Patterns of subnet usage reveal distinct scales of regulation in the transcriptional regulatory network of Escherichia coli

The set of regulatory interactions between genes, mediated by transcription factors, forms a species' transcriptional regulatory network (TRN). By comparing this network with measured gene expression data one can identify functional properties of the TRN and gain general insight into transcriptional control. We define the subnet of a node as the subgraph consisting of all nodes topologically downstream of the node, including itself. Using a large set of microarray expression data of the bacterium Escherichia coli, we find that the gene expression in different subnets exhibits a structured pattern in response to environmental changes and genotypic mutation. Subnets with less changes in their expression pattern have a higher fraction of feed-forward loop motifs and a lower fraction of small RNA targets within them. Our study implies that the TRN consists of several scales of regulatory organization: 1) subnets with more varying gene expression controlled by both transcription factors and post-transcriptional RNA regulation, and 2) subnets with less varying gene expression having more feed-forward loops and less post-transcriptional RNA regulation.Comment: 14 pages, 8 figures, to be published in PLoS Computational Biolog

Platelets of patients with chronic kidney disease demonstrate deficient platelet reactivity in vitro

<p>Abstract</p> <p>Background</p> <p>In patients with chronic kidney disease studies focusing on platelet function and properties often are non-conclusive whereas only few studies use functional platelet tests. In this study we evaluated a recently developed functional flow cytometry based assay for the analysis of platelet function in chronic kidney disease.</p> <p>Methods</p> <p>Platelet reactivity was measured using flow cytometric analysis. Platelets in whole blood were triggered with different concentrations of agonists (TRAP, ADP, CRP). Platelet activation was quantified with staining for P-selectin, measuring the mean fluorescence intensity. Area under the curve and the concentration of half-maximal response were determined.</p> <p>Results</p> <p>We studied 23 patients with chronic kidney disease (9 patients with cardiorenal failure and 14 patients with end stage renal disease) and 19 healthy controls. Expression of P-selectin on the platelet surface measured as mean fluorescence intensity was significantly less in chronic kidney disease patients compared to controls after maximal stimulation with TRAP (9.7 (7.9-10.8) vs. 11.4 (9.2-12.2), P = 0.032), ADP (1.6 (1.2-2.1) vs. 2.6 (1.9-3.5), P = 0.002) and CRP (9.2 (8.5-10.8) vs. 11.5 (9.5-12.9), P = 0.004). Also the area under the curve was significantly different. There was no significant difference in half-maximal response between both groups.</p> <p>Conclusion</p> <p>In this study we found that patients with chronic kidney disease show reduced platelet reactivity in response of ADP, TRAP and CRP compared to controls. These results contribute to our understanding of the aberrant platelet function observed in patients with chronic kidney disease and emphasize the significance of using functional whole blood platelet activation assays.</p

Integrating Multiple Biomarkers of Fish Health: A Case Study of Fish Health in Ports

Biomarkers of fish health are recognised as valuable biomonitoring tools that inform on the impact of pollution on biota. The integration of a suite of biomarkers in a statistical analysis that better illustrates the effects of exposure to xenobiotics on living organisms is most informative; however, most published ecotoxicological studies base the interpretation of results on individual biomarkers rather than on the information they carry as a set. To compare the interpretation of results from individual biomarkers with an interpretation based on multivariate analysis, a case study was selected where fish health was examined in two species of fish captured in two ports located in Western Australia. The suite of variables selected included chemical analysis of white muscle, body condition index, liver somatic index (LSI), hepatic ethoxyresorufin-O-deethylase activity, serum sorbitol dehydrogenase activity, biliary polycyclic aromatic hydrocarbon metabolites, oxidative DNA damage as measured by serum 8-oxo-dG, and stress protein HSP70 measured on gill tissue. Statistical analysis of individual biomarkers suggested little consistent evidence of the effects of contaminants on fish health. However, when biomarkers were integrated as a set by principal component analysis, there was evidence that the health status of fish in Fremantle port was compromised mainly due to increased LSI and greater oxidative DNA damage in fish captured within the port area relative to fish captured at a remote site. The conclusions achieved using the integrated set of biomarkers show the importance of viewing biomarkers of fish health as a set of variables rather than as isolated biomarkers of fish health

OAS1 Polymorphisms Are Associated with Susceptibility to West Nile Encephalitis in Horses

