Role of metabolically active hormones in the insulin resistance associated with short-term glucocorticoid treatment

BACKGROUND: The mechanisms by which glucocorticoid therapy promotes obesity and insulin resistance are incompletely characterized. Modulations of the metabolically active hormones, tumour necrosis factor alpha (TNF alpha), ghrelin, leptin and adiponectin are all implicated in the development of these cardiovascular risk factors. Little is known about the effects of short-term glucocorticoid treatment on levels of these hormones. RESEARCH METHODS AND PROCEDURES: Using a blinded, placebo-controlled approach, we randomised 25 healthy men (mean (SD) age: 24.2 (5.4) years) to 5 days of treatment with either placebo or oral dexamethasone 3 mg twice daily. Fasting plasma TNFα, ghrelin, leptin and adiponectin were measured before and after treatment. RESULTS: Mean changes in all hormones were no different between treatment arms, despite dexamethasone-related increases in body weight, blood pressure, HDL cholesterol and insulin. Changes in calculated indices of insulin sensitivity (HOMA-S, insulin sensitivity index) were strongly related to dexamethasone treatment (p < 0.001). DISCUSSION: Our data do not support a role for TNF alpha, ghrelin, leptin or adiponectin in the insulin resistance associated with short-term glucocorticoid treatment

Zebrafish hoxd4a Acts Upstream of meis1.1 to Direct Vasculogenesis, Angiogenesis and Hematopoiesis

10.1371/journal.pone.0058857PLoS ONE83

Interaction between NANOS2 and the CCR4-NOT Deadenylation Complex Is Essential for Male Germ Cell Development in Mouse

Nanos is one of the evolutionarily conserved proteins implicated in germ cell development and we have previously shown that it interacts with the CCR4-NOT deadenylation complex leading to the suppression of specific RNAs. However, the molecular mechanism and physiological significance of this interaction have remained elusive. In our present study, we identify CNOT1, a component of the CCR4-NOT deadenylation complex, as a direct factor mediating the interaction with NANOS2. We find that the first 10 amino acids (AAs) of NANOS2 are required for this binding. We further observe that a NANOS2 mutant lacking these first 10 AAs (NANOS2-ΔN10) fails to rescue defects in the Nanos2-null mouse. Our current data thus indicate that the interaction with the CCR4-NOT deadenylation complex is essential for NANOS2 function. In addition, we further demonstrate that NANOS2-ΔN10 can associate with specific mRNAs as well as wild-type NANOS2, suggesting the existence of other NANOS2-associated factor(s) that determine the specificity of RNA-binding independently of the CCR4-NOT deadenylation complex

TRY plant trait database - enhanced coverage and open access

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Associations between XPD Asp312Asn Polymorphism and Risk of Head and Neck Cancer: A Meta-Analysis Based on 7,122 Subjects

Background: To investigate the association between XPD Asp312Asn polymorphism and head and neck cancer risk through this meta-analysis. Methods: We performed a meta-analysis of 9 published case-control studies including 2,670 patients with head and neck cancer and 4,452 controls. An odds ratio (OR) with a 95 % confidence interval (CI) was applied to assess the association between XPD Asp312Asn polymorphism and head and neck cancer risk. Results: Overall, no significant association between XPD Asp312Asn polymorphism and head and neck cancer risk was found in this meta-analysis (Asn/Asn vs. Asp/Asp: OR = 0.95, 95%CI = 0.80–1.13, P = 0.550, Pheterogeneity = 0.126; Asp/Asn vs. Asp/Asp: OR = 1.11, 95%CI = 0.99–1.24, P = 0.065, P heterogeneity = 0.663; Asn/Asn+Asp/Asn vs. Asp/Asp: OR = 1.07, 95%CI = 0.97–1.19, P = 0.189, P heterogeneity = 0.627; Asn/Asn vs. Asp/Asp+Asp/Asn: OR = 0.87, 95%CI = 0.68–1.10, P = 0.243, Pheterogeneity = 0.089). In the subgroup analysis by HWE, ethnicity, and study design, there was still no significant association detected in all genetic models. Conclusions: This meta-analysis demonstrates that XPD Asp312Asn polymorphism may not be a risk factor for developing head and neck cancer

