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PubMed2005

Novel biological networks modulated by complement.

The almost complete deciphering of the human genome has paved the way for the application of new technology platforms in understanding the contribution of complex biological pathways to human pathophysiology and disease. In the post-genomic era, the concept of systems biology has gained significant momentum and biomedical research is now being conducted on an integrated and cross-disciplinary platform that pulls together its resources from diverse fields such as computational biology, bioinformatics, functional genomics, structural biology, and proteomics. In this perspective, the identity of established biologic systems is being re-examined in the light of novel findings that suggest novel associations between otherwise unrelated pathways and individual proteins. Complement exemplifies such a system that, transcending its innate immune identity, has forged functional associations with multiple pathways and networks in modulating basic biologic processes. In the present article, we provide a global overview of these unusual system associations of complement with the aid of a powerful and high-throughput bioinformatics platform. Using a novel approach called systems literature analysis that allows the rapid extraction of text-based associations between genes and pathways from the ever expanding scientific article database, we have selected a broad range of biologic processes modulated by complement proteins and have constructed an integrated map of complement-mediated networks that incorporates well over 85 diverse biologic pathways. Expanding the complement cascade beyond its approximately 35 designated components, we discuss protein-protein interactions involving novel ligands and associations with signaling cascades and cellular networks that affect both inflammatory and non-inflammatory processes. This integrated consideration of complement within a unified 'systems biology' framework underscores the concept that innate immunity goes well beyond the protection of 'self' extending links to critical developmental, homeostatic, and metabolic processes.

Complement System Proteins↗
PubMed2004

Additional paper: computational resources for metabolomics.

Metabolomics, a comprehensive extension of traditional targeted metabolite analysis, has recently attracted much attention as the biological jigsaw puzzle's missing piece that can complement transcriptome and proteome analysis. This tutorial survey introduces practical web resources with special emphasis on the computational aspects involved in processing and navigating metabolome data. The introduced materials are also accessible from the author's web directory (Atomic Reconstruction of Metabolism or ARM).

Algorithms↗
PubMed2006

Growth-induced changes in the proteome of Helicobacter pylori.

Helicobacter pylori is a major human pathogen that is responsible for a number of gastrointestinal infections. We have used 2-DE to characterise protein synthesis in bacteria grown either on solid agar-based media or in each of two broth culture media (Brucella and brain heart infusion (BHI) broth). Significant differences were observed in the proteomes of bacteria grown either on agar-based or in broth media. Major changes in protein abundance were identified using principal component analysis (PCA), which delineated the profiles derived for the three key growth conditions (i.e. agar plates, Brucella and BHI broth). Proteins detected across the gel series were identified by peptide mass mapping and Edman sequencing. A number of proteins associated with protein synthesis in general as well as specific amino acid synthesis were depressed in broth-grown bacteria compared to plate-grown bacteria. A similar reduction was also observed in the abundance of proteins involved in detoxification. Two of the most abundant spots, identified as UreB and GroEL, in plate-grown bacteria showed a >140-fold drop in abundance in bacteria grown in Brucella broth compared to bacteria grown on agar plates. Two protein spots induced in bacteria grown in broth culture were both identified as glyceraldehyde 3-phosphate dehydrogenase based on their N-terminal amino acid sequences derived by Edman degradation. The underlying causes of the changes in the proteins abundance were not clear, but it was likely that a significant proportion of the changes were due to the alkaline pH of the broth culture media.

Agar↗
PubMed2006

The human cornea proteome: bioinformatic analyses indicate import of plasma proteins into the cornea.

