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PubMed2005

Sociomics! Using the IssueCrawler to map, monitor and engage with the global proteomics research network.

We invite comment upon an experiment to locate proteomics on the WWW using a software tool called the IssueCrawler. We call our research "sociomics" because, like the bioscience omics, it is a semi-automated, computerised approach to the global analysis of data, whose computerised results can be integrated towards the development of a new "systems sociology" approach to the study of society. Our findings are that proteomics on the web is a scale-free network whose nodes display considerable "dynamic range".

Cluster Analysis↗
PubMed2005

Plant protein annotation in the UniProt Knowledgebase.

The Swiss-Prot, TrEMBL, Protein Information Resource (PIR), and DNA Data Bank of Japan (DDBJ) protein database activities have united to form the Universal Protein Resource (UniProt) Consortium. UniProt presents three database layers: the UniProt Archive, the UniProt Knowledgebase (UniProtKB), and the UniProt Reference Clusters. The UniProtKB consists of two sections: UniProtKB/Swiss-Prot (fully manually curated entries) and UniProtKB/TrEMBL (automated annotation, classification and extensive cross-references). New releases are published fortnightly. A specific Plant Proteome Annotation Program (http://www.expasy.org/sprot/ppap/) was initiated to cope with the increasing amount of data produced by the complete sequencing of plant genomes. Through UniProt, our aim is to provide the scientific community with a single, centralized, authoritative resource for protein sequences and functional information that will allow the plant community to fully explore and utilize the wealth of information available for both plant and non-plant model organisms.

Amino Acid Sequence↗
PubMed2004

Proteomic analysis of post-mitochondrial fractions of young and old rat kidney.

Proteomic analysis is defined as the characterization of the entire set of proteins encoded by a genome. Two-dimensional (2D) electrophoresis and matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF MS) are key technologies used in proteomic analysis to gain information about protein expression profiles and post-translational modifications. Knowledge about aging processes can be gained by recognizing changes in protein expression. Thus, to better understand the aging process through protein profiling, post-mitochondrial (PM) fractions of young (13-month) and old (31-month) male Fischer 344 rat kidney were differentially analyzed by 2D. We detected a total number of 380 spots on 2D gel images. Among them, 167 spots showed 2-fold significant alterations (p<0.05) between young and old PM fractions. Further, 103 proteins were identified by MALDI-TOF MS. The PM fraction of aged rat kidney showed increases in antioxidative and proteolytic proteins and decreases in cytoskeletal proteins. In addition, we found age-related changes in transport and homeostasis proteins. Thus, our results demonstrated that proteomic analysis can be effectively applied to the assessment of the age status of protein expression, and thereby provide valuable information on age-related changes of proteome.

Aging↗
PubMed2004

Genome Properties: a system for the investigation of prokaryotic genetic content for microbiology, genome annotation and comparative genomics.

MOTIVATION: The presence or absence of metabolic pathways and structures provide a context that makes protein annotation far more reliable. Compiling such information across microbial genomes improves the functional classification of proteins and provides a valuable resource for comparative genomics. RESULTS: We have created a Genome Properties system to present key aspects of prokaryotic biology using standardized computational methods and controlled vocabularies. Properties reflect gene content, phenotype, phylogeny and computational analyses. The results of searches using hidden Markov models allow many properties to be deduced automatically, especially for families of proteins (equivalogs) conserved in function since their last common ancestor. Additional properties are derived from curation, published reports and other forms of evidence. Genome Properties system was applied to 156 complete prokaryotic genomes, and is easily mined to find differences between species, correlations between metabolic features and families of uncharacterized proteins, or relationships among properties. AVAILABILITY: Genome Properties can be found at http://www.tigr.org/Genome_Properties SUPPLEMENTARY INFORMATION: http://www.tigr.org/tigr-scripts/CMR2/genome_properties_references.spl.

Chromosome Mapping↗
PubMed2006

Expanded protein information at SGD: new pages and proteome browser.

