Elevated TAK1 augments tumor growth and metastatic capacities of ovarian cancer cells through activation of NF-κB signaling

Transforming growth factor (TGF)-β-activating kinase 1 (TAK1) is a serine/threonine kinase which is frequently associated with human cancer progression. However, its functional role in tumorigenesis is still controversial. Here, we report that TAK1 enhances the oncogenic capacity of ovarian cancer cells through the activation of NF-κB signaling. We found that TAK1 is frequently upregulated and significantly associated with high-grade and metastatic ovarian cancers. Mechanistic studies showed that Ser412 phosphorylation is required for TAK1 in activating NF-κB signaling and promotes aggressiveness of ovarian cancer cells. Conversely, suppression of TAK1 activity by point mutation at Ser412, RNAi mediated gene knockdown or TAK1 specific inhibitor ((5Z) -7-Oxozeaenol) remarkably impairs tumor growth and metastasis in ovarian cancer in vitro and in vivo. Our study underscores the importance of targeting TAK1 as a promising therapeutic approach to counteract the ovarian cancer progression.published_or_final_versio

Elevated TAK1 augments tumor growth and metastatic capacities of ovarian cancer cells through activation of NF-κB signaling

Transforming growth factor (TGF)-β-activating kinase 1 (TAK1) is a serine/threonine kinase which is frequently associated with human cancer progression. However, its functional role in tumorigenesis is still controversial. Here, we report that TAK1 enhances the oncogenic capacity of ovarian cancer cells through the activation of NF-κB signaling. We found that TAK1 is frequently upregulated and significantly associated with high-grade and metastatic ovarian cancers. Mechanistic studies showed that Ser412 phosphorylation is required for TAK1 in activating NF-κB signaling and promotes aggressiveness of ovarian cancer cells. Conversely, suppression of TAK1 activity by point mutation at Ser412, RNAi mediated gene knockdown or TAK1 specific inhibitor ((5Z) -7-Oxozeaenol) remarkably impairs tumor growth and metastasis in ovarian cancer in vitro and in vivo. Our study underscores the importance of targeting TAK1 as a promising therapeutic approach to counteract the ovarian cancer progression.published_or_final_versio

Observation of anomalous decoherence effect in a quantum bath at room temperature

Decoherence of quantum objects is critical to modern quantum sciences and technologies. It is generally believed that stronger noises cause faster decoherence. Strikingly, recent theoretical research discovers the opposite case for spins in quantum baths. Here we report experimental observation of the anomalous decoherence effect for the electron spin-1 of a nitrogen-vacancy centre in high-purity diamond at room temperature. We demonstrate that under dynamical decoupling, the double-transition can have longer coherence time than the single-transition, even though the former couples to the nuclear spin bath as twice strongly as the latter does. The excellent agreement between the experimental and the theoretical results confirms the controllability of the weakly coupled nuclear spins in the bath, which is useful in quantum information processing and quantum metrology.Comment: 22 pages, related paper at http://arxiv.org/abs/1102.557

The genome and transcriptome of Trichormus sp NMC-1: insights into adaptation to extreme environments on the Qinghai-Tibet Plateau

The Qinghai-Tibet Plateau (QTP) has the highest biodiversity for an extreme environment worldwide, and provides an ideal natural laboratory to study adaptive evolution. In this study, we generated a draft genome sequence of cyanobacteria Trichormus sp. NMC-1 in the QTP and performed whole transcriptome sequencing under low temperature to investigate the genetic mechanism by which T. sp. NMC-1 adapted to the specific environment. Its genome sequence was 5.9 Mb with a G+C content of 39.2% and encompassed a total of 5362 CDS. A phylogenomic tree indicated that this strain belongs to the Trichormus and Anabaena cluster. Genome comparison between T. sp. NMC-1 and six relatives showed that functionally unknown genes occupied a much higher proportion (28.12%) of the T. sp. NMC-1 genome. In addition, functions of specific, significant positively selected, expanded orthogroups, and differentially expressed genes involved in signal transduction, cell wall/membrane biogenesis, secondary metabolite biosynthesis, and energy production and conversion were analyzed to elucidate specific adaptation traits. Further analyses showed that the CheY-like genes, extracellular polysaccharide and mycosporine-like amino acids might play major roles in adaptation to harsh environments. Our findings indicate that sophisticated genetic mechanisms are involved in cyanobacterial adaptation to the extreme environment of the QTP

