Combining bioinformatics and MS-based proteomics: clinical implications

Clinical proteomics research aims at i) discovery of protein biomarkers for screening, diagnosis and prognosis of disease, ii) discovery of protein therapeutic targets for improvement of disease prevention, treatment and follow-up, and iii) development of mass spectrometry (MS)-based assays that could be implemented in clinical chemistry, microbiology or hematology laboratories. MS has been increasingly applied in clinical proteomics studies for the identification and quantification of proteins. Bioinformatics plays a key role in the exploitation of MS data in several aspects such as the generation and curation of protein sequence databases, the development of appropriate software for MS data treatment and integration with other omics data and the establishment of adequate standard files for data sharing. In this article, we discuss the main MS approaches and bioinformatics solutions that are currently applied to accomplish the objectives of clinical proteomic research.     

Combining multiple comparisons and modeling techniques in dose-response studies

The analysis of data from dose-response studies has long been divided according to two major strategies: multiple comparison procedures and model-based approaches. Model-based approaches assume a functional relationship between the response and the dose, taken as a quantitative factor, according to a prespecified parametric model. The fitted model is then used to estimate an adequate dose to achieve a desired response but the validity of its conclusions will highly depend on the correct choice of the a priori unknown dose-response model. Multiple comparison procedures regard the dose as a qualitative factor and make very few, if any, assumptions about the underlying dose-response model. The primary goal is often to identify the minimum effective dose that is statistically significant and produces a relevant biological effect. One approach is to evaluate the significance of contrasts between different dose levels, while preserving the family-wise error rate. Such procedures are relatively robust but inference is confined to the selection of the target dose among the dose levels under investigation. We describe a unified strategy to the analysis of data from dose-response studies which combines multiple comparison and modeling techniques. We assume the existence of several candidate parametric models and use multiple comparison techniques to choose the one most likely to represent the true underlying dose-response curve, while preserving the family-wise error rate. The selected model is then used to provide inference on adequate doses.     

Combining structural and bioinformatics methods for the analysis of functionally important residues in DNA glycosylases

An essential function of DNA glycosylases is the recognition and excision of damaged bases in DNA, thereby preserving genomic integrity. Lesion recognition is a multistep process, which is only partially revealed by structural analysis of the catalytically competent complex. The functional role of additional residues can be predicted by combining structural data with analysis of amino acid conservation. The following postulate underlies this approach: if a family or superfamily can be broken into subgroups with different substrate specificities, residues highly conserved between these subgroups represent those important for enzyme catalysis and structure maintenance while residues highly conserved within a subgroup but not between subgroups represent residues important for substrate specificity. We review the bioinformatics approach used for this quantitative analysis and describe its application to the Nth superfamily and Fpg family of DNA glycosylases. These results serve as a starting point in planning site-directed mutagenesis experiments to elucidate the functional role of similar and dissimilar residues in DNA repair and other proteins.     

利用RACE技术和生物信息学资源快速钓取多个侯选同源基因

利用差异显示PCR技术获得的一条在胃癌癌旁和正常组织表达量高的EST－W123,通过与GenBank的dbest库进行电子交,选取了与W123同源度高的若干EST,在它们共有的保守序列设计了用于扩增的寡聚核苷酸引物,利用cDNA末端快速扩增（RACE）技术得到了7条带有polyA尾的3'EST,进行序列分析后,发现它们均是代表新基因或不同剪接体的EST,且具有共同的保守序列,已登录GenBank。     

Combining SSH and cDNA microarrays for rapid identification of differentially expressed genes

Comparing patterns of gene expression in cell lines and tissues has important applications in a variety of biological systems. In this study we have examined whether the emerging technology of cDNA microarrays will allow a high throughput analysis of expression of cDNA clones generated by suppression subtractive hybridization (SSH). A set of cDNA clones including 332 SSH inserts amplified by PCR was arrayed using robotic printing. The cDNA arrays were hybridized with fluorescent labeled probes prepared from RNA from ER-positive (MCF7 and T47D) and ER-negative (MDA-MB-231 and HBL-100) breast cancer cell lines. Ten clones were identified that were over-expressed by at least a factor of five in the ER-positive cell lines. Northern blot analysis confirmed over-expression of these 10 cDNAs. Sequence analysis identified four of these clones as cytokeratin 19, GATA-3, CD24 and glutathione-S-transferase mu-3. Of the remaining six cDNA clones, four clones matched EST sequences from two different genes and two clones were novel sequences. Flow cytometry and immunofluorescence confirmed that CD24 protein was over-expressed in the ER-positive cell lines. We conclude that SSH and microarray technology can be successfully applied to identify differentially expressed genes. This approach allowed the identification of differentially expressed genes without the need to obtain previously cloned cDNAs.     

