Resolving the complete genome of Kuenenia stuttgartiensis from a membrane bioreactor enrichment using Single-Molecule Real-Time sequencing

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Single-nucleotide polymorphisms in the Toll-like receptor pathway increase susceptibility to infections in severely injured trauma patients

Background: Sepsis and subsequent multiple-organ failure are the predominant causes of late mortality in trauma patients. Susceptibility and response to infection is, in part, heritable. Single-nucleotide polymorphisms (SNPs) in Toll-like receptor (TLR) and cluster of differentiation 14 (CD14) genes of innate immunity may play a key role. The aim of this study was to assess if SNPs in TLR/CD14 predisposed trauma patients to infection. Methods: A prospective cohort of trauma patients (age 18-80 years; injury severity score [ISS] ≥ 16) admitted to a Level I trauma center between January 2008 and April 2011 was genotyped for SNPs in TLR2 (T-16934A and R753Q), TLR4 (D299G and T399I), TLR9 (T-1486C and T-1237C), and CD14 (C-159T) using high-resolution melting analysis. Association of genotype with prevalence of positive culture findings (gram positive, gram negative, fungi), systemic inflammatory response syndrome (SIRS), sepsis, septic shock, and mortality was tested with χ2and logistic regression analysis. Results: Genotyping was performed for 219 patients, of whom 51% developed positive culture findings in sputum, wounds, blood

Can subtle changes in gene expression be consistently detected with different microarray platforms?

Background: The comparability of gene expression data generated with different microarray platforms is still a matter of concern. Here we address the performance and the overlap in the detection of differentially expressed genes for five different microarray platforms in a challenging biological context where differences in gene expression are few and subtle. Results: Gene expression profiles in the hippocampus of five wild-type and five transgenic δC-doublecortin-like kinase mice were evaluated with five microarray platforms: Applied Biosystems, Affymetrix, Agilent, Illumina, LGTC home-spotted arrays. Using a fixed false discovery rate of 10% we detected surprising differences between the number of differentially expressed genes per platform. Four genes were selected by ABI, 130 by Affymetrix, 3,051 by Agilent, 54 by Illumina, and 13 by LGTC. Two genes were found significantly differentially expressed by all platforms and the four genes identified by the ABI platform were found by at least three other platforms. Quantitative RT-PCR analysis confirmed 20 out of 28 of the genes detected by two or more platforms and 8 out of 15 of the genes detected by Agilent only. We observed improved correlations between platforms when ranking the genes based on the significance level than with a fixed statistical cut-off. We demonstrate significant overlap in the affected gene sets identified by the different platforms, although biological processes were represented by only partially overlapping sets of genes. Aberrances in GABA-ergic signalling in the transgenic mice were consistently found by all platforms. Conclusion: The different microarray platforms give partially complementary views on biological processes affected. Our data indicate that when analyzing samples with only subtle differences in gene expression the use of two different platforms might be more attractive than increasing the number of replicates. Commercial two-color platforms seem to have higher power for finding differentially expressed genes between groups with small differences in expression

Combined vascular endothelial growth factor and TP53 status predicts poor response to tamoxifen therapy in estrogen receptor-positive advanced breast cancer

PURPOSE: In recent studies, we showed that TP53 gene mutation or high levels of cytosolic vascular endothelial growth factor (VEGF) in estrogen receptor (ER)-alpha-positive primary breast tumors predict a poor disease outcome for patients treated with first-line tamoxifen for advanced disease. Mutant TP53 may up-regulate VEGF, whereas, on the other hand, wild-type TP53 may decrease VEGF production. EXPERIMENTAL DESIGN: In the present study, we aimed to assess the combined predictive value of TP53 gene mutation and VEGF status of 160 advanced breast cancer patients with ER-positive tumors who were treated with tamoxifen (median follow-up from start of tamoxifen treatment, 64 months). To assess TP53 gene mutation status, the entire open reading frame was sequenced; for VEGF status, an ELISA was used. RESULTS: In univariate analysis, both TP53 gene mutation (28% of the tumors) and a VEGF level above the median value were significantly associated with a short progression-free survival, post-relapse overall survival, and a poor rate of response to tamoxifen. In Cox multivariate regression analysis including the traditional predictive factors, the addition of TP53 gene mutation and VEGF status, alone or in combination, significantly predicted a poor efficacy of tamoxifen treatment. When the two factors were combined, a significantly decreased odds ratio was seen for the rate of response (odds ratio, 0.27). Similarly, an increased hazard ratio (HR) was seen for progression-free survival (HR, 2.32) and post-relapse overall survival (HR, 1.68) in the group with mutant TP53 and high VEGF compared with the group with both risk factors absent. CONCLUSIONS: Combined TP53 gene mutation status and high VEGF levels of ER-positive primary breast tumors independently predict a poor course of the disease of patients with advanced breast cancer treated with tamoxifen. These patients, having unfavorable tumor characteristics, might benefit more from other types of (individualized) treatment protocols

Complete sequencing of TP53 predicts poor response to systemic therapy of advanced breast cancer

