258 research outputs found

    Examining smoking-induced differential gene expression changes in buccal mucosa

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    <p>Abstract</p> <p>Background</p> <p>Gene expression changes resulting from conditions such as disease, environmental stimuli, and drug use, can be monitored in the blood. However, a less invasive method of sample collection is of interest because of the discomfort and specialized personnel necessary for blood sampling especially if multiple samples are being collected. Buccal mucosa cells are easily collected and may be an alternative sample material for biomarker testing. A limited number of studies, primarily in the smoker/oral cancer literature, address this tissue's efficacy as an RNA source for expression analysis. The current study was undertaken to determine if total RNA isolated from buccal mucosa could be used as an alternative tissue source to assay relative gene expression.</p> <p>Methods</p> <p>Total RNA was isolated from swabs, reverse transcribed and amplified. The amplified cDNA was used in RT-qPCR and microarray analyses to evaluate gene expression in buccal cells. Initially, RT-qPCR was used to assess relative transcript levels of four genes from whole blood and buccal cells collected from the same seven individuals, concurrently. Second, buccal cell RNA was used for microarray-based differential gene expression studies by comparing gene expression between a group of female smokers and nonsmokers.</p> <p>Results</p> <p>An amplification protocol allowed use of less buccal cell total RNA (50 ng) than had been reported previously with human microarrays. Total RNA isolated from buccal cells was degraded but was of sufficient quality to be used with RT-qPCR to detect expression of specific genes. We report here the finding of a small number of statistically significant differentially expressed genes between smokers and nonsmokers, using buccal cells as starting material. Gene Set Enrichment Analysis confirmed that these genes had a similar expression pattern to results from another study.</p> <p>Conclusions</p> <p>Our results suggest that despite a high degree of degradation, RNA from buccal cells from cheek mucosa could be used to detect differential gene expression between smokers and nonsmokers. However the RNA degradation, increase in sample variability and microarray failure rate show that buccal samples should be used with caution as source material in expression studies.</p

    Strain-dependent host transcriptional responses to toxoplasma infection are largely conserved in mammalian and avian hosts

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    Toxoplasma gondii has a remarkable ability to infect an enormous variety of mammalian and avian species. Given this, it is surprising that three strains (Types I/II/III) account for the majority of isolates from Europe/North America. The selective pressures that have driven the emergence of these particular strains, however, remain enigmatic. We hypothesized that strain selection might be partially driven by adaptation of strains for mammalian versus avian hosts. To test this, we examine in vitro, strain-dependent host responses in fibroblasts of a representative avian host, the chicken (Gallus gallus). Using gene expression profiling of infected chicken embryonic fibroblasts and pathway analysis to assess host response, we show here that chicken cells respond with distinct transcriptional profiles upon infection with Type II versus III strains that are reminiscent of profiles observed in mammalian cells. To identify the parasite drivers of these differences, chicken fibroblasts were infected with individual F1 progeny of a Type II x III cross and host gene expression was assessed for each by microarray. QTL mapping of transcriptional differences suggested, and deletion strains confirmed, that, as in mammalian cells, the polymorphic rhoptry kinase ROP16 is the major driver of strain-specific responses. We originally hypothesized that comparing avian versus mammalian host response might reveal an inversion in parasite strain-dependent phenotypes; specifically, for polymorphic effectors like ROP16, we hypothesized that the allele with most activity in mammalian cells might be less active in avian cells. Instead, we found that activity of ROP16 alleles appears to be conserved across host species; moreover, additional parasite loci that were previously mapped for strain-specific effects on mammalian response showed similar strain-specific effects in chicken cells. These results indicate that if different hosts select for different parasite genotypes, the selection operates downstream of the signaling occurring during the beginning of the host's immune response. © 2011 Ong et al

    A systematic review of population health interventions and Scheduled Tribes in India

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    <p>Abstract</p> <p>Background</p> <p>Despite India's recent economic growth, health and human development indicators of Scheduled Tribes (ST) or <it>Adivasi </it>(India's indigenous populations) lag behind national averages. The aim of this review was to identify the public health interventions or components of these interventions that are effective in reducing morbidity or mortality rates and reducing risks of ill health among ST populations in India, in order to inform policy and to identify important research gaps.</p> <p>Methods</p> <p>We systematically searched and assessed peer-reviewed literature on evaluations or intervention studies of a population health intervention undertaken with an ST population or in a tribal area, with a population health outcome(s), and involving primary data collection.</p> <p>Results</p> <p>The evidence compiled in this review revealed three issues that promote effective public health interventions with STs: (1) to develop and implement interventions that are low-cost, give rapid results and can be easily administered, (2): a multi-pronged approach, and (3): involve ST populations in the intervention.</p> <p>Conclusion</p> <p>While there is a growing body of knowledge on the health needs of STs, there is a paucity of data on how we can address these needs. We provide suggestions on how to undertake future population health intervention research with ST populations and offer priority research avenues that will help to address our knowledge gap in this area.</p