On-line optimization of glutamate production based on balanced metabolic control by RQ

In glutamate fermentations by Corynebacterium glutamicum, higher glutamate concentration could be achieved by constantly controlling dissolved oxygen concentration (DO) at a lower level; however, by-product lactate also severely accumulated. The results of analyzing activities changes of the two key enzymes, glutamate and lactate dehydrogenases involved with the fermentation, and the entire metabolic network flux analysis showed that the lactate overproduction was because the metabolic flux in TCA cycle was too low to balance the glucose glycolysis rate. As a result, the respiratory quotient (RQ) adaptive control based “balanced metabolic control” (BMC) strategy was proposed and used to regulate the TCA metabolic flux rate at an appropriate level to achieve the metabolic balance among glycolysis, glutamate synthesis, and TCA metabolic flux. Compared with the best results of various DO constant controls, the BMC strategy increased the maximal glutamate concentration by about 15% and almost completely repressed the lactate accumulation with competitively high glutamate productivity

Comparison of Ion Balance and Nitrogen Metabolism in Old and Young Leaves of Alkali-Stressed Rice Plants

BACKGROUND: Alkali stress is an important agricultural contaminant and has complex effects on plant metabolism. The aim of this study was to investigate whether the alkali stress has different effects on the growth, ion balance, and nitrogen metabolism in old and young leaves of rice plants, and to compare functions of both organs in alkali tolerance. METHODOLOGY/PRINCIPAL FINDINGS: The results showed that alkali stress only produced a small effect on the growth of young leaves, whereas strongly damaged old leaves. Rice protected young leaves from ion harm via the large accumulation of Na(+) and Cl(-) in old leaves. The up-regulation of OsHKT1;1, OsAKT1, OsHAK1, OsHAK7, OsHAK10 and OsHAK16 may contribute to the larger accumulation of Na(+) in old leaves under alkali stress. Alkali stress mightily reduced the NO(3)(-) contents in both organs. As old leaf cells have larger vacuole, under alkali stress these scarce NO(3)(-) was principally stored in old leaves. Accordingly, the expression of OsNRT1;1 and OsNRT1;2 in old leaves was up-regulated by alkali stress, revealing that the two genes might contribute to the accumulation of NO(3)(-) in old leaves. NO(3)(-) deficiency in young leaves under alkali stress might induce the reduction in OsNR1 expression and the subsequent lacking of NH(4)(+), which might be main reason for the larger down-regulation of OsFd-GOGAT and OsGS2 in young leaves. CONCLUSIONS/SIGNIFICANCE: Our results strongly indicated that, during adaptation of rice to alkali stress, young and old leaves have distinct mechanisms of ion balance and nitrogen metabolism regulation. We propose that the comparative studies of young and old tissues may be important for abiotic stress tolerance research

