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.     

VdSho1 Regulates Growth,Oxidant Adaptation and Virulence in Verticillium dahliae

Verticillium dahliae infection leads to Verticillium wilt in cotton and other dicotyledon crops. To reduce the loss of economic crops, more attention has been focused on the key genes involved in pathogenicity of this soil‐borne plant fungal pathogen. Sho1 encodes a conserved tetraspan transmembrane protein which is a key element of the two upstream branches of the HOG‐MAPK pathway in fungi. Sho1 is required for full virulence in a wide variety of pathogenic fungi. In this study, sho1 mutant in V. dahliae (designated ΔVdsho1) was generated by Agrobacterium tumefaciens‐mediated transformation. ΔVdsho1 strain was highly sensitive to menadione (at concentration of 120 μm ) and hydrogen peroxide (at concentration of 250 μm ), displayed delayed spore germination and reduced spore production compared with the wild type and the complemented strains. During infection of host cotton plants, ΔVdsho1 exhibited impaired ability of root attachment and invasive growth. Results from the present work suggest that VdSho1 controls external sensing, virulence and multiple growth‐related traits in V. dahliae and might serve as a potential target for control of Verticillium wilt.     

Photosynthetic activity and proteomic analysis highlights the utilization of atmospheric CO2 by Ulva prolifera (Chlorophyta) for rapid growth

Free‐floating Ulva prolifera is one of the causative species of green tides. When green tides occur, massive mats of floating U. prolifera thalli accumulate rapidly in surface waters with daily growth rates as high as 56%. The upper thalli of the mats experience environmental changes such as the change in carbon source, high salinity, and desiccation. In this study, the photosynthetic performances of PSI and PSII in U. prolifera thalli exposed to different atmospheric carbon dioxide (CO₂) levels were measured. Changes in photosynthesis within salinity treatments and dehydration under different CO₂ concentrations were also analyzed. The results showed that PSII activity was enhanced as CO₂ increased, suggesting that CO₂ assimilation was enhanced and U. prolifera thalli can utilize CO₂ in the atmosphere directly, even when under moderate stress. In addition, changes in the proteome of U. prolifera in response to salt stress were investigated. Stress‐tolerance proteins appeared to have an important role in the response to salinity stress, whereas the abundance of proteins related to metabolism showed no significant change under low salinity treatments. These findings may be one of the main reasons for the extremely high growth rate of free‐floating U. prolifera when green tides occur.     

Overexpression of <Emphasis Type="Italic">IrlVHA</Emphasis>-<Emphasis Type="Italic">c</Emphasis>, A Vacuolar-Type H<Superscript>+</Superscript>-ATPase c Subunit Gene from <Emphasis Type="Italic">Iris lactea</Emphasis>, Enhances Salt Tolerance in Tobacco

Vacuolar-type H⁺-ATPase (V-ATPase), a multi-subunit endomembrane proton pump, plays an important role in plant growth and response to environmental stresses. In the present study, transgenic tobacco that overexpressed the V-ATPase c subunit gene from Iris lactea (IrlVHA-c) was used to determine the function of IrlVHA-c. Quantitative PCR analysis showed that IrlVHA-c expression was induced by salt stress in I. lactea roots and leaves. Subcellular localization of green fluorescent protein (GFP) as marker combined with FM4-64 staining showed that the IrlVHA-c-GFP was localized to the endosomal compartment in tobacco cells. Compared with the wild-type, the IrlVHA-c transgenic tobacco plants exhibited greater seed germination rates, root length, fresh weight, and higher relative water content (RWC) of leaves under salt stress. Furthermore, the IrlVHA-c transgenic tobacco leaves have lower stomatal densities and larger stomatal apertures than wild-type. Under salt stress, superoxide dismutase (SOD) activity in the transgenic tobacco was significantly enhanced. Moreover, the level of malondialdehyde (MDA) in the transgenic tobacco was significantly lower than that in wild-type plants under salt stress. Taken together, these results suggested that the IrlVHA-c plays an important role in salt tolerance in transgenic tobacco by influencing stomatal movement and physiological changes.     

