Expression pattern of NLRP3 and its related cytokines in the lung and brain of avian influenza virus H9N2 infected BALB/c mice

Background

H9N2 avian influenza virus (AIV) becomes the focus for its ability of transmission to mammals and as a donor to provide internal genes to form the new epidemic lethal influenza viruses. Residue 627 in PB2 has been proven the virulence factor of H9N2 avian influenza virus in mice, but the detailed data for inflammation difference between H9N2 virus strains with site 627 mutation is still unclear. The inflammasome NLRP3 is recently reported as the cellular machinery responsible for activation of inflammatory processes and plays an important role during the development of inflammation caused by influenza virus infection.

Methods

In this study, we investigated the expression pattern of NLRP3 and its related cytokines of IL-1β and TNF-α in BALB/c mice infected by H9N2 AIV strains with only a site 627 difference at both mRNA and protein levels at different time points.

Results

The results showed that the expression level of NLRP3, IL-1β and TNF-α changed in the lung and brain of BALB/c mice after infection by V_K627 and rV_K627E. The immunohistological results showed that the positive cells of NLRP3, IL-1β and TNF-α altered the positive levels of original cells in tissues and infiltrated inflammatory cells which caused by H9N2 infection.

Conclusions

Our results provided the basic data at differences in expression pattern of NLRP3 and its related cytokines in BALB/c mice infected by H9N2 influenza viruses with only a site 627 difference. This implied that NLRP3 inflammasome plays a role in host response to influenza virus infection and determines the outcome of clinical manifestation and pathological injury. This will explain the variable of pathological presentation in tissues and enhance research on inflammation process of the AIV H9N2 infection.

     

Genome-wide screen of human bromodomain-containing proteins identifies Cecr2 as a novel DNA damage response protein

The formation of γ-H2AX foci after DNA double strand breaks (DSBs) is crucial for the cellular response to this lethal DNA damage. We previously have shown that BRG1, a chromatin remodeling enzyme, facilitates DSB repair by stimulating γ-H2AX formation, and this function of BRG1 requires the binding of BRGI to acetylated histone H3 on γ-H2AX-containing nucleosomes using its bromodomain (BRD), a protein module that specifically recognizes acetyl-Lys moieties. We also have shown that the BRD of BRG1, when ectopically expressed in cells, functions as a dominant negative inhibitor of the BRG1 activity to stimulate γ-H2AX and DSB repair. Here, we found that BRDs from a select group of proteins have no such activity, suggesting that the γ-H2AX inhibition activity of BRG1 BRD is specific. This finding led us to search for more BRDs that exhibit γ-H2AX inhibition activity in the hope of finding additional BRD-containing proteins involved in DNA damage responses. We screened a total of 52 individual BRDs present in 38 human BRD-containing proteins, comprising 93% of all human BRDs. We identified the BRD of cat eye syndrome chromosome region candidate 2 (Cecr2), which recently was shown to form a novel chromatin remodeling complex with unknown cellular functions, as having a strong γ-H2AX inhibition activity. This activity of Cecr2 BRD is specific because it depends on the chromatin binding affinity of Cecr2 BRD. Small interfering RNA knockdown experiments showed that Cecr2 is important for γ-H2AX formation and DSB repair. Therefore, our genomewide screen identifies Cecr2 as a novel DNA damage response protein.     

Significance of Serum Pepsinogens as a Biomarker for Gastric Cancer and Atrophic Gastritis Screening: A Systematic Review and Meta-Analysis

Background

Human pepsinogens are considered promising serological biomarkers for the screening of atrophic gastritis (AG) and gastric cancer (GC). However, there has been controversy in the literature with respect to the validity of serum pepsinogen (SPG) for the detection of GC and AG. Consequently, we conducted a systematic review and meta-analysis to assess the diagnostic accuracy of SPG in GC and AG detection.

