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

Toward biomarkers in multiple sclerosis: new advances

Multiple sclerosis is an autoimmune disease that commonly affects young adults. If initially characterized by acute relapses, it is later followed by only incomplete remission. Over years, progressive disability and irreversible deficit lead to chronic neurological deficits in the majority of patients. The clinical course is protracted and unpredictable, and no biological marker is useful in predicting the evolution of autoaggression and disability. It is difficult to diagnose and to monitor disease progression after the initial symptoms or even during the major clinical manifestations, and it is difficult to treat. In this review, the authors report recent advances in the field, focusing on the search of new antigens as a marker of the disease, in their relevance to the pathophysiology and diagnosis of the disease.

Intestinal aspartate proteases TiCatD and TiCatD2 of the haematophagous bug Triatoma infestans (Reduviidae): sequence characterisation, expression pattern and characterisation of proteolytic activity

Two aspartate protease encoding complementary deoxyribonucleic acids (cDNA) were characterised from the small intestine (posterior midgut) of Triatoma infestans and the corresponding genes were named TiCatD and TiCatD2. The deduced 390 and 393 amino acid sequences of both enzymes contain two regions characteristic for cathepsin D proteases and the conserved catalytic aspartate residues forming the catalytic dyad, but only TiCatD2 possesses an entire C-terminal proline loop. The amino acid sequences of TiCatD and TiCatD2 show 51-58% similarity to other insect cathepsin D-like proteases and, respectively, 88 and 58% similarity to the aspartate protease ASP25 from T. infestans available in the GenBank database. In phylogenetic analysis, TiCatD and ASP25 clearly separate from cathepsin D-like sequences of other insects, TiCatD2 groups with cathepsin D-like proteases with proline loop. The activity of purified TiCatD and TiCatD2 was highest between pH 2 and 4, respectively, and hence, deviate from the pH values of the lumen of the small intestine, which varied in correlation with the time after feeding between pH 5.2 and 6.7 as determined by means of micro pH electrodes. Both cathepsins, TiCatD and TiCatD2, were purified from the lumen of the small intestine using pepstatin affinity chromatography and identified by nanoLC-ESI-MS/MS analysis as those encoded by the cDNAs. The proteolytic activity of the purified enzymes is highest at pH 3 and the respective genes are expressed in the both regions of the midgut, stomach (anterior midgut) and small intestine, not in the rectum, salivary glands, Malpighian tubules or haemocytes. The temporal expression pattern of both genes in the small intestine after feeding revealed a feeding dependent regulation for TiCatD but not for TiCatD2.

Proteomics data collection (ProDaC): publishing and collecting proteomics data sets in public repositories using standard formats

In Proteomics, fast enhancements with regard to technology are responsible for the creation of huge data sets. Consequently, in 2006 the European Commission funded a Coordination Action named ProDaC (Proteomics Data Collection) within the 6th EU Framework Programme to foster a community-wide data collection and data sharing. The aims of ProDaC were the development of documentation and storage standards, setup of a standardized data submission pipeline and collection of data.To reach these goals, the necessary work was structured in six thematic fields (work packages): Standards for Proteomics Data Representation, Standards Implementation, Data Integration Tools, Proteomics Repository Adaptation, Data Flow Management, and Proteomics Data Exploitation. The methods building the basis of the respective fields and the achieved results are described in the following sections.

Immunogenic salivary proteins of Triatoma infestans: development of a recombinant antigen for the detection of low-level infestation of triatomines

BACKGROUND

Triatomines are vectors of Trypanosoma cruzi, the etiological agent of Chagas disease in Latin America. The most effective vector, Triatoma infestans, has been controlled successfully in much of Latin America using insecticide spraying. Though rarely undertaken, surveillance programs are necessary in order to identify new infestations and estimate the intensity of triatomine bug infestations in domestic and peridomestic habitats. Since hosts exposed to triatomines develop immune responses to salivary antigens, these responses can be evaluated for their usefulness as epidemiological markers to detect infestations of T. infestans.