Increased biochemical knowledge of normal and diseased corneas is essential for the understanding of corneal homeostasis and pathophysiology. In a recent study, we characterized the proteome of the normal human cornea and identified 141 distinct proteins. This dataset represents the most comprehensive protein study of the cornea to date and provides a useful reference for further studies of normal and diseased human corneas. The list of identified proteins is available at the Cornea Protein Database. In the present paper, we review the utilized procedures for extraction and fractionation of corneal proteins and discuss the potential roles of the identified proteins in relation to homeostasis, diseases, and wound-healing of the cornea. In addition, we compare the list of identified proteins with high quality gene expression libraries (cDNA libraries) and Serial Analysis of Gene Expression (SAGE) data. Of the 141 proteins, 86 (61%) were recognized in cDNA libraries from the corneas of dogs and rabbits, or humans with keratoconus, and 98 (69.5%) were recognized in SAGE data of mouse and human corneas. However, the percentages of identified genes in each of the protein functional groups differed markedly. Thus, exceptionally few of the traditional blood/plasma proteins and immune defense proteins that were identified in the human cornea were recognized in the gene expression libraries of the cornea. This observation strongly indicates that these abundant corneal proteins are not expressed in the cornea but originate from the surrounding pericorneal tissue.

Animals↗
PubMed2004

The path to enlightenment: making sense of genomic and proteomic information.

Whereas genomics describes the study of genome, mainly represented by its gene expression on the DNA or RNA level, the term proteomics denotes the study of the proteome, which is the protein complement encoded by the genome. In recent years, the number of proteomic experiments increased tremendously. While all fields of proteomics have made major technological advances, the biggest step was seen in bioinformatics. Biological information management relies on sequence and structure databases and powerful software tools to translate experimental results into meaningful biological hypotheses and answers. In this resource article, I provide a collection of databases and software available on the Internet that are useful to interpret genomic and proteomic data. The article is a toolbox for researchers who have genomic or proteomic datasets and need to put their findings into a biological context.

Computational Biology↗
PubMed2005

[Diagnostic application of serum protein pattern and artificial neural network software in breast cancer].

BACKGROUND & OBJECTIVE: The progress in proteomics provides a novel platform for early diagnosis of cancer, and screening for new tumor biomarkers. This study was designed to develop and evaluate a diagnostic model of breast cancer with surface enhanced laser desorption/ionization-time of flight-mass spectrometry (SELDI-TOF-MS) ProteinChip array technology and artificial neural network software. METHODS: SELDI-TOF-MS ProteinChip was used to detect serum protein patterns of 49 patients with breast cancer, and 33 healthy women. Diagnostic model was developed, and validated using artificial neural network software. RESULTS: An intact diagnostic model from all 253 discrepant protein peaks, and a terse model from the top-scored 4 peaks were built. The diagnostic sensitivity, and specificity of the intact model were 83.33% (15/18), and 88.89% (8/9)u the detection rates of breast cancer of stage I, and stage II-IV using the intact model were 90.00% (9/10), and 75.00% (6/8). The diagnostic sensitivity, and specificity of the terse model were 76.47% (13/17), and 90.00% (9/10)u the detection rates of breast cancer of stage I, and stage II-IV using the terse model were 100.00% (3/3), and 71.43% (10/14). The diagnostic values of these 2 models were similar (P>0.05). Their diagnostic abilities to breast cancer of stage I were not worse than those to breast cancer of stage II-IV (P>0.05). CONCLUSION: High sensitivity and specificity achieved by this method show great potential for early diagnosis of breast cancer, and screening for new tumor biomarkers.

Adult↗
PubMed2005

Report of the roundtable discussion organised by the Swiss Proteomics Society (SPS), Bern, 8th December 2004.

How close are we to using proteomics tools in the every day practice of physicians? What are the socio-economical issues our health care system may face with the advent of biomarkers for early diagnosis? How to get the specialists from the various disciplines integrated in proteomics to establish a common understanding of the clinical issues and develop the necessary standards (methods, biochemicals and IT)? These were the kind of questions a panel of specialists tried to answer during the roundtable discussion that took place in Bern during the Swiss Proteomics Society 2004 congress.

Automation↗
PubMed2006

CAPS: coevolution analysis using protein sequences.

