IL-33-Dependent Endothelial Activation Contributes to Apoptosis and Renal Injury in Orientia tsutsugamushi-Infected Mice

Endothelial cells (EC) are the main target for Orientia tsutsugamushi infection and EC dysfunction is a hallmark of severe scrub typhus in patients. However, the molecular basis of EC dysfunction and its impact on infection outcome are poorly understood. We found that C57BL/6 mice that received a lethal dose of O. tsutsugamushi Karp strain had a significant increase in the expression of IL-33 and its receptor ST2L in the kidneys and liver, but a rapid reduction of IL-33 in the lungs. We also found exacerbated EC stress and activation in the kidneys of infected mice, as evidenced by elevated angiopoietin (Ang) 2/Ang1 ratio, increased endothelin 1 (ET-1) and endothelial nitric oxide synthase (eNOS) expression. Such responses were significantly attenuated in the IL-33^-/- mice. Importantly, IL-33^-/- mice also had markedly attenuated disease due to reduced EC stress and cellular apoptosis. To confirm the biological role of IL-33, we challenged wild-type (WT) mice with a sub-lethal dose of O. tsutsugamushi and gave mice recombinant IL-33 (rIL-33) every 2 days for 10 days. Exogenous IL-33 significantly increased disease severity and lethality, which correlated with increased EC stress and activation, increased CXCL1 and CXCL2 chemokines, but decreased anti-apoptotic gene BCL-2 in the kidneys. To further examine the role of EC stress, we infected human umbilical vein endothelial cells (HUVEC) in vitro. We found an infection dose-dependent increase in the expression of IL-33, ST2L soluble ST2 (sST2), and the Ang2/Ang1 ratio at 24 and 48 hours post-infection. This study indicates a pathogenic role of alarmin IL-33 in a murine model of scrub typhus and highlights infection-triggered EC damage and IL-33-mediated pathological changes during the course of Orientia infection.     

PARylation of the forkhead‐associated domain protein DAWDLE regulates plant immunity

Protein poly(ADP‐ribosyl)ation (PARylation) primarily catalyzed by poly(ADP‐ribose) polymerases (PARPs) plays a crucial role in controlling various cellular responses. However, PARylation targets and their functions remain largely elusive. Here, we deployed an Arabidopsis protein microarray coupled with in vitro PARylation assays to globally identify PARylation targets in plants. Consistent with the essential role of PARylation in plant immunity, the forkhead‐associated (FHA) domain protein DAWDLE (DDL), one of PARP2 targets, positively regulates plant defense to both adapted and non‐adapted pathogens. Arabidopsis PARP2 interacts with and PARylates DDL, which was enhanced upon treatment of bacterial flagellin. Mass spectrometry and mutagenesis analysis identified multiple PARylation sites of DDL by PARP2. Genetic complementation assays indicate that DDL PARylation is required for its function in plant immunity. In contrast, DDL PARylation appears to be dispensable for its previously reported function in plant development partially mediated by the regulation of microRNA biogenesis. Our study uncovers many previously unknown PARylation targets and points to the distinct functions of DDL in plant immunity and development mediated by protein PARylation and small RNA biogenesis, respectively.     

FLEXc: protein flexibility prediction using context-based statistics,predicted structural features,and sequence information

Background

The fluctuation of atoms around their average positions in protein structures provides important information regarding protein dynamics. This flexibility of protein structures is associated with various biological processes. Predicting flexibility of residues from protein sequences is significant for analyzing the dynamic properties of proteins which will be helpful in predicting their functions.

Results

In this paper, an approach of improving the accuracy of protein flexibility prediction is introduced. A neural network method for predicting flexibility in 3 states is implemented. The method incorporates sequence and evolutionary information, context-based scores, predicted secondary structures and solvent accessibility, and amino acid properties. Context-based statistical scores are derived, using the mean-field potentials approach, for describing the different preferences of protein residues in flexibility states taking into consideration their amino acid context.The 7-fold cross validated accuracy reached 61 % when context-based scores and predicted structural states are incorporated in the training process of the flexibility predictor.

Conclusions

Incorporating context-based statistical scores with predicted structural states are important features to improve the performance of predicting protein flexibility, as shown by our computational results. Our prediction method is implemented as web service called “FLEXc” and available online at: http://hpcr.cs.odu.edu/flexc.

     

Divergence with gene flow is driven by local adaptation to temperature and soil phosphorus concentration in teosinte subspecies (Zea mays parviglumis and Zea mays mexicana)

Patterns of genomic divergence between hybridizing taxa can be heterogeneous along the genome. Both differential introgression and local adaptation may contribute to this pattern. Here, we analysed two teosinte subspecies, Zea mays ssp. parviglumis and ssp. mexicana, to test whether their divergence has occurred in the face of gene flow and to infer which environmental variables have been important drivers of their ecological differentiation. We generated 9,780 DArTseqTM SNPs for 47 populations, and used an additional data set containing 33,454 MaizeSNP50 SNPs for 49 populations. With these data, we inferred features of demographic history and performed genome wide scans to determine the number of outlier SNPs associated with climate and soil variables. The two data sets indicate that divergence has occurred or been maintained despite continuous gene flow and/or secondary contact. Most of the significant SNP associations were to temperature and to phosphorus concentration in the soil. A large proportion of these candidate SNPs were located in regions of high differentiation that had been identified previously as putative inversions. We therefore propose that genomic differentiation in teosintes has occurred by a process of adaptive divergence, with putative inversions contributing to reduced gene flow between locally adapted populations.     

Disclosure of Product System Models in Life Cycle Assessment: Achieving Transparency and Privacy

Many of the challenges facing knowledge synthesis from life cycle assessment (LCA) studies stem from the inability of study authors and readers to formally agree on the structure and content of the product system models used to perform LCA computations. This article presents a framework for formally disclosing the foreground of an LCA study in a way that permits the computations to be inspected, verified, and reproduced by a reader, provided that the reader has access to the same life cycle inventory and impact characterization resources as the author. The framework can also be used to partition a study into public and private portions, allowing both portions to be critically reviewed but omitting the private information from the disclosure. A disclosure is made up of six components, including three lists of entities in the model and three sparse matrices describing their interconnections. The entity lists make reference to previously‐published resources, including background inventory databases and characterized elementary flows, and the disclosure framework requires both author and reader to agree on the meaning of each of these references. The framework contributes to ongoing efforts within and beyond industrial ecology to improve the reproducibility and verifiability of scholarly works, and if implemented, plots a course toward distributed, platform‐independent computation and validation of LCA results.