The conserved Tpk1 regulates non-homologous end joining double-strand break repair by phosphorylation of Nej1, a homolog of the human XLF

The yeast cyclic AMP-dependent protein kinase A (PKA) is a ubiquitous serine–threonine kinase, encompassing three catalytic (Tpk1–3) and one regulatory (Bcy1) subunits. Evidence suggests PKA involvement in DNA damage checkpoint response, but how DNA repair pathways are regulated by PKA subunits remains inconclusive. Here, we report that deleting the tpk1 catalytic subunit reduces non-homologous end joining (NHEJ) efficiency, whereas tpk2-3 and bcy1 deletion does not. Epistatic analyses revealed that tpk1, as well as the DNA damage checkpoint kinase (dun1) and NHEJ factor (nej1), co-function in the same pathway, and parallel to the NHEJ factor yku80. Chromatin immunoprecipitation and resection data suggest that tpk1 deletion influences repair protein recruitments and DNA resection. Further, we show that Tpk1 phosphorylation of Nej1 at S298 (a Dun1 phosphosite) is indispensable for NHEJ repair and nuclear targeting of Nej1 and its binding partner Lif1. In mammalian cells, loss of PRKACB (human homolog of Tpk1) also reduced NHEJ efficiency, and similarly, PRKACB was found to phosphorylate XLF (a Nej1 human homolog) at S263, a corresponding residue of the yeast Nej1 S298. Together, our results uncover a new and conserved mechanism for Tpk1 and PRKACB in phosphorylating Nej1 (or XLF), which is critically required for NHEJ repair.     

Enhanced thermal and ultrasonic stability of a fungal protease encapsulated within biomimetically generated silicate nanospheres

Background

Dendrimers are highly branched synthetic macromolecules with a globular shape. They have been successfully used for generation of nanospheres at mild conditions via biomimetic silicification. Encapsulation of enzyme molecules within these nanospheres during their synthesis is a promising method for rapid and efficient entrapment of several enzymes. However, encapsulation of proteolytic enzymes has been rarely done via biomimetic silicification. As well, the operational stability of encapsulated enzyme has not been systematically reported.

Methods

A proteolytic enzyme, either α-Chymotrypsin or a fungal protease from Aspergilus Oryzea was encapsulated along with iron oxide nanoparticles within particles yielded via biomimetic silicification of different generations of polyamidoamine (PAMAM) dendrimers. Stability of encapsulated enzyme was compared to that of free enzyme during storage at room temperature. As well, their thermal and ultrasonic stabilities were measured. Scanning electron microscopy, transmission electron microscopy and optical microscopy were used to investigate the morphology of nanospheres.

Results

Determination of encapsulation efficiency revealed that ∼ 85% of fungal protease with concentration 1.4 mg mL^− 1 stock solution was immobilized within particles yielded by generation 0. Based on microscopic images the generated particles interconnected with each other and had spherical morphologies independent of generation. Kinetic analysis of encapsulated fungal protease demonstrated that Mechaelis-Menten constant (K_m) slightly increased.

Conclusion

PAMAM dendrimer generation 0 could be effectively used for rapid encapsulation of a fungal protease from Aspegilus Oryzae.

General significance

Encapsulation significantly enhances the thermal and ultrasonic stabilities of enzymes, suggesting a range of diverse applications for them.     

D-4F reduces EO6 immunoreactivity, SREBP-1c mRNA levels, and renal inflammation in LDL receptor-null mice fed a Western diet

LDL receptor-null (LDLR(-/-)) mice on a Western diet (WD) develop endothelial dysfunction and atherosclerosis, which are improved by the apolipoprotein A-I (apoA-I) mimetic peptide D-4F. Focusing on the kidney, LDLR(-/-)mice were fed a WD with D-4F or the inactive control peptide scrambled D-4F (ScD-4F) added to their drinking water. The control mice (ScD-4F) developed glomerular changes, increased immunostaining for MCP-1/CCL2 chemokine, increased macrophage CD68 and F4/80 antigens, and increased oxidized phospholipids recognized by the EO6 monoclonal antibody in both glomerular and tublo-interstitial areas. All of these parameters were significantly reduced by D-4F treatment, approaching levels found in wild-type C57BL/6J or LDLR(-/-) mice fed a chow diet. Sterol-regulatory element binding protein-1c (SREBP-1c) mRNA levels and triglyceride levels were elevated in the kidneys of the control mice (ScD-4F) fed the WD compared with C57BL/6J and LDLR(-/-) mice on chow (P < 0.001 and P < 0.001, respectively) and compared with D-4F-treated mice on the WD (P < 0.01). There was no significant difference in plasma lipids, lipoproteins, glucose, blood pressure, or renal apoB levels between D-4F- and ScD-4F-treated mice. We conclude that D-4F reduced renal oxidized phospholipids, resulting in lower expression of SREBP-1c, which, in turn, resulted in lower triglyceride content and reduced renal inflammation.     

Simple testing procedures for the Holling type II model

In this paper, we consider predator–prey data that can be viewed as solutions to a planar system of ordinary differential equations (ODE) observed with random error. The ODE system admits a limit cycle, while the random error is supposed to act additively in the log-scale. One of the oldest such systems is Holling’s type II model. In spite of its simplicity, it is still very popular in data analyses, although more sophisticated models have been introduced in the literature. We propose a simple way of deciding whether a set of predator–prey pairs is indicative or not of a departure from this basic model by exploiting the geometric properties of the solution in the phase plane. To illustrate our method, we use simulated and real data.     