UNLABELLED: Coevolution Analysis using Protein Sequences (CAPS) is a PERL based software that identifies co-evolution between amino acid sites. Blosum-corrected amino acid distances are used to identify amino acid co-variation. The phylogenetic sequence relationships are used to remove the phylogenetic and stochastic dependencies between sites. The 3D protein structure is used to identify the nature of the dependencies between co-evolving amino acid sites. Friendly interpretable output files are generated. AVAILABILITY: CAPS version 1 is available at http://bioinf.gen.tcd.ie/~faresm/software/caps/. Distribution versions for Linux/Unix, Mac OS X and Windows operating systems are available, including manual and example files.

Algorithms↗
PubMed2002

Proteomic tools for biomedicine.

Proteomic tools measure gene expression, protein activity and interactions of biological events at the protein level. Proteins are the major catalysts of biological functions and contain several dimensions of information that collectively indicate the actual rather than the potential functional state as indicated by mRNA analysis. Measurements can be made in terms of protein quantity, location, and time-point. For the future we see a further integration of existing and new technologies for proteomics from a wide range of areas of biochemistry, chemistry, physics, computing science and molecular biology. This will further advance our knowledge of how biological systems are built up and what mechanisms control these systems. However, the potential of proteomics to comprehensively answer all biological questions is limited as only protein activity is measured. A unification of genomics, proteomics, and other technologies is needed if we are to start to understand the complexity of biological function in the context of disease and health.

Proteome↗
PubMed2002

Biological data becomes computer literate: new advances in bioinformatics.

Bioinformatics is an art and science concerned with the use of computing in biological research areas such as genomics, transcriptomics, proteomics, genetics, and evolution. This review paints a broad picture of bioinformatics, drawing examples from genomic sequencing and microarray analysis. I highlight the role of bioinformatics at multiple points along the path from high-tech data generation to biological discovery.

Computational Biology↗
PubMed2004

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.

Algorithms↗
PubMed2003

Integr8: enhanced inter-operability of European molecular biology databases.

OBJECTIVES: The increasing production of molecular biology data in the post-genomic era, and the proliferation of databases that store it, require the development of an integrative layer in database services to facilitate the synthesis of related information. The solution of this problem is made more difficult by the absence of universal identifiers for biological entities, and the breadth and variety of available data. METHODS: Integr8 was modelled using UML (Universal Modelling Language). Integr8 is being implemented as an n-tier system using a modern object-oriented programming language (Java). An object-relational mapping tool, OJB, is being used to specify the interface between the upper layers and an underlying relational database. RESULTS: The European Bioinformatics Institute is launching the Integr8 project. Integr8 will be an automatically populated database in which we will maintain stable identifiers for biological entities, describe their relationships with each other (in accordance with the central dogma of biology), and store equivalences between identified entities in the source databases. Only core data will be stored in Integr8, with web links to the source databases providing further information. CONCLUSIONS: Integr8 will provide the integrative layer of the next generation of bioinformatics services from the EBI. Web-based interfaces will be developed to offer gene-centric views of the integrated data, presenting (where known) the links between genome, proteome and phenotype.

Computational Biology↗
PubMed2006

Human Disease Glycomics/Proteome Initiative Workshop and the 4th HUPO Annual Congress.

At the Human Disease Glycomics/Proteome Initiative workshop held on August 27 on the occasion of the fourth HUPO Congress in Munich, Germany, the working groups reported on pilot studies, performed by 21 laboratories world-wide, to analyze glycan using MS. During the steering committee on July 31 in Osaka, Japan, it was reported that these groups have developed a system using MS to assess the world-wide network on the screening of congenital disorders of glycosylation. The concept of glycobioinformatics was also explained at this meeting. The session on PTMs laid particular emphasis on the importance of functional glycomics using glycosyltransferase genes as well as on the importance of identifying the target protein(s) carrying the sugar chains.

Carbohydrates↗
PubMed2006

MASCOT HTML and XML parser: an implementation of a novel object model for protein identification data.

