Syncopation and the Score

The first and second authors were supported by an EPSRC DTA (www.epsrc.ac.uk) studentship

Establishing a generalized polyepigenetic biomarker for tobacco smoking

Large-scale epigenome-wide association meta-analyses have identified multiple 'signatures'' of smoking. Drawing on these findings, we describe the construction of a polyepigenetic DNA methylation score that indexes smoking behavior and that can be utilized for multiple purposes in population health research. To validate the score, we use data from two birth cohort studies: The Dunedin Longitudinal Study, followed to age-38 years, and the Environmental Risk Study, followed to age-18 years. Longitudinal data show that changes in DNA methylation accumulate with increased exposure to tobacco smoking and attenuate with quitting. Data from twins discordant for smoking behavior show that smoking influences DNA methylation independently of genetic and environmental risk factors. Physiological data show that changes in DNA methylation track smoking-related changes in lung function and gum health over time. Moreover, DNA methylation changes predict corresponding changes in gene expression in pathways related to inflammation, immune response, and cellular trafficking. Finally, we present prospective data about the link between adverse childhood experiences (ACEs) and epigenetic modifications; these findings document the importance of controlling for smoking-related DNA methylation changes when studying biological embedding of stress in life-course research. We introduce the polyepigenetic DNA methylation score as a tool both for discovery and theory-guided research in epigenetic epidemiology.This article is freely available via Open Access. Click on the Publisher URL to access it via the publisher's site.The Dunedin Longitudinal Study is funded by the New Zealand Health Research Council, the New Zealand Ministry of Business, Innovation, and Employment, the National Institute on Aging (AG032282), and the Medical Research Council (MR/P005918/1). The E-Risk Study is funded by the Medical Research Council (G1002190) and the National Institute of Child Health and Human Development (HD077482). Additional support was provided by a Distinguished Investigator Award from the American Asthma Foundation to Dr. Mill, and by the Jacobs Foundation and the Avielle Foundation. Dr. Arseneault is the Mental Health Leadership Fellow for the U.K. Economic and Social Research Council. Dr. Belsky is a Jacobs Foundation Fellow. This work used a high-performance computing facility partially supported by grant 2016-IDG-1013 (“HARDAC + : Reproducible HPC for Next-generation Genomics”) from the North Carolina Biotechnology Center. Illumina DNA methylation data are accessible from the Gene Expression Omnibus (accession code: GSE105018).pre-print, post-print, publisher's PD

siRNAs: Potential therapeutic agents against Hepatitis C Virus

Hepatitis C virus is a major cause of chronic liver diseases which can lead to permanent liver damage, hepatocellular carcinoma and death. The presently available treatment with interferon plus ribavirin, has limited benefits due to adverse side effects such as anemia, depression and "flu-like" symptoms. Needless to mention, the effectiveness of interferon therapy is predominantly, if not exclusively, limited to virus type 3a and 3b whereas in Europe and North America the majority of viral type is 1a and 2a. Due to the limited efficiency of current therapy, RNA interference (RNAi) a novel regulatory and powerful silencing approach for molecular therapeutics through a sequence-specific RNA degradation process represents an alternative option. Several reports have indicated the efficiency and specificity of synthetic and vector based siRNAs inhibiting HCV replication. In the present review, we focused that combination of siRNAs against virus and host genes will be a better option to treat HC

Phenotype Recognition with Combined Features and Random Subspace Classifier Ensemble

