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Epigenetic dysregulation contributes to the high cardiovascular disease burden in chronic kidney disease (CKD) patients. Although microRNAs (miRNAs) are central epigenetic regulators, which substantially affect the development and progression of cardiovascular disease (CVD), no data on miRNA dysregulation in CKD-associated CVD are available until now. We now performed high-throughput miRNA sequencing of peripheral blood mononuclear cells from ten clinically stable hemodialysis (HD) patients and ten healthy controls, which allowed us to identify 182 differentially expressed miRNAs (e.g., miR-21, miR-26b, miR-146b, miR-155). To test biological relevance, we aimed to connect miRNA dysregulation to differential gene expression. Genome-wide gene expression profiling by MACE (Massive Analysis of cDNA Ends) identified 80 genes to be differentially expressed between HD patients and controls, which could be linked to cardiovascular disease (e.g., KLF6, DUSP6, KLF4), to infection / immune disease (e.g., ZFP36, SOCS3, JUND), and to distinct proatherogenic pathways such as the Toll-like receptor signaling pathway (e.g., IL1B, MYD88, TICAM2), the MAPK signaling pathway (e.g., DUSP1, FOS, HSPA1A), and the chemokine signaling pathway (e.g., RHOA, PAK1, CXCL5). Formal interaction network analysis proved biological relevance of miRNA dysregulation, as 68 differentially expressed miRNAs could be connected to 47 reciprocally expressed target genes. Our study is the first comprehensive miRNA analysis in CKD that links dysregulated miRNA expression with differential expression of genes connected to inflammation and CVD. After recent animal data suggested that targeting miRNAs is beneficial in experimental CVD, our data may now spur further research in the field of CKD-associated human CVD.
The project focuses on the efficiency of combined technologies to reduce the release of micropollutants and bacteria into surface waters via sewage treatment plants of different size and via stormwater overflow basins of different types. As a model river in a highly populated catchment area, the river Schussen and, as a control, the river Argen, two tributaries of Lake Constance, Southern Germany, are under investigation in this project. The efficiency of the different cleaning technologies is monitored by a wide range of exposure and effect analyses including chemical and microbiological techniques as well as effect studies ranging from molecules to communities.
Background: The rationale for gathering information from plants procuring nitrogen through symbiotic interactions controlled by a common genetic program for a sustainable biofuel production is the high energy demanding application of synthetic nitrogen fertilizers. We curated sequence information publicly available for the biofuel plant sugarcane, performed an analysis of the common SYM pathway known to control symbiosis in other plants, and provide results, sequences and literature links as an online database.
Methods: Sugarcane sequences and informations were downloaded from the nucEST database, cleaned and trimmed with seqclean, assembled with TGICL plus translating mapping method, and annotated. The annotation is based on BLAST searches against a local formatted plant Uniprot90 generated with CD-HIT for functional assignment, rpsBLAST to CDD database for conserved domain analysis, and BLAST search to sorghum's for Gene Ontology (GO) assignment. Gene expression was normalized according the Unigene standard, presented as ESTs/100 kb. Protein sequences known in the SYM pathway were used as queries to search the SymGRASS sequence database. Additionally, antimicrobial peptides described in the PhytAMP database served as queries to retrieve and generate expression profiles of these defense genes in the libraries compared to the libraries obtained under symbiotic interactions.
Results: We describe the SymGRASS, a database of sugarcane orthologous genes involved in arbuscular mycorrhiza (AM) and root nodule (RN) symbiosis. The database aggregates knowledge about sequences, tissues, organ, developmental stages and experimental conditions, and provides annotation and level of gene expression for sugarcane transcripts and SYM orthologous genes in sugarcane through a web interface. Several candidate genes were found for all nodes in the pathway, and interestingly a set of symbiosis specific genes was found.
Conclusions: The knowledge integrated in SymGRASS may guide studies on molecular, cellular and physiological mechanisms by which sugarcane controls the establishment and efficiency of endophytic associations. We believe that the candidate sequences for the SYM pathway together with the pool of exclusively expressed tentative consensus (TC) sequences are crucial for the design of molecular studies to unravel the mechanisms controlling the establishment of symbioses in sugarcane, ultimately serving as a basis for the improvement of grass crops.