Simultaneous extraction and rapid visualization of peptidomic and lipidomic body fluids fingerprints using mesoporous aluminosilicate and MALDI‐TOF MS

Herein we report the use of mesoporous aluminosilicate (MPAS) for the simultaneous extraction of peptides and lipids from complex body fluids such as human plasma and synovial fluid. We show that MPAS particles, given their mesostructural features with nanometric pore size and high surface area, are an efficient device for simultaneous extraction of peptidome and lipidome from as little as a few microliters of body fluids. The peptides and the lipids, selected and enriched by MPAS particles and rapidly visualized by MALDI‐TOF MS, could form part of a diagnostic profile of the “peptidome” and the “lipidome” of healthy versus diseased subjects in comparative studies. The ability of this approach to rapidly reveal the overall pattern of changes in both lipidome and peptidome signatures of complex biofluids could be of valuable interest for handling large numbers of samples required in ‐omics studies for the purpose of finding novel biomarkers.     

Combining bioinformatics techniques to explore the molecular mechanisms involved in pancreatic cancer metastasis and prognosis

This article aims to explore the underlying molecular mechanisms and prognosis‐related genes in pancreatic cancer metastasis. Pancreatic cancer metastasis‐related gene chip data were downloaded from GENE EXPRESSION OMNIBUS(GEO)database. Differentially expressed genes were screened after R‐package pre‐treatment. Functional annotations and related signalling pathways were analysed using DAVID software. GEPIA (Gene Expression Profiling Interactive Analysis) was used to perform prognostic analysis, and differential genes associated with prognosis were screened and validated using data from GEO. We screened 40 healthy patients, 40 primary pancreatic cancer and 40 metastatic pancreatic cancer patients, collected serum, designed primers and used qPCR to test the expression of prognosis‐related genes in each group. 109 differentially expressed genes related with pancreatic cancer metastasis were screened, of which 49 were up‐regulated and 60 were down‐regulated. Functional annotation and pathway analysis revealed differentially expressed genes were mainly concentrated in protein activation cascade, extracellular matrix construction, decomposition, etc In the biological process, it is mainly involved in signalling pathways such as PPAR, PI3K‐Akt and ECM receptor interaction. Prognostic analysis showed the expression levels of four genes were significantly correlated with the overall survival time of patients with pancreatic cancer, namely SCG5, CRYBA2, CPE and CHGB. qPCR experiments showed the expression of these four genes was decreased in both the primary pancreatic cancer group and the metastatic pancreatic cancer group, and the latter was more significantly reduced. Pancreatic cancer metastasis is closely related to the activation of PPAR pathway, PI3K‐Akt pathway and ECM receptor interaction. SCG5, CRYBA2, CPE and CHGB genes are associated with the prognosis of pancreatic cancer, and their low expression suggests a poor prognosis.     

Combining proteomics and bioinformatics to explore novel tegumental antigens as vaccine candidates against Echinococcus granulosus infection

Echinococcus granulosus is the parasite responsible for cystic echinococcosis (CE), an important worldwide-distributed zoonosis. New effective vaccines against CE could potentially have great economic and health benefits. Here, we describe an innovative vaccine design scheme starting from an antigenic fraction enriched in tegumental antigens from the protoscolex stage (termed PSEx) already known to induce protection against CE. We first used mass spectrometry to characterize the protein composition of PSEx followed by Gene Ontology analysis to study the potential Biological Processes, Molecular Functions, and Cellular Localizations of the identified proteins. Following, antigenicity predictions and determination of conservancy degree against other organisms were determined. Thus, nine novel proteins were identified as potential vaccine candidates. Furthermore, linear B cell epitopes free of posttranslational modifications were predicted in the whole PSEx proteome through colocalization of in silico predicted epitopes within peptide fragments identified by matrix-assisted laser desorption/ionization-TOF/TOF. Resulting peptides were termed “clean linear B cell epitopes,” and through BLASTp scanning against all nonhelminth proteins, those with 100% identity against any other protein were discarded. Then, the secondary structure was predicted for peptides and their corresponding proteins. Peptides with highly similar secondary structure respect to their parental protein were selected, and those potentially toxic and/or allergenic were discarded. Finally, the selected clean linear B cell epitopes were mapped within their corresponding 3D-modeled protein to analyze their possible antibody accessibilities, resulting in 14 putative peptide vaccine candidates. We propose nine novel proteins and 14 peptides to be further tested as vaccine candidates against CE.     

Global computing for bioinformatics

Global computing, the collaboration of idle PCs via the Internet in a SETI@home style, emerges as a new way of massive parallel multiprocessing with potentially enormous CPU power. Its relations to the broader, fast-moving field of Grid computing are discussed without attempting a review of the latter. This review (i) includes a short table of milestones in global computing history, (ii) lists opportunities global computing offers for bioinformatics, (iii) describes the structure of problems well suited for such an approach, (iv) analyses the anatomy of successful projects and (v) points to existing software frameworks. Finally, an evaluation of the various costs shows that global computing indeed has merit, if the problem to be solved is already coded appropriately and a suitable global computing framework can be found. Then, either significant amounts of computing power can be recruited from the general public, or--if employed in an enterprise-wide Intranet for security reasons--idle desktop PCs can substitute for an expensive dedicated cluster.     