The recent explosion in protein data generated from both directed small-scale studies and large-scale proteomics efforts has greatly expanded the quantity of available protein information and has prompted the Saccharomyces Genome Database (SGD; http://www.yeastgenome.org/) to enhance the depth and accessibility of protein annotations. In particular, we have expanded ongoing efforts to improve the integration of experimental information and sequence-based predictions and have redesigned the protein information web pages. A key feature of this redesign is the development of a GBrowse-derived interactive Proteome Browser customized to improve the visualization of sequence-based protein information. This Proteome Browser has enabled SGD to unify the display of hidden Markov model (HMM) domains, protein family HMMs, motifs, transmembrane regions, signal peptides, hydropathy plots and profile hits using several popular prediction algorithms. In addition, a physico-chemical properties page has been introduced to provide easy access to basic protein information. Improvements to the layout of the Protein Information page and integration of the Proteome Browser will facilitate the ongoing expansion of sequence-specific experimental information captured in SGD, including post-translational modifications and other user-defined annotations. Finally, SGD continues to improve upon the availability of genetic and physical interaction data in an ongoing collaboration with BioGRID by providing direct access to more than 82,000 manually-curated interactions.

Computer Graphics↗
PubMed2004

Proteomic analysis of the Arabidopsis nucleolus suggests novel nucleolar functions.

The eukaryotic nucleolus is involved in ribosome biogenesis and a wide range of other RNA metabolism and cellular functions. An important step in the functional analysis of the nucleolus is to determine the complement of proteins of this nuclear compartment. Here, we describe the first proteomic analysis of plant (Arabidopsis thaliana) nucleoli, in which we have identified 217 proteins. This allows a direct comparison of the proteomes of an important nuclear structure between two widely divergent species: human and Arabidopsis. The comparison identified many common proteins, plant-specific proteins, proteins of unknown function found in both proteomes, and proteins that were nucleolar in plants but nonnucleolar in human. Seventy-two proteins were expressed as GFP fusions and 87% showed nucleolar or nucleolar-associated localization. In a striking and unexpected finding, we have identified six components of the postsplicing exon-junction complex (EJC) involved in mRNA export and nonsense-mediated decay (NMD)/mRNA surveillance. This association was confirmed by GFP-fusion protein localization. These results raise the possibility that in plants, nucleoli may have additional functions in mRNA export or surveillance.

Arabidopsis↗
PubMed2002

Proteomic technologies in modern biomedical science.

This review highlights modern technologies employed in proteomics. Methods of sample preparations are discussed with special emphasis on the requirements for preparation of biological material, which may seriously influence the results of proteomic studies. Methods of solubilization, electrophoresis, chromatographic protein separation, and visualization of protein spots in gels are described. Modern methods of mass spectrometry used in proteomic studies include combination of protein chips with mass spectrometry. The review also describes approaches of functional proteomics, i.e., interactomics, and also bioinformatic resources used in proteomics for image analysis of 2D-gel-electrophoresis and for identification of protein sequences by mass spectra.

Biomedical Research↗
PubMedDate not supplied

Proteomics and bioinformatics strategies to design countermeasures against infectious threat agents.

The potential devastation resulting from an intentional outbreak caused by biological warfare agents such as Brucella abortus and Bacillus anthracis underscores the need for next generation vaccines. Proteomics, genomics, and systems biology approaches coupled with the bacterial ghost (BG) vaccine delivery strategy offer an ideal approach for developing safer, cost-effective, and efficacious vaccines for human use in a relatively rapid time frame. Critical to any subunit vaccine development strategy is the identification of a pathogen's proteins with the greatest potential of eliciting a protective immune response. These proteins are collectively referred to as the pathogen's immunome. Proteomics provides high-resolution identification of these immunogenic proteins using standard proteomic technologies, Western blots probed with antisera from infected patients, and the pathogen's sequenced and annotated genome. Selected immunoreactive proteins can be then cloned and expressed in nonpathogenic Gram-negative bacteria. Subsequently, a temperature shift or chemical induction process is initiated to induce expression of the PhiX174 E-lysis gene, whose protein product forms an E tunnel between the inner and outer membrane of the bacteria, expelling all intracellular contents. The BG vaccine system is a proven strategy developed for many different pathogens and tested in a complete array of animal models. The BG vaccine system also has great potential for producing multiagent vaccines for protection to multiple species in a single formulation.