Nonparametric inverse-probability-weighted estimators based on the highly adaptive lasso

Inverse-probability-weighted estimators are the oldest and potentially most commonly used class of procedures for the estimation of causal effects. By adjusting for selection biases via a weighting mechanism, these procedures estimate an effect of interest by constructing a pseudopopulation in which selection biases are eliminated. Despite their ease of use, these estimators require the correct specification of a model for the weighting mechanism, are known to be inefficient, and suffer from the curse of dimensionality. We propose a class of nonparametric inverse-probability-weighted estimators in which the weighting mechanism is estimated via undersmoothing of the highly adaptive lasso, a nonparametric regression function proven to converge at nearly $n^{-1/3}$-rate to the true weighting mechanism. We demonstrate that our estimators are asymptotically linear with variance converging to the nonparametric efficiency bound. Unlike doubly robust estimators, our procedures require neither derivation of the efficient influence function nor specification of the conditional outcome model. Our theoretical developments have broad implications for the construction of efficient inverse-probability-weighted estimators in large statistical models and a variety of problem settings. We assess the practical performance of our estimators in simulation studies and demonstrate use of our proposed methodology with data from a large-scale epidemiologic study.     

Flow visualisation study of spiral flow in the aorta–renal bifurcation

The aim of this study was to analyse the flow dynamics in an idealised model of the aorta–renal bifurcation using flow visualisation, with a particular focus on the effect of aorta-to-renal flow ratio and flow spirality. The recirculation length was longest when there was low flow in the renal artery and smaller in the presence of spiral flow. The results also indicate that patients without spiral flow or who have low flow in the renal artery due to the presence of stenosis may be susceptible to heightened development of atherosclerotic lesions.     

Modeling habitat connectivity in support of multiobjective species movement: An application to amphibian habitat systems

Reasoning about the factors underlying habitat connectivity and the inter-habitat movement of species is essential to many areas of biological inquiry. In order to better describe and understand the ways in which the landscape may support species movement, an increasing amount of research has focused on identification of paths or corridors that may be important in providing connectivity among habitat. The least-cost path problem has proven to be an instrumental analytical tool in this sense. A complicating aspect of such path identification methods is how to best reconcile and integrate the array of criteria or objectives that species may consider in traversal of a landscape. In cases where habitat connectivity is thought to be influenced or guided by multiple objectives, numerous solutions to least-cost path problems can exist, representing tradeoffs between the objectives. In practice though, identification of these solutions can be very challenging and as such, only a small proportion of them are typically examined leading to a weak characterization of habitat connectivity. To address this computational challenge, a multiobjective optimization framework is proposed. A generalizable multiobjective least-cost path model is first detailed. A non-inferior set estimation (MONISE) algorithm for identifying supported efficient solutions to the multiobjective least-cost path model is then described. However, it is well known that unsupported efficient solutions (which are equally important) can also exist, but are typically ignored given that they are more difficult to identify. Thus, to enable the identification of the full set of efficient solutions (supported and unsupported) to the multiobjective model, a multi-criteria labeling algorithm is then proposed. The developed framework is applied to assess different conceptualizations of habitat connectivity supporting amphibian movement in a wetland system. The results highlight the range of tradeoffs in characterizations of connectivity that can exist when multiple objectives are thought to contribute to movement decisions and that the number of unsupported efficient solutions (which are typically ignored) can vastly outweigh that of the supported efficient solutions.     

A high-fat, refined-carbohydrate diet induces endothelial dysfunction and oxidant/antioxidant imbalance and depresses NOS protein expression.

We tested whether consumption of a high-fat, high-sucrose (HFS) diet can affect endothelium-dependent relaxation, whether this precedes the development of diet-induced hypertension previously noted in this model, and whether it is mediated, in part, by changes in nitric oxide synthase (NOS) and/or NOS regulatory proteins. Female Fischer rats were fed either a HFS diet or standard low-fat, complex-carbohydrate chow starting at 2 mo of age for 7 mo. Vasoconstrictive response to KCl and phenylephrine was similar in both groups. Vasorelaxation to acetylcholine was significantly impaired in the HFS animals, and there were no differences in relaxation to sodium nitroprusside, suggesting that the endothelial dysfunction is due, at least in part, to nitric oxide deficiency. HFS consumption decreased protein expression of endothelial NOS in aorta, renal, and heart tissues, neuronal NOS in kidney, heart, aorta, and brain, and inducible NOS in heart and aorta. Caveolin-1 and soluble guanylate cyclase protein expression did not change, but AKT protein expression decreased in heart and aorta and increased in kidney tissue. Consumption of HFS diet raised brain carbonyl content and plasma hydrogen peroxide concentration and diminished plasma total antioxidant capacity. Because blood pressure, which is known to eventually rise in this model, was not as yet significantly elevated, the present data suggest that endothelial dysfunction precedes the onset of diet-induced hypertension. The lack of a quantitative change in caveolin-1 and soluble guanylate cyclase protein content indicates that alteration in these proteins is not responsible for the endothelial dysfunction. Thus nitric oxide deficiency combined with antioxidant/oxidant imbalance, appears to be a primary factor in the development of endothelial dysfunction in this model.     

Rejoinder to “Instrumented difference-in-differences”

We thank all the discussants for the careful reading and insightful comments. In our rejoinder, we extend the discussion of how the assumptions of instrumented difference-in-differences (iDID) compare to the assumptions of the standard instrumental variable method. We also make additional comments on how iDID is related to the fuzzy DID. We highlight future research directions to enhance the utility of iDID, including extensions to adjust for covariate shift in two-sample iDID design, and generalization of iDID to multiple time points and a multi-valued instrumental variable for DID.