TP53 has been implicated in regulation of the cell cycle, DNA repair, and apoptosis. We studied, in primary breast tumors through direct cDNA sequencing of exons 2-11, whether TP53 gene mutations can predict response in patients with advanced disease to either first-line tamoxifen therapy (202 patients, of whom 55% responded) or up-front (poly)chemotherapy (41 patients, of whom 46% responded). TP53 mutations were detected in 90 of 243 (37%) tumors, and one-fourth of these mutations resulted in a premature termination of the protein. The mutations were observed in 32% (65 of 202) of the primary tumors of tamoxifen-treated patients and in 61% (25 of 41) of the primary tumors of the chemotherapy patients. TP53 mutation was significantly associated with a poor response to tamoxifen [31% versu

Transcriptional Profiling of Human Familial Longevity Indicates a Role for ASF1A and IL7R

The Leiden Longevity Study consists of families that express extended survival across generations, decreased morbidity in middle-age, and beneficial metabolic profiles. To identify which pathways drive this complex phenotype of familial longevity and healthy aging, we performed a genome-wide gene expression study within this cohort to screen for mRNAs whose expression changes with age and associates with longevity. We first compared gene expression profiles from whole blood samples between 50 nonagenarians and 50 middle-aged controls, resulting in identification of 2,953 probes that associated with age. Next, we determined which of these probes associated with longevity by comparing the offspring of the nonagenarians (50 subjects) and the middle-aged controls. The expression of 360 probes was found to change differentially with age in members of the long-lived families. In a RT-qPCR replication experiment utilizing 312 controls, 332 offspring and 79 nonagenarians, we confirmed a nonagenarian specific expression profile for 21 genes out of 25 tested. Since only some of the offspring will have inherited the beneficial longevity profile from their long-lived parents, the contrast between offspring and controls is expected to be weak. Despite this dilution of the longevity effects, reduced expression levels of two genes, ASF1A and IL7R, involved in maintenance of chromatin structure and the immune system, associated with familial longevity already in middle-age. The size of this association increased when controls were compared to a subfraction of the offspring that had the highest probability to age healthily and become long-lived according to beneficial metabolic parameters. In conclusion, an “aging-signature” formed of 21 genes was identified, of which reduced expression of ASF1A and IL7R marked familial longevity already in middle-age. This indicates that expression changes of genes involved in metabolism, epigenetic control and immune function occur as a function of age, and some of these, like ASF1A and IL7R, represent early features of familial longevity and healthy ageing

Deep sequencing-based expression analysis shows major advances in robustness, resolution and inter-lab portability over five microarray platforms

The hippocampal expression profiles of wild-type mice and mice transgenic for δC-doublecortin-like kinase were compared with Solexa/Illumina deep sequencing technology and five different microarray platforms. With Illumina's digital gene expression assay, we obtained ∼2.4 million sequence tags per sample, their abundance spanning four orders of magnitude. Results were highly reproducible, even across laboratories. With a dedicated Bayesian model, we found differential expression of 3179 transcripts with an estimated false-discovery rate of 8.5%. This is a much higher figure than found for microarrays. The overlap in differentially expressed transcripts found with deep sequencing and microarrays was most significant for Affymetrix. The changes in expression observed by deep sequencing were larger than observed by microarrays or quantitative PCR. Relevant processes such as calmodulin-dependent protein kinase activity and vesicle transport along microtubules were found affected by deep sequencing but not by microarrays. While undetectable by microarrays, antisense transcription was found for 51% of all genes and alternative polyadenylation for 47%. We conclude that deep sequencing provides a major advance in robustness, comparability and richness of expression profiling data and is expected to boost collaborative, comparative and integrative genomics studies

How much Florida can be found in Lower Saxony? On the empirical evidence of the “creative class” in a German territorial Federal State

Empirische Analysen zur Wirtschaftsgeographie der „Kreativen Klasse“ beschränken sich zumeist auf urbane Regionen. Der vorliegende Artikel testet drei von Richard Floridas Kernaussagen für das überwiegend nicht urban geprägte Bundesland Niedersachsen in Deutschland: die räumliche Verteilung der Mitglieder der „Kreativen Klasse“, ihr Binnenmigrationsmuster und ihre Gründungsmotive. Einige von Floridas Annahmen bestätigen sich auch für Niedersachsen, andere nicht. Politische Handlungsempfehlungen am Ende des Textes sollen helfen, die Wirkungen der Beschäftigungseffekte der „Kreativen Klasse“ auf die übrige Wirtschaft Niedersachsens zu steigern.Empirical results on the economic geography of the creative class are mainly restricted to urban areas. This paper tests three of Richard Florida’s ideas for the largely non-urban Federal State of Lower Saxony, Germany: the spatial distribution of creative class members, their internal migration pattern and their entrepreneurial motivation. Some of Florida’s assumptions hold true for Lower Saxony as well, while others do not. Recommendations for policy-makers are provided in order to increase the effects of creative class employment on the real economy in Lower Saxony and its regions