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1.
Acc Chem Res ; 57(13): 1777-1789, 2024 Jul 02.
Article in English | MEDLINE | ID: mdl-38872074

ABSTRACT

ConspectusSophisticated genetic networks play a pivotal role in orchestrating cellular responses through intricate signaling pathways across diverse environmental conditions. Beyond the inherent complexity of natural cellular signaling networks, the construction of artificial signaling pathways (ASPs) introduces a vast array of possibilities for reshaping cellular responses, enabling programmable control of living organisms. ASPs can be integrated with existing cellular networks and redirect output responses as desired, allowing seamless communication and coordination with other cellular processes, thereby achieving designable transduction within cells. Among diversified ASPs, establishing connections between originally independent endogenous genes is of particular significance in modifying the genetic networks, so that cells can be endowed with new capabilities to sense and deal with abnormal factors related to differentiated gene expression (i.e., solve the issues of the aberrant gene expression induced by either external or internal stimuli). In a typical scenario, the two genes X and Y in the cell are originally expressed independently. After the introduction of an ASP, changes in the expression of gene X may exert a designed impact on gene Y, subsequently inducing the cellular response related to gene Y. If X represents a disease signal and Y serves as a therapeutic module, the introduction of the ASP empowers cells with a new spontaneous defense system to handle potential risks, which holds great potential for both fundamental and translational studies.In this Account, we primarily review our endeavors in the construction of RNA-mediated ASPs between endogenous genes that can respond to differentiated RNA expression. In contrast to other molecules that may be restricted to specific pathways, synthetic RNA circuits can be easily utilized and expanded as a general platform for constructing ASPs with a high degree of programmability and tunability for diversified functionalities through predictable Watson-Crick base pairing. We first provide an overview of recent advancements in RNA-based genetic circuits, encompassing but not limited to utilization of RNA toehold switches, siRNA and CRISPR systems. Despite notable progress, most reported RNA circuits have to contain at least one exogenous RNA X as input or one engineered RNA Y as a target, which is not suitable for establishing endogenous gene connections. While exogenous RNAs can be engineered and controlled as desired, constructing a general and efficient platform for manipulation of naturally occurring RNAs poses a formidable challenge, especially for the mammalian system. With a focus on this goal, we are devoted to developing efficient strategies to manipulate cell responses by establishing RNA-mediated ASPs between endogenous genes, particularly in mammalian cells. Our step-by-step progress in engineering customized cell signaling circuits, from bacterial cells to mammalian cells, from gene expression regulation to phenotype control, and from small RNA to long mRNA of low abundance and more complex secondary structures, is systematically described. Finally, future perspectives and potential applications of these RNA-mediated ASPs between endogenous genes are also discussed.


Subject(s)
RNA , Signal Transduction , Humans , RNA/metabolism , RNA/genetics , Gene Regulatory Networks
2.
Angew Chem Int Ed Engl ; 63(14): e202319309, 2024 Apr 02.
Article in English | MEDLINE | ID: mdl-38298112

ABSTRACT

Engineering of genetic networks with artificial signaling pathways (ASPs) can reprogram cellular responses and phenotypes under different circumstances for a variety of diagnostic and therapeutic purposes. However, construction of ASPs between originally independent endogenous genes in mammalian cells is highly challenging. Here we report an amplifiable RNA circuit that can theoretically build regulatory connections between any endogenous genes in mammalian cells. We harness the system of catalytic hairpin assembly with combination of controllable CRISPR-Cas9 function to transduce the signals from distinct messenger RNA expression of trigger genes into manipulation of target genes. Through introduction of these RNA-based genetic circuits, mammalian cells are endowed with autonomous capabilities to sense the changes of RNA expression either induced by ligand stimuli or from various cell types and control the cellular responses and fates via apoptosis-related ASPs. Our design provides a generalized platform for construction of ASPs inside the genetic networks of mammalian cells based on differentiated RNA expression.


Subject(s)
RNA, Catalytic , Animals , RNA, Catalytic/metabolism , RNA/genetics , RNA, Messenger/genetics , RNA, Messenger/metabolism , Apoptosis , Signal Transduction , Gene Regulatory Networks , Mammals/metabolism
3.
Angew Chem Int Ed Engl ; 62(2): e202214698, 2023 01 09.
Article in English | MEDLINE | ID: mdl-36373715

ABSTRACT

Nucleic acid (NA) computation has been widely developed in the past years to solve kinds of logic and mathematic issues in both information technologies and biomedical analysis. However, the difficulty to integrate non-NA molecules limits its power as a universal platform for molecular computation. Here, we report a versatile prototype of hybridized computation integrated with both nucleic acids and non-NA molecules. Employing the conformationally controlled ligand converters, we demonstrate that non-NA molecules, including both small molecules and proteins, can be computed as nucleic acid strands to construct the circuitry with increased complexity and scalability, and can be even programmed to solve arithmetical calculations within the computational nucleic acid system. This study opens a new door for molecular computation in which all-NA circuits can be expanded with integration of various ligands, and meanwhile, ligands can be precisely programmed by the nuclei acid computation.


Subject(s)
Nucleic Acids , Computers, Molecular , Logic
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