Effects of tobacco smoke on gene expression and cellular pathways in a cellular model of oral leukoplakia

Abstract In addition to being causally linked to the formation of multiple tumor types, tobacco use has been associated with decreased efficacy of anticancer treatment and reduced survival time. A detailed understanding of the cellular mechanisms that are affected by tobacco smoke (TS) should facilitate the development of improved preventive and therapeutic strategies. We have investigated the effects of a TS extract on the transcriptome of MSK-Leuk1 cells, a cellular model of oral leukoplakia. Using Affymetrix HGU133 Plus 2 arrays, 411 differentially expressed probe sets were identified. The observed transcriptome changes were grouped according to functional information and translated into molecular interaction network maps and signaling pathways. Pathways related to cellular proliferation, inflammation, apoptosis, and tissue injury seemed to be perturbed. Analysis of networks connecting the affected genes identified specific modulated molecular interactions, hubs, and key transcription regulators. Thus, TS was found to induce several epidermal growth factor receptor (EGFR) ligands forming an EGFR-centered molecular interaction network, as well as several aryl hydrocarbon receptor-dependent genes, including the xenobiotic metabolizing enzymes CYP1A1 and CYP1B1. Notably, the latter findings in vitro are consistent with our parallel finding that CYP1A1 and CYP1B1 levels were increased in oral mucosa of smokers. Collectively, these results offer insights into the mechanisms underlying the procarcinogenic effects of TS and raise the possibility that inhibitors of EGFR or aryl hydrocarbon receptor signaling will prevent or delay the development of TS-related tumors. Moreover, the inductive effects of TS on xenobiotic metabolizing enzymes may help explain the reduced efficacy of chemotherapy, and suggest targets for chemopreventive agents in smokers

Advances in structure elucidation of small molecules using mass spectrometry

The structural elucidation of small molecules using mass spectrometry plays an important role in modern life sciences and bioanalytical approaches. This review covers different soft and hard ionization techniques and figures of merit for modern mass spectrometers, such as mass resolving power, mass accuracy, isotopic abundance accuracy, accurate mass multiple-stage MS(n) capability, as well as hybrid mass spectrometric and orthogonal chromatographic approaches. The latter part discusses mass spectral data handling strategies, which includes background and noise subtraction, adduct formation and detection, charge state determination, accurate mass measurements, elemental composition determinations, and complex data-dependent setups with ion maps and ion trees. The importance of mass spectral library search algorithms for tandem mass spectra and multiple-stage MS(n) mass spectra as well as mass spectral tree libraries that combine multiple-stage mass spectra are outlined. The successive chapter discusses mass spectral fragmentation pathways, biotransformation reactions and drug metabolism studies, the mass spectral simulation and generation of in silico mass spectra, expert systems for mass spectral interpretation, and the use of computational chemistry to explain gas-phase phenomena. A single chapter discusses data handling for hyphenated approaches including mass spectral deconvolution for clean mass spectra, cheminformatics approaches and structure retention relationships, and retention index predictions for gas and liquid chromatography. The last section reviews the current state of electronic data sharing of mass spectra and discusses the importance of software development for the advancement of structure elucidation of small molecules

Identification of common genetic risk variants for autism spectrum disorder

Autism spectrum disorder (ASD) is a highly heritable and heterogeneous group of neurodevelopmental phenotypes diagnosed in more than 1% of children. Common genetic variants contribute substantially to ASD susceptibility, but to date no individual variants have been robustly associated with ASD. With a marked sample-size increase from a unique Danish population resource, we report a genome-wide association meta-analysis of 18,381 individuals with ASD and 27,969 controls that identified five genome-wide-significant loci. Leveraging GWAS results from three phenotypes with significantly overlapping genetic architectures (schizophrenia, major depression, and educational attainment), we identified seven additional loci shared with other traits at equally strict significance levels. Dissecting the polygenic architecture, we found both quantitative and qualitative polygenic heterogeneity across ASD subtypes. These results highlight biological insights, particularly relating to neuronal function and corticogenesis, and establish that GWAS performed at scale will be much more productive in the near term in ASD

