The Red Flour Beetle as a Model for Bacterial Oral Infections

Experimental infection systems are important for studying antagonistic interactions and coevolution between hosts and their pathogens. The red flour beetle Tribolium castaneum and the spore-forming bacterial insect pathogen Bacillus thuringiensis (Bt) are widely used and tractable model organisms. However, they have not been employed yet as an efficient experimental system to study host-pathogen interactions. We used a high throughput oral infection protocol to infect T. castaneum insects with coleopteran specific B. thuringiensis bv. tenebrionis (Btt) bacteria. We found that larval mortality depends on the dietary spore concentration and on the duration of exposure to the spores. Furthermore, differential susceptibility of larvae from different T. castaneum populations indicates that the host genetic background influences infection success. The recovery of high numbers of infectious spores from the cadavers indicates successful replication of bacteria in the host and suggests that Btt could establish infectious cycles in T. castaneum in nature. We were able to transfer plasmids from Btt to a non-pathogenic but genetically well-characterised Bt strain, which was thereafter able to successfully infect T. castaneum, suggesting that factors residing on the plasmids are important for the virulence of Btt. The availability of a genetically accessible strain will provide an ideal model for more in-depth analyses of pathogenicity factors during oral infections. Combined with the availability of the full genome sequence of T. castaneum, this system will enable analyses of host responses during infection, as well as addressing basic questions concerning host-parasite coevolution

Cancer history and other personal factors affect quality of life in patients with hepatitis C

BACKGROUND: Although patients with chronic hepatitis C (CHC) have been found to have reduced quality of life, little is known about how other characteristics affect their quality of life. The purpose of this study was to investigate the effect of other characteristics, including history of cancer, on quality of life in patients with CHC. METHODS: One hundred forty patients from clinics at three hospitals in New York City completed a detailed epidemiologic interview about demographic and lifestyle characteristics and the SF-36 measuring health-related quality of life. We compared results from our patients to normative data using t-tests of differences between means. We used multivariate analyses to determine other personal and health-related factors associated with quality of life outcomes. RESULTS: Compared to normative data, these patients had reduced quality of life, particularly on physical functioning. The summary Physical Component Score (PCS) was 45.4 ± 10.6 and the Mental Component Score (MCS) was 48.2 ± 11.1, vs norms of 50 ± 10.0; p-values were <0.0001 and <0.05, respectively. In multivariate analyses, the PCS was significantly lower among those with cancer history, ≥ 2 other chronic conditions, less education, low physical activity, and higher alanine aminotransferase (ALT) levels. Cancer was more important for men, while other chronic conditions were more important for women. On the MCS, history of depression, low physical activity, alcohol use, and female gender were independently associated with poorer scores. CONCLUSION: Several health and lifestyle factors independently influence quality of life in CHC patients. Different factors are important for men and women

PILER-CR: Fast and accurate identification of CRISPR repeats

BACKGROUND: Sequencing of prokaryotic genomes has recently revealed the presence of CRISPR elements: short, highly conserved repeats separated by unique sequences of similar length. The distinctive sequence signature of CRISPR repeats can be found using general-purpose repeat- or pattern-finding software tools. However, the output of such tools is not always ideal for studying these repeats, and significant effort is sometimes needed to build additional tools and perform manual analysis of the output. RESULTS: We present PILER-CR, a program specifically designed for the identification and analysis of CRISPR repeats. The program executes rapidly, completing a 5 Mb genome in around 5 seconds on a current desktop computer. We validate the algorithm by manual curation and by comparison with published surveys of these repeats, finding that PILER-CR has both high sensitivity and high specificity. We also present a catalogue of putative CRISPR repeats identified in a comprehensive analysis of 346 prokaryotic genomes. CONCLUSION: PILER-CR is a useful tool for rapid identification and classification of CRISPR repeats. The software is donated to the public domain. Source code and a Linux binary are freely available at

Evaluation of the zucker diabetic fatty (ZDF) rat as a model for human disease based on urinary peptidomic profiles

Representative animal models for diabetes-associated vascular complications are extremely relevant in assessing potential therapeutic drugs. While several rodent models for type 2 diabetes (T2D) are available, their relevance in recapitulating renal and cardiovascular features of diabetes in man is not entirely clear. Here we evaluate at the molecular level the similarity between Zucker diabetic fatty (ZDF) rats, as a model of T2D-associated vascular complications, and human disease by urinary proteome analysis. Urine analysis of ZDF rats at early and late stages of disease compared to age- matched LEAN rats identified 180 peptides as potentially associated with diabetes complications. Overlaps with human chronic kidney disease (CKD) and cardiovascular disease (CVD) biomarkers were observed, corresponding to proteins marking kidney damage (eg albumin, alpha-1 antitrypsin) or related to disease development (collagen). Concordance in regulation of these peptides in rats versus humans was more pronounced in the CVD compared to the CKD panels. In addition, disease-associated predicted protease activities in ZDF rats showed higher similarities to the predicted activities in human CVD. Based on urinary peptidomic analysis, the ZDF rat model displays similarity to human CVD but might not be the most appropriate model to display human CKD on a molecular level

