Browsing by Author "Kang, Taek"
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Item CRISPR-Based Self-Cleaving Mechanism for Controllable Gene Delivery in Human Cells(Oxford University Press, 2014-12-18) Moore, Richard; Spinhirne, Alec; Lai, Michael J.; Preisser, Samantha; Li, Yi; Kang, Taek; Bleris, Leonidas; 0000 0001 2535 9739 (Bleris, L); 2012076942 (Bleris, L)Controllable gene delivery via vector-based systems remains a formidable challenge in mammalian synthetic biology and a desirable asset in gene therapy applications. Here, we introduce a methodology to control the copies and residence time of a gene product delivered in host human cells but also selectively disrupt fragments of the delivery vehicle. A crucial element of the proposed system is the CRISPR protein Cas9. Upon delivery, Cas9 guided by a custom RNA sequence cleaves the delivery vector at strategically placed targets thereby inactivating a co-expressed gene of interest. Importantly, using experiments in human embryonic kidney cells, we show that specific parameters of the system can be adjusted to fine-tune the delivery properties. We envision future applications in complex synthetic biology architectures, gene therapy and trace-free delivery.;Item Discriminating Direct and Indirect Connectivities in Biological Networks(National Academy of Sciences) Kang, Taek; Moore, Richard; Li, Yi; Sontag, Eduardo; Bleris, Leonidas; 0000 0001 2535 9739 (Bleris, L); Kang, Taek; Moore, Richard; Li, Yi; Bleris, LeonidasReverse engineering of biological pathways involves an iterative process between experiments, data processing, and theoretical analysis. Despite concurrent advances in quality and quantity of data as well as computing resources and algorithms, difficulties in deciphering direct and indirect network connections are prevalent. Here, we adopt the notions of abstraction, emulation, benchmarking, and validation in the context of discovering features specific to this family of connectivities. After subjecting benchmark synthetic circuits to perturbations, we inferred the network connections using a combination of nonparametric single-cell data resampling and modular response analysis. Intriguingly, we discovered that recovered weights of specific network edges undergo divergent shifts under differential perturbations, and that the particular behavior is markedly different between topologies. Our results point to a conceptual advance for reverse engineering beyond weight inference. Investigating topological changes under differential perturbations may address the longstanding problem of discriminating direct and indirect connectivities in biological networks.;Item Mir-192-Mediated Positive Feedback Loop Controls the Robustness of Stress-Induced P53 Oscillations in Breast Cancer Cells(Public Library of Science) Moore, Richard; Ooi, Hsu Kiang; Kang, Taek; Bleris, Leonidas; Ma, Lan; 55515673900 (Ma, L); Moore, Richard; Ooi, Hsu Kiang; Kang, Taek; Bleris, Leonidas; Ma, LanThe p53 tumor suppressor protein plays a critical role in cellular stress and cancer prevention. A number of post-transcriptional regulators, termed microRNAs, are closely connected with the p53-mediated cellular networks. While the molecular interactions among p53 and microRNAs have emerged, a systems-level understanding of the regulatory mechanism and the role of microRNAs-forming feedback loops with the p53 core remains elusive. Here we have identified from literature that there exist three classes of microRNA-mediated feedback loops revolving around p53, all with the nature of positive feedback coincidentally. To explore the relationship between the cellular performance of p53 with the microRNA feedback pathways, we developed a mathematical model of the core p53-MDM2 module coupled with three microRNA-mediated positive feedback loops involving miR-192, miR-34a, and miR-29a. Simulations and bifurcation analysis in relationship to extrinsic noise reproduce the oscillatory behavior of p53 under DNA damage in single cells, and notably show that specific microRNA abrogation can disrupt the wild-type cellular phenotype when the ubiquitous cell-to-cell variability is taken into account. To assess these in silico results we conducted microRNA-perturbation experiments in MCF7 breast cancer cells. Time-lapse microscopy of cell-population behavior in response to DNA double-strand breaks, together with image classification of single-cell phenotypes across a population, confirmed that the cellular p53 oscillations are compromised after miR-192 perturbations, matching well with the model predictions. Our study via modeling in combination with quantitative experiments provides new evidence on the role of microRNA-mediated positive feedback loops in conferring robustness to the system performance of stress-induced response of p53.;Item Synthetic Gene Circuits as Benchmarks for Understanding Biological Networks(December 2023) Kang, Taek; Gogate, Vibhav; Bleris, Leonidas; Prasad, Shalini; Morcos, Faruck; Schmidtke, DavidThe expression of genes is controlled by regulatory networks, which perform fundamental information processing and control mechanisms in a cell. Unraveling and modelling these networks will be indispensable to gain a systems-level understanding of biological organisms and genetically related diseases. With their ability to emulate and interface with naturally occurring networks, synthetic gene networks are powerful tools in this process. Recent advancements in genetic engineering technologies have expanded the possibilities in design and implementation of synthetic networks, offering unprecedented opportunities to examine and perturb their activity in cellular milieu. In this thesis, we present development and characterization of synthetic gene circuits constructed specifically for the purpose of mimicking and monitoring the regulatory strategies in human cells. First, we introduce a reverse engineering pipeline using synthetic gene circuit as a benchmark for biological reverse engineering. We discuss the advantages of this method and how one can engineer the circuits amenable to reverse engineering. Using several synthetic gene circuits, we show that network reconstruction results not only reproduce the benchmark network topologies, but also identifies a novel feature that can be critical towards solving a commonly misidentified topology. Furthermore, we consider the application of using synthetic circuits to characterize a rare and complex gene regulatory motif on its output expression. Specifically, we demonstrate that an intragenic miRNA-mediated output regulation operates as a filter with respect to promoter strength and reduces expression noise. Lastly, we present novel microRNA sensing systems based on CRISPR/Cas systems that offer new opportunities for engineering systems.