Helicobacter pylori infection is associated with an increased rate of diabetes.

ObjectiveChronic infections could be contributing to the socioeconomic gradient in chronic diseases. Although chronic infections have been associated with increased levels of inflammatory cytokines and cardiovascular disease, there is limited evidence on how infections affect risk of diabetes.Research design and methodsWe examined the association between serological evidence of chronic viral and bacterial infections and incident diabetes in a prospective cohort of Latino elderly. We analyzed data on 782 individuals aged >60 years and diabetes-free in 1998-1999, whose blood was tested for antibodies to herpes simplex virus 1, varicella virus, cytomegalovirus, Helicobacter pylori, and Toxoplasma gondii and who were followed until June 2008. We used Cox proportional hazards regression to estimate the relative incidence rate of diabetes by serostatus, with adjustment for age, sex, education, cardiovascular disease, smoking, and cholesterol levels.ResultsIndividuals seropositive for herpes simplex virus 1, varicella virus, cytomegalovirus, and T. gondii did not show an increased rate of diabetes, whereas those who were seropositive for H. pylori at enrollment were 2.7 times more likely at any given time to develop diabetes than seronegative individuals (hazard ratio 2.69 [95% CI 1.10-6.60]). Controlling for insulin resistance, C-reactive protein and interleukin-6 did not attenuate the effect of H. pylori infection.ConclusionsWe demonstrated for the first time that H. pylori infection leads to an increased rate of incident diabetes in a prospective cohort study. Our findings implicate a potential role for antibiotic and gastrointestinal treatment in preventing diabetes

Protein disorder prediction at multiple levels of sensitivity and specificity

Background: Many protein regions and some entire proteins have no definite tertiary structure, existing instead as dynamic, disorder ensembles under different physiochemical circumstances. Identification of these protein disorder regions is important for protein production, protein structure prediction and determination, and protein function annotation. A number of different disorder prediction software and web services have been developed since the first predictor was designed by Dunker\u27s lab in 1997. However, most of the software packages use a pre-defined threshold to select ordered or disordered residues. In many situations, users need to choose ordered or disordered residues at different sensitivity and specificity levels. Results: Here we benchmark a state of the art disorder predictor, DISpro, on a large protein disorder dataset created from Protein Data Bank and systematically evaluate the relationship of sensitivity and specificity. Also, we extend its functionality to allow users to trade off specificity and sensitivity by setting different decision thresholds. Moreover, we compare DISpro with seven other automated disorder predictors on the 95 protein targets used in the seventh edition of Critical Assessment of Techniques for Protein Structure Prediction (CASP7). DISpro is ranked as one of the best predictors. Conclusion: The evaluation and extension of DISpro make it a more valuable and useful tool for structural and functional genomics

Protein disorder prediction at multiple levels of sensitivity and specificity

BACKGROUND: Many protein regions and some entire proteins have no definite tertiary structure, existing instead as dynamic, disorder ensembles under different physiochemical circumstances. Identification of these protein disorder regions is important for protein production, protein structure prediction and determination, and protein function annotation. A number of different disorder prediction software and web services have been developed since the first predictor was designed by Dunker's lab in 1997. However, most of the software packages use a pre-defined threshold to select ordered or disordered residues. In many situations, users need to choose ordered or disordered residues at different sensitivity and specificity levels. RESULTS: Here we benchmark a state of the art disorder predictor, DISpro, on a large protein disorder dataset created from Protein Data Bank and systematically evaluate the relationship of sensitivity and specificity. Also, we extend its functionality to allow users to trade off specificity and sensitivity by setting different decision thresholds. Moreover, we compare DISpro with seven other automated disorder predictors on the 95 protein targets used in the seventh edition of Critical Assessment of Techniques for Protein Structure Prediction (CASP7). DISpro is ranked as one of the best predictors. CONCLUSION: The evaluation and extension of DISpro make it a more valuable and useful tool for structural and functional genomics

Rest-Frame Ultraviolet to Near Infrared Observations of an Interacting Lyman Break Galaxy at z = 4.42

We present the rest-frame ultraviolet through near infrared spectral energy distribution for an interacting Lyman break galaxy at a redshift z=4.42, the highest redshift merging system known with clearly resolved tidal features. The two objects in this system - HDF-G4 and its previously unidentified companion - are both B_{435} band dropouts, have similar V_{606}-i_{775} and i_{775}-z_{850} colors, and are separated by 1", which at z=4.42 corresponds to 7 kpc projected nuclear separation; all indicative of an interacting system. Fits to stellar population models indicate a stellar mass of M_\star = 2.6\times 10^{10} M_\odot, age of \tau_\star = 720 My, and exponential star formation history with an e-folding time \tau_0 = 440 My. Using these derived stellar populations as constraints, we model the HDF-G4 system using hydrodynamical simulations, and find that it will likely evolve into a quasar by z\sim3.5, and a quiescent, compact spheroid by z\sim 2.5 similar to those observed at z > 2. And, the existence of such an object supports galaxy formation models in which major mergers drive the high redshift buildup of spheroids and black holes.Comment: 7 pages, 7 figures, accepted for publication in Ap

