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Reciprocal modifications of CLIC4 in tumor epithelium and stroma mark malignant progression of multiple human cancers.

PURPOSE: CLIC4, a member of a family of intracellular chloride channels, is regulated by p53, c-Myc, and tumor necrosis factor-alpha. Regulation by factors involved in cancer pathogenesis, together with the previously shown proapoptotic activity of CLIC4, suggests that the protein may have a tumor suppressor function. To address this possibility, we characterized the expression profile, subcellular localization, and gene integrity of CLIC4 in human cancers and determined the functional consequences of CLIC4 expression in tumor epithelium and stromal cells. EXPERIMENTAL DESIGN: CLIC4 expression profiles were analyzed by genomics, proteomics, bioinformatics, and tissue microarrays. CLIC4 expression, as a consequence of crosstalk between stroma and epithelium, was tested in vitro by coculture of breast epithelial tumor cells and normal fibroblasts, and the functional consequences of CLIC4 expression was tested in vivo in xenografts of human breast tumor cell lines reconstituted with CLIC4 or mixed with fibroblasts that overexpress CLIC4 transgenically. RESULTS: In cDNA arrays of matched human normal and tumor tissues, CLIC4 expression was reduced in renal, ovarian, and breast cancers. However, CLIC4 protein levels were variable in tumor lysate arrays. Transcript sequences of CLIC4 from the human expressed sequence tag database and manual sequencing of cDNA from 60 human cancer cell lines (NCI60) failed to reveal deletion or mutations in the CLIC4 gene. On matched tissue arrays, CLIC4 was predominantly nuclear in normal human epithelial tissues but not cancers. With advancing malignant progression, CLIC4 staining became undetectable in tumor cells, but expression increased in stromal cells coincident with up-regulation of alpha-smooth muscle actin, suggesting that CLIC4 is up-regulated in myofibroblasts. Coculture of cancer cells and fibroblasts induced the expression of both CLIC4 and alpha-smooth muscle actin in fibroblasts adjacent to tumor nests. Introduction of CLIC4 or nuclear targeted CLIC4 via adenovirus into human breast cancer xenografts inhibited tumor growth, whereas overexpression of CLIC4 in stromal cells of xenografts enhanced tumor growth. CONCLUSION: Loss of CLIC4 in tumor cells and gain in tumor stroma is common to many human cancers and marks malignant progression. Up-regulation of CLIC4 in tumor stroma is coincident with myofibroblast conversion, generally a poor prognostic indicator. Reactivation and restoration of CLIC4 in tumor cells or the converse in tumor stromal cells could provide a novel approach to inhibit tumor growth.

Actins↗

Bioinformatics: towards new directions for public health.

OBJECTIVES: Epidemiologists are reformulating their classical approaches to diseases by considering various issues associated to "omics" areas and technologies. Traditional differences between epidemiology and genetics include background, training, terminologies, study designs and others. Public health and epidemiology are increasingly looking forward to using methodologies and informatics tools, facilitated by the Bioinformatics community, for managing genomic information. Our aim is to describe which are the most important implications related with the increasing use of genomic information for public health practice, research and education. To review the contribution of bioinformatics to these issues, in terms of providing the methods and tools needed for processing genetic information from pathogens and patients. To analyze the research challenges in biomedical informatics related with the need of integration of clinical, environmental and genetic data and the new scenarios arisen in public health. METHODS: Review of the literature, Internet resources and material and reports generated by internal and external research projects. RESULTS: New developments are needed to advance in the study of the interactions between environmental agents and genetic factors involved in the development of diseases. The use of biomarkers, biobanks, and integrated genomic/clinical databases poses serious challenges for informaticians in order to extract useful information and knowledge for public health, biomedical research and healthcare. CONCLUSIONS: From an informatics perspective, integrated medical/biological ontologies and new semantic-based models for managing information provide new challenges for research in areas such as genetic epidemiology and the "omics" disciplines, among others. In this regard, there are various ethical, privacy, informed consent and social implications, that should be carefully addressed by researchers, practitioners and policy makers.

Computational Biology↗

Nuclear Receptor Signaling Atlas (www.nursa.org): hyperlinking the nuclear receptor signaling community.

