Varicella-Zoster viruses associated with post-herpetic neuralgia induce sodium current density increases in the ND7-23 Nav-1.8 neuroblastoma cell line

Post-herpetic neuralgia (PHN) is the most significant complication of herpes zoster caused by reactivation of latent Varicella-Zoster virus (VZV). We undertook a heterologous infection in vitro study to determine whether PHN-associated VZV isolates induce changes in sodium ion channel currents known to be associated with neuropathic pain. Twenty VZV isolates were studied blind from 11 PHN and 9 non-PHN subjects. Viruses were propagated in the MeWo cell line from which cell-free virus was harvested and applied to the ND7/23-Nav1.8 rat DRG x mouse neuroblastoma hybrid cell line which showed constitutive expression of the exogenous Nav 1.8, and endogenous expression of Nav 1.6 and Nav 1.7 genes all encoding sodium ion channels the dysregulation of which is associated with a range of neuropathic pain syndromes. After 72 hrs all three classes of VZV gene transcripts were detected in the absence of infectious virus. Single cell sodium ion channel recording was performed after 72 hr by voltage-clamping. PHN-associated VZV significantly increased sodium current amplitude in the cell line when compared with non-PHN VZV, wild-type (Dumas) or vaccine VZV strains ((POka, Merck and GSK). These sodium current increases were unaffected by acyclovir pre-treatment but were abolished by exposure to Tetrodotoxin (TTX) which blocks the TTX-sensitive fast Nav 1.6 and Nav 1.7 channels but not the TTX-resistant slow Nav 1.8 channel. PHN-associated VZV sodium current increases were therefore mediated in part by the Nav 1.6 and Nav 1.7 sodium ion channels. An additional observation was a modest increase in message levels of both Nav1.6 and Nav1.7 mRNA but not Nav 1.8 in PHN virally infected cells

Integrating Quantitative Knowledge into a Qualitative Gene Regulatory Network

Despite recent improvements in molecular techniques, biological knowledge remains incomplete. Any theorizing about living systems is therefore necessarily based on the use of heterogeneous and partial information. Much current research has focused successfully on the qualitative behaviors of macromolecular networks. Nonetheless, it is not capable of taking into account available quantitative information such as time-series protein concentration variations. The present work proposes a probabilistic modeling framework that integrates both kinds of information. Average case analysis methods are used in combination with Markov chains to link qualitative information about transcriptional regulations to quantitative information about protein concentrations. The approach is illustrated by modeling the carbon starvation response in Escherichia coli. It accurately predicts the quantitative time-series evolution of several protein concentrations using only knowledge of discrete gene interactions and a small number of quantitative observations on a single protein concentration. From this, the modeling technique also derives a ranking of interactions with respect to their importance during the experiment considered. Such a classification is confirmed by the literature. Therefore, our method is principally novel in that it allows (i) a hybrid model that integrates both qualitative discrete model and quantities to be built, even using a small amount of quantitative information, (ii) new quantitative predictions to be derived, (iii) the robustness and relevance of interactions with respect to phenotypic criteria to be precisely quantified, and (iv) the key features of the model to be extracted that can be used as a guidance to design future experiments

Transcriptomic Analysis Reveals Novel Mechanistic Insight into Murine Biological Responses to Multi-Walled Carbon Nanotubes in Lungs and Cultured Lung Epithelial Cells

There is great interest in substituting animal work with in vitro experimentation in human health risk assessment; however, there are only few comparisons of in vitro and in vivo biological responses to engineered nanomaterials. We used high-content genomics tools to compare in vivo pulmonary responses of multiwalled carbon nanotubes (MWCNT) to those in vitro in cultured lung epithelial cells (FE1) at the global transcriptomic level. Primary size, surface area and other properties of MWCNT- XNRI -7 (Mitsui7) were characterized using DLS, SEM and TEM. Mice were exposed via a single intratracheal instillation to 18, 54, or 162 μg of Mitsui7/mouse. FE1 cells were incubated with 12.5, 25 and 100 μg/ml of Mitsui7. Tissue and cell samples were collected at 24 hours post-exposure. DNA microarrays were employed to establish mechanistic differences and similarities between the two models. Microarray results were confirmed using gene-specific RT-qPCR. Bronchoalveolar lavage (BAL) fluid was assessed for indications of inflammation in vivo. A strong dose-dependent activation of acute phase and inflammation response was observed in mouse lungs reflective mainly of an inflammatory response as observed in BAL. In vitro, a wide variety of core cellular functions were affected including transcription, cell cycle, and cellular growth and proliferation. Oxidative stress, fibrosis and inflammation processes were altered in both models. Although there were similarities observed between the two models at the pathway-level, the specific genes altered under these pathways were different, suggesting that the underlying mechanisms of responses are different in cells in culture and the lung tissue. Our results suggest that careful consideration should be given in selecting relevant endpoints when substituting animal with in vitro testing