Enhanced limonene production in cyanobacteria reveals photosynthesis limitations

Terpenes are the major secondary metabolites produced by plants, and have diverse industrial applications as pharmaceuticals, fragrance, solvents, and biofuels. Cyanobacteria are equipped with efficient carbon fixation mechanism, and are ideal cell factories to produce various fuel and chemical products. Past efforts to produce terpenes in photosynthetic organisms have gained only limited success. Here we engineered the cyanobacterium Synechococcus elongatus PCC 7942 to efficiently produce limonene through modeling guided study. Computational modeling of limonene flux in response to photosynthetic output has revealed the downstream terpene synthase as a key metabolic flux-controlling node in the MEP (2-C-methyl-d-erythritol 4-phosphate) pathway-derived terpene biosynthesis. By enhancing the downstream limonene carbon sink, we achieved over 100-fold increase in limonene productivity, in contrast to the marginal increase achieved through stepwise metabolic engineering. The establishment of a strong limonene flux revealed potential synergy between photosynthate output and terpene biosynthesis, leading to enhanced carbon flux into the MEP pathway. Moreover, we show that enhanced limonene flux would lead to NADPH accumulation, and slow down photosynthesis electron flow. Fine-tuning ATP/NADPH toward terpene biosynthesis could be a key parameter to adapt photosynthesis to support biofuel/bioproduct production in cyanobacteria

Simultaneous conversion of all cell wall components by an oleaginous fungus without chemi-physical pretreatment

Lignin utilization during biomass conversion has been a major challenge for lignocellulosic biofuel. In particular, the conversion of lignin along with carbohydrate for fungible fuels and chemicals will both improve the overall carbon efficiency and reduce the need for chemical pretreatments. However, few biomass-converting microorganisms have the capacity to degrade all cell wall components including lignin, cellulose, and hemicellulose. We hereby evaluated a unique oleaginous fungus strain, Cunninghamella echinulata FR3, for its capacity to degrade lignin during biomass conversion to lipid, and the potential to carry out consolidated fermentation without chemical pretreatment, especially when combined with sorghum (Sorghum bicolor) bmr mutants with reduced lignin content. The study clearly showed that lignin was consumed together with carbohydrate during biomass conversion for all sorghum samples, which indicates that this organism has the potential for biomass conversion without chemical pretreatment. Even though dilute acid pretreatment of biomass resulted in more weight loss during fungal fermentation than untreated biomass, the lipid yields were comparable for untreated bmr6/bmr12 double mutant and dilute acid-pretreated wild-type biomass samples. The mechanisms for lignin degradation in oleaginous fungi were further elucidated through transcriptomics and chemical analysis. The studies showed that in C. echinulata FR3, the Fenton reaction may play an important role in lignin degradation. This discovery is among the first to show that a mechanism for lignin degradation similar to those found in white and brown rot basidiomycetous fungi exists in an oleaginous fungus. This study suggests that oleaginous fungi such as C. echinulata FR3 can be employed for complete biomass utilization in a consolidated platform without chemical pretreatment or can be used to convert lignin waste into lipids

MRE11 liberates cGAS from nucleosome sequestration during tumorigenesis

Oncogene-induced replication stress generates endogenous DNA damage that activates cGAS-STING-mediated signalling and tumour suppression1-3. However, the precise mechanism of cGAS activation by endogenous DNA damage remains enigmatic, particularly given that high-affinity histone acidic patch (AP) binding constitutively inhibits cGAS by sterically hindering its activation by double-stranded DNA (dsDNA)4-10. Here we report that the DNA double-strand break sensor MRE11 suppresses mammary tumorigenesis through a pivotal role in regulating cGAS activation. We demonstrate that binding of the MRE11-RAD50-NBN complex to nucleosome fragments is necessary to displace cGAS from acidic-patch-mediated sequestration, which enables its mobilization and activation by dsDNA. MRE11 is therefore essential for cGAS activation in response to oncogenic stress, cytosolic dsDNA and ionizing radiation. Furthermore, MRE11-dependent cGAS activation promotes ZBP1-RIPK3-MLKL-mediated necroptosis, which is essential to suppress oncogenic proliferation and breast tumorigenesis. Notably, downregulation of ZBP1 in human triple-negative breast cancer is associated with increased genome instability, immune suppression and poor patient prognosis. These findings establish MRE11 as a crucial mediator that links DNA damage and cGAS activation, resulting in tumour suppression through ZBP1-dependent necroptosis