METHODOLOGY/PRINCIPAL FINDINGS

T. infestans salivary proteins were separated by 2D-gel electrophoresis and tested for their immunogenicity by Western blotting using sera from chickens and guinea pigs experimentally exposed to T. infestans. From five highly immunogenic protein spots, eight salivary proteins were identified by nano liquid chromatography-electrospray ionization-tandem mass spectrometry (nanoLC-ESI-MS/MS) and comparison to the protein sequences of the National Center for Biotechnology Information (NCBI) database and expressed sequence tags of a unidirectionally cloned salivary gland cDNA library from T. infestans combined with the NCBI yeast protein sub-database. The 14.6 kDa salivary protein [gi|149689094] was produced as recombinant protein (rTiSP14.6) in a mammalian cell expression system and recognized by all animal sera. The specificity of rTiSP14.6 was confirmed by the lack of reactivity to anti-mosquito and anti-sand fly saliva antibodies. However, rTiSP14.6 was recognized by sera from chickens exposed to four other triatomine species, Triatoma brasiliensis, T. sordida, Rhodnius prolixus, and Panstrongylus megistus and by sera of chickens from an endemic area of T. infestans and Chagas disease in Bolivia.

CONCLUSIONS/SIGNIFICANCE

The recombinant rTiSP14.6 is a suitable and promising epidemiological marker for detecting the presence of small numbers of different species of triatomines and could be developed for use as a new tool in surveillance programs, especially to corroborate vector elimination in Chagas disease vector control campaigns.

Off-target decoding of a multitarget kinase inhibitor by chemical proteomics

Unbiased: Chemical proteomics was used to profile compound interactions in an unbiased fashion. We present here the application of different compound-immobilization routes for decoding nonprotein kinase off-targets of the multitarget kinase inhibitor C1, which interacts with distinct compound moieties. Since the approval of the first selective tyrosine kinase inhibitor, imatinib, various drugs have been developed to target protein kinases. However, due to a high degree of structural conservation of the ATP binding site, off-target effects have been reported for several drugs. Here, we report on off-target decoding for a multitarget protein kinase inhibitor by chemical proteomics, by focusing on interactions with nonprotein kinases. We tested two different routes for the immobilization of the inhibitor on a carrier matrix, and thus identified off-targets that interact with distinct compound moieties. Besides several of the kinases known to bind to the compound, the pyridoxal kinase (PDXK), which has been described to interact with the CDK inhibitor (R)-roscovitine, was captured. The PDXK-inhibitor interaction was shown to occur at the substrate binding site rather than at the ATP binding site. In addition, carbonic anhydrase 2 (CA2) binding was demonstrated, and the determination of the IC(50) revealed an enzyme inhibition in the submicromolar range. The data demonstrate that different compound immobilization routes for chemical proteomics approaches are a valuable method to improve the knowledge about the off-target profile of a compound.

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.

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.

2-D differential membrane proteome analysis of scarce protein samples

Proteome studies with small sample amounts are difficult to perform, especially when membrane proteins are the focus of interest. In our study a new method for the analysis of scarce membrane protein samples combining large gel 2-D-CTAB/SDS-PAGE with fluorescence dye saturation labelling (satDIGE) was developed, allowing a highly sensitive differential analysis of different cell states. After Triton X-114 phase partitioning, enriched membrane protein samples of T cells were labelled at cysteine residues using fluorescence dyes and separated by large gel 2D-CTAB/SDS-PAGE. For a differential analysis 3 mug protein was found to be sufficient to detect proteins in a widespread well-separated diagonal spot pattern.

The HUPO Brain Proteome Project – No need to hurry?

The HUPO Brain Proteome Project (HUPO BPP) is dedicated to the analysis of the brain proteome and has initiated two pilot studies in order to elaborate a standardised system for data collection and reprocessing. Samples of mouse brains (different developmental stages) and human brain tissue (biopsy and post-mortem samples) were shipped to different laboratories in Europe, Asia and the US that were invited to identify as many proteins as possible using their own approaches. In addition, a centralised data reprocessing strategy has been elaborated in an iterative way to generate highly reliable lists of identified proteins. This consortium could be a good example for a standardized proteomics workflow.

