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Open Access Publications from the University of California

Scholarly Works (5 results)

  • Thesis
  • Peer Reviewed
UCLA Electronic Theses and Dissertations (2012)

The gammaherpesviruses are unique in their oncogenic potential and their ability to establish lifelong infection. Their success results from a variety of delicate interactions with the natural hosts. In this thesis, we study the interaction between a host response termed the unfolded protein response (UPR) and infection of murine gammaherpesvirus 68 (MHV-68). MHV-68 is a model virus widely used to study the human gammaherpesviruses. UPR is triggered by accumulated unfolded proteins in the endoplasmic reticulum (ER) and activates a collection of signaling pathways (IRE1, ATF6, PERK) that can be beneficial or deleterious to viral replication. We found that cellular UPR is important for MHV-68 replication. The infection cycle of MHV-68 leads to a changing UPR in the host cells. Cellular UPR is inhibited at the early stages of infection and becomes upregulated later on.

To identify viral modulators of cellular UPR, an unbiased screen was conducted, uncovering M1 as a strong UPR inducer and ORF40 as an inhibitor. M1 is found to localize to the ER and markedly induces the production of ER chaperones. It selectively induces the chaperon-producing branches (IRE1, ATF6) while sparing the translation-blocking arm (PERK). On the other hand, the viral helicase-primase component ORF40 is capable of downregulating each UPR pathway. We provide evidence that ORF40 may function through binding to and stabilizing the inactive complexes of the transmembrane stress sensors and chaperones to prevent UPR initiation. Despite the seemingly contradictory effects of the two viral proteins, further investigation revealed distinct expression patterns of ORF40 and M1 genes. ORF40 is expressed at the early stages of virus infection while M1 peaks at later stages. Intriguingly, M1 is found to be able to interfere with the anti-UPR function of ORF40. These findings explain the dynamic modulation of cellular UPR by MHV-68 during infection with ORF40 functioning at the early stage and M1 at the late stages of viral life cycle.

Collectively, the delicate regulation of UPR by MHV-68 suggests this cellular response is crucial in controlling gammaherpesvirus infection. Further investigation on the molecular interaction between the virus and UPR may yield important information for developing new anti-viral therapies.

    Cover page: Interactions between the Unfolded Protein Response and Murine Gammaherpesvirus-68 Infection
    • Article
    • Peer Reviewed
    UCLA Previously Published Works (2014)
    Combination chemotherapy with multiple drugs has been widely applied to cancer treatment owing to enhanced efficacy and reduced drug resistance. For drug combination experiment analysis, response surface modeling has been commonly adopted. In this paper, we introduce a Hill-based global response surface model and provide an application of the model to a 512-run drug combination experiment with three chemicals, namely AG490, U0126, and indirubin-3  ' -monoxime (I-3-M), on lung cancer cells. The results demonstrate generally improved goodness of fit of our model from the traditional polynomial model, as well as the original Hill model on the basis of fixed-ratio drug combinations. We identify different dose-effect patterns between normal and cancer cells on the basis of our model, which indicates the potential effectiveness of the drug combination in cancer treatment. Meanwhile, drug interactions are analyzed both qualitatively and quantitatively. The distinct interaction patterns between U0126 and I-3-M on two types of cells uncovered by the model could be a further indicator of the efficacy of the drug combination.
      Cover page: An application of a Hill‐based response surface model for a drug combination experiment on lung cancer
      • Article
      • Peer Reviewed
      UCLA Previously Published Works (2011)
      Abstract Background Cells constantly sense many internal and environmental signals and respond through their complex signaling network, leading to particular biological outcomes. However, a systematic characterization and optimization of multi-signal responses remains a pressing challenge to traditional experimental approaches due to the arising complexity associated with the increasing number of signals and their intensities. Results We established and validated a data-driven mathematical approach to systematically characterize signal-response relationships. Our results demonstrate how mathematical learning algorithms can enable systematic characterization of multi-signal induced biological activities. The proposed approach enables identification of input combinations that can result in desired biological responses. In retrospect, the results show that, unlike a single drug, a properly chosen combination of drugs can lead to a significant difference in the responses of different cell types, increasing the differential targeting of certain combinations. The successful validation of identified combinations demonstrates the power of this approach. Moreover, the approach enables examining the efficacy of all lower order mixtures of the tested signals. The approach also enables identification of system-level signaling interactions between the applied signals. Many of the signaling interactions identified were consistent with the literature, and other unknown interactions emerged. Conclusions This approach can facilitate development of systems biology and optimal drug combination therapies for cancer and other diseases and for understanding key interactions within the cellular network upon treatment with multiple signals.
        Cover page: Systematic quantitative characterization of cellular responses induced by multiple signals
        • Article
        • Peer Reviewed
        UCLA Previously Published Works (2011)
        The ability to control cellular functions can bring about many developments in basic biological research and its applications. The presence of multiple signals, internal as well as externally imposed, introduces several challenges for controlling cellular functions. Additionally the lack of clear understanding of the cellular signaling network limits our ability to infer the responses to a number of signals. This work investigates the control of Kaposi's sarcoma-associated herpesvirus reactivation upon treatment with a combination of multiple signals. We utilize mathematical model-based as well as experiment-based approaches to achieve the desired goals of maximizing virus reactivation. The results show that appropriately selected control signals can induce virus lytic gene expression about ten folds higher than a single drug; these results were validated by comparing the results of the two approaches, and experimentally using multiple assays. Additionally, we have quantitatively analyzed potential interactions between the used combinations of drugs. Some of these interactions were consistent with existing literature, and new interactions emerged and warrant further studies. The work presents a general method that can be used to quantitatively and systematically study multi-signal induced responses. It enables optimization of combinations to achieve desired responses. It also allows identifying critical nodes mediating the multi-signal induced responses. The concept and the approach used in this work will be directly applicable to other diseases such as AIDS and cancer.
          Cover page: Control of Kaposi's Sarcoma-Associated Herpesvirus Reactivation Induced by Multiple Signals
          • Article
          • Peer Reviewed
          UCLA Previously Published Works (2015)
          Viruses rely on host chaperone network to support their infection. In particular, the endoplasmic reticulum (ER) resident chaperones play key roles in synthesizing and processing viral proteins. Influx of a large amount of foreign proteins exhausts the folding capacity in ER and triggers the unfolded protein response (UPR). A fully-executed UPR comprises signaling pathways that induce ER folding chaperones, increase protein degradation, block new protein synthesis and may eventually activate apoptosis, presenting both opportunities and threats to the virus. Here, we define a role of the MHV-68M1 gene in differential modulation of UPR pathways to enhance ER chaperone production. Ectopic expression of M1 markedly induces ER chaperone genes and expansion of ER. The M1 protein accumulates in ER during infection and this localization is indispensable for its function, suggesting M1 acts from the ER. We found that M1 protein selectively induces the chaperon-producing pathways (IRE1, ATF6) while, interestingly, sparing the translation-blocking arm (PERK). We identified, for the first time, a viral factor capable of selectively intervening the initiation of ER stress signaling to induce chaperon production. This finding provides a unique opportunity of using viral protein as a tool to define the activation mechanisms of individual UPR pathways.
            Cover page: M1 of Murine Gamma-Herpesvirus 68 Induces Endoplasmic Reticulum Chaperone ProductionCreative Commons 'BY' version 4.0 license
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