Molecular Characterization, Sequence Analysis, and Taxonomic Position of Newly Isolated Fish Iridoviruses

AbstractWithin the past decade, iridoviruses have been identified as the causative agents of systemic disease in a variety of commercially and recreationally important fish. Here we examine nine iridoviruses from fish, reptiles, and amphibians and demonstrate that all isolates were more similar to frog virus 3, the type species of the genusRanavirus,than to lymphocystis disease virus, the type species of the genusLymphocystivirus.Comparison of viral protein synthesis profiles, restriction endonuclease digestion patterns, and the amino acid sequence of the major capsid protein indicated that iridoviruses isolated from the same geographic region were similar, if not identical, whereas viruses from different areas were distinct. Moreover, using primers complementary to the conserved major capsid protein, we found that both PCR and RT-PCR successfully amplified virus-specific nucleic acid from all nine isolates. These studies demonstrate that the piscine iridoviruses examined here were members of the genusRanavirus,and suggest that surveys of pathogenic “fish viruses” may need to include neighboring amphibian and reptilian populations. In addition, the results indicate that PCR readily identified vertebrate iridoviruses and suggest that PCR will be useful in the diagnosis of fish disease

Transcriptome Profiling of \u3ci\u3eSaccharomyces cerevisiae\u3c/i\u3e Mutants Lacking C2H2 Zinc Finger Proteins

BackgroundThe budding yeast Saccharomyces cerevisiae is a eukaryotic organism with extensive genetic redundancy. Large-scale gene deletion analysis has shown that over 80% of the ~6200 predicted genes are nonessential and that the functions of 30% of all ORFs remain unclassified, implying that yeast cells can tolerate deletion of a substantial number of individual genes. For example, a class of zinc finger proteins containing C2H2 zinc fingers in tandem arrays of two or three is predicted to be transcription factors; however, seven of the thirty-one predicted genes of this class are nonessential, and their functions are poorly understood. In this study we completed a transcriptomic profiling of three mutants lacking C2H2 zinc finger proteins, ypr013cΔ, ypr015cΔ and ypr013cΔypr015cΔ. ResultsGene expression patterns were remarkably different between wild type and the mutants. The results indicate altered expression of 79 genes in ypr013 cΔ, 185 genes in ypr015 cΔ and 426 genes in the double mutant when compared with that of the wild type strain. More than 80% of the alterations in the double mutants were not observed in either one of the single deletion mutants. Functional categorization based on Munich Information Center for Protein Sequences (MIPS) revealed up-regulation of genes related to transcription and down-regulation of genes involving cell rescue and defense, suggesting a decreased response to stress conditions. Genes related to cell cycle and DNA processing whose expression was affected by single or double deletions were also identified. ConclusionOur results suggest that microarray analysis can define the biological roles of zinc finger proteins with unknown functions and identify target genes that are regulated by these putative transcriptional factors. These findings also suggest that both YPR013C and YPR015C have biological processes in common, in addition to their own regulatory pathways

Transcriptome profiling of Saccharomyces cerevisiae mutants lacking C2H2 zinc finger proteins

<p>Abstract</p> <p>Background</p> <p>The budding yeast <it>Saccharomyces cerevisiae</it> is a eukaryotic organism with extensive genetic redundancy. Large-scale gene deletion analysis has shown that over 80% of the ~6200 predicted genes are nonessential and that the functions of 30% of all ORFs remain unclassified, implying that yeast cells can tolerate deletion of a substantial number of individual genes. For example, a class of zinc finger proteins containing C2H2 zinc fingers in tandem arrays of two or three is predicted to be transcription factors; however, seven of the thirty-one predicted genes of this class are nonessential, and their functions are poorly understood. In this study we completed a transcriptomic profiling of three mutants lacking C2H2 zinc finger proteins, <it>ypr013cΔ,</it><it>ypr015cΔ</it> and <it>ypr013cΔypr015cΔ</it>.</p> <p>Results</p> <p>Gene expression patterns were remarkably different between wild type and the mutants. The results indicate altered expression of 79 genes in<it> ypr013</it>cΔ, 185 genes in <it>ypr015</it>cΔ and 426 genes in the double mutant when compared with that of the wild type strain. More than 80% of the alterations in the double mutants were not observed in either one of the single deletion mutants. Functional categorization based on Munich Information Center for Protein Sequences (MIPS) revealed up-regulation of genes related to transcription and down-regulation of genes involving cell rescue and defense, suggesting a decreased response to stress conditions. Genes related to cell cycle and DNA processing whose expression was affected by single or double deletions were also identified.</p> <p>Conclusion</p> <p>Our results suggest that microarray analysis can define the biological roles of zinc finger proteins with unknown functions and identify target genes that are regulated by these putative transcriptional factors. These findings also suggest that both YPR013C and YPR015C have biological processes in common, in addition to their own regulatory pathways.</p

High-throughput next-generation sequencing technologies foster new cutting-edge computing techniques in bioinformatics

