Antagonistic bioactivity of an endophytic bacterium H-6

An endophytic bacterium, H-6, was isolated from leaves of Huperzia serrata grown in the Lushan Mountain, China. The strain was identified as Burkholderia sp. H-6 based on morphological, physiological and biochemical methods as well as on 16S rDNA analysis. This strain inhibited mycelium growth in vitro of 6 plant pathogenic fungi, especially of Phytophthora capsici, Fusarium graminearumt and Sclerotinia libertiana. In greenhouse pot experiments, soil drenches with cell densities of 106, 108 and 1010 CFU ml-1 H-6 reduced significantly P. capsici, in pepper seedling by 51.7, 58.7 and 60.2%, respectively, compared to the inoculated control, 3 weeks after sowing. Growth parameters such as lengths and fresh weights of roots and shoots of P. capsici-inoculated control plants were significantly lower compared to P. capsici-inoculated and H-6-treated plants, which is an added advantage of the strain used as potential biocontrol agent in future.Key words: Endophytic bacterium, 16S rDNA gene, antagonistic activity, Huperzia serrata

Observation of a ppb mass threshoud enhancement in \psi^\prime\to\pi^+\pi^-J/\psi(J/\psi\to\gamma p\bar{p}) decay

The decay channel $\psi^\prime\to\pi^+\pi^-J/\psi(J/\psi\to\gamma p\bar{p})$ is studied using a sample of $1.06\times 10^8$ $\psi^\prime$ events collected by the BESIII experiment at BEPCII. A strong enhancement at threshold is observed in the $p\bar{p}$ invariant mass spectrum. The enhancement can be fit with an $S$-wave Breit-Wigner resonance function with a resulting peak mass of $M=1861^{+6}_{-13} {\rm (stat)}^{+7}_{-26} {\rm (syst)} {\rm MeV/}c^2$ and a narrow width that is $\Gamma<38 {\rm MeV/}c^2$ at the 90% confidence level. These results are consistent with published BESII results. These mass and width values do not match with those of any known meson resonance.Comment: 5 pages, 3 figures, submitted to Chinese Physics

Preclinical evaluation of transcriptional targeting strategies for carcinoma of the breast in a tissue slice model system

INTRODUCTION: In view of the limited success of available treatment modalities for metastatic breast cancer, alternative and complementary strategies need to be developed. Adenoviral vector mediated strategies for breast cancer gene therapy and virotherapy are a promising novel therapeutic platform for the treatment of breast cancer. However, the promiscuous tropism of adenoviruses (Ads) is a major concern. Employing tissue specific promoters (TSPs) to restrict transgene expression or viral replication is an effective way to increase specificity towards tumor tissues and to reduce adverse effects in non-target tissues such as the liver. In this regard, candidate breast cancer TSPs include promoters of the genes for the epithelial glycoprotein 2 (EGP-2), cyclooxygenase-2 (Cox-2), α-chemokine SDF-1 receptor (stromal-cell-derived factor, CXCR4), secretory leukoprotease inhibitor (SLPI) and survivin. METHODS: We employed E1-deleted Ads that express the reporter gene luciferase under the control of the promoters of interest. We evaluated this class of vectors in various established breast cancer cell lines, primary breast cancer cells and finally in the most stringent preclinical available substrate system, constituted by precision cut tissue slices of human breast cancer and liver. RESULTS: Overall, the CXCR4 promoter exhibited the highest luciferase activity in breast cancer cell lines, primary breast cancer cells and breast cancer tissue slices. Importantly, the CXCR4 promoter displayed a very low activity in human primary fibroblasts and human liver tissue slices. Interestingly, gene expression profiles correlated with the promoter activities both in breast cancer cell lines and primary breast cancer cells. CONCLUSION: These data suggest that the CXCR4 promoter has an ideal 'breast cancer-on/liver-off' profile, and could, therefore, be a powerful tool in Ad vector based gene therapy or virotherapy of the carcinoma of the breast

Conditionally Replicating Adenovirus Expressing TIMP2 Increases Survival in a Mouse Model of Disseminated Ovarian Cancer

