Score risk model for predicting severe fever with thrombocytopenia syndrome mortality

Abstract Background Severe fever with thrombocytopenia syndrome (SFTS) is an emerging epidemic infectious disease with high mortality in East Aisa, especially in China. To predict the prognosis of SFTS precisely is important in clinical practice. Methods From May 2013 to November 2015, 233 suspected SFTS patients were tested for SFTS virus using RT-PCR. Cox regression model was utilized to comfirm independent risk factors for mortality. A risk score model for mortality was constructed based on regression coefficient of risk factors. Log-rank test was used to evaluate the significance of this model. Results One hundred seventy-four patients were confirmed with SFTS, of which 40 patients died (23%). Baseline age, serum aspartate aminotransferase (AST) and serum creatinine (sCr) level were independent risk factors of mortality. The area under ROC curve (AUCs) of these parameters for predicting death were 0.771, 0.797 and 0.764, respectively. And hazard ratio (HR) were 1.128, 1.002 and 1.013, respectively. The cutoff value of the risk model was 10. AUC of the model for predicting mortality was 0.892, with sensitivity and specificity of 82.5 and 86.6%, respectively. Log-rank test indicated strong statistical significance (\ud7 2 \u2009=\u200988.35, p \u2009<\u20090.001). Conclusions This risk score model may be helpful to predicting the prognosis of SFTS patients

Genome-Wide Identification, Evolution, and Expression Analysis of the TCP Gene Family in Rose (Rosa chinensis Jacq.)

Roses have not only high ornamental and economic values but also cultural importance worldwide. As a plant-specific transcription factor gene family, the TCP (TEOSINTE BRANCHED 1, CYCLOIDEA, PROLIFERATING CELL FACTOR LAND 2) genes have been indicated to be involved in various aspects of plant biological processes, such as leaf morphogenesis and senescence, lateral branching, flower development, stress response and hormone signaling. Currently, TCP genes have been identified and analyzed in many plants, yet there is no systematic analysis in Rosa chinensis. Here, we identified 16 RcTCP genes from R. chinensis genome, which were unevenly distributed in five out of all seven chromosomes. Phylogenetic and structural analyses showed that RcTCP family could be classified into two classes, I (namely PCF) and II, and class II genes can be further divided into CIN and CyC/TB1 subclasses. The different classes of TCP genes were showed to have undergone different evolutionary processes, and genes in the same branch shared similar motifs, gene structures and conserved structural domains. Promoter analysis showed that RcTCPs had many cis-acting elements that are mainly associated with plant growth and development, plant hormones and abiotic/biotic stress responses. Furthermore, the expression levels of RcTCPs under vegetative and reproductive growth and drought stress treatments were analyzed based on public RNA-seq dataset, and it was shown that RcTCPs exhibited serious tissue-specific expression, with most of them dominantly expressed in flowers, leaves and stems, with high levels of expression at different stages of flower and bud differentiation, particularly during petal formation and gametophyte development. The high inducement of seven RcTCP genes from PCF class in drought stress indicated their important roles in biological processes against drought stress. Our results provide valuable information for the evolution and functional characterization of TCP genes in R. chinensis

MET18 Connects the Cytosolic Iron-Sulfur Cluster Assembly Pathway to Active DNA Demethylation in <i>Arabidopsis</i>

<div><p>DNA demethylation mediated by the DNA glycosylase ROS1 helps determine genomic DNA methylation patterns and protects active genes from being silenced. However, little is known about the mechanism of regulation of ROS1 enzymatic activity. Using a forward genetic screen, we identified an anti-silencing (ASI) factor, ASI3, the dysfunction of which causes transgene promoter hyper-methylation and silencing. Map-based cloning identified ASI3 as MET18, a component of the cytosolic iron-sulfur cluster assembly (CIA) pathway. Mutation in <i>MET18</i> leads to hyper-methylation at thousands of genomic loci, the majority of which overlap with hypermethylated loci identified in <i>ros1</i> and <i>ros1dml2dml3</i> mutants. Affinity purification followed by mass spectrometry indicated that ROS1 physically associates with MET18 and other CIA components. Yeast two-hybrid and split luciferase assays showed that ROS1 can directly interact with MET18 and another CIA component, AE7. Site-directed mutagenesis of ROS1 indicated that the conserved iron-sulfur motif is indispensable for ROS1 enzymatic activity. Our results suggest that ROS1-mediated active DNA demethylation requires MET18-dependent transfer of the iron-sulfur cluster, highlighting an important role of the CIA pathway in epigenetic regulation.</p></div

MET18 physically associates with ROS1.