Bacillus anthracis↗
PubMed2003

Genomics, proteomics and bioinformatics of human heart failure.

Unraveling the molecular complexities of human heart failure, particularly end-stage failure, can be achieved by combining multiple investigative approaches. There are several parts to the problem. Each patient is the product of a complex set of genetic variations, different degrees of influence of diets and lifestyles, and usually heart transplantation patients are treated with multiple drugs. The genomic status of the myocardium of any one transplant patient can be analysed using gene arrays (cDNA- or oligonucleotide-based) each with its own strengths and weaknesses. The proteins expressed by these failing hearts (myocardial proteomics) were first investigated over a decade ago using two-dimensional polyacrylamide gel electrophoresis (2DGE) which promised to resolve several thousand proteins in a single sample of failing heart. However, while 2DGE is very successful for the abundant and moderately expressed proteins, it struggles to identify proteins expressed at low levels. Highly focused first dimension separations combined with recent advances in mass spectrometry now provide new hope for solving this difficulty. Protein arrays are a more recent form of proteomics that hold great promise but, like the above methods, they have their own drawbacks. Our approach to solving the problems inherent in the genomics and proteomics of heart failure is to provide experts in each analytical method with a sample from the same human failing heart. This requires a sufficiently large number of samples from a sufficiently large pool of heart transplant patients as well as a large pool of non-diseased, non-failing human hearts. We have collected more than 200 hearts from patients undergoing heart transplantations and a further 50 non-failing hearts. By combining our expertise we expect to reduce and possibly eliminate the inherent difficulties of each analytical approach. Finally, we recognise the need for bioinformatics to make sense of the large quantities of data that will flow from our laboratories. Thus, we plan to provide meaningful molecular descriptions of a number of different conditions that result in terminal heart failure.

Animals↗
PubMed2006

Improving the reliability and throughput of mass spectrometry-based proteomics by spectrum quality filtering.

In contemporary peptide-centric or non-gel proteome studies, vast amounts of peptide fragmentation data are generated of which only a small part leads to peptide or protein identification. This motivates the development and use of a filtering algorithm that removes spectra that contribute little to protein identification. Removal of unidentifiable spectra reduced both the amount of computational and human time spent on analyzing spectra as well as the chances of obtaining false identifications. Thorough testing on various proteome datasets from different instruments showed that the best suggested machine-learning classifier is, on average, able to recognize half of the unidentified spectra as bad spectra. Further analyses showed that several unidentified spectra classified as good were derived from peptides carrying unanticipated amino acid modifications or contained sequence tags that allowed peptide identification using homology searches. The implementation of the classifiers is available under the GNU General Public License at http://www.bioinfo.no/software/spectrumquality.

Adult↗
PubMed2004

Cluster-C, an algorithm for the large-scale clustering of protein sequences based on the extraction of maximal cliques.

Although the characterization of proteins cannot solely rely upon sequence similarity, it has been widely proved that all-vs-all massive sequence comparisons may be an effective approach and a good basis for the prediction of biochemical functions or for the delineation of common shared properties. The program Cluster-C presented here enables a stand-alone and efficient construction of protein families within whole proteomes. The algorithm, which is based on the detection of cliques, ensures a high level of connectivity within the clusters. As opposed to the single transitive linkage method, Cluster-C allows a large number of sequences to be classified in such a way that the multidomain proteins do not produce a chain-grouping effect resulting in meaningless clusters. Moreover, some proteins can be present in several different but relevant clusters, which is of help in the determination of their functional domains. In the present analysis we used the Z-value, an evaluation of the significance of the similarity score, as the criterion for connecting sequences (the user can freely define the threshold of the similarity criterion). The clusters built with a rather low threshold (Z= 14) include more than 97% of the sequences and are consistent with known protein families and PROSITE patterns.