Methods

We searched PubMed, Embase, and the Chinese National Knowledge Infrastructure (CNKI) for correlative original studies published up to September 30, 2014. The summary sensitivity, specificity, positive diagnostic likelihood ratio (DLR+), negative diagnostic likelihood ratio (DLR-), area under the summary receiver operating characteristic curve (AUC) and diagnostic odds ratio (DOR) were used to evaluate SPG in GC and AG screening based on bivariate random effects models. The inter-study heterogeneity was evaluated by the I² statistics and publication bias was assessed using Begg and Mazumdar’s test. Meta-regression and subgroup analyses were performed to explore study heterogeneity.

Results

In total, 31 studies involving 1,520 GC patients and 2,265 AG patients were included in the meta-analysis. The summary sensitivity, specificity, DLR+, DLR-, AUC and DOR for GC screening using SPG were 0.69 (95% CI: 0.60–0.76), 0.73 (95% CI: 0.62–0.82), 2.57 (95% CI: 1.82–3.62), and 0.43 (95% CI: 0.34–0.54), 0.76 (95% CI: 0.72–0.80) and 6.01 (95% CI: 3.69–9.79), respectively. For AG screening, the summary sensitivity, specificity, DLR+, DLR-, AUC and DOR were 0.69 (95% CI: 0.55–0.80), 0.88 (95% CI: 0.77–0.94), 5.80 (95% CI: 3.06–10.99), and 0.35 (95% CI: 0.24–0.51), 0.85 (95% CI: 0.82–0.88) and 16.50 (95% CI: 8.18–33.28), respectively. In subgroup analysis, the use of combination of concentration of PGI and the ratio of PGI:PGII as measurement of SPG for GC screening yielded sensitivity of 0.70 (95% CI: 0.66–0.75), specificity of 0.79 (95% CI: 0.79–0.80), DOR of 6.92 (95% CI: 4.36–11.00), and AUC of 0.78 (95% CI: 0.72–0.81), while the use of concentration of PGI yielded sensitivity of 0.55 (95% CI: 0.51–0.60), specificity of 0.79 (95% CI: 0.76–0.82), DOR of 6.88 (95% CI: 2.30–20.60), and AUC of 0.77 (95% CI: 0.73–0.92). For AG screening, the use of ratio of PGI:PGII as measurement of SPG yielded sensitivity of 0.69 (95% CI: 0.52–0.83), specificity of 0.84 (95% CI: 0.68–0.93), DOR of 11.51 (95% CI: 6.14–21.56), and AUC of 0.83 (95% CI: 0.80–0.86), the use of combination of concentration of PGI and the ratio of PGI:PGII yield sensitivity of 0.79 (95% CI: 0.72–0.85), specificity of 0.89 (95% CI: 0.85–0.93), DOR of 24.64 (95% CI: 6.95–87.37), and AUC of 0.87 (95% CI: 0.81–0.92), concurrently, the use of concentration of PGI yield sensitivity of 0.46 (95% CI: 0.38–0.54), specificity of 0.93 (95% CI: 0.91–0.95), DOR of 19.86 (95% CI: 0.86–456.91), and AUC of 0.86 (95% CI: 0.52–1.00).

Conclusion

SPG has great potential as a noninvasive, population-based screening tool in GC and AG screening. In addition, given the potential publication bias and high heterogeneity of the included studies, further high quality studies are required in the future.     

Artificial leaf aids analysis of chlorophyll fluorescence and P700 absorbance in studies involving microalgae

Measuring chlorophyll fluorescence and P700 absorbance has been widely used to study photosynthesis in both terrestrial plants and algae. However, in order to apply these measurement techniques to study microalgae, a concentrated suspension of algae, which is usually prepared by centrifugation, is required. In this study, instead of using centrifugation, we concentrated microalgae on a nitrocellulose membrane using filtration to create an ‘artificial leaf’ before analysis. Overall, we were able to generate values of the appropriate photosynthetic parameters that were comparable to those obtained when chlorophyll fluorescence and P700 absorbance were measured following centrifugation. There were no statistically significant differences (P > 0.05) between the artificial leaf method and the traditional cuvette method for determining chlorophyll fluorescence or P700 absorbance at appropriate chlorophyll concentrations. We were also able to reduce background noise by using a filter membrane as a carrier. Therefore, an artificial leaf has the potential to be a valuable tool for phycologists interested in studying microalgal photosynthesis by enabling them to eliminate tedious centrifugation steps. In addition, fluorometers commonly used for studying the leaves of higher plants will also be suitable for studying microalgae.     

