SalmoNet, an integrated network of ten Salmonella enterica strains reveals common and distinct pathways to host adaptation

Salmonella enterica is a prominent bacterial pathogen with implications on human and animal health. Salmonella serovars could be classified as gastro-intestinal or extra-intestinal. Genome-wide comparisons revealed that extra-intestinal strains are closer relatives of gastro-intestinal strains than to each other indicating a parallel evolution of this trait. Given the complexity of the differences, a systems-level comparison could reveal key mechanisms enabling extra-intestinal serovars to cause systemic infections. Accordingly, in this work, we introduce a unique resource, SalmoNet, which combines manual curation, high-throughput data and computational predictions to provide an integrated network for Salmonella at the metabolic, transcriptional regulatory and protein-protein interaction levels. SalmoNet provides the networks separately for five gastro-intestinal and five extra-intestinal strains. As a multi-layered, multi-strain database containing experimental data, SalmoNet is the first dedicated network resource for Salmonella. It comprehensively contains interactions between proteins encoded in Salmonella pathogenicity islands, as well as regulatory mechanisms of metabolic processes with the option to zoom-in and analyze the interactions at specific loci in more detail. Application of SalmoNet is not limited to strain comparisons as it also provides a Salmonella resource for biochemical network modeling, host-pathogen interaction studies, drug discovery, experimental validation of novel interactions, uncovering new pathological mechanisms from emergent properties and epidemiological studies. SalmoNet is available at http://salmonet.org

In-vivo optical detection of cancer using chlorin e6 – polyvinylpyrrolidone induced fluorescence imaging and spectroscopy

<p>Abstract</p> <p>Background</p> <p>Photosensitizer based fluorescence imaging and spectroscopy is fast becoming a promising approach for cancer detection. The purpose of this study was to examine the use of the photosensitizer chlorin e6 (Ce6) formulated in polyvinylpyrrolidone (PVP) as a potential exogenous fluorophore for fluorescence imaging and spectroscopic detection of human cancer tissue xenografted in preclinical models as well as in a patient.</p> <p>Methods</p> <p>Fluorescence imaging was performed on MGH human bladder tumor xenografted on both the chick chorioallantoic membrane (CAM) and the murine model using a fluorescence endoscopy imaging system. In addition, fiber optic based fluorescence spectroscopy was performed on tumors and various normal organs in the same mice to validate the macroscopic images. In one patient, fluorescence imaging was performed on angiosarcoma lesions and normal skin in conjunction with fluorescence spectroscopy to validate Ce6-PVP induced fluorescence visual assessment of the lesions.</p> <p>Results</p> <p>Margins of tumor xenografts in the CAM model were clearly outlined under fluorescence imaging. Ce6-PVP-induced fluorescence imaging yielded a specificity of 83% on the CAM model. In mice, fluorescence intensity of Ce6-PVP was higher in bladder tumor compared to adjacent muscle and normal bladder. Clinical results confirmed that fluorescence imaging clearly captured the fluorescence of Ce6-PVP in angiosarcoma lesions and good correlation was found between fluorescence imaging and spectral measurement in the patient.</p> <p>Conclusion</p> <p>Combination of Ce6-PVP induced fluorescence imaging and spectroscopy could allow for optical detection and discrimination between cancer and the surrounding normal tissues. Ce6-PVP seems to be a promising fluorophore for fluorescence diagnosis of cancer.</p

Social Relationships and Mortality Risk: A Meta-analytic Review

In a meta-analysis, Julianne Holt-Lunstad and colleagues find that individuals' social relationships have as much influence on mortality risk as other well-established risk factors for mortality, such as smoking

Resistance of Collard Green Genotypes to Bemisia tabaci Biotype B: Characterization of Antixenosis

Bemisia tabaci (Genn.) biotype B (Hemiptera: Aleyrodidae) is an important pest of vegetable crops, including collard greens Brassica oleracea var. acephala (Brassicaceae). The use of resistant genotypes is an interesting option to reduce insect populations and can be used as an important tool for integrated pest management (IPM). This study evaluated 32 genotypes of collard greens against the attack of silver leaf whitefly, with the aim to characterize antixenosis. Initially, a multiple-choice trial was conducted using all genotypes, in which the adult attractiveness was assessed on two leaves per genotype at 24 and 48 h after infestation. After 48 h, one leaf of each genotype was randomly selected for the determination of the number of eggs per square centimeter. From the results of the multiple-choice trial, 13 genotypes were selected for a no-choice oviposition test, following the same method of the previous test. Colorimetric analyses were also performed to establish possible correlations between leaf color and insect colonization. Genotypes HS-20, OE, and VA were less attractive, demonstrating antixenosis. Genotypes LG, VE, J, MG, MOP, HS-20, VA, and MT had less oviposition in the multiple-choice test, which indicated expression of antixenosis. In the no-choice test, genotypes VE, P1C, CCB, RI-919, H, and J had less oviposition, which also characterized antixenosis. Therefore, genotypes VE and J showed the highest resistance stability because both had less oviposition in both test modalities. Thus, the resistance to B. tabaci biotype B indicates the genotypes HS-20, OE, VA, VE, and J are promising for use in breeding programs to develop resistance to whitefly.Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Depto de Proteção Vegetal Fac de Ciências Agronômicas Univ Estadual Paulista (UNESP)Instituto Agronômico Centro de FitossanidadeDepto de Proteção Vegetal Fac de Ciências Agronômicas Univ Estadual Paulista (UNESP)CNPq: 305649/2013-