse brain proteomes. Proteins identified in human brain samples during the project's pilot phase were put into biological context through integration with various annotation sources followed by a bioinformatics analysis. The data set was related to the genome sequence via the genes encoding identified proteins including an assessment of splice variant identification as well as an analysis of tissue specificity of the respective transcripts. Proteins were furthermore categorised according to subcellular localisation, molecular function and biological process, grouped into protein families and mapped to biological pathways they are known to act in. Involvement in pathological conditions was examined based on association with entries in the online version of Mendelian Inheritance in Man and an interaction network was derived from curated protein-proteininteraction data. Overall a non-redundant set of 1804 proteins was identified in human brain samples. In the majority of cases splice variants could be unambiguously identified by unique peptides, including matches to several hypothetical transcripts of known as well as predicted genes.

A comparison of the HUPO Brain Proteome Project pilot with other proteomics studies.

The pilot phase of the Brain Proteome Project (BPP), the Human Proteome Organization (HUPO) initiative that focuses on studies of the brain of both humans and mice, has now been completed. Participating laboratories studied the proteomes of two human samples derived from biopsy and autopsy as well as three mouse samples from various developmental stages. With the combined and centrally reprocessed data now available, a comparison in terms of protein identifications and project organization is made between the HUPO BPP pilot and three other proteomics studies: the HUPO Plasma Proteome Project (PPP) pilot, a proteome of human blood platelets and a recently published comprehensive mouse proteome. Finally, as any comparison between large-scale proteomics datasets is decidedly non-trivial, we also evaluate and discuss several ways to go about comparing such different result sets.

The power of cooperative investigation: summary and comparison of the HUPO Brain Proteome Project pilot study results.

Within the pilot phase of the HUPO Brain Proteome Project, nine participating laboratories analysed human (epilepsy and/or post mortem material) and mouse brain samples (embryonic, juvenile and adult), respectively, using a variety of different state of the art techniques. Thirty-seven different analytical approaches were accomplished. Of these analyses, 17 were done differentially, i.e. the protein expression patterns of the different samples (human or mouse) were compared. A catalogue of all proteins present in the respective sample was built in 20 analyses (mapping). All data were collected in the Data Collection Center in Bochum, Germany, and were reprocessed according to thoroughly defined parameters. In this report, a summary of all results and inter-laboratory comparisons with respect to the number of identified proteins, the analysed organism, and the used techniques is presented.

Automated reprocessing pipeline for searching heterogeneous mass spectrometric data of the HUPO Brain Proteome Project pilot phase.

The newly available techniques for sensitive proteome analysis and the resulting amount of data require a new bioinformatics focus on automatic methods for spectrum reprocessing and peptide/protein validation. Manual validation of results in such studies is not feasible and objective enough for quality relevant interpretation. The necessity for tools enabling an automatic quality control is, therefore, important to produce reliable and comparable data in such big consortia as the Human Proteome Organization Brain Proteome Project. Standards and well-defined processing pipelines are important for these consortia. We show a way for choosing the right database model, through collecting data, processing these with a decoy database and end up with a quality controlled protein list merged from several search engines, including a known false-positive rate.

HUPO Brain Proteome Project: summary of the pilot phase and introduction of a comprehensive data reprocessing strategy.

The Human Proteome Organisation (HUPO) initiated several projects focusing on the proteome analysis of distinct human organs. The Brain Proteome Project (BPP) is the initiative dedicated to the brain, its development and correlated diseases. Two pilot studies have been performed aiming at the comparison of techniques, laboratories and approaches. With the help of the results gained, objective data submission, storage and reprocessing workflow have been established. The biological relevance of the data will be drawn from the inter-laboratory comparisons as well as from the re-calculation of all data sets submitted by the different groups. In the following, results of the single groups as well as the centralised reprocessing effort will be summarised and compared, showing the added value of this concerted work.

The HUPO Brain Proteome Project jamboree: centralised summary of the pilot studies.

The Bioinformatics Committee of the HUPO Brain Proteome Project (HUPO BPP) meets regularly to execute the post-lab analyses of the data produced in the HUPO BPP pilot studies. On January 9-11, 2006 the members as well as invited analysts came together at the European Bioinformatics Institute in Hinxton, UK for the pilot studies jamboree. The results of the reprocessing were presented and tasks forces were initiated to compile, to interpret and to summarise the data obtained.

Proteome analysis of glandular parotid and submandibular-sublingual saliva in comparison to whole human saliva by two-dimensional gel electrophoresis.

The secretions of the salivary parotid and submandibular-sublingual (SMSL) glands constitute the main part of whole human saliva (WS) in which proline-rich proteins (PRPs) and mucins represent dominant groups. Although proteome analysis had been performed on WS, no identification of PRPs or mucins by 2-DE and MS was achieved in WS and no comprehensive analysis of both glandular secretions is available so far. The aim of this study was to compare the protein map of WS to parotid and SMSL secretions for the display of PRPs and mucins. WS and glandular secretions were subjected to 2-DE and spots were analyzed by MALDI-MS. New components identified in WS were cyclophilin-B and prolyl-4-hydroxylase. Also acidic and basic PRPs as well as the proline-rich glycoprotein (PRG) could now be mapped in WS. Acidic PRPs were found equally in parotid and SMSL secretions, whereas basic PRPs and PRG were found primarily in parotid secretion. Salivary mucin MUC7 was identified in SMSL secretion. Thus, the more abundant proteins of WS can be explained mainly by mixed contributions of parotid and SMSL secretions with only few components remaining that may be derived from local sources in the oral cavity.