Algorithms↗
PubMed2006

Development of an open source laboratory information management system for 2-D gel electrophoresis-based proteomics workflow.

BACKGROUND: In the post-genome era, most research scientists working in the field of proteomics are confronted with difficulties in management of large volumes of data, which they are required to keep in formats suitable for subsequent data mining. Therefore, a well-developed open source laboratory information management system (LIMS) should be available for their proteomics research studies. RESULTS: We developed an open source LIMS appropriately customized for 2-D gel electrophoresis-based proteomics workflow. The main features of its design are compactness, flexibility and connectivity to public databases. It supports the handling of data imported from mass spectrometry software and 2-D gel image analysis software. The LIMS is equipped with the same input interface for 2-D gel information as a clickable map on public 2DPAGE databases. The LIMS allows researchers to follow their own experimental procedures by reviewing the illustrations of 2-D gel maps and well layouts on the digestion plates and MS sample plates. CONCLUSION: Our new open source LIMS is now available as a basic model for proteome informatics, and is accessible for further improvement. We hope that many research scientists working in the field of proteomics will evaluate our LIMS and suggest ways in which it can be improved.

Computational Biology↗
PubMed2005

Ultra-high sensitivity multi-photon detection imaging in proteomics analyses.

We report on the use of 125I and 131I labeling and of new, multicolor, multi-photon detection (MPD) methods to routinely and quantitatively detect protein spots on two-dimensional gel electrophoresis plates in the zeptomole to attomole range. We demonstrate that the MPD methodology can be used to detect radioactive labels on two-dimensional gels and has several characteristics that are advantageous for functional proteomics. First, by using single particle detectors, the sensitivity for detection of radiolabels can be improved dramatically. Second, because single particle detectors can differentiate the particle energies produced by different decay processes, it is possible to choose combinations of radioisotopes that can be detected and quantified individually on the same 2-D gel. Third, the MPD technology is essentially linear over six to seven orders of magnitude, i.e., it is possible to accurately quantify radiolabeled proteins over a range from at least 60 zeptomoles to 60 femtomoles. Finally for radionuclides that decay by electron capture, e.g., with emission of both beta and gamma rays, co-incident detection of two particles/photons can be used to detect such radionuclides well below background radiation levels. These methods are used to monitor acidic/phosphorylated proteins in as little as 60 ng of HeLa cells proteins.

Color↗
PubMed2003

Proteome analysis at the level of subcellular structures.

The targeting of proteins to particular subcellular sites is an important principle of the functional organization of cells at the molecular level. In turn, knowledge about the subcellular localization of a protein is a characteristic that may provide a hint as to the function of the protein. The combination of classic biochemical fractionation techniques for the enrichment of particular subcellular structures with the large-scale identification of proteins by mass spectrometry and bioinformatics provides a powerful strategy that interfaces cell biology and proteomics, and thus is termed 'subcellular proteomics'. In addition to its exceptional power for the identification of previously unknown gene products, the analysis of proteins at the subcellular level is the basis for monitoring important aspects of dynamic changes in the proteome such as protein transloction. This review summarizes data from recent subcellular proteomics studies with an emphasis on the type of data that can retrieved from such studies depending on the design of the analytical strategy.

Animals↗
PubMedDate not supplied

Recognition and classification of histones using support vector machine.