The advent of high-throughput next generation sequencing technologies have fostered enormous potential applications of supercomputing techniques in genome sequencing, epi-genetics, metagenomics, personalized medicine, discovery of non-coding RNAs and protein-binding sites. To this end, the 2008 International Conference on Bioinformatics and Computational Biology (Biocomp) – 2008 World Congress on Computer Science, Computer Engineering and Applied Computing (Worldcomp) was designed to promote synergistic inter/multidisciplinary research and education in response to the current research trends and advances. The conference attracted more than two thousand scientists, medical doctors, engineers, professors and students gathered at Las Vegas, Nevada, USA during July 14–17 and received great success. Supported by International Society of Intelligent Biological Medicine (ISIBM), International Journal of Computational Biology and Drug Design (IJCBDD), International Journal of Functional Informatics and Personalized Medicine (IJFIPM) and the leading research laboratories from Harvard, M.I.T., Purdue, UIUC, UCLA, Georgia Tech, UT Austin, U. of Minnesota, U. of Iowa etc, the conference received thousands of research papers. Each submitted paper was reviewed by at least three reviewers and accepted papers were required to satisfy reviewers' comments. Finally, the review board and the committee decided to select only 19 high-quality research papers for inclusion in this supplement to BMC Genomics based on the peer reviews only. The conference committee was very grateful for the Plenary Keynote Lectures given by: Dr. Brian D. Athey (University of Michigan Medical School), Dr. Vladimir N. Uversky (Indiana University School of Medicine), Dr. David A. Patterson (Member of United States National Academy of Sciences and National Academy of Engineering, University of California at Berkeley) and Anousheh Ansari (Prodea Systems, Space Ambassador). The theme of the conference to promote synergistic research and education has been achieved successfully

Identification of plasma lipid biomarkers for prostate cancer by lipidomics and bioinformatics

Background: Lipids have critical functions in cellular energy storage, structure and signaling. Many individual lipid molecules have been associated with the evolution of prostate cancer; however, none of them has been approved to be used as a biomarker. The aim of this study is to identify lipid molecules from hundreds plasma apparent lipid species as biomarkers for diagnosis of prostate cancer. Methodology/Principal Findings: Using lipidomics, lipid profiling of 390 individual apparent lipid species was performed on 141 plasma samples from 105 patients with prostate cancer and 36 male controls. High throughput data generated from lipidomics were analyzed using bioinformatic and statistical methods. From 390 apparent lipid species, 35 species were demonstrated to have potential in differentiation of prostate cancer. Within the 35 species, 12 were identified as individual plasma lipid biomarkers for diagnosis of prostate cancer with a sensitivity above 80%, specificity above 50% and accuracy above 80%. Using top 15 of 35 potential biomarkers together increased predictive power dramatically in diagnosis of prostate cancer with a sensitivity of 93.6%, specificity of 90.1% and accuracy of 97.3%. Principal component analysis (PCA) and hierarchical clustering analysis (HCA) demonstrated that patient and control populations were visually separated by identified lipid biomarkers. RandomForest and 10-fold cross validation analyses demonstrated that the identified lipid biomarkers were able to predict unknown populations accurately, and this was not influenced by patient's age and race. Three out of 13 lipid classes, phosphatidylethanolamine (PE), ether-linked phosphatidylethanolamine (ePE) and ether-linked phosphatidylcholine (ePC) could be considered as biomarkers in diagnosis of prostate cancer. Conclusions/Significance: Using lipidomics and bioinformatic and statistical methods, we have identified a few out of hundreds plasma apparent lipid molecular species as biomarkers for diagnosis of prostate cancer with a high sensitivity, specificity and accuracy

A revision of the genus Tylopsis Fieber (Orthoptera: Tettigoniidae)

Volume: 15Start Page: 297End Page: 32

Quantification of Small Extracellular Vesicles by Size Exclusion Chromatography with Fluorescence Detection

Chemical analysis of small extracellular vesicles (sEVs) circulating in body fluids holds potentials in noninvasive diagnosis of diseases and evaluation of therapeutic treatments. However, quantification of sEVs remains a challenge due to lacking of cost-effective analytical protocols. Herein we report a facile method based on size exclusion chromatography with fluorescence detection (SEC-FD) for sEVs quantification. After removal of cells and cell debris, a 0.50 mL sample (e.g., cell culture medium) is incubated with CM-Dil dye to fluorescently label sEVs. The incubation solution is then separated on a SEC column packed with Sepharose CL-4B. The eluent is monitored fluorescently at Ex553 nm/Em570 nm by using a fluorometer equipped with a 50-μL flow through cuvette. Separation efficiency of the proposed SEC-FD method was evaluated by analyzing 100 nm liposomes and albumin-FITC conjugate. Liposomes were eluted out in less than 6 min, about 10 min before albumin-FITC. A separation repeatability (RSD in retention time) of 1.4% (<i>n</i> = 5) was obtained for liposomes. In analysis of cell culture media, linear calibration curves based on SEC-FD peak height versus sEVs concentration were obtained with <i>r</i>² value of 0.996. Intraday quantification repeatability (RSD in peak height) was 3.2% (<i>n</i> = 5). The detection limit was estimated to be 2.9 × 10⁷ exosome particles/mL. The proposed assay was applied to the first study of sEVs secretion from TK6 cells cultured in serum-free medium for a culturing period from 1 to 48 h

Effect of multiple individual lipid species in diagnosis of prostate cancer.

<p>The points indicated by the two head arrows are the predictive powers of top 15 plasma apparent lipid species when they are used together in diagnosis of prostate cancer. Using top 15 plasma apparent lipid species has the highest sensitivity (93.6%), the highest specificity (90.1%), and higher accuracy (ROC Area, 97.3%) in the diagnosis of prostate cancer as compared with using any other combination of different numbers.</p