    Mapping Dynamic Histone Acetylation Patterns to Gene Expression in Nanog-depleted Murine Embryonic Stem Cells

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    Embryonic stem cells (ESC) have the potential to self-renew indefinitely and to differentiate into any of the three germ layers. The molecular mechanisms for self-renewal, maintenance of pluripotency and lineage specification are poorly understood, but recent results point to a key role for epigenetic mechanisms. In this study, we focus on quantifying the impact of histone 3 acetylation (H3K9,14ac) on gene expression in murine embryonic stem cells. We analyze genome-wide histone acetylation patterns and gene expression profiles measured over the first five days of cell differentiation triggered by silencing Nanog, a key transcription factor in ESC regulation. We explore the temporal and spatial dynamics of histone acetylation data and its correlation with gene expression using supervised and unsupervised statistical models. On a genome-wide scale, changes in acetylation are significantly correlated to changes in mRNA expression and, surprisingly, this coherence increases over time. We quantify the predictive power of histone acetylation for gene expression changes in a balanced cross-validation procedure. In an in-depth study we focus on genes central to the regulatory network of Mouse ESC, including those identified in a recent genome-wide RNAi screen and in the PluriNet, a computationally derived stem cell signature. We find that compared to the rest of the genome, ESC-specific genes show significantly more acetylation signal and a much stronger decrease in acetylation over time, which is often not reflected in an concordant expression change. These results shed light on the complexity of the relationship between histone acetylation and gene expression and are a step forward to dissect the multilayer regulatory mechanisms that determine stem cell fate.Comment: accepted at PLoS Computational Biolog

    Altered translation of GATA1 in Diamond-Blackfan anemia

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    Ribosomal protein haploinsufficiency occurs in diverse human diseases including Diamond-Blackfan anemia (DBA)[superscript 1, 2], congenital asplenia[superscript 3] and T cell leukemia[superscript 4]. Yet, how mutations in genes encoding ubiquitously expressed proteins such as these result in cell-type– and tissue-specific defects remains unknown[superscript 5]. Here, we identify mutations in GATA1, encoding the critical hematopoietic transcription factor GATA-binding protein-1, that reduce levels of full-length GATA1 protein and cause DBA in rare instances. We show that ribosomal protein haploinsufficiency, the more common cause of DBA, can lead to decreased GATA1 mRNA translation, possibly resulting from a higher threshold for initiation of translation of this mRNA in comparison with other mRNAs. In primary hematopoietic cells from patients with mutations in RPS19, encoding ribosomal protein S19, the amplitude of a transcriptional signature of GATA1 target genes was globally and specifically reduced, indicating that the activity, but not the mRNA level, of GATA1 is decreased in patients with DBA associated with mutations affecting ribosomal proteins. Moreover, the defective hematopoiesis observed in patients with DBA associated with ribosomal protein haploinsufficiency could be partially overcome by increasing GATA1 protein levels. Our results provide a paradigm by which selective defects in translation due to mutations affecting ubiquitous ribosomal proteins can result in human disease.National Institutes of Health (U.S.) (Grant P01 HL32262)National Institutes of Health (U.S.) (Grant U54 HG003067-09

    Identification of differentially expressed subnetworks based on multivariate ANOVA

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    <p>Abstract</p> <p>Background</p> <p>Since high-throughput protein-protein interaction (PPI) data has recently become available for humans, there has been a growing interest in combining PPI data with other genome-wide data. In particular, the identification of phenotype-related PPI subnetworks using gene expression data has been of great concern. Successful integration for the identification of significant subnetworks requires the use of a search algorithm with a proper scoring method. Here we propose a multivariate analysis of variance (MANOVA)-based scoring method with a greedy search for identifying differentially expressed PPI subnetworks.</p> <p>Results</p> <p>Given the MANOVA-based scoring method, we performed a greedy search to identify the subnetworks with the maximum scores in the PPI network. Our approach was successfully applied to human microarray datasets. Each identified subnetwork was annotated with the Gene Ontology (GO) term, resulting in the phenotype-related functional pathway or complex. We also compared these results with those of other scoring methods such as <it>t </it>statistic- and mutual information-based scoring methods. The MANOVA-based method produced subnetworks with a larger number of proteins than the other methods. Furthermore, the subnetworks identified by the MANOVA-based method tended to consist of highly correlated proteins.</p> <p>Conclusion</p> <p>This article proposes a MANOVA-based scoring method to combine PPI data with expression data using a greedy search. This method is recommended for the highly sensitive detection of large subnetworks.</p