The nuclear receptor signaling (NRS) field has generated a substantial body of information on nuclear receptors, their ligands and coregulators, with the ultimate goal of constructing coherent models of the biological and clinical significance of these molecules. As a component of the Nuclear Receptor Signaling Atlas (NURSA)--the development of a functional atlas of nuclear receptor biology--the NURSA Bioinformatics Resource is developing a strategy to organize and integrate legacy and future information on these molecules in a single web-based resource (www.nursa.org). This entails parallel efforts of (i) developing an appropriate software framework for handling datasets from NURSA laboratories and (ii) designing strategies for the curation and presentation of public data relevant to NRS. To illustrate our approach, we have described here in detail the development of a web-based interface for the NURSA quantitative PCR nuclear receptor expression dataset, incorporating bioinformatics analysis which provides novel perspectives on functional relationships between these molecules. We anticipate that the free and open access of the community to a platform for data mining and hypothesis generation strategies will be a significant contribution to the progress of research in this field.

Animals↗

Epigenetic regulation of HOXA2 expression affects tumor progression and predicts breast cancer patient survival.

Accumulating evidence suggests that genetic and epigenetic biomarkers hold potential for enhancing the early detection and monitoring of breast cancer (BC). Epigenetic alterations of the Homeobox A2 (HOXA2) gene have recently garnered significant attention in the clinical management of various malignancies. However, the precise role of HOXA2 in breast tumorigenesis has remained elusive. To address this point, we conducted high-throughput RNA sequencing and DNA methylation array studies on laser-microdissected human BC samples, paired with normal tissue samples. Additionally, we performed comprehensive in silico analyses using large public datasets: TCGA and METABRIC. The diagnostic performance of HOXA2 was calculated by means of receiver operator characteristic curves. Its prognostic significance was assessed through immunohistochemical studies and Kaplan-Meier Plotter database interrogation. Moreover, we explored the function of HOXA2 and its role in breast carcinogenesis through in silico, in vitro, and in vivo investigations. Our work revealed significant hypermethylation and downregulation of HOXA2 in human BC tissues. Low HOXA2 expression correlated with increased BC aggressiveness and unfavorable patient survival outcomes. Suppression of HOXA2 expression significantly heightened cell proliferation, migration, and invasion in BC cells, and promoted tumor growth in mice. Conversely, transgenic HOXA2 overexpression suppressed these cellular processes and promoted apoptosis of cancer cells. Interestingly, a strategy of pharmacological demethylation successfully restored HOXA2 expression in malignant cells, reducing their neoplastic characteristics. Bioinformatics analyses, corroborated by in vitro experimentations, unveiled a novel implication of HOXA2 in the lipid metabolism of BC. Specifically, depletion of HOXA2 leaded to a concomitantly decreased expression of PPARγ and its target CIDEC, a master regulator of lipid droplet (LD) accumulation, thereby resulting in reduced LD abundance in BC cells. In summary, our study identifies HOXA2 as a novel prognosis-relevant tumor suppressor in the mammary gland.

Humans↗

Histone acetylase GCN5 enters the nucleus via importin-alpha in protozoan parasite Toxoplasma gondii.

The histone acetyltransferase GCN5 acetylates nucleosomal histones to alter gene expression. How GCN5 gains entry into the nucleus of the cell has not been determined. We have mapped a six-amino acid motif (RKRVKR) that serves as a necessary and sufficient nuclear localization signal (NLS) for GCN5 in the protozoan pathogen Toxoplasma gondii (TgGCN5). Virtually nothing is known about nucleocytoplasmic transport in these parasites (phylum Apicomplexa), and this study marks the first demonstrated NLS delineated for members of the phylum. The TgGCN5 NLS has predictive value because it successfully identifies other nuclear proteins in three different apicomplexan genomic databases. Given the basic composition of the T. gondii NLS, we hypothesized that TgGCN5 physically interacts with importin-alpha, the main transport receptor in the importin/karyopherin nuclear import pathway. We cloned the importin-alpha gene from T. gondii (TgIMPalpha), which encodes a protein of 545 amino acids that possesses an importin-beta-binding domain and armadillo/beta-catenin-like repeats. In vitro co-immunoprecipitation experiments confirm that TgIMPalpha directly interacts with TgGCN5, but this interaction is abolished if the TgGCN5 NLS is deleted. Taken together, these data argue that TgGCN5 gains access to the parasite nucleus by interacting with TgIMPalpha. Bioinformatics analysis of the T. gondii genome reveals that other components of the importin pathway are present in the organism. This study demonstrates the utility of T. gondii as a model for the study of nucleocytoplasmic trafficking in early eukaryotic cells.

