Disclosing ambiguous gene aliases by automatic literature profiling

Submitted by Nuzia Santos ([email protected]) on 2015-01-14T10:55:18Z No. of bitstreams: 1 Disclosing ambiguous gene aliases by automatic.pdf: 217573 bytes, checksum: ce54aa2c4ea49eb989f9e7308d827ce6 (MD5)Approved for entry into archive by Nuzia Santos ([email protected]) on 2015-01-14T10:55:25Z (GMT) No. of bitstreams: 1 Disclosing ambiguous gene aliases by automatic.pdf: 217573 bytes, checksum: ce54aa2c4ea49eb989f9e7308d827ce6 (MD5)Approved for entry into archive by Nuzia Santos ([email protected]) on 2015-01-14T11:01:59Z (GMT) No. of bitstreams: 1 Disclosing ambiguous gene aliases by automatic.pdf: 217573 bytes, checksum: ce54aa2c4ea49eb989f9e7308d827ce6 (MD5)Made available in DSpace on 2015-01-14T11:01:59Z (GMT). No. of bitstreams: 1 Disclosing ambiguous gene aliases by automatic.pdf: 217573 bytes, checksum: ce54aa2c4ea49eb989f9e7308d827ce6 (MD5) Previous issue date: 2010Fundação Oswaldo Cruz. Centro de Pesquisa René Rachou. Centro de Excelência em Bioinformática. Belo Horizonte, MG, Brasil/Fundação Oswaldo Cruz. Centro de Pesquisa René Rachou. Grupo de Genômica e Biologia Computacional. Belo Horizonte, MG, BrasilGlaxoSmithKline Moore Dr. Molecular Discovery Research. Research Triangle Park, NC, USAFundação Oswaldo Cruz. Centro de Pesquisa René Rachou. Centro de Excelência em Bioinformática. Belo Horizonte, MG, Brasil/Fundação Oswaldo Cruz. Centro de Pesquisa René Rachou. Grupo de Genômica e Biologia Computacional. Belo Horizonte, MG, BrasilBackground Retrieving pertinent information from biological scientific literature requires cutting-edge text mining methods which may be able to recognize the meaning of the very ambiguous names of biological entities. Aliases of a gene share a common vocabulary in their respective collections of PubMed abstracts. This may be true even when these aliases are not associated with the same subset of documents. This gene-specific vocabulary defines a unique fingerprint that can be used to disclose ambiguous aliases. The present work describes an original method for automatically assessing the ambiguity levels of gene aliases in large gene terminologies based exclusively in the content of their associated literature. The method can deal with the two major problems restricting the usage of current text mining tools: 1) different names associated with the same gene; and 2) one name associated with multiple genes, or even with non-gene entities. Important, this method does not require training examples. Results Aliases were considered “ambiguous” when their Jaccard distance to the respective official gene symbol was equal or greater than the smallest distance between the official gene symbol and one of the three internal controls (randomly picked unrelated official gene symbols). Otherwise, they were assigned the status of “synonyms”. We evaluated the coherence of the results by comparing the frequencies of the official gene symbols in the text corpora retrieved with their respective “synonyms” or “ambiguous” aliases. Official gene symbols were mentioned in the abstract collections of 42 % (70/165) of their respective synonyms. No official gene symbol occurred in the abstract collections of any of their respective ambiguous aliases. In overall, querying PubMed with official gene symbols and “synonym” aliases allowed a 3.6-fold increase in the number of unique documents retrieved. Conclusions These results confirm that this method is able to distinguish between synonyms and ambiguous gene aliases based exclusively on their vocabulary fingerprint. The approach we describe could be used to enhance the retrieval of relevant literature related to a gen

Inhibition of the kynurenine-NAD+ pathway leads to energy failure and exacerbates apoptosis in pneumococcal meningitis

Pneumococcal meningitis causes neurological sequelae, including learning and memory deficits in up to half of the survivors. In both humans and in animal models of the disease, there is apoptotic cell death in the hippocampus, a brain region involved in learning and memory function. We previously demonstrated that in an infant rat model of pneumococcal meningitis, there is activation of the kynurenine (KYN) pathway in the hippocampus, and that there was a positive correlation between the concentration of 3-hydroxykynurenine and the extent of hippocampal apoptosis. To clarify the role of the KYN pathway in the pathogenesis of hippocampal apoptosis in pneumococcal meningitis, we specifically inhibited 2 key enzymes of the KYN pathway and assessed hippocampal apoptosis, KYN pathway metabolites, and nicotinamide adenine dinucleotide (NAD) concentrations by high-performance liquid chromatography. Pharmacological inhibition of kynurenine 3-hydroxylase and kynureninase led to decreased cellular NAD levels and increased apoptosis in the hippocampus. The cerebrospinal fluid levels of tumor necrosis factor and interleukin-1? and -? were not affected. Our data suggest that activation of the KYN pathway in pneumococcal meningitis is neuroprotective by compensating for an increased NAD demand caused by infection and inflammation;this mechanism may prevent energy failure and apoptosis in the hippocampus

