Human Papillomavirus 16 E5 Induces Bi-Nucleated Cell Formation By Cell-Cell Fusion

Human Papillomaviruses (HPV) 16 is a DNA virus encoding three oncogenes – E5, E6, and E7. The E6 and E7 proteins have well-established roles as inhibitors of tumor suppression, but the contribution of E5 to malignant transformation is controversial. Using spontaneously immortalized human keratinocytes (HaCaT cells), we demonstrate that expression of HPV16 E5 is necessary and sufficient for the formation of bi-nucleated cells, a common characteristic of precancerous cervical lesions. Expression of E5 from non-carcinogenic HPV6b does not produce bi-nucleate cells. Video microscopy and biochemical analyses reveal that bi-nucleates arise through cell-cell fusion. Although most E5-induced bi-nucleates fail to propagate, co-expression of HPV16 E6/E7 enhances the proliferation of these cells. Expression of HPV16 E6/E7 also increases bi-nucleated cell colony formation. These findings identify a new role for HPV16 E5 and support a model in which complementary roles of the HPV16 oncogenes lead to the induction of carcinogenesis

The First Illumina-Based De Novo Transcriptome Sequencing and Analysis of Safflower Flowers

BACKGROUND: The safflower, Carthamus tinctorius L., is a worldwide oil crop, and its flowers, which have a high flavonoid content, are an important medicinal resource against cardiovascular disease in traditional medicine. Because the safflower has a large and complex genome, the development of its genomic resources has been delayed. Second-generation Illumina sequencing is now an efficient route for generating an enormous volume of sequences that can represent a large number of genes and their expression levels. METHODOLOGY/PRINCIPAL FINDINGS: To investigate the genes and pathways that might control flavonoids and other secondary metabolites in the safflower, we used Illumina sequencing to perform a de novo assembly of the safflower tubular flower tissue transcriptome. We obtained a total of 4.69 Gb in clean nucleotides comprising 52,119,104 clean sequencing reads, 195,320 contigs, and 120,778 unigenes. Based on similarity searches with known proteins, we annotated 70,342 of the unigenes (about 58% of the identified unigenes) with cut-off E-values of 10(-5). In total, 21,943 of the safflower unigenes were found to have COG classifications, and BLAST2GO assigned 26,332 of the unigenes to 1,754 GO term annotations. In addition, we assigned 30,203 of the unigenes to 121 KEGG pathways. When we focused on genes identified as contributing to flavonoid biosynthesis and the biosynthesis of unsaturated fatty acids, which are important pathways that control flower and seed quality, respectively, we found that these genes were fairly well conserved in the safflower genome compared to those of other plants. CONCLUSIONS/SIGNIFICANCE: Our study provides abundant genomic data for Carthamus tinctorius L. and offers comprehensive sequence resources for studying the safflower. We believe that these transcriptome datasets will serve as an important public information platform to accelerate studies of the safflower genome, and may help us define the mechanisms of flower tissue-specific and secondary metabolism in this non-model plant

Precision measurements of A1N in the deep inelastic regime

We have performed precision measurements of the double-spin virtual-photon asymmetry A1A1 on the neutron in the deep inelastic scattering regime, using an open-geometry, large-acceptance spectrometer and a longitudinally and transversely polarized 3He target. Our data cover a wide kinematic range 0.277≤x≤0.5480.277≤x≤0.548 at an average Q2Q2 value of 3.078 (GeV/c)2, doubling the available high-precision neutron data in this x range. We have combined our results with world data on proton targets to make a leading-order extraction of the ratio of polarized-to-unpolarized parton distribution functions for up quarks and for down quarks in the same kinematic range. Our data are consistent with a previous observation of anA1n zero crossing near x=0.5x=0.5. We find no evidence of a transition to a positive slope in(Δd+Δd¯)/(d+d¯) up to x=0.548x=0.548

Biological detoxification of the mycotoxin deoxynivalenol and its use in genetically engineered crops and feed additives

Deoxynivalenol (DON) is the major mycotoxin produced by Fusarium fungi in grains. Food and feed contaminated with DON pose a health risk to humans and livestock. The risk can be reduced by enzymatic detoxification. Complete mineralization of DON by microbial cultures has rarely been observed and the activities turned out to be unstable. The detoxification of DON by reactions targeting its epoxide group or hydroxyl on carbon 3 is more feasible. Microbial strains that de-epoxidize DON under anaerobic conditions have been isolated from animal digestive system. Feed additives claimed to de-epoxidize trichothecenes enzymatically are on the market but their efficacy has been disputed. A new detoxification pathway leading to 3-oxo-DON and 3-epi-DON was discovered in taxonomically unrelated soil bacteria from three continents; the enzymes involved remain to be identified. Arabidopsis, tobacco, wheat, barley, and rice were engineered to acetylate DON on carbon 3. In wheat expressing DON acetylation activity, the increase in resistance against Fusarium head blight was only moderate. The Tri101 gene from Fusarium sporotrichioides was used; Fusarium graminearum enzyme which possesses higher activity towards DON would presumably be a better choice. Glycosylation of trichothecenes occurs in plants, contributing to the resistance of wheat to F. graminearum infection. Marker-assisted selection based on the trichothecene-3-O-glucosyltransferase gene can be used in breeding for resistance. Fungal acetyltransferases and plant glucosyltransferases targeting carbon 3 of trichothecenes remain promising candidates for engineering resistance against Fusarium head blight. Bacterial enzymes catalyzing oxidation, epimerization, and less likely de-epoxidation of DON may extend this list in future

The IDENTIFY study: the investigation and detection of urological neoplasia in patients referred with suspected urinary tract cancer - a multicentre observational study

Objective To evaluate the contemporary prevalence of urinary tract cancer (bladder cancer, upper tract urothelial cancer [UTUC] and renal cancer) in patients referred to secondary care with haematuria, adjusted for established patient risk markers and geographical variation. Patients and Methods This was an international multicentre prospective observational study. We included patients aged ≥16 years, referred to secondary care with suspected urinary tract cancer. Patients with a known or previous urological malignancy were excluded. We estimated the prevalence of bladder cancer, UTUC, renal cancer and prostate cancer; stratified by age, type of haematuria, sex, and smoking. We used a multivariable mixed-effects logistic regression to adjust cancer prevalence for age, type of haematuria, sex, smoking, hospitals, and countries. Results Of the 11 059 patients assessed for eligibility, 10 896 were included from 110 hospitals across 26 countries. The overall adjusted cancer prevalence (n = 2257) was 28.2% (95% confidence interval [CI] 22.3–34.1), bladder cancer (n = 1951) 24.7% (95% CI 19.1–30.2), UTUC (n = 128) 1.14% (95% CI 0.77–1.52), renal cancer (n = 107) 1.05% (95% CI 0.80–1.29), and prostate cancer (n = 124) 1.75% (95% CI 1.32–2.18). The odds ratios for patient risk markers in the model for all cancers were: age 1.04 (95% CI 1.03–1.05; P < 0.001), visible haematuria 3.47 (95% CI 2.90–4.15; P < 0.001), male sex 1.30 (95% CI 1.14–1.50; P < 0.001), and smoking 2.70 (95% CI 2.30–3.18; P < 0.001). Conclusions A better understanding of cancer prevalence across an international population is required to inform clinical guidelines. We are the first to report urinary tract cancer prevalence across an international population in patients referred to secondary care, adjusted for patient risk markers and geographical variation. Bladder cancer was the most prevalent disease. Visible haematuria was the strongest predictor for urinary tract cancer