Acetyltransferases↗

ParPEST: a pipeline for EST data analysis based on parallel computing.

BACKGROUND: Expressed Sequence Tags (ESTs) are short and error-prone DNA sequences generated from the 5' and 3' ends of randomly selected cDNA clones. They provide an important resource for comparative and functional genomic studies and, moreover, represent a reliable information for the annotation of genomic sequences. Because of the advances in biotechnologies, ESTs are daily determined in the form of large datasets. Therefore, suitable and efficient bioinformatic approaches are necessary to organize data related information content for further investigations. RESULTS: We implemented ParPEST (Parallel Processing of ESTs), a pipeline based on parallel computing for EST analysis. The results are organized in a suitable data warehouse to provide a starting point to mine expressed sequence datasets. The collected information is useful for investigations on data quality and on data information content, enriched also by a preliminary functional annotation. CONCLUSION: The pipeline presented here has been developed to perform an exhaustive and reliable analysis on EST data and to provide a curated set of information based on a relational database. Moreover, it is designed to reduce execution time of the specific steps required for a complete analysis using distributed processes and parallelized software. It is conceived to run on low requiring hardware components, to fulfill increasing demand, typical of the data used, and scalability at affordable costs.

Algorithms↗

Molecular phylogenetics and comparative modeling of HEN1, a methyltransferase involved in plant microRNA biogenesis.

BACKGROUND: Recently, HEN1 protein from Arabidopsis thaliana was discovered as an essential enzyme in plant microRNA (miRNA) biogenesis. HEN1 transfers a methyl group from S-adenosylmethionine to the 2'-OH or 3'-OH group of the last nucleotide of miRNA/miRNA* duplexes produced by the nuclease Dicer. Previously it was found that HEN1 possesses a Rossmann-fold methyltransferase (RFM) domain and a long N-terminal extension including a putative double-stranded RNA-binding motif (DSRM). However, little is known about the details of the structure and the mechanism of action of this enzyme, and about its phylogenetic origin. RESULTS: Extensive database searches were carried out to identify orthologs and close paralogs of HEN1. Based on the multiple sequence alignment a phylogenetic tree of the HEN1 family was constructed. The fold-recognition approach was used to identify related methyltransferases with experimentally solved structures and to guide the homology modeling of the HEN1 catalytic domain. Additionally, we identified a La-like predicted RNA binding domain located C-terminally to the DSRM domain and a domain with a peptide prolyl cis/trans isomerase (PPIase) fold, but without the conserved PPIase active site, located N-terminally to the catalytic domain. CONCLUSION: The bioinformatics analysis revealed that the catalytic domain of HEN1 is not closely related to any known RNA:2'-OH methyltransferases (e.g. to the RrmJ/fibrillarin superfamily), but rather to small-molecule methyltransferases. The structural model was used as a platform to identify the putative active site and substrate-binding residues of HEN and to propose its mechanism of action.

Amino Acid Sequence↗

Identification of a novel human glutathione S-transferase using bioinformatics.

In searching the expressed sequence tag (EST) data-base of GenBank with coding sequences of 11 known human glutathione S-transferases in conjunction with bioinformatic analysis, we have identified five ESTs that encode a new human glutathione S-transferase (GST) designated GST A4. The cDNA clone (I.M.A.G.E. Consortium cDNA Clone ID 515157) had an insert length of 1279 bp and contains an open reading frame of 666 bp, which encodes a protein of 222 amino acid residues. The GST A4 protein is identical in length to human GST A1 and A2 and is 54% identical to human GST A1 and A2. Sequence comparison with other human GSTs suggests that it is a new GST belonging to the alpha class GSTs. Northern blot analysis and EST database searches have demonstrated that the GST A4 mRNA is expressed at a high level in brain, placenta, and skeletal muscle and much lower in lung and liver. Analysis of the sequence tagged site (STS) database indicated that the GST A4 gene is located on chromosome 6. This STS represents a previously unidentified transcript further confirming the novelty of the new sequence.