Effects of Thyroxine Exposure on Osteogenesis in Mouse Calvarial Pre-Osteoblasts

The incidence of craniosynostosis is one in every 1,800-2500 births. The gene-environment model proposes that if a genetic predisposition is coupled with environmental exposures, the effects can be multiplicative resulting in severely abnormal phenotypes. At present, very little is known about the role of gene-environment interactions in modulating craniosynostosis phenotypes, but prior evidence suggests a role for endocrine factors. Here we provide a report of the effects of thyroid hormone exposure on murine calvaria cells. Murine derived calvaria cells were exposed to critical doses of pharmaceutical thyroxine and analyzed after 3 and 7 days of treatment. Endpoint assays were designed to determine the effects of the hormone exposure on markers of osteogenesis and included, proliferation assay, quantitative ALP activity assay, targeted qPCR for mRNA expression of Runx2, Alp, Ocn, and Twist1, genechip array for 28,853 targets, and targeted osteogenic microarray with qPCR confirmations. Exposure to thyroxine stimulated the cells to express ALP in a dose dependent manner. There were no patterns of difference observed for proliferation. Targeted RNA expression data confirmed expression increases for Alp and Ocn at 7 days in culture. The genechip array suggests substantive expression differences for 46 gene targets and the targeted osteogenesis microarray indicated 23 targets with substantive differences. 11 gene targets were chosen for qPCR confirmation because of their known association with bone or craniosynostosis (Col2a1, Dmp1, Fgf1, 2, Igf1, Mmp9, Phex, Tnf, Htra1, Por, and Dcn). We confirmed substantive increases in mRNA for Phex, FGF1, 2, Tnf, Dmp1, Htra1, Por, Igf1 and Mmp9, and substantive decreases for Dcn. It appears thyroid hormone may exert its effects through increasing osteogenesis. Targets isolated suggest a possible interaction for those gene products associated with calvarial suture growth and homeostasis as well as craniosynostosis. © 2013 Cray et al

Cross-Platform Comparison of Microarray-Based Multiple-Class Prediction

High-throughput microarray technology has been widely applied in biological and medical decision-making research during the past decade. However, the diversity of platforms has made it a challenge to re-use and/or integrate datasets generated in different experiments or labs for constructing array-based diagnostic models. Using large toxicogenomics datasets generated using both Affymetrix and Agilent microarray platforms, we carried out a benchmark evaluation of cross-platform consistency in multiple-class prediction using three widely-used machine learning algorithms. After an initial assessment of model performance on different platforms, we evaluated whether predictive signature features selected in one platform could be directly used to train a model in the other platform and whether predictive models trained using data from one platform could predict datasets profiled using the other platform with comparable performance. Our results established that it is possible to successfully apply multiple-class prediction models across different commercial microarray platforms, offering a number of important benefits such as accelerating the possible translation of biomarkers identified with microarrays to clinically-validated assays. However, this investigation focuses on a technical platform comparison and is actually only the beginning of exploring cross-platform consistency. Further studies are needed to confirm the feasibility of microarray-based cross-platform prediction, especially using independent datasets

Genome wide analysis of gene expression changes in skin from patients with type 2 diabetes

Non-healing chronic ulcers are a serious complication of diabetes and are a major healthcare problem. While a host of treatments have been explored to heal or prevent these ulcers from forming, these treatments have not been found to be consistently effective in clinical trials. An understanding of the changes in gene expression in the skin of diabetic patients may provide insight into the processes and mechanisms that precede the formation of non-healing ulcers. In this study, we investigated genome wide changes in gene expression in skin between patients with type 2 diabetes and non-diabetic patients using next generation sequencing. We compared the gene expression in skin samples taken from 27 patients (13 with type 2 diabetes and 14 non-diabetic). This information may be useful in identifying the causal factors and potential therapeutic targets for the prevention and treatment of diabetic related diseases

Hierarchical information clustering by means of topologically embedded graphs

We introduce a graph-theoretic approach to extract clusters and hierarchies in complex data-sets in an unsupervised and deterministic manner, without the use of any prior information. This is achieved by building topologically embedded networks containing the subset of most significant links and analyzing the network structure. For a planar embedding, this method provides both the intra-cluster hierarchy, which describes the way clusters are composed, and the inter-cluster hierarchy which describes how clusters gather together. We discuss performance, robustness and reliability of this method by first investigating several artificial data-sets, finding that it can outperform significantly other established approaches. Then we show that our method can successfully differentiate meaningful clusters and hierarchies in a variety of real data-sets. In particular, we find that the application to gene expression patterns of lymphoma samples uncovers biologically significant groups of genes which play key-roles in diagnosis, prognosis and treatment of some of the most relevant human lymphoid malignancies.Comment: 33 Pages, 18 Figures, 5 Table