ABSTRACT
Herein, an efficient strategy is demonstrated to prepare a visible-light-driven Nb/Se co-doped BiOI photocatalyst with exposed (110) facets. The results show that its photocatalytic activity is around 17 times higher than that of pure BiOI. This work paves the way towards the fabrication of efficient photocatalysts that have tunable charge dynamics.
ABSTRACT
Examining global effects of toxins on gene expression profiles is proving to be a powerful method for toxicity assessment and for investigating mechanisms of toxicity. This study demonstrated the application of prokaryotic real-time gene expression profiling in Escherichia coli for toxicity assessment of environmental pollutants in water samples, by use of a cell-array library of 93 E. coli K12 strains with transcriptional green fluorescent protein (GFP) fusions covering most known stress response genes. The high-temporal-resolution gene expression data, for the first time, revealed complex and time-dependent transcriptional activities of various stress-associated genes in response to mercury and mitomycin (MMC) exposure and allowed for gene clustering analysis based on temporal response patterns. Compound-specific and distinctive gene expression profiles were obtained for MMC and mercury at different concentrations. MMC (genotoxin) induced not only the SOS response, which regulates DNA damage and repair, but also many other stress genes associated with drug resistance/sensitivity and chemical detoxification. A number of genes belonging to the P-type ATPase family and the MerR family were identified to be related to mercury resistance, among which zntA was found to be up-regulated at an increasing level as the mercury concentration increased. A mechanism-based evaluation of toxins based on real-time gene expression profiles promises, to be an efficient and informative method for toxicity assessment in environmental samples.
Subject(s)
Escherichia coli K12/drug effects , Escherichia coli Proteins/metabolism , Gene Expression Profiling , Gene Expression Regulation, Bacterial/physiology , Mercury/toxicity , Mitomycin/toxicity , Antibiotics, Antineoplastic/toxicity , Dose-Response Relationship, Drug , Environmental Monitoring , Environmental Pollutants/toxicity , Escherichia coli K12/genetics , Escherichia coli K12/metabolism , Escherichia coli Proteins/genetics , Sensitivity and SpecificityABSTRACT
Acheron, a Lupus antigen ortholog, was identified as a novel death-associated transcript from the intersegmental muscles of the moth Manduca sexta. Acheron is phylogenetically-conserved and represents a new sub-family of Lupus antigen proteins. Acheron is expressed predominantly in neurons and muscle in vertebrates, and regulates several developmental events including myogenesis, neurogenesis and possibly metastasis. Using Acheron as bait, we performed a yeast two-hybrid screen with a mouse embryo cDNA library and identified CASK-C, a novel CASK/Lin-2 isoform, as an Acheron binding partner. Acheron and CASK-C bind via the C-terminus of Acheron and the CaMKII-like domain of CASK-C. Co-immunoprecipitation assays verify this interaction and demonstrate that Acheron also forms a complex with all members of the Id (inhibitor of differentiation) proteins. Taken together, these data suggest a mechanism by which Acheron may regulate development and pathology.
Subject(s)
Autoantigens/metabolism , Guanylate Kinases/metabolism , Inhibitor of Differentiation Proteins/metabolism , Ribonucleoproteins/metabolism , Amino Acid Sequence , Animals , Guanylate Kinases/chemistry , Humans , Inhibitor of Differentiation Proteins/chemistry , Insect Proteins/metabolism , Molecular Sequence Data , Moths/chemistry , Protein Structure, Tertiary , Sequence Alignment , Two-Hybrid System Techniques , SS-B AntigenABSTRACT
[This corrects the article DOI: 10.2478/s11658-008-0046-1.].
ABSTRACT
High-throughput technologies, such as proteomic screening and DNA micro-arrays, produce vast amounts of data requiring comprehensive analytical methods to decipher the biologically relevant results. One approach would be to manually search the biomedical literature; however, this would be an arduous task. We developed an automated literature-mining tool, termed MedGene, which comprehensively summarizes and estimates the relative strengths of all human gene-disease relationships in Medline. Using MedGene, we analyzed a novel micro-array expression dataset comparing breast cancer and normal breast tissue in the context of existing knowledge. We found no correlation between the strength of the literature association and the magnitude of the difference in expression level when considering changes as high as 5-fold; however, a significant correlation was observed (r = 0.41; p = 0.05) among genes showing an expression difference of 10-fold or more. Interestingly, this only held true for estrogen receptor (ER) positive tumors, not ER negative. MedGene identified a set of relatively understudied, yet highly expressed genes in ER negative tumors worthy of further examination.