Post-transcriptional control of tumor cell autonomous metastatic potential by the CCR4-NOT deadenylase CNOT7

Accumulating evidence supports the role of an aberrant transcriptome as a driver of metastatic potential. Deadenylation is a general regulatory node for post-transcriptional control by microRNAs and other determinants of RNA stability. Previously, we demonstrated that the CCR4-NOT scaffold component Cnot2 is an inherited metastasis susceptibility gene. In this study, using orthotopic metastasis assays and genetically engineered mouse models, we show that one of the enzymatic subunits of the CCR4-NOT complex, Cnot7, is also a metastasis modifying gene. We demonstrate that higher expression of Cnot7 drives tumor cell autonomous metastatic potential, which requires its deadenylase activity. Furthermore, metastasis promotion by CNOT7 is dependent on interaction with CNOT1 and TOB1. CNOT7 ribonucleoprotein-immunoprecipitation (RIP) and integrated transcriptome wide analyses reveal that CNOT7-regulated transcripts are enriched for a tripartite 3’UTR motif bound by RNA-binding proteins known to complex with CNOT7, TOB1, and CNOT1. Collectively, our data support a model of CNOT7, TOB1, CNOT1, and RNA-binding proteins collectively exerting post-transcriptional control on a metastasis suppressive transcriptional program to drive tumor cell metastasis

Regulation of Translation in Haloarchaea: 5′- and 3′-UTRs Are Essential and Have to Functionally Interact In Vivo

Recently a first genome-wide analysis of translational regulation using prokaryotic species had been performed which revealed that regulation of translational efficiency plays an important role in haloarchaea. In fact, the fractions of genes under differential growth phase-dependent translational control in the two species Halobacterium salinarum and Haloferax volcanii were as high as in eukaryotes. However, nothing is known about the mechanisms of translational regulation in archaea. Therefore, two genes exhibiting opposing directions of regulation were selected to unravel the importance of untranslated regions (UTRs) for differential translational control in vivo

hElp3 Directly Modulates the Expression of HSP70 Gene in HeLa Cells via HAT Activity

Human Elongator complex, which plays a key role in transcript elongation in vitro assay, is incredibly similar in either components or function to its yeast counterpart. However, there are only a few studies focusing on its target gene characterization in vivo. We studied the effect of down-regulation of the human elongation protein 3 (hELP3) on the expression of HSP70 through antisense strategy. Transfecting antisense plasmid p1107 into HeLa cells highly suppressed hELP3 expression, and substantially reduced expression of HSP70 mRNA and protein. Furthermore, chromatin immunoprecipitation assay (ChIP Assay) revealed that hElp3 participates in the transcription elongation of HSPA1A in HeLa cells. Finally, complementation and ChIP Assay in yeast showed that hElp3 can not only complement the growth and slow activation of HSP70 (SSA3) gene transcription, but also directly regulates the transcription of SSA3. On the contrary, these functions are lost when the HAT domain is deleted from hElp3. These data suggest that hElp3 can regulate the transcription of HSP70 gene, and the HAT domain of hElp3 is essential for this function. These findings now provide novel insights and evidence of the functions of hELP3 in human cells

Functional Maps of Protein Complexes from Quantitative Genetic Interaction Data

Recently, a number of advanced screening technologies have allowed for the comprehensive quantification of aggravating and alleviating genetic interactions among gene pairs. In parallel, TAP-MS studies (tandem affinity purification followed by mass spectroscopy) have been successful at identifying physical protein interactions that can indicate proteins participating in the same molecular complex. Here, we propose a method for the joint learning of protein complexes and their functional relationships by integration of quantitative genetic interactions and TAP-MS data. Using 3 independent benchmark datasets, we demonstrate that this method is >50% more accurate at identifying functionally related protein pairs than previous approaches. Application to genes involved in yeast chromosome organization identifies a functional map of 91 multimeric complexes, a number of which are novel or have been substantially expanded by addition of new subunits. Interestingly, we find that complexes that are enriched for aggravating genetic interactions (i.e., synthetic lethality) are more likely to contain essential genes, linking each of these interactions to an underlying mechanism. These results demonstrate the importance of both large-scale genetic and physical interaction data in mapping pathway architecture and function