The Incidence of Highly-Obscured Star-Forming Regions in SINGS Galaxies

Using the new capabilities of the Spitzer Space Telescope and extensive multiwavelength data from the Spitzer Infrared Nearby Galaxies Survey (SINGS), it is now possible to study the infrared properties of star formation in nearby galaxies down to scales equivalent to large HII regions. We are therefore able to determine what fraction of large, infrared-selected star-forming regions in normal galaxies are highly obscured and address how much of the star formation we miss by relying solely on the optical portion of the spectrum. Employing a new empirical method for deriving attenuations of infrared-selected star-forming regions we investigate the statistics of obscured star formation on 500pc scales in a sample of 38 nearby galaxies. We find that the median attenuation is 1.4 magnitudes in H-alpha and that there is no evidence for a substantial sub-population of uniformly highly-obscured star-forming regions. The regions in the highly-obscured tail of the attenuation distribution (A_H-alpha > 3) make up only ~4% of the sample of nearly 1800 regions, though very embedded infrared sources on the much smaller scales and lower luminosities of compact and ultracompact HII regions are almost certainly present in greater numbers. The highly-obscured cases in our sample are generally the bright, central regions of galaxies with high overall attenuation but are not otherwise remarkable. We also find that a majority of the galaxies show decreasing radial trends in H-alpha attenuation. The small fraction of highly-obscured regions seen in this sample of normal, star-forming galaxies suggests that on 500pc scales the timescale for significant dispersal or break up of nearby, optically-thick dust clouds is short relative to the lifetime of a typical star-forming region.Comment: Accepted for publication in ApJ; emulateapj style, 30 pages, 18 figures (compressed versions), 3 table

Incorporating multiple sets of eQTL weights into gene-by-environment interaction analysis identifies novel susceptibility loci for pancreatic cancer.

It is of great scientific interest to identify interactions between genetic variants and environmental exposures that may modify the risk of complex diseases. However, larger sample sizes are usually required to detect gene-by-environment interaction (G × E) than required to detect genetic main association effects. To boost the statistical power and improve the understanding of the underlying molecular mechanisms, we incorporate functional genomics information, specifically, expression quantitative trait loci (eQTLs), into a data-adaptive G × E test, called aGEw. This test adaptively chooses the best eQTL weights from multiple tissues and provides an extra layer of weighting at the genetic variant level. Extensive simulations show that the aGEw test can control the Type 1 error rate, and the power is resilient to the inclusion of neutral variants and noninformative external weights. We applied the proposed aGEw test to the Pancreatic Cancer Case-Control Consortium (discovery cohort of 3,585 cases and 3,482 controls) and the PanScan II genome-wide association study data (replication cohort of 2,021 cases and 2,105 controls) with smoking as the exposure of interest. Two novel putative smoking-related pancreatic cancer susceptibility genes, TRIP10 and KDM3A, were identified. The aGEw test is implemented in an R package aGE.We thank the two anonymous reviewers for their constructive comments. This research was supported by the National Institutes of Health (NIH) grant R01CA169122; P.W. was supported by NIH grants R01HL116720 and R21HL126032. S.H.O. was supported by NIH grant P30CA008748. R.E.N. and the Queensland Pancreatic Cancer Study were funded by the Australian National Health and Medical Research Council. The authors thank Ms. Jessica Swann and the National Institute of Statistical Sciences writing workshop for editorial assistance and suggestions. The authors acknowledge the Texas Advanced Computing Center at The University of Texas at Austin for providing computing resources. The authors alone are responsible for the views expressed in this article and they do not necessarily represent the views, decisions or policies of the institutions with which they are affiliated. The authors declare that there is no conflict of interest

Menstrual And Reproductive Factors, Hormone Use, And Risk Of Pancreatic Cancer: Analysis From The International Pancreatic Cancer Case-control Consortium (Panc4)

Objectives: We aimed to evaluate the relation between menstrual and reproductive factors, exogenous hormones, and risk of pancreatic cancer (PC). Methods: Eleven case-control studies within the International Pancreatic Cancer Case-control Consortium took part in the present study, including in total 2838 case and 4748 control women. Pooled estimates of odds ratios (ORs) and their 95% confidence intervals (CIs) were calculated using a 2-step logistic regression model and adjusting for relevant covariates. Results: An inverse OR was observed in women who reported having had hysterectomy (ORyesvs.no, 0.78; 95% CI, 0.67-0.91), remaining significant in postmenopausal women and never-smoking women, adjusted for potential PC confounders. A mutually adjusted model with the joint effect for hormone replacement therapy (HRT) and hysterectomy showed significant inverse associations with PC in women who reported having had hysterectomy with HRT use (OR, 0.64; 95% CI, 0.48-0.84). Conclusions: Our large pooled analysis suggests that women who have had a hysterectomy may have reduced risk of PC. However, we cannot rule out that the reduced risk could be due to factors or indications for having had a hysterectomy. Further investigation of risk according to HRT use and reason for hysterectomy may be necessary