Gene expression imputation across multiple brain regions provides insights into schizophrenia risk

Transcriptomic imputation approaches combine eQTL reference panels with large-scale genotype data in order to test associations between disease and gene expression. These genic associations could elucidate signals in complex genome-wide association study (GWAS) loci and may disentangle the role of different tissues in disease development. We used the largest eQTL reference panel for the dorso-lateral prefrontal cortex (DLPFC) to create a set of gene expression predictors and demonstrate their utility. We applied DLPFC and 12 GTEx-brain predictors to 40,299 schizophrenia cases and 65,264 matched controls for a large transcriptomic imputation study of schizophrenia. We identified 413 genic associations across 13 brain regions. Stepwise conditioning identified 67 non-MHC genes, of which 14 did not fall within previous GWAS loci. We identified 36 significantly enriched pathways, including hexosaminidase-A deficiency, and multiple porphyric disorder pathways. We investigated developmental expression patterns among the 67 non-MHC genes and identified specific groups of pre- and postnatal expression

Genomic Dissection of Bipolar Disorder and Schizophrenia, Including 28 Subphenotypes

publisher: Elsevier articletitle: Genomic Dissection of Bipolar Disorder and Schizophrenia, Including 28 Subphenotypes journaltitle: Cell articlelink: https://doi.org/10.1016/j.cell.2018.05.046 content_type: article copyright: © 2018 Elsevier Inc

Reprogramming a DNA methylation mutant

Chemical modification of the cytosine base via the addition of a methyl group to form 5-­‐methylcytosine (5-­‐mC) is a well-­‐studied example of an epigenetic mark, which contributes to regulation of gene expression, chromatin organisation and other such cellular processes without affecting the underlying DNA sequence. In recent years it was shown that 5-­‐mC is not the only DNA modification found within the vertebrate genome. 5-­‐hydroxymethylcytosine (5-­‐hmC) was first described in 1952 although it wasn’t until 2009 when it was rediscovered in mammalian tissues that it sparked intense interest in the field. Research has found that unlike the 5-­‐mC base from which it is derived, 5-­‐hmC displays variable levels and patterns across a multitude of tissue and cell types. As such the patterns of these DNA modifications can act as an identifier of cell state. This thesis aims to characterize the methyl and hydroxymethyl profiles of induced pluripotent stem cells (iPSCs), derived from control mouse embryonic fibroblast cell line (p53-­‐/-­‐) as well as and methylation hypomorphic (p53-­‐/-­‐, Dnmt1 -­‐/-­‐) mutant cell lines. As such both somatic cells were subject to reprogramming with Yamanaka factors (Oct4, cMyc, Klf4 and Sox2) via the piggyback transposition technique. Successful reprogramming was confirmed by a number of techniques and outcomes, including the de novo expression of a number of key pluripotency related factors (Nanog, Sall4 and Gdf3). Reprogrammed cells were then analysed for transcriptomic changes as well as alterations to their methyl and hydroxymethyl landscapes that accompany reprogramming. Through this work I have shown that the reprogramming of MEF derived cell lines results in a global increase in 5-­‐hmC for both p53-­‐/-­‐ and (p53-­‐/-­‐, Dnmt1 -­‐/-­‐) hypomorphic mutant cell lines – possibly through the reactivation of an alternative form of DNMT1. I demonstrate by both antibody based dot blot assay and genome wide sequencing that the reprogramming of the (p53-­‐/-­‐, Dnmt1 -­‐/-­‐) somatic cells towards a pluripotent state brings about an increase in methylation levels within the cells. This latter observation may indicate that the reprogramming of the cells is driving them towards a more wild type phenotypic state. My studies suggest that lack of DNMT1 function is not a barrier to reprogramming of somatic cells