Rhizosphere shapes the associations between protistan predators and bacteria within microbiomes through the deterministic selection on bacterial communities

The assembly of bacterial communities in the rhizosphere is well-documented and plays a crucial role in supporting plant performance. However, we have limited knowledge of how plant rhizosphere determines the assembly of protistan predators and whether the potential associations between protistan predators and bacterial communities shift due to rhizosphere selection. To address this, we examined bacterial and protistan taxa from 443 agricultural soil samples including bulk and rhizosphere soils. Our results presented distinct patterns of bacteria and protistan predators in rhizosphere microbiome assembly. Community assembly of protistan predators was determined by a stochastic process in the rhizosphere and the diversity of protistan predators was reduced in the rhizosphere compared to bulk soils, these may be attributed to the indirect impacts from the altered bacterial communities that showed deterministic process assembly in the rhizosphere. Interestingly, we observed that the plant rhizosphere facilitates more close interrelationships between protistan predators and bacterial communities, which might promote a healthy rhizosphere microbial community for plant growth. Overall, our findings indicate that the potential predator–prey relationships within the microbiome, mediated by plant rhizosphere, might contribute to plant performance in agricultural ecosystems

Genome-wide association meta-analyses and fine-mapping elucidate pathways influencing albuminuria

Abstract: Increased levels of the urinary albumin-to-creatinine ratio (UACR) are associated with higher risk of kidney disease progression and cardiovascular events, but underlying mechanisms are incompletely understood. Here, we conduct trans-ethnic (n = 564,257) and European-ancestry specific meta-analyses of genome-wide association studies of UACR, including ancestry- and diabetes-specific analyses, and identify 68 UACR-associated loci. Genetic correlation analyses and risk score associations in an independent electronic medical records database (n = 192,868) reveal connections with proteinuria, hyperlipidemia, gout, and hypertension. Fine-mapping and trans-Omics analyses with gene expression in 47 tissues and plasma protein levels implicate genes potentially operating through differential expression in kidney (including TGFB1, MUC1, PRKCI, and OAF), and allow coupling of UACR associations to altered plasma OAF concentrations. Knockdown of OAF and PRKCI orthologs in Drosophila nephrocytes reduces albumin endocytosis. Silencing fly PRKCI further impairs slit diaphragm formation. These results generate a priority list of genes and pathways for translational research to reduce albuminuria

Target genes, variants, tissues and transcriptional pathways influencing human serum urate levels.

Elevated serum urate levels cause gout and correlate with cardiometabolic diseases via poorly understood mechanisms. We performed a trans-ancestry genome-wide association study of serum urate in 457,690 individuals, identifying 183 loci (147 previously unknown) that improve the prediction of gout in an independent cohort of 334,880 individuals. Serum urate showed significant genetic correlations with many cardiometabolic traits, with genetic causality analyses supporting a substantial role for pleiotropy. Enrichment analysis, fine-mapping of urate-associated loci and colocalization with gene expression in 47 tissues implicated the kidney and liver as the main target organs and prioritized potentially causal genes and variants, including the transcriptional master regulators in the liver and kidney, HNF1A and HNF4A. Experimental validation showed that HNF4A transactivated the promoter of ABCG2, encoding a major urate transporter, in kidney cells, and that HNF4A p.Thr139Ile is a functional variant. Transcriptional coregulation within and across organs may be a general mechanism underlying the observed pleiotropy between urate and cardiometabolic traits.The Genotype-Tissue Expression (GTEx) Project was supported by the Common Fund of the Office of the Director of the National Institutes of Health, and by NCI, NHGRI, NHLBI, NIDA, NIMH, and NINDS. Variant annotation was supported by software resources provided via the Caché Campus program of the InterSystems GmbH to Alexander Teumer

Genome-wide association meta-analyses and fine-mapping elucidate pathways influencing albuminuria