Protein identification using MS is an important technique in proteomics as well as a major generator of proteomics data. We have designed the protein identification data object model (PDOM) and developed a parser based on this model to facilitate the analysis and storage of these data. The parser works with HTML or XML files saved or exported from MASCOT MS/MS ions search in peptide summary report or MASCOT PMF search in protein summary report. The program creates PDOM objects, eliminates redundancy in the input file, and has the capability to output any PDOM object to a relational database. This program facilitates additional analysis of MASCOT search results and aids the storage of protein identification information. The implementation is extensible and can serve as a template to develop parsers for other search engines. The parser can be used as a stand-alone application or can be driven by other Java programs. It is currently being used as the front end for a system that loads HTML and XML result files of MASCOT searches into a relational database. The source code is freely available at http://www.ccbm.jhu.edu and the program uses only free and open-source Java libraries.

Databases, Protein↗
PubMed2005

Probabilistic prediction of protein-protein interactions from the protein sequences.

Prediction of protein-protein interactions is very important for several bioinformatics tasks though it is not a straightforward problem. In this paper, employing only protein sequence information, a framework is presented to predict protein-protein interactions using a probabilistic-based tree augmented nai ve (TAN) Bayesian network. Our framework also provides a confidence level for every predicted interaction, which is useful for further analysis by the biologists. The framework is applied to the yeast interaction datasets for predicting interactions and it is shown that our framework gives better performance than support vector machine (SVM). The framework is implemented as a webserver and is available for prediction.

Artificial Intelligence↗
PubMed2006

A wavelet-based data pre-processing analysis approach in mass spectrometry.

Recently, mass spectrometry analysis has a become an effective and rapid approach in detecting early-stage cancer. To identify proteomic patterns in serum to discriminate cancer patients from normal individuals, machine-learning methods, such as feature selection and classification, have already been involved in the analysis of mass spectrometry (MS) data with some success. However, the performance of existing machine learning methods for MS data analysis still needs improving. The study in this paper proposes a wavelet-based pre-processing approach to MS data analysis. The approach applies wavelet-based transforms to MS data with the aim of de-noising the data that are potentially contaminated in acquisition. The effects of the selection of wavelet function and decomposition level on the de-noising performance have also been investigated in this study. Our comparative experimental results demonstrate that the proposed de-noising pre-processing approach has potentials to remove possible noise embedded in MS data, which can lead to improved performance for existing machine learning methods in cancer detection.

Algorithms↗
PubMed2004

Impaired cognitive performance in neuronal nitric oxide synthase knockout mice is associated with hippocampal protein derangements.

Nitric oxide is implicated in modulation of memory and pharmacological as well as genetic inhibition of neuronal nitric oxide synthase (nNOS) leads to impaired cognitive function. We therefore decided to study learning and memory functions and cognitive flexibility in the Morris water maze (MWM) in 1-month-old male mice lacking nNOS (nNOS KO). Hippocampal protein profiling was carried out to possibly link protein derangement to impaired cognitive function. Two-dimensional gel electrophoresis with in-gel digestion of spots and subsequent MALDI-TOF identification of proteins and quantification of proteins using specific software was applied. In the memory as well as in the relearning task of the MWM, most of the nNOS KO failed to find the submerged platform within a given time. Proteomic evaluation of hippocampus, the main anatomical structure computing cognitive functions, revealed aberrant expression of a synaptosomal associated protein of the exocytotic machinery (NSF), glycolytic enzymes, chaperones 78 kDa glucose-regulated protein, T-complex protein 1; the signaling structure guanine nucleotide-binding protein G(I)/G(S)/G(T) and heterogeneous nuclear ribonucleoprotein H of the splicing machinery. We conclude that nNOS knockout mice show impaired spatial performance in the MWM, a finding that may be either linked to direct effects of nNOS/NO and/or to specific hippocampal protein derangements.

Animals↗