Amino Acid Sequence↗

Meeting report: eGenomics: Cataloguing our Complete Genome Collection II.

This article summarizes the proceedings of the "eGenomics: Cataloguing our Complete Genome Collection II" workshop held November 10-11, 2005, at the European Bioinformatics Institute. This exploratory workshop, organized by members of the Genomic Standards Consortium (GSC), brought together researchers from the genomic, functional OMICS, and computational biology communities to discuss standardization activities across a range of projects. The workshop proceedings and outcomes are set to help guide the development of the GSC's Minimal Information about a Genome Sequence (MIGS) specification.

Animals↗

Evaluation of ontology development tools for bioinformatics.

Ontologies are being used nowadays in many areas, including bioinformatics. To assist users in developing and maintaining ontologies a number of tools have been developed. In this paper we compare four such tools, Protégé-2000, Chimaera, DAG-Edit and OilEd. As test ontologies we have used ontologies from the Gene Ontology Consortium. No system is preferred in all situations, but each system has its own strengths and weaknesses.

Computational Biology↗

Designing and executing scientific workflows with a programmable integrator.

MOTIVATION: As in many other fields of science, computational methods in molecular biology need to intersperse information access and algorithm execution in a computational workflow. Users often find difficulties when transferring data between data sources and applications. In most cases there is no standard solution for workflow design and execution and tailored scripting mechanisms are implemented in a case by case basis. RESULTS: In this paper, we present a general purpose 'programmable integrator' that can access information from a variety of sources in a coordinated manner. Its usefulness in complex bioinformatics applications is claimed and supported by some application examples. AVAILABILITY: Tools are freely available to non-profit educations and research institutions. Usage by commercial organizations requires a license agreement. Software requirements: Java v1.3 (http://java.sun.com), Xerces XML Parser (http://xml.apache.org/xerces-j) and Kweelt implementation of XQuery (http://kweelt.sourceforge.net/).

Algorithms↗

A tool for sharing annotated research data: the "Category 0" UMLS (Unified Medical Language System) vocabularies.

BACKGROUND: Large biomedical data sets have become increasingly important resources for medical researchers. Modern biomedical data sets are annotated with standard terms to describe the data and to support data linking between databases. The largest curated listing of biomedical terms is the the National Library of Medicine's Unified Medical Language System (UMLS). The UMLS contains more than 2 million biomedical terms collected from nearly 100 medical vocabularies. Many of the vocabularies contained in the UMLS carry restrictions on their use, making it impossible to share or distribute UMLS-annotated research data. However, a subset of the UMLS vocabularies, designated Category 0 by UMLS, can be used to annotate and share data sets without violating the UMLS License Agreement. METHODS: The UMLS Category 0 vocabularies can be extracted from the parent UMLS metathesaurus using a Perl script supplied with this article. There are 43 Category 0 vocabularies that can be used freely for research purposes without violating the UMLS License Agreement. Among the Category 0 vocabularies are: MESH (Medical Subject Headings), NCBI (National Center for Bioinformatics) Taxonomy and ICD-9-CM (International Classification of Diseases-9-Clinical Modifiers). RESULTS: The extraction file containing all Category 0 terms and concepts is 72,581,138 bytes in length and contains 1,029,161 terms. The UMLS Metathesaurus MRCON file (January, 2003) is 151,048,493 bytes in length and contains 2,146,899 terms. Therefore the Category 0 vocabularies, in aggregate, are about half the size of the UMLS metathesaurus.A large publicly available listing of 567,921 different medical phrases were automatically coded using the full UMLS metatathesaurus and the Category 0 vocabularies. There were 545,321 phrases with one or more matches against UMLS terms while 468,785 phrases had one or more matches against the Category 0 terms. This indicates that when the two vocabularies are evaluated by their fitness to find at least one term for a medical phrase, the Category 0 vocabularies performed 86% as well as the complete UMLS metathesaurus. CONCLUSION: The Category 0 vocabularies of UMLS constitute a large nomenclature that can be used by biomedical researchers to annotate biomedical data. These annotated data sets can be distributed for research purposes without violating the UMLS License Agreement. These vocabularies may be of particular importance for sharing heterogeneous data from diverse biomedical data sets. The software tools to extract the Category 0 vocabularies are freely available Perl scripts entered into the public domain and distributed with this article.

