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Molecular Biology Reports - The largest protein of the nuclear envelope (NE) is Nesprin-1 which forms a network along the NE interacting with actin, Emerin, Lamin, and SUN proteins. Mutations in...  相似文献   
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Although metagenomics has been previously employed for pathogen discovery, its cost and complexity have prevented its use as a practical front-line diagnostic for unknown infectious diseases. Here we demonstrate the utility of two metagenomics-based strategies, a pan-viral microarray (Virochip) and deep sequencing, for the identification and characterization of 2009 pandemic H1N1 influenza A virus. Using nasopharyngeal swabs collected during the earliest stages of the pandemic in Mexico, Canada, and the United States (n = 17), the Virochip was able to detect a novel virus most closely related to swine influenza viruses without a priori information. Deep sequencing yielded reads corresponding to 2009 H1N1 influenza in each sample (percentage of aligned sequences corresponding to 2009 H1N1 ranging from 0.0011% to 10.9%), with up to 97% coverage of the influenza genome in one sample. Detection of 2009 H1N1 by deep sequencing was possible even at titers near the limits of detection for specific RT-PCR, and the percentage of sequence reads was linearly correlated with virus titer. Deep sequencing also provided insights into the upper respiratory microbiota and host gene expression in response to 2009 H1N1 infection. An unbiased analysis combining sequence data from all 17 outbreak samples revealed that 90% of the 2009 H1N1 genome could be assembled de novo without the use of any reference sequence, including assembly of several near full-length genomic segments. These results indicate that a streamlined metagenomics detection strategy can potentially replace the multiple conventional diagnostic tests required to investigate an outbreak of a novel pathogen, and provide a blueprint for comprehensive diagnosis of unexplained acute illnesses or outbreaks in clinical and public health settings.  相似文献   
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Obesity is associated with increased breast cancer (BrCA) incidence. Considering that inactivation of estrogen receptor (ER)α promotes obesity and metabolic dysfunction in women and female mice, understanding the mechanisms and tissue-specific sites of ERα action to combat metabolic-related disease, including BrCA, is of clinical importance. To study the role of ERα in adipose tissue we generated fat-specific ERα knock-out (FERKO) mice. Herein we show that ERα deletion increased adipocyte size, fat pad weight, and tissue expression and circulating levels of the secreted glycoprotein, lipocalin 2 (Lcn2), an adipokine previously associated with BrCA development. Chromatin immunoprecipitation and luciferase reporter studies showed that ERα binds the Lcn2 promoter to repress its expression. Because adipocytes constitute an important cell type of the breast microenvironment, we examined the impact of adipocyte ERα deletion on cancer cell behavior. Conditioned medium from ERα-null adipocytes and medium containing pure Lcn2 increased proliferation and migration of a subset of BrCA cells in culture. The proliferative and promigratory effects of ERα-deficient adipocyte-conditioned medium on BrCA cells was reversed by Lcn2 deletion. BrCA cell responsiveness to exogenous Lcn2 was heightened in cell types where endogenous Lcn2 expression was minimal, but components of the Lcn2 signaling pathway were enriched, i.e. SLC22A17 and 3-hydroxybutyrate dehydrogenase (BDH2). In breast tumor biopsies from women diagnosed with BrCA we found that BDH2 expression was positively associated with adiposity and circulating Lcn2 levels. Collectively these data suggest that reduction of ERα expression in adipose tissue promotes adiposity and is linked with the progression and severity of BrCA via increased adipocyte-specific Lcn2 production and enhanced tumor cell Lcn2 sensitivity.  相似文献   
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