构树钟乳体毛的发育及钟乳体成分研究

构树(Broussonetis Papyrifea)幼茎、芽、叶的表面具钟乳体毛。它是一长圆锥状单细胞毛,基部有无管漏斗状基座包裹,腔内有呈轮纹状沉积的钟乳体。钟乳体毛发生很早,自芽的第3幼叶(自叶原基数起)开始发生。原表皮细胞进行不均等的垂周分裂,其小的发育成表皮细胞,大的发育成钟乳体毛。基座由原表皮细胞垂周及横分裂而形成。其内钟乳体发育较迟,要等叶长至6cm,宽4—5cm时,才从毛尖或毛尖之下侧壁处开始沉积。构树钟乳体成分中含硫酸钙,这可能正是构树积累硫的速度快,净化大气中有害的SO2气体和可能抗SO2污染很强的原因。对筛选和培育抗SO2毒气更强的植物提供了参考。     

Meta-analysis of TYK2 gene polymorphisms association with susceptibility to autoimmune and inflammatory diseases

The aim of our meta-analysis was to quantitatively summarize the association of TYK2 gene polymorphisms with autoimmune and inflammatory diseases. 11 studies that included data from 21497 cases and 22647 controls were identified. OR was used as a measure of the effect of the association in a fixed/random effect model. Meta-analysis was performed for six TYK2 gene polymorphisms (rs34536443, rs2304256, rs280523, rs280519, rs12720270 and rs12720356). Significant association was found in rs34536443 (C versus G: OR = 0.76, 95% CI = 0.69–0.84, P < 0.00001; GC + CC versus GG: OR = 0.78, 95% CI = 0.68–0.90, P = 0.0005; CC versus GG + GC: OR = 0.76, 95% CI = 0.28–2.05, P = 0.58; CC versus GG: OR = 0.74, 95% CI = 0.27–2.02, P = 0.56; GC versus GG: OR = 0.78, 95% CI = 0.68–0.90, P = 0.0006) and rs2304256 (A versus C: OR = 0.78, 95% CI = 0.70–0.87, P < 0.0001; CA + AA versus CC: OR = 0.69, 95% CI = 0.59–0.81, P < 0.0001; AA versus CC + CA: OR = 0.75, 95% CI = 0.66–1.00, P = 0.05; AA versus CC: OR = 0.64, 95% CI = 0.47–0.86, P = 0.003; CA versus CC: OR = 0.70, 95% CI = 0.60–0.83, P < 0.0001) in TYK2 gene, but not for the other polymorphisms (rs280523, rs280519, rs12720270, and rs12720356). This meta-analysis demonstrates that autoimmune and inflammatory diseases is associated with TYK2 gene rs34536443 and rs2304256 polymorphisms, but not rs280523, rs280519, rs12720270 and rs12720356.     

Genetic Analysis of the Biosynthesis of 2-Methoxy-3-Isobutylpyrazine,a Major Grape-Derived Aroma Compound Impacting Wine Quality