    Identification of restriction endonuclease with potential ability to cleave the HSV-2 genome: Inherent potential for biosynthetic versus live recombinant microbicides

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    <p>Abstract</p> <p>Background</p> <p>Herpes Simplex virus types 1 and 2 are enveloped viruses with a linear dsDNA genome of ~120–200 kb. Genital infection with HSV-2 has been denoted as a major risk factor for acquisition and transmission of HIV-1. Developing biomedical strategies for HSV-2 prevention is thus a central strategy in reducing global HIV-1 prevalence. This paper details the protocol for the isolation of restriction endunucleases (REases) with potent activity against the HSV-2 genome and models two biomedical interventions for preventing HSV-2.</p> <p>Methods and Results</p> <p>Using the whole genome of HSV-2, 289 REases and the bioinformatics software Webcutter2; we searched for potential recognition sites by way of genome wide palindromics. REase application in HSV-2 biomedical therapy was modeled concomitantly. Of the 289 enzymes analyzed; 77(26.6%) had potential to cleave the HSV-2 genome in > 100 but < 400 sites; 69(23.9%) in > 400 but < 700 sites; and the 9(3.1%) enzymes: BmyI, Bsp1286I, Bst2UI, BstNI, BstOI, EcoRII, HgaI, MvaI, and SduI cleaved in more than 700 sites. But for the 4: PacI, PmeI, SmiI, SwaI that had no sign of activity on HSV-2 genomic DNA, all 130(45%) other enzymes cleaved < 100 times. In silico palindromics has a PPV of 99.5% for in situ REase activity (2) Two models detailing how the REase EcoRII may be applied in developing interventions against HSV-2 are presented: a nanoparticle for microbicide development and a "recombinant lactobacillus" expressing cell wall anchored receptor (truncated nectin-1) for HSV-2 plus EcoRII.</p> <p>Conclusion</p> <p>Viral genome slicing by way of these bacterially- derived R-M enzymatic peptides may have therapeutic potential in HSV-2 infection; a cofactor for HIV-1 acquisition and transmission.</p

    Age-Related Impairment of Ultrasonic Vocalization in Tau.P301L Mice: Possible Implication for Progressive Language Disorders

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    Tauopathies, including Alzheimer's Disease, are the most frequent neurodegenerative diseases in elderly people and cause various cognitive, behavioural and motor defects, but also progressive language disorders. For communication and social interactions, mice produce ultrasonic vocalization (USV) via expiratory airflow through the larynx. We examined USV of Tau.P301L mice, a mouse model for tauopathy expressing human mutant tau protein and developing cognitive, motor and upper airway defects.At age 4-5 months, Tau.P301L mice had normal USV, normal expiratory airflow and no brainstem tauopathy. At age 8-10 months, Tau.P301L mice presented impaired USV, reduced expiratory airflow and severe tauopathy in the periaqueductal gray, Kolliker-Fuse and retroambiguus nuclei. Tauopathy in these nuclei that control upper airway function and vocalization correlates well with the USV impairment of old Tau.P301L mice.In a mouse model for tauopathy, we report for the first time an age-related impairment of USV that correlates with tauopathy in midbrain and brainstem areas controlling vocalization. The vocalization disorder of old Tau.P301L mice could be, at least in part, reminiscent of language disorders of elderly suffering tauopathy

    Microarray-based gene set analysis: a comparison of current methods

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    BACKGROUND: The analysis of gene sets has become a popular topic in recent times, with researchers attempting to improve the interpretability and reproducibility of their microarray analyses through the inclusion of supplementary biological information. While a number of options for gene set analysis exist, no consensus has yet been reached regarding which methodology performs best, and under what conditions. The goal of this work was to examine the performance characteristics of a collection of existing gene set analysis methods, on both simulated and real microarray data sets. Of particular interest was the potential utility gained through the incorporation of inter-gene correlation into the analysis process. RESULTS: Each of six gene set analysis methods was applied to both simulated and publicly available microarray data sets. Overall, the various methodologies were all found to be better at detecting gene sets that moved from non-active (i.e., genes not expressed) to active states (or vice versa), rather than those that simply changed their level of activity. Methods which incorporate correlation structures were found to provide increased ability to detect altered gene sets in some settings. CONCLUSION: Based on the results obtained through the analysis of simulated data, it is clear that the performance of gene set analysis methods is strongly influenced by the features of the data set in question, and that methods which incorporate correlation structures into the analysis process tend to achieve better performance, relative to methods which rely on univariate test statistics
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