5th HUPO BPP Bioinformatics Meeting at the European Bioinformatics Institute in Hinxton, UK--Setting the analysis frame.

The Bioinformatics Committee of the HUPO Brain Proteome Project (HUPO BPP) meets regularly to execute the post-lab analyses of the data produced in the HUPO BPP pilot studies. On July 7, 2005 the members came together for the 5th time at the European Bioinformatics Institute (EBI) in Hinxton, UK, hosted by Rolf Apweiler. As a main result, the parameter set of the semi-automated data re-analysis of MS/MS spectra has been elaborated and the subsequent work steps have been defined.

Collection of soluble variants of membrane proteins for transcriptomics and proteomics.

The existence of a soluble splice variant for a gene encoding a transmembrane protein suggests that this gene plays a role in intercellular signalling, particularly in immunological processes. Also, the absence of a splice variant of a reported soluble variant suggests exclusive control of the solubilisation by proteolytic cleavage. Soluble splice variants of membrane proteins may also be interesting targets for crystallisation as their structure may be expected to preserve, at least partially, their function as integral membrane proteins, whose structures are most difficult to determine. This paper presents a dataset derived from the literature in an attempt to collect all reported soluble variants of membrane proteins, be they splice variants or shedded. A list of soluble variants is derived in silico from Ensembl. These are checked on their presence in multiple organisms and their number of membranespanning regions is inspected. The findings then are confirmed by a comparison with identified proteins of a recent global proteomics study of human blood plasma. Finally, a tool to determine novel soluble variants by proteomics is provided.

Tryptic transpeptidation products observed in proteome analysis by liquid chromatography-tandem mass spectrometry.

Commonly, prior to mass spectrometry based analysis of proteins or protein mixtures, the proteins are subjected to specific enzymatic proteolysis. For this purpose trypsin is most frequently used. However, the process of proteolysis is not unflawed. For example, some side activities of trypsin are known and have already been described in the literature (e.g., chymotryptic activity). Here, we describe the occurrence of transpeptidated peptides during standard proteome analysis using two-dimensional polyacrylamide gel electrophoresis followed by mass spectrometric protein identification. Different types of transpeptidated peptides have been detected. The most frequently observed transpeptidation reaction is N-terminal addition of arginine or lysine to peptides. Furthermore, addition of two amino acids to the N-terminus of a peptide has also been detected. Another transpeptidation that we observed, is combination of two peptides, which were originally located in different regions of the analyzed protein. Currently, the full amount of peptides generated by transpeptidation is not clear. However, it should be recognized that protein information is presently lost as these effects are not detectable with available database search software.

Towards data management of the HUPO Human Brain Proteome Project pilot phase.

The pilot phase of the Human Brain Proteome Project as a part of the Human Proteome Organisation has just been started. In two pilot studies, 18 different laboratories are analyzing mouse brains of three age stages and human brain autopsy versus biopsy material, respectively. The overall aim is to elucidate the portfolio of available techniques as well as to elaborate common standards. As a first step, it was decided to use the common bioinformatics platform ProteinScape that was introduced to the participating groups in a two day course in Bochum, Germany.

Evaluation of algorithms for protein identification from sequence databases using mass spectrometry data.

In this work, the commonly used algorithms for mass spectrometry based protein identification, Mascot, MS-Fit, ProFound and SEQUEST, were studied in respect to the selectivity and sensitivity of their searches. The influence of various search parameters were also investigated. Approximately 6600 searches were performed using different search engines with several search parameters to establish a statistical basis. The applied mass spectrometric data set was chosen from a current proteome study. The huge amount of data could only be handled with computational assistance. We present a software solution for fully automated triggering of several peptide mass fingerprinting (PMF) and peptide fragmentation fingerprinting (PFF) algorithms. The development of this high-throughput method made an intensive evaluation based on data acquired in a typical proteome project possible. Previous evaluations of PMF and PFF algorithms were mainly based on simulations.

Ultrasensitive detection of unstained proteins in acrylamide gels by native UV fluorescence.

Visualization of proteins inside acrylamide and other gels usually relies on different staining methods. To omit the protein-staining procedure, we visualized unstained proteins inside acrylamide gels by laser excitation with ultraviolet (UV) light (280 nm, 35 mJ/cm2) and directly detected native UV fluorescence. In one-dimensional gels, a detection limit as low as 1 ng for bovine serum albumin and 5 ng for other proteins with a linear dynamic range (2.7 orders of magnitude) comparable to state of the art fluorescent dyes could be achieved. In addition, the application of this method to 20 microg of a whole cell lysate separated in a two-dimensional gel showed more than 600 spots. Since protein labeling always represents a serious obstacle in protein identification technologies, the working efficiency with our procedure can be considered as a significant improvement for protein visualization and reproducibility in proteomics.