Ovarian cancer remains difficult to treat mainly due to presentation of the disease at an advanced stage. Conditionally-replicating adenoviruses (CRAds) are promising anti-cancer agents that selectively kill the tumor cells. The present study evaluated the efficacy of a novel CRAd (Ad5/3-CXCR4-TIMP2) containing the CXCR4 promoter for selective viral replication in cancer cells together with TIMP2 as a therapeutic transgene, targeting the matrix metalloproteases (MMPs) in a murine orthotopic model of disseminated ovarian cancer. An orthotopic model of ovarian cancer was established in athymic nude mice by intraperitonal injection of the human ovarian cancer cell line, SKOV3-Luc, expressing luciferase. Upon confirmation of peritoneal dissemination of the cells by non-invasive imaging, mice were randomly divided into four treatment groups: PBS, Ad-ΔE1-TIMP2, Ad5/3-CXCR4, and Ad5/3-CXCR4-TIMP2. All mice were imaged weekly to monitor tumor growth and were sacrificed upon reaching any of the predefined endpoints, including high tumor burden and significant weight loss along with clinical evidence of pain and distress. Survival analysis was performed using the Log-rank test. The median survival for the PBS cohort was 33 days; for Ad-ΔE1-TIMP2, 39 days; for Ad5/3-CXCR4, 52.5 days; and for Ad5/3-CXCR4-TIMP2, 63 days. The TIMP2-armed CRAd delayed tumor growth and significantly increased survival when compared to the unarmed CRAd. This therapeutic effect was confirmed to be mediated through inhibition of MMP9. Results of the in vivo study support the translational potential of Ad5/3-CXCR4-TIMP2 for treatment of human patients with advanced ovarian cancer

The N-terminus of FILIA Forms an Atypical KH Domain with a Unique Extension Involved in Interaction with RNA

FILIA is a member of the recently identified oocyte/embryo expressed gene family in eutherian mammals, which is characterized by containing an N-terminal atypical KH domain. Here we report the structure of the N-terminal fragment of FILIA (FILIA-N), which represents the first reported three-dimensional structure of a KH domain in the oocyte/embryo expressed gene family of proteins. The structure of FILIA-N revealed a unique N-terminal extension beyond the canonical KH region, which plays important roles in interaction with RNA. By co-incubation with the lysates of mice ovaries, FILIA and FILIA-N could sequester specific RNA components, supporting the critical roles of FILIA in regulation of RNA transcripts during mouse oogenesis and early embryogenesis

Foundations of Black Hole Accretion Disk Theory

This review covers the main aspects of black hole accretion disk theory. We begin with the view that one of the main goals of the theory is to better understand the nature of black holes themselves. In this light we discuss how accretion disks might reveal some of the unique signatures of strong gravity: the event horizon, the innermost stable circular orbit, and the ergosphere. We then review, from a first-principles perspective, the physical processes at play in accretion disks. This leads us to the four primary accretion disk models that we review: Polish doughnuts (thick disks), Shakura-Sunyaev (thin) disks, slim disks, and advection-dominated accretion flows (ADAFs). After presenting the models we discuss issues of stability, oscillations, and jets. Following our review of the analytic work, we take a parallel approach in reviewing numerical studies of black hole accretion disks. We finish with a few select applications that highlight particular astrophysical applications: measurements of black hole mass and spin, black hole vs. neutron star accretion disks, black hole accretion disk spectral states, and quasi-periodic oscillations (QPOs).Comment: 91 pages, 23 figures, final published version available at http://www.livingreviews.org/lrr-2013-

Network Analysis Identifies ELF3 as a QTL for the Shade Avoidance Response in Arabidopsis