Methoxypyrazines (MPs) are strongly odorant volatile molecules with vegetable-like fragrances that are widespread in plants. Some grapevine (Vitis vinifera) varieties accumulate significant amounts of MPs, including 2-methoxy-3-isobutylpyrazine (IBMP), which is the major MP in grape berries. MPs are of particular importance in white Sauvignon Blanc wines. The typicality of these wines relies on a fine balance between the pea pod, capsicum character of MPs and the passion fruit/grapefruit character due to volatile thiols. Although MPs play a crucial role in Sauvignon varietal aromas, excessive concentrations of these powerful odorants alter wine quality and reduce consumer acceptance, particularly in red wines. The last step of IBMP biosynthesis has been proposed to involve the methoxylation of the nonvolatile precursor 2-hydroxy-3-isobutylpyrazine to give rise to the highly volatile IBMP. In this work, we have used a quantitative trait loci approach to investigate the genetic bases of IBMP biosynthesis. This has led to the identification of two previously uncharacterized S-adenosyl-methionine-dependent O-methyltransferase genes, termed VvOMT3 and VvOMT4. Functional characterization of these two O-methyltransferases showed that the VvOMT3 protein was highly specific and efficient for 2-hydroxy-3-isobutylpyrazine methylation. Based on its differential expression in high- and low-MP-producing grapevine varieties, we propose that VvOMT3 is a key gene for IBMP biosynthesis in grapevine.The pleasure experienced while enjoying a glass of wine is the result of sophisticated sensory, neurophysiological, and psychological processes triggered by wine aroma. Wine flavor is the result of a complex mixture of volatile compounds in the headspace of the glass that induces feelings of pleasure at the brain level (Shepherd, 2006). During the last 40 years, over 800 volatile molecules have been formally identified in wines, in concentrations ranging from hundreds of milligrams per liter down to a few picograms per liter (Ebeler and Thorngate, 2009; Styger et al., 2011). Among all of them, a relatively limited number of compounds, called varietal (or primary) aromas, play a crucial role in wine flavor and typicality. These aromas, which are related to the grape variety, belong to a limited number of chemical families, including monoterpenes, C13 norisoprenoids, volatile sulfur compounds, and methoxypyrazines (MPs; Ebeler and Thorngate, 2009). Quite frequently, they exist mostly in the grape (Vitis vinifera) berry as nonvolatile, odorless, “bound” forms that can be released by chemical and enzymatic reactions occurring during the winemaking and wine aging processes, thus enhancing wine’s varietal expression (Styger et al., 2011). Two classical examples are the glycoside precursors of the monoterpenols (Strauss et al., 1986) and the cysteinylated or glutathionylated precursors of the volatile thiols (Tominaga et al., 1998; Peña-Gallego et al., 2012). Noticeable exceptions are the MPs, which are found in grape berries exclusively as free, volatile molecules.MPs are strongly odorant volatile heterocycles, with vegetable-like fragrances, that are widely occurring in the plant kingdom (Maga, 1982). In grape, they can be detected in fruits, leaves, shoots, and roots (Dunlevy et al., 2010). They are found in different grape varieties and are particularly abundant in the so-called Bordeaux cultivars (i.e. cv Cabernet Franc, Cabernet Sauvignon [CS], Sauvignon Blanc, Merlot, and Carménère [Car]; Bayonove et al., 1975; Lacey et al., 1991; Roujou de Boubée et al., 2002; Belancic and Agosin, 2007), whereas they are rarely detected in other cultivars, such as cv Pinot Noir (PN), Chardonnay, or Petit Verdot (PV). This finding indicates a strong genotype dependency of MP biosynthesis (Koch et al., 2010). MPs are accumulated in berries until bunch closure or véraison, and then their level declines after véraison (Hashizume and Samuta, 1999; Ryona et al., 2008). MP concentration in wine is highly correlated with the grape berry content at harvest (Roujou de Boubée et al., 2002). Three MPs are found in grape berries: 2-methoxy-3-isobutylpyrazine (IBMP), which is the most abundant, and two others, 2-methoxy-3-isopropylpyrazine (IPMP) and 2-methoxy-3-sec-butylpyrazine (SBMP; Ebeler and Thorngate, 2009). Both IBMP and IPMP display very low sensory detection thresholds in the wine matrix, ranging from 1 to 16 ng L^–1.MPs are of particular importance in white Sauvignon Blanc wines. The typicality of these wines relies on a fine balance between the pea pod, capsicum character of MPs and the passion fruit/grapefruit character due to volatile thiols (Dubourdieu et al., 2006; Lund et al., 2009). Although MPs play a crucial role in Sauvignon varietal aromas, excessive concentrations of these extremely powerful odorants will reduce consumer acceptance (Parr et al., 2007). In red wine, MPs are considered as off-flavor, and red wines can be depreciated by concentrations above 10 ng L^–1 (Allen et al., 1991; Roujou de Boubée et al., 2000; Belancic and Agosin, 2007). Given the importance of MPs, either as typical varietal aromas or as detrimental off-flavors, deciphering the genetic and molecular determinism of their accumulation is of high interest for viticulture.In spite of this, until recently little was known about the MP biosynthesis pathway or the MP biosynthetic genes, either in grapevine or other plant species. Theoretical biosynthesis pathways have been proposed since the mid-1970s. They all start by the addition of an α-dicarbonyl on a branched amino acid (Leu for IBMP, Val for IPMP) to form a 2-hydroxy-3-alkylpyrazine, which is subsequently transformed into the corresponding MP, by a methoxylation reaction (Murray and Whitfield 1975; Gallois et al., 1988). While the initial addition step remains to be demonstrated in plants, an S-adenosyl-l-Met (SAM)-dependent O-methyltransferase (OMT), capable of converting 2-hydroxy-3-isobutylpyrazine (IBHP) into IBMP, has been detected in CS shoots, partially purified and sequenced (Hashizume et al., 2001a, 2001b; Fig. 1). Recently, Dunlevy et al. (2010) characterized two OMTs, VvOMT1 and VvOMT2, capable of methylating IBHP in vitro, albeit with high apparent K_m values. To investigate the genetic bases of MP biosynthesis in grape berries, we performed a quantitative trait loci (QTL) analysis, which has led to the identification of two previously uncharacterized OMTs termed VvOMT3 and VvOMT4. Functional characterization of these two OMTs showed that VvOMT3 was highly specific and efficient for IBHP methylation. Based on its differential expression in high-MP and low-MP grapevine varieties, we propose that VvOMT3 and, to a lesser extent, VvOMT4 are key genes for MP biosynthesis in grapevine berries.Open in a separate windowFigure 1.Putative biosynthesis pathway for IBMP adapted from Hashizume et al. (2001a). SAHcy, S-Adenosyl-l-homo-Cys.     

