Transcription activator-like effector hybrids for conditional control and rewiring of chromosomal transgene expression

Li, Yi; Moore, Richard; Guinn, Michael Tyler; Bleris, Leonidas

doi:10.1038/srep00897

Cited by 67 publications

(89 citation statements)

References 32 publications

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“…Using the proposed methodology, individual nodes of a network can be perturbed from their steady-state using transcriptional or posttranscriptional inhibitors [e.g., TALEs/CRISPR (37,38) or siRNAs]. The pre-and postperturbation steady states can be measured at the mRNA or protein levels, and fed into MRA to predict divergent LRC and accordingly the network structure.…”

Section: Discussionmentioning

confidence: 99%

Discriminating direct and indirect connectivities in biological networks

Kang

Moore

et al. 2015

Proc. Natl. Acad. Sci. U.S.A.

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Reverse 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. A focal point of systems biology is the reverse engineering of gene regulatory networks (1-5). The methods have shifted from intuitive inference of local connectivities to comprehensive analysis of large networks, involving heterogeneous data sets from high-throughput experiments and complex theoretical tools (6-10). Despite significant advances, a fundamental reverse engineering bottleneck is the ability to discriminate between direct and indirect connections. In a simple case, assuming three nodes in a cascade formulation, where an input node is activating an intermediary node which in turn is activating an output node, a reverse engineering algorithm may infer an activating edge from the input node to the output, even though there is no direct biological interaction.Unfortunately, the limitation in correctly distinguishing the effects stemming from indirect connectivities is pervasive (11-13) and justifies the urgent need for new and reliable methods to eliminate spurious edges. Importantly, remedies to address this problem should not further muddle the interpretation by removing true network edges (14). A number of theoretical approaches have been proposed to overcome this hurdle (4, 15-18), but the ability to experimentally verify the conclusions drawn by reverse engineering tools remains paramount.The majority of efforts to address the verification issue adopt in silico benchmark suites that are based on biological pathway approximations (19). Although these models do include a number of commonly observed topologies and have provided significant insights, they do not fully capture the complexity of the biological realm and the associated heterogeneity and intrinsic variability. On the other hand, engineered synthetic gene circuits are orthogonal to the endogenous pathways yet operate within the natural cellular context using the available resources. Thus, sy...

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Section: Discussionmentioning

confidence: 99%

Discriminating direct and indirect connectivities in biological networks

Kang

Moore

et al. 2015

Proc. Natl. Acad. Sci. U.S.A.

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“…Because of their simple DNA recognition code, the frequency of engineering active TALE-based enzymes is very high (4, 39). Consequently, there have been many recent successes modulating mammalian gene expression with synthetic TALE enzymes (14, 18,19, 21, 22, 35, 36, 40–42). In 2012, an engineered version of the CRISPR/Cas9 system was developed as the first platform for targeting proteins to DNA target sites through RNA:DNA interactions rather than direct protein-DNA interactions (43).…”

Section: Introductionmentioning

confidence: 99%

Engineering synthetic TALE and CRISPR/Cas9 transcription factors for regulating gene expression

Kabadi

Gersbach

2014

Methods

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Engineered DNA-binding proteins that can be targeted to specific sites in the genome to manipulate gene expression have enabled many advances in biomedical research. This includes generating tools to study fundamental aspects of gene regulation and the development of a new class of gene therapies that alter the expression of endogenous genes. Designed transcription factors have entered clinical trials for the treatment of human diseases and others are in preclinical development. High-throughput and user-friendly platforms for designing synthetic DNA-binding proteins present innovative methods for deciphering cell biology and designing custom synthetic gene circuits. We review two platforms for designing synthetic transcription factors for manipulating gene expression: Transcription Activator-Like Effectors (TALEs) and the RNA-guided Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)/Cas9 system. We present an overview of each technology and a guide for designing and assembling custom TALE- and CRISPR/Cas9-based transcription factors. We also discuss characteristics of each platform that are best suited for different applications.

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“…The reduced restrictions in the design of TALE-based DNA-binding proteins makes this technology a highly interesting method not only for introducing DSBs but also for targeting other functional activities such as transcription factors, histone modifiers and DNA modifiers to specific sites in the DNA [167,199]. Of note, due to the highly repetitive sequence elements in TALE proteins, they are prone to rearrangements if transduced via γ-retroviral or lentiviral vectors [200].…”

Section: Talenmentioning

confidence: 98%