Quantitative Trait Loci (QTL) analyses in immortal populations are a powerful method for exploring the genetic mechanisms that control interactions of organisms with their environment. However, QTL analyses frequently do not culminate in the identification of a causal gene due to the large chromosomal regions often underlying QTLs. A reasonable approach to inform the process of causal gene identification is to incorporate additional genome-wide information, which is becoming increasingly accessible. In this work, we perform QTL analysis of the shade avoidance response in the Bayreuth-0 (Bay-0, CS954) x Shahdara (Sha, CS929) recombinant inbred line population of Arabidopsis. We take advantage of the complex pleiotropic nature of this trait to perform network analysis using co-expression, eQTL and functional classification from publicly available datasets to help us find good candidate genes for our strongest QTL, SAR2. This novel network analysis detected EARLY FLOWERING 3 (ELF3; AT2G25930) as the most likely candidate gene affecting the shade avoidance response in our population. Further genetic and transgenic experiments confirmed ELF3 as the causative gene for SAR2. The Bay-0 and Sha alleles of ELF3 differentially regulate developmental time and circadian clock period length in Arabidopsis, and the extent of this regulation is dependent on the light environment. This is the first time that ELF3 has been implicated in the shade avoidance response and that different natural alleles of this gene are shown to have phenotypic effects. In summary, we show that development of networks to inform candidate gene identification for QTLs is a promising technique that can significantly accelerate the process of QTL cloning

Derivation of a Triple Mosaic Adenovirus for Cancer Gene Therapy

A safe and efficacious cancer medicine is necessary due to the increasing population of cancer patients whose particular diseases cannot be cured by the currently available treatment. Adenoviral (Ad) vectors represent a promising therapeutic medicine for human cancer therapy. However, several improvements are needed in order for Ad vectors to be effective cancer therapeutics, which include, but are not limited to, improvement of cellular uptake, enhanced cancer cell killing activity, and the capability of vector visualization and tracking once injected into the patients. To this end, we attempted to develop an Ad as a multifunctional platform incorporating targeting, imaging, and therapeutic motifs. In this study, we explored the utility of this proposed platform by generating an Ad vector containing the poly-lysine (pK), the herpes simplex virus type 1 (HSV-1) thymidine kinase (TK), and the monomeric red fluorescent protein (mRFP1) as targeting, tumor cell killing, and imaging motifs, respectively. Our study herein demonstrates the generation of the triple mosaic Ad vector with pK, HSV-1 TK, and mRFP1 at the carboxyl termini of Ad minor capsid protein IX (pIX). In addition, the functionalities of pK, HSV-1 TK, and mRFP1 proteins on the Ad vector were retained as confirmed by corresponding functional assays, indicating the potential multifunctional application of this new Ad vector for cancer gene therapy. The validation of the triple mosaic Ad vectors also argues for the ability of pIX modification as a base for the development of multifunctional Ad vectors

Moving toward a system genetics view of disease

Testing hundreds of thousands of DNA markers in human, mouse, and other species for association to complex traits like disease is now a reality. However, information on how variations in DNA impact complex physiologic processes flows through transcriptional and other molecular networks. In other words, DNA variations impact complex diseases through the perturbations they cause to transcriptional and other biological networks, and these molecular phenotypes are intermediate to clinically defined disease. Because it is also now possible to monitor transcript levels in a comprehensive fashion, integrating DNA variation, transcription, and phenotypic data has the potential to enhance identification of the associations between DNA variation and diseases like obesity and diabetes, as well as characterize those parts of the molecular networks that drive these diseases. Toward that end, we review methods for integrating expression quantitative trait loci (eQTLs), gene expression, and clinical data to infer causal relationships among gene expression traits and between expression and clinical traits. We further describe methods to integrate these data in a more comprehensive manner by constructing coexpression gene networks that leverage pairwise gene interaction data to represent more general relationships. To infer gene networks that capture causal information, we describe a Bayesian algorithm that further integrates eQTLs, expression, and clinical phenotype data to reconstruct whole-gene networks capable of representing causal relationships among genes and traits in the network. These emerging network approaches, aimed at processing high-dimensional biological data by integrating data from multiple sources, represent some of the first steps in statistical genetics to identify multiple genetic perturbations that alter the states of molecular networks and that in turn push systems into disease states. Evolving statistical procedures that operate on networks will be critical to extracting information related to complex phenotypes like disease, as research goes beyond a single-gene focus. The early successes achieved with the methods described herein suggest that these more integrative genomics approaches to dissecting disease traits will significantly enhance the identification of key drivers of disease beyond what could be achieved by genetic association studies alone