Drought stress and plant ecotype drive microbiome recruitment in switchgrass rhizosheath

The rhizosheath, a layer of soil grains that adheres firmly to roots, is beneficial for plant growth and adaptation to drought environments. Switchgrass is a perennial C4 grass which can form contact rhizosheath under drought conditions. In this study, we characterized the microbiomes of four different rhizocompartments of two switchgrass ecotypes (Alamo and Kanlow) grown under drought or well-watered conditions via 16S ribosomal RNA amplicon sequencing. These four rhizocompartments, the bulk soil, rhizosheath soil, rhizoplane, and root endosphere, harbored both distinct and overlapping microbial communities. The root compartments (rhizoplane and root endosphere) displayed low-complexity communities dominated by Proteobacteria and Firmicutes. Compared to bulk soil, Cyanobacteria and Bacteroidetes were selectively enriched, while Proteobacteria and Firmicutes were selectively depleted, in rhizosheath soil. Taxa from Proteobacteria or Firmicutes were specifically selected in Alamo or Kanlow rhizosheath soil. Following drought stress, Citrobacter and Acinetobacter were further enriched in rhizosheath soil, suggesting that rhizosheath microbiome assembly is driven by drought stress. Additionally, the ecotype-specific recruitment of rhizosheath microbiome reveals their differences in drought stress responses. Collectively, these results shed light on rhizosheath microbiome recruitment in switchgrass and lay the foundation for the improvement of drought tolerance in switchgrass by regulating the rhizosheath microbiome.