Algorithms↗

Analysis of the lambdoid prophage element e14 in the E. coli K-12 genome.

BACKGROUND: Many sequenced bacterial genomes harbor phage-like elements or cryptic prophages. These elements have been implicated in pathogenesis, serotype conversion and phage immunity. The e14 element is a defective lambdoid prophage element present at 25 min in the E. coli K-12 genome. This prophage encodes important functional genes such as lit (T4 exclusion), mcrA (modified cytosine restriction activity) and pin (recombinase). RESULTS: Bioinformatic analysis of the e14 prophage sequence shows the modular nature of the e14 element which shares a large part of its sequence with the Shigella flexneri phage SfV. Based on this similarity, the regulatory region including the repressor and Cro proteins and their binding sites were identified. The protein product of b1149 was found to be a fusion of a replication protein and a terminase. The genes b1143, b1151 and b1152 were identified as putative pseudogenes. A number of duplications of the stfE tail fibre gene of the e14 are seen in plasmid p15B. A protein based comparative approach using the COG database as a starting point helped detect lambdoid prophage like elements in a representative set of completely sequenced genomes. CONCLUSIONS: The e14 element was characterized for the function of its encoded genes, the regulatory regions, replication origin and homology with other phage and bacterial sequences. Comparative analysis at nucleotide and protein levels suggest that a number of important phage related functions are missing in the e14 genome including parts of the early left operon, early right operon and late operon. The loss of these genes is the result of at least three major deletions that have occurred on e14 since its integration. A comparative protein level approach using the COG database can be effectively used to detect defective lambdoid prophage like elements in bacterial genomes.

Bacillus subtilis↗

NERVE: new enhanced reverse vaccinology environment.

BACKGROUND: Since a milestone work on Neisseria meningitidis B, Reverse Vaccinology has strongly enhanced the identification of vaccine candidates by replacing several experimental tasks using in silico prediction steps. These steps have allowed scientists to face the selection of antigens from the predicted proteome of pathogens, for which cell culture is difficult or impossible, saving time and money. However, this good example of bioinformatics-driven immunology can be further developed by improving in silico steps and implementing biologist-friendly tools. RESULTS: We introduce NERVE (New Enhanced Reverse Vaccinology Environment), an user-friendly software environment for the in silico identification of the best vaccine candidates from whole proteomes of bacterial pathogens. The software integrates multiple robust and well-known algorithms for protein analysis and comparison. Vaccine candidates are ranked and presented in a html table showing relevant information and links to corresponding primary data. Information concerning all proteins of the analyzed proteome is not deleted along selection steps but rather flows into an SQL database for further mining and analyses. CONCLUSION: After learning from recent years' works in this field and analysing a large dataset, NERVE has been implemented and tuned as the first available tool able to rank a restricted pool (approximately 8-9% of the whole proteome) of vaccine candidates and to show high recall (approximately 75-80%) of known protective antigens. These vaccine candidates are required to be "safe" (taking into account autoimmunity risk) and "easy" for further experimental, high-throughput screening (avoiding possibly not soluble antigens). NERVE is expected to help save time and money in vaccine design and is available as an additional file with this manuscript; updated versions will be available at http://www.bio.unipd.it/molbinfo.

Algorithms↗

Evolution of web services in bioinformatics.