Histones are DNA-binding proteins found in the chromatin of all eukaryotic cells. They are highly conserved and can be grouped into five major classes: H1/H5, H2A, H2B, H3, and H4. Two copies of H2A, H2B, H3, and H4 bind to about 160 base pairs of DNA forming the core of the nucleosome (the repeating structure of chromatin) and H1/H5 bind to its DNA linker sequence. Overall, histones have a high arginine/lysine content that is optimal for interaction with DNA. This sequence bias can make the classification of histones difficult using standard sequence similarity approaches. Therefore, in this paper, we applied support vector machine (SVM) to recognize and classify histones on the basis of their amino acid and dipeptide composition. On evaluation through a five-fold cross-validation, the SVM-based method was able to distinguish histones from nonhistones (nuclear proteins) with an accuracy around 98%. Similarly, we obtained an overall >95% accuracy in discriminating the five classes of histones through the application of 1-versus-rest (1-v-r) SVM. Finally, we have applied this SVM-based method to the detection of histones from whole proteomes and found a comparable sensitivity to that accomplished by hidden Markov motifs (HMM) profiles.

Amino Acid Sequence↗
PubMed2006

Cytokeratin-20 and seminal vesicle secretory protein VI as possible marker proteins in urinary bladder preneoplastic lesions induced by N-butyl-N-(4-hydroxybutyl) nitrosamine.

BACKGROUND: A simple and non-invasive methods for the diagnosis of transitional cell carcinoma of the bladder are needed for the prevention of invasive tumor. A proteomic technology has recently been developed to facilitate protein profiling of biological mixtures. We tried to detect the marker proteins by proteomic approach during the initiation stages on N-butyl-N-(4-hydroxybutyl) nitrosamine (BBN)-induced bladder carcinogenesis in rats. METHODS: Ten rats in group A were given 0.05% BBN in drinking water for 12 weeks. Other 10 rats in group B with 10 rats were designated as a control group and were not given BBN. Whole urinary bladders of all rats were excised at 12 weeks from the beginning of the experiment. Conventional proteomics was performed with high resolution 2-dimension gel electrophoresis followed by computational image analysis and protein identification using mass spectrometry. RESULTS: A comparison of urinary bladder hyperplasia tissue with control tissue showed that five proteins; actin gamma2 propeptide, cytokeratin-20 (CK-20), proapolipoprotein, alpha2 actin (alpha-cardiac actin) and heat shock 27 kDa protein-1 were over-expressed in hyperplastic tissues. Three proteins; transcription factor myocardin, seminal vesicle secretory protein VI (SVS-VI) precursor and hypothetical protein RMT-7 were under-expressed in hyperplastic tissues. CONCLUSION: In our animal mode, BBN-induced urinary bladder mucosal hyperplasia resulted in an increase in the expression of five proteins and a decrease in the expression of three proteins. Of these, CK-20 and SVS-VI seem to be of particular interest. However other method such as Western blotting seems to be needed for confirmation of these proteins and more information on human bladder tissue is needed for clinical application.

Animals↗
PubMed2025

Emerging protein sequencing technologies: proteomics without mass spectrometry?

INTRODUCTION: Liquid chromatography-tandem mass spectrometry (LC-MS/MS) has been a leading method for proteomics for 30 years. Advantages provided by LC-MS/MS are offset by significant disadvantages, including cost. Recently, several non-mass spectrometric methods have emerged, but little information is available about their capacity to analyze the complex mixtures routine for mass spectrometry. AREAS COVERED: We review recent non-mass-spectrometric methods for sequencing proteins and peptides, including those using nanopores, sequencing by degradation, reverse translation, and short-epitope mapping, with comments on bioinformatics challenges, fundamental limitations, and areas where new technologies will be more or less competitive with LC-MS/MS. In addition to conventional literature searches, instrument vendor websites, patents, webinars, and preprints were also consulted to give a more up-to-date picture. EXPERT OPINION: Many new technologies are promising. However, demonstrations that they outperform mass spectrometry in terms of peptides and proteins identified have not yet been published, and astute observers note important disadvantages, especially relating to the dynamic range of single-molecule measurements of complex mixtures. Still, even if the performance of emerging methods proves inferior to LC-MS/MS, their low cost could create a different kind of revolution: a dramatic increase in the number of biology laboratories engaging in new forms of proteomics research.

Proteomics↗