<p>Abstract</p> <p>Background</p> <p>Automated, image based high-content screening is a fundamental tool for discovery in biological science. Modern robotic fluorescence microscopes are able to capture thousands of images from massively parallel experiments such as RNA interference (RNAi) or small-molecule screens. As such, efficient computational methods are required for automatic cellular phenotype identification capable of dealing with large image data sets. In this paper we investigated an efficient method for the extraction of quantitative features from images by combining second order statistics, or Haralick features, with curvelet transform. A random subspace based classifier ensemble with multiple layer perceptron (MLP) as the base classifier was then exploited for classification. Haralick features estimate image properties related to second-order statistics based on the grey level co-occurrence matrix (GLCM), which has been extensively used for various image processing applications. The curvelet transform has a more sparse representation of the image than wavelet, thus offering a description with higher time frequency resolution and high degree of directionality and anisotropy, which is particularly appropriate for many images rich with edges and curves. A combined feature description from Haralick feature and curvelet transform can further increase the accuracy of classification by taking their complementary information. We then investigate the applicability of the random subspace (RS) ensemble method for phenotype classification based on microscopy images. A base classifier is trained with a RS sampled subset of the original feature set and the ensemble assigns a class label by majority voting.</p> <p>Results</p> <p>Experimental results on the phenotype recognition from three benchmarking image sets including HeLa, CHO and RNAi show the effectiveness of the proposed approach. The combined feature is better than any individual one in the classification accuracy. The ensemble model produces better classification performance compared to the component neural networks trained. For the three images sets HeLa, CHO and RNAi, the Random Subspace Ensembles offers the classification rates 91.20%, 98.86% and 91.03% respectively, which compares sharply with the published result 84%, 93% and 82% from a multi-purpose image classifier WND-CHARM which applied wavelet transforms and other feature extraction methods. We investigated the problem of estimation of ensemble parameters and found that satisfactory performance improvement could be brought by a relative medium dimensionality of feature subsets and small ensemble size.</p> <p>Conclusions</p> <p>The characteristics of curvelet transform of being multiscale and multidirectional suit the description of microscopy images very well. It is empirically demonstrated that the curvelet-based feature is clearly preferred to wavelet-based feature for bioimage descriptions. The random subspace ensemble of MLPs is much better than a number of commonly applied multi-class classifiers in the investigated application of phenotype recognition.</p

Intracranial Administration of P Gene siRNA Protects Mice from Lethal Chandipura Virus Encephalitis

Background: In parts of India, Chandipura Virus (CHPV) has emerged as an encephalitis causing pathogen in both epidemic and sporadic forms. This pediatric disease follows rapid course leading to 55–75 % mortality. In the absence of specific treatment, effectiveness of RNA interference (RNAi) was evaluated. Methods and Findings: Efficacy of synthetic short interfering RNA (siRNA) or short hairpin RNA (shRNA) in protecting mice from CHPV infection was assessed. The target genes were P and M genes primarily because important role of the former in viral replication and lethal nature of the latter. Real time one step RT-PCR and plaque assay were used for the assessment of gene silencing. Using pAcGFP1N1-CHPV-P, we showed that P-2 siRNA was most efficient in reducing the expression of P gene in-vitro. Both quantitative assays documented 2logs reduction in the virus titer when P-2, M-5 or M-6 siRNAs were transfected 2hr post infection (PI). Use of these siRNAs in combination did not result in enhanced efficiency. P-2 siRNA was found to tolerate four mismatches in the center. As compared to five different shRNAs, P-2 siRNA was most effective in inhibiting CHPV replication. An extended survival was noted when mice infected intracranially with 100 LD 50 CHPV were treated with cationic lipid complexed 5 mg P-2 siRNA simultaneously. Infection with 10LD 50 and treatment with two doses of siRNA first, simultaneously and second 24 hr PI, resulted in 70 % survival. Surviving mice showed 4logs less CHPV titers in brain without histopathological changes or antibody response. Gene expression profiles of P-2 siRNA treated mice showed no interferon response. First dose of siRNA at 2h

siRNA-Based Targeting of Cyclin E Overexpression Inhibits Breast Cancer Cell Growth and Suppresses Tumor Development in Breast Cancer Mouse Model