Bioinformaticians have developed large collections of tools to make sense of the rapidly growing pool of molecular biological data. Biological systems tend to be complex and in order to understand them, it is often necessary to link many data sets and use more than one tool. Therefore, bioinformaticians have experimented with several strategies to try to integrate data sets and tools. Owing to the lack of standards for data sets and the interfaces of the tools this is not a trivial task. Over the past few years building services with web-based interfaces has become a popular way of sharing the data and tools that have resulted from many bioinformatics projects. This paper discusses the interoperability problem and how web services are being used to try to solve it, resulting in the evolution of tools with web interfaces from HTML/web form-based tools not suited for automatic workflow generation to a dynamic network of XML-based web services that can easily be used to create pipelines.

Computational Biology↗

Human members of the eukaryotic protein kinase family.

BACKGROUND: Eukaryotic protein kinases (EPKs) constitute one of the largest recognized protein families represented in the human genome. EPKs, which are similar to each other in sequence, structure and biochemical properties, are important players in virtually every signaling pathway involved in normal development and disease. Near completion of projects to sequence the human genome and transcriptome provide an opportunity to identify and perform sequence analysis on a nearly complete set of human EPKs. RESULTS: Publicly available genetic sequence data were searched for human sequences that potentially represent EPK family members. After removal of duplicates, splice variants and pseudogenes, this search yielded 510 sequences with recognizable similarity to the EPK family. Protein sequences of putative EPK catalytic domains identified in the search were aligned, and a phonogram was constructed based on the alignment. Representative sequence records in GenBank were identified, and derived information about gene mapping and nomenclature was summarized. CONCLUSIONS: This work represents a nearly comprehensive census and early bioinformatics overview of the EPKs encoded in the human genome. Evaluation of the sequence relationships between these proteins contributes contextual information that enhances understanding of individual family members. This curation of human EPK sequences provides tools and a framework for the further characterization of this important class of enzymes.

Binding Sites↗

A study of statistical methods for function prediction of protein motifs.

Automatic discovery of new protein motifs (i.e. amino acid patterns) is one of the major challenges in bioinformatics. Several algorithms have been proposed that can extract statistically significant motif patterns from any set of protein sequences. With these methods, one can generate a large set of candidate motifs that may be biologically meaningful. This article examines methods to predict the functions of these candidate motifs. We use several statistical methods: a popularity method, a mutual information method and probabilistic translation models. These methods capture, from different perspectives, the correlations between the matched motifs of a protein and its assigned Gene Ontology terms that characterise the function of the protein. We evaluate these different methods using the known motifs in the InterPro database. Each method is used to rank candidate terms for each motif. We then use the expected mean reciprocal rank to evaluate the performance. The results show that, in general, all these methods perform well, suggesting that they can all be useful for predicting the function of an unknown motif. Among the methods tested, a probabilistic translation model with a popularity prior performs the best.

Algorithms↗

Automated genome sequence analysis and annotation.

MOTIVATION: Large-scale genome projects generate a rapidly increasing number of sequences, most of them biochemically uncharacterized. Research in bioinformatics contributes to the development of methods for the computational characterization of these sequences. However, the installation and application of these methods require experience and are time consuming. RESULTS: We present here an automatic system for preliminary functional annotation of protein sequences that has been applied to the analysis of sets of sequences from complete genomes, both to refine overall performance and to make new discoveries comparable to those made by human experts. The GeneQuiz system includes a Web-based browser that allows examination of the evidence leading to an automatic annotation and offers additional information, views of the results, and links to biological databases that complement the automatic analysis. System structure and operating principles concerning the use of multiple sequence databases, underlying sequence analysis tools, lexical analyses of database annotations and decision criteria for functional assignments are detailed. The system makes automatic quality assessments of results based on prior experience with the underlying sequence analysis tools; overall error rates in functional assignment are estimated at 2.5-5% for cases annotated with highest reliability ('clear' cases). Sources of over-interpretation of results are discussed with proposals for improvement. A conservative definition for reporting 'new findings' that takes account of database maturity is presented along with examples of possible kinds of discoveries (new function, family and superfamily) made by the system. System performance in relation to sequence database coverage, database dynamics and database search methods is analysed, demonstrating the inherent advantages of an integrated automatic approach using multiple databases and search methods applied in an objective and repeatable manner. AVAILABILITY: The GeneQuiz system is publicly available for analysis of protein sequences through a Web server at http://www.sander.ebi.ac. uk/gqsrv/submit

Amino Acid Sequence↗