Developing an NLP and IR-based algorithm for analyzing gene-disease relationships.

OBJECTIVES: High-throughput techniques such as cDNA microarray, oligonucleotide arrays, and serial analysis of gene expression (SAGE) have been developed and used to automatically screen huge amounts of gene expression data. However, researchers usually spend lots of time and money on discovering gene-disease relationships by utilizing these techniques. We prototypically implemented an algorithm that can provide some kind of predicted results for biological researchers before they proceed with experiments, and it is very helpful for them to discover gene-disease relationships more efficiently. METHODS: Due to the fast development of computer technology, many information retrieval techniques have been applied to analyze huge digital biomedical databases available worldwide. Therefore we highly expect that we can apply information retrieval (IR) technique to extract useful information for the relationship of specific diseases and genes from MEDLINE articles. Furthermore, we also applied natural language processing (NLP) methods to do the semantic analysis for the relevant articles to discover the relationships between genes and diseases. RESULTS: We have extracted gene symbols from our literature collection according to disease MeSH classifications. We have also built an IR-based retrieval system, "Biomedical Literature Retrieval System (BLRS)" and applied the N-gram model to extract the relationship features which can reveal the relationship between genes and diseases. Finally, a relationship network of a specific disease has been built to represent the gene-disease relationships. CONCLUSIONS: A relationship feature is a functional word that can reveal the relationship between one single gene and a disease. By incorporating many modern IR techniques, we found that BLRS is a very powerful information discovery tool for literature searching. A relationship network which contains the information on gene symbol, relationship feature, and disease MeSH term can provide an integrated view to discover gene-disease relationships.

Potentiation of thyrotropin-releasing hormone-stimulated prolactin mRNA levels in GH3 cells by acetylcholine.

We have examined the effect of acetylcholine (ACh) pretreatment on the thyrotropin-releasing hormone (TRH) induced prolactin gene expression in GH3 cells, a rat pituitary tumor cell line. Prolonged exposure (greater than 6 h) to ACh enhanced the TRH-induced prolactin mRNA accumulation in a time- and concentration-dependent manner while ACh by itself did not affect the basal prolactin mRNA levels appreciably. Maximal augmentation of the TRH-induced prolactin mRNA accumulation was obtained when cells were pretreated with 10(-5) M ACh for 24 h. The activation was mimicked by carbachol and oxotremorine and was blocked by the simultaneous presence of atropine. Preincubation of GH3 cells with pertussis toxin abolished the augmenting effect of ACh. These results indicate that prolonged exposure to muscarinic receptor agonists may enhance the TRH-stimulated prolactin mRNA expression and a pertussis toxin sensitive G-protein may be involved.

Expression of c-myc proto-oncogene during podophyllotoxin induced IW32 erythroleukemia cell differentiation.

The effect of hemin or podophyllotoxin on the differentiation of the erythropoietin (epo)-producing IW32 erythroleukemia cells was investigated. Podophyllotoxin induced IW32 cells to differentiate, and hemin potentiated the differentiation. Hemin had no effect on cell proliferation whereas podophyllotoxin inhibited cell growth. c-myc mRNA levels decreased biphasically by hemin or podophyllotoxin, while the combined treatment of hemin plus podophyllotoxin did not result in the initial decrease in c-myc mRNA level. Our data suggested that down-regulation of c-myc expression was not a prerequisite of IW32 cell differentiation induced by hemin and podophyllotoxin combined.

Nucleotide sequence of a novel arylesterase gene from Vibro mimicus and characterization of the enzyme expressed in Escherichia coli.

A gene coding for an arylesterase of Vibrio mimicus was cloned. Sequence determination reveals that the esterase gene has an open reading frame of 600 nucleotides which encodes a protein of M(r) 22,300. The deduced amino acid sequence contain a pentapeptide GDSLS (residues 27-31), which was also found in the phospholipid-cholesterol acyltransferase from Aeromonas hydrophila. Substitution of Ser-29 by alanine or cysteine in the cloned gene abolished the esterase activity in the tributyrin plate assay. On the other hand, the activity was not lost when Ser-31 was changed to alanine. The cloned gene was expressed in Escherichia coli, and the protein purified by a four-step procedure. The purified protein migrated on SDS/PAGE as a single band with an apparent M(r) of 22,100. This enzyme favoured the hydrolysis of several arylesters and was classified as an arylesterase (EC 3.1.1.2). N-Terminal analysis showed that Ser-20 was the first amino acid of the mature secreted protein, suggesting that the N-terminal 19 hydrophobic amino acids served as a signal peptide.