Publisher Copyright: © 2019, The Author(s).Increased levels of the urinary albumin-to-creatinine ratio (UACR) are associated with higher risk of kidney disease progression and cardiovascular events, but underlying mechanisms are incompletely understood. Here, we conduct trans-ethnic (n = 564,257) and European-ancestry specific meta-analyses of genome-wide association studies of UACR, including ancestry- and diabetes-specific analyses, and identify 68 UACR-associated loci. Genetic correlation analyses and risk score associations in an independent electronic medical records database (n = 192,868) reveal connections with proteinuria, hyperlipidemia, gout, and hypertension. Fine-mapping and trans-Omics analyses with gene expression in 47 tissues and plasma protein levels implicate genes potentially operating through differential expression in kidney (including TGFB1, MUC1, PRKCI, and OAF), and allow coupling of UACR associations to altered plasma OAF concentrations. Knockdown of OAF and PRKCI orthologs in Drosophila nephrocytes reduces albumin endocytosis. Silencing fly PRKCI further impairs slit diaphragm formation. These results generate a priority list of genes and pathways for translational research to reduce albuminuria.Peer reviewe

Genome-wide association meta-analyses and fine-mapping elucidate pathways influencing albuminuria

Increased levels of the urinary albumin-to-creatinine ratio (UACR) are associated with higher risk of kidney disease progression and cardiovascular events, but underlying mechanisms are incompletely understood. Here, we conduct trans-ethnic (n = 564,257) and European-ancestry specific meta-analyses of genome-wide association studies of UACR, including ancestry- and diabetes-specific analyses, and identify 68 UACR-associated loci. Genetic correlation analyses and risk score associations in an independent electronic medical records database (n = 192,868) reveal connections with proteinuria, hyperlipidemia, gout, and hypertension. Fine-mapping and trans-Omics analyses with gene expression in 47 tissues and plasma protein levels implicate genes potentially operating through differential expression in kidney (including TGFB1, MUC1, PRKCI, and OAF), and allow coupling of UACR associations to altered plasma OAF concentrations. Knockdown of OAF and PRKCI orthologs in Drosophila nephrocytes reduces albumin endocytosis. Silencing fly PRKCI further impairs slit diaphragm formation. These results generate a priority list of genes and pathways for translational research to reduce albuminuria

An RNA-sequencing-based transcriptome for a significantly prognostic novel driver signature identification in bladder urothelial carcinoma

Bladder cancer (BC) is the ninth most common malignancy worldwide. Bladder urothelial carcinoma (BLCA) constitutes more than 90% of bladder cancer (BC). The five-year survival rate is 5–70%, and patients with BLCA have a poor clinical outcome. The identification of novel clinical molecular markers in BLCA is still urgent to allow for predicting clinical outcomes. This study aimed to identify a novel signature integrating the three-dimension transcriptome of protein coding genes, long non-coding RNAs, microRNAs that is related to the overall survival of patients with BLCA, contributing to earlier prediction and effective treatment selection, as well as to the verification of the established model in the subtypes identified. Gene expression profiling and the clinical information of 400 patients diagnosed with BLCA were retrieved from The Cancer Genome Atlas (TCGA) database. A univariate Cox regression analysis, robust likelihood-based survival modelling analysis and random forests for survival regression and classification algorithms were used to identify the critical biomarkers. A multivariate Cox regression analysis was utilized to construct a risk score formula with a maximum area under the curve (AUC = 0.7669 in the training set). The significant signature could classify patients into high-risk and low-risk groups with significant differences in overall survival time. Similar results were confirmed in the test set (AUC = 0.645) and in the entire set (AUC = 0.710). The multivariate Cox regression analysis indicated that the five-RNA signature was an independent predictive factor for patients with BLCA. Non-negative matrix factorization and a similarity network fusion algorithm were applied for identifying three molecular subtypes. The signature could separate patients in every subtype into high- and low- groups with a distinct difference. Gene set variation analysis of protein-coding genes associated with the five prognostic RNAs demonstrated that the co-expressed protein-coding genes were involved in the pathways and biological process of tumourigenesis. The five-RNA signature could serve as to some degree a reliable independent signature for predicting outcome in patients with BLCA

A transcriptional co-expression network-based approach to identify prognostic biomarkers in gastric carcinoma