The p53HMM algorithm: using profile hidden markov models to detect p53-responsive genes

<p>Abstract</p> <p>Background</p> <p>A computational method (called p53HMM) is presented that utilizes Profile Hidden Markov Models (PHMMs) to estimate the relative binding affinities of putative p53 response elements (REs), both p53 single-sites and cluster-sites. These models incorporate a novel "Corresponded Baum-Welch" training algorithm that provides increased predictive power by exploiting the redundancy of information found in the repeated, palindromic p53-binding motif. The predictive accuracy of these new models are compared against other predictive models, including position specific score matrices (PSSMs, or weight matrices). We also present a new dynamic acceptance threshold, dependent upon a putative binding site's distance from the Transcription Start Site (TSS) and its estimated binding affinity. This new criteria for classifying putative p53-binding sites increases predictive accuracy by reducing the false positive rate.</p> <p>Results</p> <p>Training a Profile Hidden Markov Model with corresponding positions matching a combined-palindromic p53-binding motif creates the best p53-RE predictive model. The p53HMM algorithm is available on-line: <url>http://tools.csb.ias.edu</url></p> <p>Conclusion</p> <p>Using Profile Hidden Markov Models with training methods that exploit the redundant information of the homotetramer p53 binding site provides better predictive models than weight matrices (PSSMs). These methods may also boost performance when applied to other transcription factor binding sites.</p

The heparan sulfate sulfotransferase 3-OST3A (HS3ST3A) is a novel tumor regulator and a prognostic marker in breast cancer

International audienceHeparan sulfate (HS) proteoglycan chains are key components of the breast tumor microenvironment that critically influence the behavior of cancer cells. It is established that abnormal synthesis and processing of HS play a prominent role in tumorigenesis, albeit mechanisms remain mostly obscure. HS function is mainly controlled by sulfotransferases, and here we report a novel cellular and pathophysiological significance for the 3-O-sulfotransferase 3-OST3A (HS3ST3A), catalyzing the final maturation step of HS, in breast cancer. We show that 3-OST3A is epigenetically repressed in all breast cancer cell lines of a panel representative of distinct molecular subgroups, except in human epidermal growth factor receptor 2-positive (HER2+) sloan-kettering breast cancer (SKBR3) cells. Epigenetic mechanisms involved both DNA methylation and histone modifications, producing different repressive chromatin environments depending on the cell molecular signature. Gain and loss of function experiments by cDNA and siRNA transfection revealed profound effects of 3-OST3A expression on cell behavior including apoptosis, proliferation, response to trastuzumab in vitro and tumor growth in xenografted mice. 3-OST3A exerted dual activities acting as tumor-suppressor in lumA-michigan cancer foundation (MCF)-7 and triple negative-MD Anderson (MDA) metastatic breast (MB)-231 cells, or as an oncogenic factor in HER2+-SKBR3 cells. Mechanistically, fluorescence-resonance energy transfer-fluorescence-lifetime imaging microscopy experiments indicated that the effects of 3-OST3A in MCF-7 cells were mediated by altered interactions between HS and fibroblast growth factor-7 (FGF-7). Further, this interplay between HS and FGF-7 modulated downstream ERK, AKT and p38 cascades, suggesting that altering 3-O-sulfation affects FGFR2IIIb-mediated signaling. Corroborating our cellular data, a clinical study conducted in a cohort of breast cancer patients uncovered that, in HER2+ patients, high level expression of 3-OST3A in tumors was associated with reduced relapse-free survival. Our findings define 3-OST3A as a novel regulator of breast cancer pathogenicity, displaying tumor-suppressive or oncogenic activities in a cell-and tumor-dependent context, and demonstrate the clinical value of the HS-O-sulfotransferase 3-OST3A as a prognostic marker in HER2+ patients

FIB-SEM imaging of carbon nanotubes in mouse lung tissue

Ultrastructural characterisation is important for understanding carbon nanotube (CNT) toxicity and how the CNTs interact with cells and tissues. The standard method for this involves using transmission electron microscopy (TEM). However, in particular, the sample preparation, using a microtome to cut thin sample sections for TEM, can be challenging for investigation of regions with agglomerations of large and stiff CNTs because the CNTs cut with difficulty. As a consequence, the sectioning diamond knife may be damaged and the uncut CNTs are left protruding from the embedded block surface excluding them from TEM analysis. To provide an alternative to ultramicrotomy and subsequent TEM imaging, we studied focused ion beam scanning electron microscopy (FIB-SEM) of CNTs in the lungs of mice, and we evaluated the applicability of the method compared to TEM. FIB-SEM can provide serial section volume imaging not easily obtained with TEM, but it is time-consuming to locate CNTs in the tissue. We demonstrate that protruding CNTs after ultramicrotomy can be used to locate the region of interest, and we present FIB-SEM images of CNTs in lung tissue. FIB-SEM imaging was applied to lung tissue from mice which had been intratracheally instilled with two different multiwalled CNTs; one being short and thin, and the other longer and thicker. FIB-SEM was found to be most suitable for detection of the large CNTs (Ø ca. 70 nm), and to be well suited for studying CNT agglomerates in biological samples which is challenging using standard TEM techniques. [Figure: see text] ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s00216-013-7566-x) contains supplementary material, which is available to authorized users

