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Infection of most cell types with herpes simplex virus (HSV) mutants lacking the activation functions of VP16 and/or ICP0 results in repression of viral gene expression. However, the human osteosarcoma cell line U2OS supports the replication of VP16 and ICP0 mutants to nearly wild type levels. Prior to the studies presented in this thesis, the basis for the permissivity of U2OS cells to VP16 and ICP0 mutants had not been explored. Here, somatic cell fusion assays were used to determine that U2OS cells support the replication of VP16 and ICP0 mutants due to a defect in an innate gene silencing mechanism. The artificial induction of interferon stimulated genes that occurs during the somatic cell fusion assays is not the basis for the observed repression of viral gene expression. As one means of identifying components of the antiviral pathway defective in U2OS cells, restrictive cell types were treated with kinase inhibitors and infected with VP16 and/or ICP0 mutants. Although several compounds were identified which compensate for the defect in gene expression of VP16 mutants, these drugs also stimulate mutant virus gene expression in U2OS. Thus, U2OS are most likely not defective in the cellular signalling pathway(s) targeted by these compound(s). Finally, the importance of VP16 and ICP0 in modulating chromatin structure on the viral genome in both restrictive and permissive cells was examined, uncovering an essential role for both proteins in altering histone occupancy and acetylation levels. Importantly, U2OS cells have a defect in the chromatin-based pathway targeted by ICP0. However, evidence suggests that the ability of VP16 and ICP0 to affect histone occupancy and acetylation levels is not required for viral gene expression. Taken together, the results of this thesis demonstrate that U2OS cells support the replication of VP16 and ICP0 mutants due to a defect in an innate antiviral mechanism which does not involve the targets of several well characterized kinase inhibitors. The significance of the defect in a chromatin-based pathway targeted by ICP0 in U2OS cells remains to be elucidated. / Virology

State-of-the-art fluorescent imaging research is strictly limited to eight fluorophore labels duringthe study of intercellular interactions among organelles. The number of excited fluorophore colorsis restricted due to overlap in the narrow spectra of visual wavelength. However, this requires aconsiderable effort of analysis to be able to tell the overlapping signals apart. Significant overlapalready occurs with the use of more than four fluorophores and is leaving researchers limited to asmall number of labels and the hard decision to prioritize between cellular labels to use. Except for the physical limitations of fluorescent labeling, the labeling itself causes behavioralabnormalities due to sample perturbation. In addition to this, the labeling dye or dye-adjacentantibodies are potentially causing phototoxicity and photobleaching thus limiting the timescale oflive cell imaging. Nontoxic imaging modalities such as transmitted-light microscopes, such asbright-field and phase contrast methods, are available but not nearly achieving images of thespecificity as when using fluorophore labeling. An approach that could increase the number of organelles simultaneously studied withfluorophore labels, while being cost-effective and nontoxic as transmitted-light microscopes wouldbe an invaluable tool in the quest to enhance knowledge of cellular studies of organelles. Here wepresent a deep learning solution, using convolutional neural networks built to predict thefluorophore labeling effect on the nucleus, from a transmitted-light input. This solution renders afluorescent channel available for another marker and would eliminate the process of labeling thenucleus with dye or dye-conjugated antibodies by instead using deep convolutional neuralnetworks. / Allra senaste forskningen inom fluorescensmikroskopi är begränsat till upp till åtta fluoroforer förstudier av intracellulära kommunikationer mellan organeller. Antalet fluorescerande färger ärbegränsade till följd av spektralt överlapp i det synliga våglängdsområdet. Överlappande signalerbehöver matematiskt bearbetas vilket innebär ökad arbetsinsats och signifikant överlappning skerredan vid användning av fler än fyra fluoroforer. Denna begräsning innebär i slutändan att forskarehar ett litet antal fluoroforer att arbeta med och behöver därmed prioritera vilka cellulära strukturersom kan märkas samtidigt. Utöver de spektrala begräsningarna med fluorescensmikroskopi, så innebär även själva färgningenav cellulära komponenter en negativ cellulär påverkan i form av avvikande beteende.Fluorescerande färgämnen och märkta antikroppar orsakar potentiellt fototoxicitet ochljusblekning, vilket begränsar tidsrymden vid studier av levande celler. Ljusfältsmikroskop sombright-field and faskontrast har inte en toxisk påverkan men producerar inte i närheten likadetaljerade bilder som fluorescensmikroskop gör. Ett tillvägagångssätt som skulle kunna öka antalet organeller som simultant kan undersökas medfluoroforer, som samtidigt är kostnadseffektiv och inte har en toxisk påverkan somljusfältsmikroskop, skulle vara ett ovärderligt verktyg för utökad kunskap vid cellulära studier avorganeller. Här presenteras en maskininlärningsmetod byggd med artificiella neuronnät för attpredicera fluorescerande infärgningen av cellkärnan i fluorescensmikroskop, med bilder frånljusfältsmikroskop. Denna lösning frigör en fluorofor som kan användas till andra organellersamtidigt som arbetet med fluorescerande infärgning av cellkärnan inte längre är nödvändigt ochersätts med ett artificiellt neuronnät.