West Nile virus, first identified within the United States in 1999, has since spread across the continental states and infected birds, humans and domestic animals, resulting in numerous deaths. Previous studies in mice identified the Oas1b gene, a member of the OAS/RNASEL innate immune system, as a determining factor for resistance to West Nile virus (WNV) infection. A recent case-control association study described mutations of human OAS1 associated with clinical susceptibility to WNV infection. Similar studies in horses, a particularly susceptible species, have been lacking, in part, because of the difficulty in collecting populations sufficiently homogenous in their infection and disease states. The equine OAS gene cluster most closely resembles the human cluster, with single copies of OAS1, OAS3 and OAS2 in the same orientation. With naturally occurring susceptible and resistant sub-populations to lethal West Nile encephalitis, we undertook a case-control association study to investigate whether, similar to humans (OAS1) and mice (Oas1b), equine OAS1 plays a role in resistance to severe WNV infection. We identified naturally occurring single nucleotide mutations in equine (Equus caballus) OAS1 and RNASEL genes and, using Fisher's Exact test, we provide evidence that mutations in equine OAS1 contribute to host susceptibility. Virtually all of the associated OAS1 polymorphisms were located within the interferon-inducible promoter, suggesting that differences in OAS1 gene expression may determine the host's ability to resist clinical manifestations associated with WNV infection

Common Variants at 10 Genomic Loci Influence Hemoglobin A(1C) Levels via Glycemic and Nonglycemic Pathways

OBJECTIVE-Glycated hemoglobin (HbA(1c)), used to monitor and diagnose diabetes, is influenced by average glycemia over a 2- to 3-month period. Genetic factors affecting expression, turnover, and abnormal glycation of hemoglobin could also be associated with increased levels of HbA(1c). We aimed to identify such genetic factors and investigate the extent to which they influence diabetes classification based on HbA(1c) levels.RESEARCH DESIGN AND METHODS-We studied associations with HbA(1c) in up to 46,368 nondiabetic adults of European descent from 23 genome-wide association studies (GWAS) and 8 cohorts with de novo genotyped single nucleotide polymorphisms (SNPs). We combined studies using inverse-variance meta-analysis and tested mediation by glycemia using conditional analyses. We estimated the global effect of HbA(1c) loci using a multilocus risk score, and used net reclassification to estimate genetic effects on diabetes screening.RESULTS-Ten loci reached genome-wide significant association with HbA(1c), including six new loci near FN3K (lead SNP/P value, rs1046896/P = 1.6 x 10(-26)), HFE (rs1800562/P = 2.6 x 10(-20)), TMPRSS6 (rs855791/P = 2.7 x 10(-14)), ANK1 (rs4737009/P = 6.1 x 10(-12)), SPTA1 (rs2779116/P = 2.8 x 10(-9)) and ATP11A/TUBGCP3 (rs7998202/P = 5.2 x 10(-9)), and four known HbA(1c) loci: HK1 (rs16926246/P = 3.1 x 10(-54)), MTNR1B (rs1387153/P = 4.0 X 10(-11)), GCK (rs1799884/P = 1.5 x 10(-20)) and G6PC2/ABCB11 (rs552976/P = 8.2 x 10(-18)). We show that associations with HbA(1c) are partly a function of hyperglycemia associated with 3 of the 10 loci (GCK, G6PC2 and MTNR1B). The seven nonglycemic loci accounted for a 0.19 (%HbA(1c)) difference between the extreme 10% tails of the risk score, and would reclassify similar to 2% of a general white population screened for diabetes with HbA(1c).CONCLUSIONS-GWAS identified 10 genetic loci reproducibly associated with HbA(1c). Six are novel and seven map to loci where rarer variants cause hereditary anemias and iron storage disorders. Common variants at these loci likely influence HbA(1c) levels via erythrocyte biology, and confer a small but detectable reclassification of diabetes diagnosis by HbA(1c) Diabetes 59: 3229-3239, 201

An organoid biobank for childhood kidney cancers that captures disease and tissue heterogeneity

Kidney tumours are among the most common solid tumours in children, comprising distinct subtypes differing in many aspects, including cell-of-origin, genetics, and pathology. Pre-clinical cell models capturing the disease heterogeneity are currently lacking. Here, we describe the first paediatric cancer organoid biobank. It contains tumour and matching normal kidney organoids from over 50 children with different subtypes of kidney cancer, including Wilms tumours, malignant rhabdoid tumours, renal cell carcinomas, and congenital mesoblastic nephromas. Paediatric kidney tumour organoids retain key properties of native tumours, useful for revealing patient-specific drug sensitivities. Using single cell RNA-sequencing and high resolution 3D imaging, we further demonstrate that organoid cultures derived from Wilms tumours consist of multiple different cell types, including epithelial, stromal and blastemal-like cells. Our organoid biobank captures the heterogeneity of paediatric kidney tumours, providing a representative collection of well-characterised models for basic cancer research, drug-screening and personalised medicine