Microbial Community Structure and Arsenic Biogeochemistry in an Acid Vapor-Formed Spring in Tengchong Geothermal Area,China

Arsenic biogeochemistry has been studied extensively in acid sulfate-chloride hot springs, but not in acid sulfate hot springs with low chloride. In this study, Zhenzhuquan in Tengchong geothermal area, a representative acid sulfate hot spring with low chloride, was chosen to study arsenic geochemistry and microbial community structure using Illumina MiSeq sequencing. Over 0.3 million 16S rRNA sequence reads were obtained from 6-paired parallel water and sediment samples along its outflow channel. Arsenic oxidation occurred in the Zhenxhuquan pool, with distinctly high ratios of arsenate to total dissolved arsenic (0.73–0.86). Coupled with iron and sulfur oxidation along the outflow channel, arsenic accumulated in downstream sediments with concentrations up to 16.44 g/kg and appeared to significantly constrain their microbial community diversity. These oxidations might be correlated with the appearance of some putative functional microbial populations, such as Aquificae and Pseudomonas (arsenic oxidation), Sulfolobus (sulfur and iron oxidation), Metallosphaera and Acidicaldus (iron oxidation). Temperature, total organic carbon and dissolved oxygen significantly shaped the microbial community structure of upstream and downstream samples. In the upstream outflow channel region, most microbial populations were microaerophilic/anaerobic thermophiles and hyperthermophiles, such as Sulfolobus, Nocardia, Fervidicoccus, Delftia, and Ralstonia. In the downstream region, aerobic heterotrophic mesophiles and thermophiles were identified, including Ktedonobacteria, Acidicaldus, Chthonomonas and Sphingobacteria. A total of 72.41–95.91% unassigned-genus sequences were derived from the downstream high arsenic sediments 16S rRNA clone libraries. This study could enable us to achieve an integrated understanding on arsenic biogeochemistry in acid hot springs.     

Combining Untargeted and Targeted Proteomic Strategies for Discrimination and Quantification of Cashmere Fibers

Cashmere is regarded as a specialty and luxury fiber due to its scarcity and high economic value. For fiber quality assessment, it is technically very challenging to distinguish and quantify the cashmere fiber from yak or wool fibers because of their highly similar physical appearance and substantial protein sequence homology. To address this issue, we propose a workflow combining untargeted and targeted proteomics strategies for selecting, verifying and quantifying biomarkers for cashmere textile authentication. Untargeted proteomic surveys were first applied to identify 174, 157, and 156 proteins from cashmere, wool and yak fibers, respectively. After marker selection at different levels, peptides turned out to afford much higher selectivity than proteins for fiber species discrimination. Subsequently, parallel reaction monitoring (PRM) methods were developed for ten selected peptide markers. The PRM-based targeted analysis of peptide markers enabled accurate determination of fiber species and cashmere percentages in different fiber mixtures. Furthermore, collective use of these peptide makers allowed us to discriminate and quantify cashmere fibers in commercial finished fabrics that have undergone heavy chemical treatments. Cashmere proportion measurement in fabric samples using our proteomic approach was in good agreement with results from traditional light microscopy, yet our method can be more readily standardized to become an objective and robust assay for assessing authenticity of fibers and textiles. We anticipate that the proteomic strategies presented in our study could be further implicated in discovery of quality trait markers for other products containing highly homologous proteomes.     

Kinetic Characterization of 100 Glycoside Hydrolase Mutants Enables the Discovery of Structural Features Correlated with Kinetic Constants

The use of computational modeling algorithms to guide the design of novel enzyme catalysts is a rapidly growing field. Force-field based methods have now been used to engineer both enzyme specificity and activity. However, the proportion of designed mutants with the intended function is often less than ten percent. One potential reason for this is that current force-field based approaches are trained on indirect measures of function rather than direct correlation to experimentally-determined functional effects of mutations. We hypothesize that this is partially due to the lack of data sets for which a large panel of enzyme variants has been produced, purified, and kinetically characterized. Here we report the k_cat and K_M values of 100 purified mutants of a glycoside hydrolase enzyme. We demonstrate the utility of this data set by using machine learning to train a new algorithm that enables prediction of each kinetic parameter based on readily-modeled structural features. The generated dataset and analyses carried out in this study not only provide insight into how this enzyme functions, they also provide a clear path forward for the improvement of computational enzyme redesign algorithms.