<p>A. Mass spectrometric analysis of MET18 affinity purification. Selected unique proteins co-purified from MET18-3FH transgenic plants but not from wild-type are indicated. B.Y2H assays of protein interactions between ROS1, MET18 and AE7. MET18-AE7 interaction served as a positive control. C. Split luciferase assay of interactions between ROS1 and MET18 or AE7 in <i>Arabidopsis</i> protoplasts confirmed that ROS1 interacts with MET18 and AE7. ROS1, MET18 and AE7 were transiently expressed in protoplasts by plasmids transfection. D. Split luciferase assay of protein interactions in <i>tobacco</i> leaves. The full-length and deletion forms of ROS1 proteins were designated with white boxes. The four conserved amino acids were designated with red line as iron-sulfur motif (blue dashed line). The photograph was taken at 3 day-post-infiltration.</p

Comparison of hyper-DMRs among <i>met18-3</i>, <i>ros1-4</i>, and <i>rdd</i> mutants.

<p>A. Venn diagram showing the numbers of hyper-DMRs that overlap among <i>met18-1</i> (Orange), <i>met18-2</i> (Green) and <i>ros1-4</i> (Blue). Box plots displaying the distribution patterns of average DNA methylation levels (CG, CHG and CHH) calculated from the corresponding overlapping or unique hyper-DMRs. B. Venn diagram showing the numbers of hyper-DMRs that overlap among <i>met18-1</i> (Orange), <i>met18-2</i> (Green) and <i>rdd</i> (Gray). Box plots displaying the distribution patterns of average DNA methylation levels (CG, CHG and CHH) calculated from the corresponding overlapping or unique hyper-DMRs.</p

Characterization of the <i>asi3-1</i> (<i>met18-3</i>) mutant.

<p>A. Root phenotypes of the <i>asi3-1</i> mutant on ½ MS medium containing 1% glucose or sucrose. Seedlings were photographed 14 days after germination. Col-0, <i>35S</i>::<i>SUC2</i>, and <i>ros1-13</i> were used as controls. B. Quantitative RT-PCR results showing the relative expression levels of <i>SUC2</i>, <i>NPTII</i>, and <i>HPTII</i> transgenes in <i>asi3-1</i> mutant and <i>35S</i>::<i>SUC2</i> seedlings. <i>ACTIN 2</i> was used as an internal control. C. Kanamycin-sensitivity assay. D. Map-based cloning of the <i>asi3-1</i> mutation. E. The gene model structure of the <i>AT5G48120</i> (<i>ASI3/MET18</i>) gene. A Q-to-stop codon mutation in the 142nd amino acid of the <i>AT5G48120</i> gene is in <i>asi3-1</i> (<i>met18-3</i>) mutant. Two other T-DNA insertion mutants are shown. The exon, intron, and UTR regions are marked by a black box, black line, and white box, respectively. F. Root phenotypes of the <i>MET18-3FH</i>/<i>asi3-1</i> transgenic lines. Several randomly selected transgenic plants in the T3 generation were grown on ½ MS medium containing 1% sucrose. Seedlings were photographed 12 days after germination. G. Quantitative RT-PCR results showing the <i>SUC2</i> transgene expression levels in <i>MET18-3FH</i> transgenic plants.</p

Epigenetic modification changes of the <i>35S</i>::<i>SUC2 transgene</i> promoter in <i>met18-3</i> mutant.

<p>A. Diagram of the <i>35S</i>::<i>SUC2</i> transgene and an IGB snapshot of DNA methylation levels in the promoter region in different cytosine contexts. The positions of primer pairs used in ChIP-qPCR are as labeled. B. DNA methylation levels in the promoter region of <i>35S</i>::<i>SUC2</i>. DNA methylation levels were quantified based on whole-genome bisulfite sequencing data. C. DNA methylation-sensitive PCR (Chop-PCR) results showing increased DNA methylation in <i>met18-3</i> and <i>ros1-13</i> mutants. Complementation with <i>MET18</i> genomic sequence rescued increased DNA methylation. Non-digested DNA was used as the control PCR template.</p

The iron-sulfur-binding motif is required for ROS1 enzymatic activity.

<p>A. Protein sequence alignment showing four highly conserved cysteine residues (red) among ROS1 family proteins in <i>Arabidopsis</i> and EndoIII and MutY in <i>E</i>. <i>coli</i>. Two other enzymatically important aspartic acid residues (blue) and lysine residues (green) are also labeled. Asterisks indicate the amino acids that were subjected to site-directed mutagenesis. B. DNA nicking activity assay. Purified recombinant ROS1 and its mutated forms were incubated with purified closed circular (CC) plasmid DNA (methylated and unmethylated). The reaction products were resolved by agarose gel electrophoresis. The quantity of nicks was estimated by the fraction of open circular (OC) plasmids. Unmethylated plasmids were used as a control. Purified MBP protein was used as a negative control to monitor background nuclease activity from <i>E</i>. <i>coli</i>. Coomassie brilliant blue (CBB)-stained SDS-PAGE gel showing the proper expression of purified wild-type and mutated ROS1 proteins. Equal amount of proteins were loaded.</p