Ontologies for molecular biology and bioinformatics

About five years ago, ontology was almost unknown in bioinformatics, even more so in molecular biology. Nowadays, many bioinformatics articles mention it in connection with text mining, data integration or as a metaphysical cure for problems in standardisation of nomenclature and other applications. This article attempts to give an account of what concept ontologies in the domain of biology and bioinformatics are; what they are not; how they can be constructed; how they can be used; and some fallacies and pitfalls creators and users should be aware of.     

Rat mitochondrion-neuron focused microarray (rMNChip) and bioinformatics tools for rapid identification of differential pathways in brain tissues

Mitochondrial function is of particular importance in brain because of its high demand for energy (ATP) and efficient removal of reactive oxygen species (ROS). We developed rat mitochondrion-neuron focused microarray (rMNChip) and integrated bioinformatics tools for rapid identification of differential pathways in brain tissues. rMNChip contains 1,500 genes involved in mitochondrial functions, stress response, circadian rhythms and signal transduction. The bioinformatics tool includes an algorithm for computing of differentially expressed genes, and a database for straightforward and intuitive interpretation for microarray results. Our application of these tools to RNA samples derived from rat frontal cortex (FC), hippocampus (HC) and hypothalamus (HT) led to the identification of differentially-expressed signal-transduction-bioenergenesis and neurotransmitter-synthesis pathways with a dominant number of genes (FC/HC = 55/6; FC/HT = 55/4) having significantly (p<0.05, FDR<10.70%) higher (≥1.25 fold) RNA levels in the frontal cortex than the others, strongly suggesting active generation of ATP and neurotransmitters and efficient removal of ROS. Thus, these tools for rapid and efficient identification of differential pathways in brain regions will greatly facilitate our systems-biological study and understanding of molecular mechanisms underlying complex and multifactorial neurodegenerative diseases.     

Adaptations for rapid and forceful contraction in wing muscles of the male golden-collared manakin: sex and species comparisons

The courtship display of the male golden-collared manakin (Manacus vitellinus) of Panamanian rainforests is noteworthy for several types of whip-crack-like sounds created by a rapid overhead flip of the wings. We have hypothesized that this courtship behavior. which is not performed by females, is associated with steroid-sensitive and sexually dimorphic neuromuscular systems. Presumably, muscles creating the motion of the wingsnap in males are specialized for greater force generation and speed of contraction. We tested this hypothesis by examining mass, fiber diameter, metabolic enzyme activity, and myosin isoform expression in several muscles of male and female manakins and in both sexes of a non-wingsnapping bird, the zebra finch (Taenopygia guttata). We have identified three wing muscles, the scapulohumeralis caudalis, the supracoracoideus, and the pectoralis major, that differ in one or more of these characteristics across sex and species, suggesting they are specialized for faster contraction and greater force production in male manakins. These muscles normally function to raise and lower the wings during flight. As this movement is the principal motion of the wingsnap, these adaptations presumably underlie the performance of the wingsnap display.     

Emerging bioinformatics for the metabolome

Metabolic profiling applied to functional genomics (metabolomics) is in an early stage of development. Here, the technologies used for metabolite profiling are briefly covered, illustrated by a few pioneering studies. Issues related to bioinformatics, namely data analysis, visualisation and archival, are the main focus of this review. Arguably there is already a need for databases containing metabolite profiles specific for a single organism, and a generic repository containing all metabolite profiling results, regardless of species. Data analyses and visualisations that combine the biological context with chemistry details are suggested as being the most promising.     

Designing XML schemas for bioinformatics

Data interchange bioinformatics databases will, in the future, most likely take place using extensible markup language (XML). The document structure will be described by an XML Schema rather than a document type definition (DTD). To ensure flexibility, the XML Schema must incorporate aspects of Object-Oriented Modeling. This impinges on the choice of the data model, which, in turn, is based on the organization of bioinformatics data by biologists. Thus, there is a need for the general bioinformatics community to be aware of the design issues relating to XML Schema. This paper, which is aimed at a general bioinformatics audience, uses examples to describe the differences between a DTD and an XML Schema and indicates how Unified Modeling Language diagrams may be used to incorporate Object-Oriented Modeling in the design of schema.     

Tools and collaborative environments for bioinformatics research

Advanced research requires intensive interaction among a multitude of actors, often possessing different expertise and usually working at a distance from each other. The field of collaborative research aims to establish suitable models and technologies to properly support these interactions. In this article, we first present the reasons for an interest of Bioinformatics in this context by also suggesting some research domains that could benefit from collaborative research. We then review the principles and some of the most relevant applications of social networking, with a special attention to networks supporting scientific collaboration, by also highlighting some critical issues, such as identification of users and standardization of formats. We then introduce some systems for collaborative document creation, including wiki systems and tools for ontology development, and review some of the most interesting biological wikis. We also review the principles of Collaborative Development Environments for software and show some examples in Bioinformatics. Finally, we present the principles and some examples of Learning Management Systems. In conclusion, we try to devise some of the goals to be achieved in the short term for the exploitation of these technologies.