Background Gastric carcinoma is a very diverse disease. The progression of gastric carcinoma is influenced by complicated gene networks. This study aims to investigate the actual and potential prognostic biomarkers related to survival in gastric carcinoma patients to further our understanding of tumor biology. Methods A weighted gene co-expression network analysis was performed with a transcriptome dataset to identify networks and hub genes relevant to gastric carcinoma prognosis. Data was obtained from 300 primary gastric carcinomas (GSE62254). A validation dataset (GSE34942 and GSE15459) and TCGA dataset confirmed the results. Gene ontology, the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, and gene set enrichment analysis (GSEA) were performed to identify the clusters responsible for the biological processes and pathways of this disease. Results A brown transcriptional module enriched in the organizational process of the extracellular matrix was significantly correlated with overall survival (HR = 1.586, p = 0.005, 95% CI [1.149–2.189]) and disease-free survival (HR = 1.544, p = 0.008, 95% CI [1.119–2.131]). These observations were confirmed in the validation dataset (HR = 1.664, p = 0.006, 95% CI [1.155–2.398] in overall survival). Ten hub genes were identified and confirmed in the validation dataset from this brown module; five key biomarkers (COL8A1, FRMD6, TIMP2, CNRIP1 and GPR124 (ADGRA2)) were identified for further research in microsatellite instability (MSI) and epithelial-tomesenchymal transition (MSS/EMT) gastric carcinoma molecular subtypes. A high expression of these genes indicated a poor prognosis. Conclusion A transcriptional co-expression network-based approach was used to identify prognostic biomarkers in gastric carcinoma. This method may have potential for use in personalized therapies, however, large-scale randomized controlled clinical trials and replication experiments are needed before these key biomarkers can be applied clinically

Polypeptides Micelles Composed of Methoxy-Poly(Ethylene Glycol)-Poly(<span style="font-variant: small-caps">l</span>-Glutamic Acid)-Poly(<span style="font-variant: small-caps">l</span>-Phenylalanine) Triblock Polymer for Sustained Drug Delivery

Methoxy-poly(ethylene glycol)-poly(l-glutamic acid)-poly(l-phenylalanine) triblock polymers with different architecture were synthesized as drug carrier to obtain sustained and controlled release by tuning the composition. These triblock polymers were prepared by ring opening polymerization and poly(ethylene glycol) was used as an initiator. Polymerization was confirmed by 1H NMR, FT-IR and gel penetration chromatography. The polymers can self-assemble to form micelles in aqueous medium and their critical micelle concentrations values were examined. The micelles were spherical shape with size of 50&#8315;100 nm and especially can arranged in a regular manner. Sorafenib was selected as the model drug and the drug loading performance was dependent on the composition of the block copolymer. In vitro drug release indicated that the polymers can realize controlled and sustained drug release. Furthermore, in vitro cytotoxicity assay showed that the polymers were biocompatible and the drug-loaded micelles can increase toxicity towards tumor cells. Confocal fluorescence microscopy assays illustrated that the micelles can be uptaken quickly and release drug persistently to inhibit tumor cell growth

Improved light extraction efficiency of GaN-based flip-chip light-emitting diodes with

GaN-based flip-chip light-emitting diodes (FC-LEDs) grown on nanopatterned sapphire substrates (NPSS) are fabricated using self-assembled SiO2 nanospheres as masks during inductively coupled plasma etching. By controlling the pattern spacing, epitaxial GaN can be grown from the top or bottom of patterns to obtain two different GaN/substrate interfaces. The optoelectronic characteristics of FC-LED chips with different GaN/sapphire interfaces are studied. The FC-LED with an antireflective interface layer consisting of a NPSS with GaN in the pattern spacings demonstrates better optical properties than the FC-LED with an interface embedded with air voids. Our study indicates that the two types of FC-LEDs grown on NPSS show higher crystal quality and improved electrical and optical characteristics compared with those of FC-LEDs grown on conventional planar sapphire substrates

High-resistive layers obtained through periodic growth and in situ annealing of InGaN by metalorganic chemical vapor deposition

High-resistive layers were obtained by periodic growth and in situ annealing of InGaN. The effect of the annealing temperature of InGaN on the indium content and the material sheet resistive was investigated. The indium content decreased as the increase of in situ annealing temperature. Additionally, the material sheet resistance increased with the increase of the in situ annealing temperature for the annealed samples and reached 2 × 1010Ω/sq in the light and 2 × 1011Ω/sq in the dark when the in situ annealing temperature reached 970∘C. The acquirement of high-resistive layers is attributed to the generation of indium vacancy-related defects. Introducing indium vacancy-related defects to compensate background carriers can be an effective method to grow high-resistance material