Bridging Proteomics and Medical Science – the 5th HUPO Brain Proteome Workshop in Dublin, Ireland

More than 70 interested colleagues attended the 5th Workshop of the HUPO Brain Proteome Project (HUPO BPP) at the UCD Conway Institute, Dublin, Ireland. An overview of the outcome of the pilot study was presented and the new subprojects "Clinical Neuroproteomics of Human Body Fluids" as well as "Cerebellum 2D-mapping" were announced. In addition the election of the HUPO BPP committees and the future directions of this project were discussed and decided. The meeting was enhanced by several talks highlighting the application of proteomics in biomedical research.

Proteomics-driven progress in neurodegeneration research

Proteomics technologies have been widely used in the investigation of neurodegenerative and psychiatric disorders, and in particular in the detection of differences between healthy individuals and patients suffering from such diseases. Thus, brain and cerebrospinal fluid (CSF) samples from patients with Alzheimer's disease, Down syndrome, Pick's disease, Parkinson's disease, schizophrenia, and other disorders as well as brain and CSF from animals serving as models of neurological disorders have been analyzed by proteomics. 2-DE followed by MALDI-TOF-MS has been mainly applied as this proteomics approach provides the possibility of convenient quantification of protein levels and detection of post-translational modifications. About 330 unique proteins with deranged levels and modifications have been detected by proteomics approaches to be related to neurodegeneration and psychiatric disorders. They are mainly involved in metabolism pathways, cytoskeleton formation, signal transduction, guidance, detoxification, transport, and conformational changes. In this article, we provide a summary of the major contributions of proteomics technologies in the study of neurodegenerative and psychiatric diseases, in particular, in the detection of changes in protein levels and modifications related to these disorders.

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.

Genomics, proteomics, metabolomics: what is in a word for multiple sclerosis?

PURPOSE OF REVIEW

Multiple sclerosis (MS) is the most common chronic inflammatory neurological disease. Despite major advances the aetiology of this disease it is still not completely understood. In the post-genome era, advances in global screening technologies offer an opportunity to accelerate the search of new pathological pathways and to identify new therapeutic targets. Some recent publications using novel global screening methods at the genome, transcriptome, proteome and metabolome levels are discussed.

RECENT FINDINGS

The genetic association of susceptibility to MS with loci outside the MHC has been reconfirmed. Evidence of parent-of-origin and seasonal effects on disease susceptibility add further complexity to the genetics of MS. The search for MS susceptibility genes continues using the candidate-gene approach as well as large-scale single-nucleotide-polymorphism association studies and novel cross-species synteny analysis. Genome-wide expression profiling using microarrays produced numerous therapeutic targets and is progressing towards profiling of rare cells. Advances in classical proteomics methods paved the way to new initiatives aiming at determining the proteome of the nervous system in normal and diseased states. Although progress is still slow, array-based methods are making an impact on the MS field.

SUMMARY

The complexity of MS is clearly reflected in the latest findings using global profiling methods. Nevertheless, these new technologies are confirming some of the basic aspects of the disease pathophysiology, i.e. its polygenicity, the central role of neuroinflammation and the emerging neurodegenerative processes. These data are primarily the results of genomic approaches, yet promising attempts are also made using proteomics and metabolomics.

Proteomics strategies for protein identification

The information from genome sequencing provides new approaches for systems-wide understanding of protein networks and cellular function. DNA microarray technologies have advanced to the point where nearly complete monitoring of gene expression is feasible in several organisms. An equally important goal is to comprehensive survey cellular proteomes and profile protein changes under different cellular states. This presents a complex analytical problem, due to the chemical variability between proteins and peptides. Here, we discuss strategies to improve accuracy and sensitivity of peptide identification, distinguish represented protein isoforms, and quantify relative changes in protein abundance.

A Bioinformatics Perspective on Proteomics: Data Storage, Analysis, and Integration

The field of proteomics is advancing rapidly as a result of powerful new technologies and proteomics experiments yield a vast and increasing amount of information. Data regarding protein occurrence, abundance, identity, sequence, structure, properties, and interactions need to be stored. Currently, a common standard has not yet been established and open access to results is needed for further development of robust analysis algorithms. Databases for proteomics will evolve from pure storage into knowledge resources, providing a repository for information (meta-data) which is mainly not stored in simple flat files. This review will shed light on recent steps towards the generation of a common standard in proteomics data storage and integration, but is not meant to be a comprehensive overview of all available databases and tools in the proteomics community.