Pneumococcal meningitis causes accumulation of neurotoxic kynurenine metabolites in brain regions prone to injury

Pneumococcal meningitis (PM) is characterized by an intense inflammatory host reaction that contributes to the development of cortical necrosis and hippocampal apoptosis. Inflammatory conditions in the brain are known to induce tryptophan degradation along the kynurenine pathway, resulting in accumulation of neurotoxic metabolites. In the present study, we investigated the contribution of the kynurenine pathway to brain injury in experimental PM by measuring the concentration of its metabolites and the enzymatic activities and mRNA levels of its major enzymes in the vulnerable brain regions. In the late phase of acute PM, we found a significant transcriptional upregulation of kynurenine-3-hydroxylase and an accumulation of the neurotoxic metabolites 3-hydroxykynurenine (3-HKYN) and 3-hydroxyanthranilic acid in cortex and hippocampus. The positive correlation between the concentration of 3-HKYN and the extent of hippocampal apoptosis adds support to the concept that 3-HKYN contributes to brain injury in PM

MST (Molecular Serotyping Tool): a Program for Computer-Assisted Molecular Identification of Escherichia coli and Shigella O Antigens▿

Escherichia coli and Shigella O antigens can be inferred using the rfb-restriction fragment length polymorphism (RFLP) molecular test. We present herein a dynamic programming algorithm-based software to compare the rfb-RFLP patterns of clinical isolates with those in a database containing the 171 previously published patterns corresponding to all known E. coli/Shigella O antigens

Automatic Assignment of Prokaryotic Genes to Functional Categories Using Literature Profiling

<div><p>In the last years, there was an exponential increase in the number of publicly available genomes. Once finished, most genome projects lack financial support to review annotations. A few of these gene annotations are based on a combination of bioinformatics evidence, however, in most cases, annotations are based solely on sequence similarity to a previously known gene, which was most probably annotated in the same way. As a result, a large number of predicted genes remain unassigned to any functional category despite the fact that there is enough evidence in the literature to predict their function. We developed a classifier trained with term-frequency vectors automatically disclosed from text <em>corpora</em> of an ensemble of genes representative of each functional category of the J. Craig Venter Institute Comprehensive Microbial Resource (JCVI-CMR) ontology. The classifier achieved up to 84% precision with 68% recall (for confidence≥0.4), F-measure 0.76 (recall and precision equally weighted) in an independent set of 2,220 genes, from 13 bacterial species, previously classified by JCVI-CMR into unambiguous categories of its ontology. Finally, the classifier assigned (confidence≥0.7) to functional categories a total of 5,235 out of the ∼24 thousand genes previously in categories “Unknown function” or “Unclassified” for which there is literature in MEDLINE. Two biologists reviewed the literature of 100 of these genes, randomly picket, and assigned them to the same functional categories predicted by the automatic classifier. Our results confirmed the hypothesis that it is possible to confidently assign genes of a real world repository to functional categories, based exclusively on the automatic profiling of its associated literature. The LitProf - Gene Classifier web server is accessible at: <a href="http://www.cebio.org/litprofGC">www.cebio.org/litprofGC</a>.</p> </div

Gene and protein expression of galectin-3 and galectin-9 in experimental pneumococcal meningitis

Inflammation of the subarachnoid and ventricular space contributes to the development of brain damage i.e. cortical necrosis and hippocampal apoptosis in pneumococcal meningitis (PM). Galectin-3 and -9 are known pro-inflammatory mediators and regulators of apoptosis. Here, the gene and protein expression profile for both galectins was assessed in the disease progression of PM. The mRNA of Lgals3 and Lgals9 increased continuously in the cortex and in the hippocampus from 22 h to 44 h after infection. At 44 h after infection, mRNA levels of Lgals9 in the hippocampus were 7-fold and those of Lgals3 were 30-fold higher than in uninfected controls (P<0.01). Galectin-9 protein did not change, but galectin-3 significantly increased in cortex and hippocampus with the duration of PM. Galectin-3 was localized to polymorphonuclear neutrophils, microglia, monocytes and macrophages, suggesting an involvement of galectin-3 in the neuroinflammatory processes leading to brain damage in PM

Examples of genes classified by LitProf- Gene Classifier and further validated by manually reviewing their literature.

*<p>The GO terms from Biological Process, Molecular Function and Cellular Component ontologies associated with each gene in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0047436#pone-0047436-t004" target="_blank">table 4</a> (or, in most cases, their prokaryotic orthologs) were retrieved from AmiGO (<a href="http://amigo.geneontology.org" target="_blank">http://amigo.geneontology.org</a>) by querying the database with their canonical gene names. In most cases the GO terms retrieved supported the functional categorization predicted by LitProf – Gene Classifier, although there is not an exact correspondence between GO and JCVI-CMR ontologies. Six gene names out 16 tested had no match in AmiGO.</p

Taxonomy distribution of genes in the training dataset.

<p>Taxonomy distribution of genes in the training dataset.</p