Cyclin E is aberrantly expressed in many types of cancer including breast cancer. High levels of the full length as well as the low molecular weight isoforms of cyclin E are associated with poor prognosis of breast cancer patients. Notably, cyclin E overexpression is also correlated with triple-negative basal-like breast cancers, which lack specific therapeutic targets. In this study, we used siRNA to target cyclin E overexpression and assessed its ability to suppress breast cancer growth in nude mice. Our results revealed that cyclin E siRNA could effectively inhibit overexpression of both full length and low molecular weight isoforms of cyclin E. We found that depletion of cyclin E promoted apoptosis of cyclin E-overexpressing cells and blocked their proliferation and transformation phenotypes. Significantly, we further demonstrated that administration of cyclin E siRNA could inhibit breast tumor growth in nude mice. In addition, we found that cyclin E siRNA synergistically enhanced the cell killing effects of doxorubicin in cell culture and this combination greatly suppressed the tumor growth in mice. In conclusion, our results indicate that cyclin E, which is overexpressed in 30% of breast cancer, may serve as a novel and effective therapeutic target. More importantly, our study clearly demonstrates a very promising therapeutic potential of cyclin E siRNA for treating the cyclin E-overexpressing breast cancers, including the very malignant triple-negative breast cancers

A Transient Transgenic RNAi Strategy for Rapid Characterization of Gene Function during Embryonic Development

RNA interference (RNAi) is a powerful strategy for studying the phenotypic consequences of reduced gene expression levels in model systems. To develop a method for the rapid characterization of the developmental consequences of gene dysregulation, we tested the use of RNAi for “transient transgenic” knockdown of mRNA in mouse embryos. These methods included lentiviral infection as well as transposition using the Sleeping Beauty (SB) and PiggyBac (PB) transposable element systems. This approach can be useful for phenotypic validation of putative mutant loci, as we demonstrate by confirming that knockdown of Prdm16 phenocopies the ENU-induced cleft palate (CP) mutant, csp1. This strategy is attractive as an alternative to gene targeting in embryonic stem cells, as it is simple and yields phenotypic information in a matter of weeks. Of the three methodologies tested, the PB transposon system produced high numbers of transgenic embryos with the expected phenotype, demonstrating its utility as a screening method

Integrin β1 is required for the invasive behaviour but not proliferation of squamous cell carcinoma cells in vivo

Integrin β1 is both overexpressed and in an ‘active' conformation in vulval squamous cell carcinomas (VSCCs) compared to matched normal skin. To investigate the significance of integrin β1 deregulation we stably knocked-down integrin β1 expression in the VSCC cell line A431. In vitro analysis revealed that integrin β1 is required for cell adhesion, cell spreading and invasion. However, integrin β1 is not required for cell growth or activation of FAK and ERK signalling in vitro or in vivo. Strikingly, while control tumours were able to invade the dermis, integrin β1 knockdown tumours were significantly more encapsulated and less invasive

Premature Senescence and Increased TGFβ Signaling in the Absence of Tgif1

Transforming growth factor β (TGFβ) signaling regulates cell cycle progression in several cell types, primarily by inducing a G1 cell cycle arrest. Tgif1 is a transcriptional corepressor that limits TGFβ responsive gene expression. Here we demonstrate that primary mouse embryo fibroblasts (MEFs) lacking Tgif1 proliferate slowly, accumulate increased levels of DNA damage, and senesce prematurely. We also provide evidence that the effects of loss of Tgif1 on proliferation and senescence are not limited to primary cells. The increased DNA damage in Tgif1 null MEFs can be partially reversed by culturing cells at physiological oxygen levels, and growth in normoxic conditions also partially rescues the proliferation defect, suggesting that in the absence of Tgif1 primary MEFs are less able to cope with elevated levels of oxidative stress. Additionally, we show that Tgif1 null MEFs are more sensitive to TGFβ-mediated growth inhibition, and that treatment with a TGFβ receptor kinase inhibitor increases proliferation of Tgif1 null MEFs. Conversely, persistent treatment of wild type cells with low levels of TGFβ slows proliferation and induces senescence, suggesting that TGFβ signaling also contributes to cellular senescence. We suggest that in the absence of Tgif1, a persistent increase in TGFβ responsive transcription and a reduced ability to deal with hyperoxic stress result in premature senescence in primary MEFs