Browsing by Author "Li, Yi"
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Item Assembly and Validation of Versatile Transcription Activator-Like Effector Libraries(Nature Publishing Group, 2014-05-06) Li, Yi; Ehrhardt, Kristina; Zhang, Michael Q.; Bleris, Leonidas; 0000 0001 2535 9739 (Bleris, L); 0000 0001 1707 1372 (Zhang, MQ); 2012076942 (Bleris, L); 99086074 (Zhang, MQ); Zhang, Michael Q.The ability to perturb individual genes in genome-wide experiments has been instrumental in unraveling cellular and disease properties. Here we introduce, describe the assembly, and demonstrate the use of comprehensive and versatile transcription activator-like effector (TALE) libraries. As a proof of principle, we built an 11-mer library that covers all possible combinations of the nucleotides that determine the TALE-DNA binding specificity. We demonstrate the versatility of the methodology by constructing a constraint library, customized to bind to a known p53 motif. To verify the functionality in assays, we applied the 11-mer library in yeast-one-hybrid screens to discover TALEs that activate human SCN9A and miR-34b respectively. Additionally, we performed a genome-wide screen using the complete 11-mer library to confirm known genes that confer cycloheximide resistance in yeast. Considering the highly modular nature of TALEs and the versatility and ease of constructing these libraries we envision broad implications for high-throughput genomic assays. ;Item Content Spread and User Relations in Social Computing(2019-08) Li, Yi; 0000-0002-0875-3475 (Li, Y); Wu, WeiliWith the rapid growth of social media and the rise in popularity of social networks, content sharing and spreading have become the major activities for social media users. One of the valuable characteristics of social networks is its capability for user generated content to circulate rapidly through the whole network and spread influence on others. Another characteristic is its openness to everyone. It enables not only news organizations and government agencies to post information, but also ordinary citizens to post from their own perspectives and experiences. In this way, users have the access to more comprehensive and complicated information online. On one hand, social networks offer users many valuable experiences. We can take advantages of social networks such that, for example, the spread of innovation ideas can be maximized, or the expectation of users can be satisfied. On the other hand, we hope to take actions on the negative side that social networks bring to users. For example, to limit the spread of rumors and misinformation or to minimize the negative influence of cybervictims. In this dissertation, we study several problems regarding both positive and negative content spread on social network. First, we study the emerging problems of misinformation/rumor blocking and minimizing the cyberbullying influence on specific user based on Independent Cascade diffusion model and its variance Competitive Independent Cascade model. We formulate these two problems as optimization problems and design algorithms with performance guarantees. Second, we propose a content spread maximization problem and formulate the problem from a marginal gain perspective. As the considered problems are all NP-hard, we focus on the analysis of approximation results. Third, because the network structures are changing dynamically, we predict the missing links and emerging links based on community structure. Last, we study the correlations between user generated content and their roles in online discussion forum.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 Exploiting the CRISPR/Cas9 PAM Constraint for Single-Nucleotide Resolution Interventions(2016-01-20) Li, Yi; Mendiratta, Saurabh; Ehrhardt, Kristina; Kashyap, Neha; White, Michael A.; Bleris, Leonidas; 0000 0001 2535 9739 (Bleris, L)CRISPR/Cas9 is an enabling RNA-guided technology for genome targeting and engineering. An acute DNA binding constraint of the Cas9 protein is the Protospacer Adjacent Motif (PAM). Here we demonstrate that the PAM requirement can be exploited to specifically target single-nucleotide heterozygous mutations while exerting no aberrant effects on the wildtype alleles. Specifically, we target the heterozygous G13A activating mutation of KRAS in colorectal cancer cells and we show reversal of drug resistance to a MEK small-molecule inhibitor. Our study introduces a new paradigm in genome editing and therapeutic targeting via the use of gRNA to guide Cas9 to a desired protospacer adjacent motif.Item Mapping the Operational Landscape of MicroRNAs in Synthetic Gene Circuits.(Nature Partner Journals, 2018-10-22) Quarton, Tyler; Ehrhardt, Kristina; Lee, James; Kannan, Srijaa; Li, Yi; Ma, Lan; Bleris, Leonidas; Quarton, Tyler; Ehrhardt, Kristina; Lee, James; Kannan, Srijaa; Li, Yi; Ma, Lan; Bleris, LeonidasMicroRNAs are a class of short, noncoding RNAs that are ubiquitous modulators of gene expression, with roles in development, homeostasis, and disease. Engineered microRNAs are now frequently used as regulatory modules in synthetic biology. Moreover, synthetic gene circuits equipped with engineered microRNA targets with perfect complementarity to endogenous microRNAs establish an interface with the endogenous milieu at the single-cell level. The function of engineered microRNAs and sensor systems is typically optimized through extensive trial-and-error. Here, using a combination of synthetic biology experimentation in human embryonic kidney cells and quantitative analysis, we investigate the relationship between input genetic template abundance, microRNA concentration, and output under microRNA control. We provide a framework that employs the complete operational landscape of a synthetic gene circuit and enables the stepwise development of mathematical models. We derive a phenomenological model that recapitulates experimentally observed nonlinearities and contains features that provide insight into the microRNA function at various abundances. Our work facilitates the characterization and engineering of multi-component genetic circuits and specifically points to new insights on the operation of microRNAs as mediators of endogenous information and regulators of gene expression in synthetic biology.Item Synthetic Mammalian Transgene Negative Autoregulation(2013-06-04) Shimoga, Vinay; White, Jacob T.; Li, Yi; Sontag, Eduardo; Bleris, Leonidas; 0000 0001 2535 9739 (Bleris, L); 2012076942 (Bleris, L)Biological networks contain overrepresented small-scale topologies, typically called motifs. A frequently appearing motif is the transcriptional negative-feedback loop, where a gene product represses its own transcription. Here, using synthetic circuits stably integrated in human kidney cells, we study the effect of negative-feedback regulation on cell-wide (extrinsic) and gene-specific (intrinsic) sources of uncertainty. We develop a theoretical approach to extract the two noise components from experiments and show that negative feedback results in significant total noise reduction by reducing extrinsic noise while marginally increasing intrinsic noise. We compare the results to simple negative regulation, where a constitutively transcribed transcription factor represses a reporter protein. We observe that the control architecture also reduces the extrinsic noise but results in substantially higher intrinsic fluctuations. We conclude that negative feedback is the most efficient way to mitigate the effects of extrinsic fluctuations by a sole regulatory wiring.;