Search for CP Violation in the Decay Z -> b (b bar) g

About three million hadronic decays of the Z collected by ALEPH in the years 1991-1994 are used to search for anomalous CP violation beyond the Standard Model in the decay Z -> b \bar{b} g. The study is performed by analyzing angular correlations between the two quarks and the gluon in three-jet events and by measuring the differential two-jet rate. No signal of CP violation is found. For the combinations of anomalous CP violating couplings, ${\hat{h}}_b = {\hat{h}}_{Ab}g_{Vb}-{\hat{h}}_{Vb}g_{Ab}$ and $h^{\ast}_b = \sqrt{\hat{h}_{Vb}^{2}+\hat{h}_{Ab}^{2}}$, limits of \hat{h}_b < 0.59$and$h^{\ast}_{b} < 3.02$ are given at 95\% CL.Comment: 8 pages, 1 postscript figure, uses here.sty, epsfig.st

Characterization of Novel and Uncharacterized p53 SNPs in the Chinese Population – Intron 2 SNP Co-Segregates with the Common Codon 72 Polymorphism

Multiple single nucleotide polymorphisms (SNPs) have been identified in the tumor suppressor gene p53, though the relevance of many of them is unclear. Some of them are also differentially distributed in various ethnic populations, suggesting selective functionality. We have therefore sequenced all exons and flanking regions of p53 from the Singaporean Chinese population and report here the characterization of some novel and uncharacterized SNPs - four in intron 1 (nucleotide positions 8759/10361/10506/11130), three in intron 3 (11968/11969/11974) and two in the 3′UTR (19168/19514). Allelic frequencies were determined for all these and some known SNPs, and were compared in a limited scale to leukemia and lung cancer patient samples. Intron 2 (11827) and 7 (14181/14201) SNPs were found to have a high minor allele frequency of between 26–47%, in contrast to the lower frequencies found in the US population, but similar in trend to the codon 72 polymorphism (SNP12139) that shows a distribution pattern correlative with latitude. Several of the SNPs were linked, such as those in introns 1, 3 and 7. Most interestingly, we noticed the co-segregation of the intron 2 and the codon 72 SNPs, the latter which has been shown to be expressed in an allele-specific manner, suggesting possible regulatory cross-talk. Association analysis indicated that the T/G alleles in both the co-segregating intron 7 SNPs and a 4tagSNP haplotype was strongly associated increased susceptibility to lung cancer in non-smoker females [OR: 1.97 (1.32, 3.394)]. These data together demonstrate high SNP diversity in p53 gene between different populations, highlighting ethnicity-based differences, and their association with cancer risk

Time-Dependent Subcellular Distribution and Effects of Carbon Nanotubes in Lungs of Mice

BACKGROUND AND METHODS:Pulmonary deposited carbon nanotubes (CNTs) are cleared very slowly from the lung, but there is limited information on how CNTs interact with the lung tissue over time. To address this, three different multiwalled CNTs were intratracheally instilled into female C57BL/6 mice: one short (850 nm) and tangled, and two longer (4 μm and 5.7 μm) and thicker. We assessed the cellular interaction with these CNTs using transmission electron microscopy (TEM) 1, 3 and 28 days after instillation. RESULTS:TEM analysis revealed that the three CNTs followed the same overall progression pattern over time. Initially, CNTs were taken up either by a diffusion mechanism or via endocytosis. Then CNTs were agglomerated in vesicles in macrophages. Lastly, at 28 days post-exposure, evidence suggesting CNT escape from vesicle enclosures were found. The longer and thicker CNTs more often perturbed and escaped vesicular enclosures in macrophages compared to the smaller CNTs. Bronchoalveolar lavage (BAL) showed that the CNT exposure induced both an eosinophil influx and also eosinophilic crystalline pneumonia. CONCLUSION:Two very different types of multiwalled CNTs had very similar pattern of cellular interactions in lung tissue, with the longer and thicker CNTs resulting in more severe effects in terms of eosinophil influx and incidence of eosinophilic crystalline pneumonia (ECP)