Literature DB >> 25218181

A quantitative framework for the forward design of synthetic miRNA circuits.

Ryan J Bloom1, Sally M Winkler1, Christina D Smolke1.   

Abstract

Synthetic genetic circuits incorporating regulatory components based on RNA interference (RNAi) have been used in a variety of systems. A comprehensive understanding of the parameters that determine the relationship between microRNA (miRNA) and target expression levels is lacking. We describe a quantitative framework supporting the forward engineering of gene circuits that incorporate RNAi-based regulatory components in mammalian cells. We developed a model that captures the quantitative relationship between miRNA and target gene expression levels as a function of parameters, including mRNA half-life and miRNA target-site number. We extended the model to synthetic circuits that incorporate protein-responsive miRNA switches and designed an optimized miRNA-based protein concentration detector circuit that noninvasively measures small changes in the nuclear concentration of β-catenin owing to induction of the Wnt signaling pathway. Our results highlight the importance of methods for guiding the quantitative design of genetic circuits to achieve robust, reliable and predictable behaviors in mammalian cells.

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Year:  2014        PMID: 25218181     DOI: 10.1038/nmeth.3100

Source DB:  PubMed          Journal:  Nat Methods        ISSN: 1548-7091            Impact factor:   28.547


  46 in total

Review 1.  RNAi: the nuts and bolts of the RISC machine.

Authors:  Witold Filipowicz
Journal:  Cell       Date:  2005-07-15       Impact factor: 41.582

2.  Ultrasonic characterization of whole cells and isolated nuclei.

Authors:  Linda R Taggart; Ralph E Baddour; Anoja Giles; Gregory J Czarnota; Michael C Kolios
Journal:  Ultrasound Med Biol       Date:  2007-03       Impact factor: 2.998

3.  Crystal structures of a series of RNA aptamers complexed to the same protein target.

Authors:  S Rowsell; N J Stonehouse; M A Convery; C J Adams; A D Ellington; I Hirao; D S Peabody; P G Stockley; S E Phillips
Journal:  Nat Struct Biol       Date:  1998-11

4.  Scaffold number in yeast signaling system sets tradeoff between system output and dynamic range.

Authors:  Ty M Thomson; Kirsten R Benjamin; Alan Bush; Tonya Love; David Pincus; Orna Resnekov; Richard C Yu; Andrew Gordon; Alejandro Colman-Lerner; Drew Endy; Roger Brent
Journal:  Proc Natl Acad Sci U S A       Date:  2011-11-23       Impact factor: 11.205

Review 5.  Signal transduction of beta-catenin.

Authors:  B M Gumbiner
Journal:  Curr Opin Cell Biol       Date:  1995-10       Impact factor: 8.382

6.  Genetic control of mammalian T-cell proliferation with synthetic RNA regulatory systems.

Authors:  Yvonne Y Chen; Michael C Jensen; Christina D Smolke
Journal:  Proc Natl Acad Sci U S A       Date:  2010-04-26       Impact factor: 11.205

7.  Mammalian microRNAs predominantly act to decrease target mRNA levels.

Authors:  Huili Guo; Nicholas T Ingolia; Jonathan S Weissman; David P Bartel
Journal:  Nature       Date:  2010-08-12       Impact factor: 49.962

8.  A synthetic biology framework for programming eukaryotic transcription functions.

Authors:  Ahmad S Khalil; Timothy K Lu; Caleb J Bashor; Cherie L Ramirez; Nora C Pyenson; J Keith Joung; James J Collins
Journal:  Cell       Date:  2012-08-03       Impact factor: 41.582

9.  Design of small molecule-responsive microRNAs based on structural requirements for Drosha processing.

Authors:  Chase L Beisel; Yvonne Y Chen; Stephanie J Culler; Kevin G Hoff; Christina D Smolke
Journal:  Nucleic Acids Res       Date:  2010-12-11       Impact factor: 16.971

10.  Quantitative characteristics of gene regulation by small RNA.

Authors:  Erel Levine; Zhongge Zhang; Thomas Kuhlman; Terence Hwa
Journal:  PLoS Biol       Date:  2007-09       Impact factor: 8.029

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  19 in total

1.  A self-regulating biomolecular comparator for processing oscillatory signals.

Authors:  Deepak K Agrawal; Elisa Franco; Rebecca Schulman
Journal:  J R Soc Interface       Date:  2015-10-06       Impact factor: 4.118

2.  Rationally Designed MicroRNA-Based Genetic Classifiers Target Specific Neurons in the Brain.

Authors:  Marianna K Sayeg; Benjamin H Weinberg; Susie S Cha; Michael Goodloe; Wilson W Wong; Xue Han
Journal:  ACS Synth Biol       Date:  2015-04-13       Impact factor: 5.110

Review 3.  Mammalian synthetic biology in the age of genome editing and personalized medicine.

Authors:  Patrick Ho; Yvonne Y Chen
Journal:  Curr Opin Chem Biol       Date:  2017-06-16       Impact factor: 8.822

4.  Biomedical Applications of RNA-Based Devices.

Authors:  Cameron M Kim; Christina D Smolke
Journal:  Curr Opin Biomed Eng       Date:  2017-10-18

5.  Bottom-up approaches in synthetic biology and biomaterials for tissue engineering applications.

Authors:  Mitchell S Weisenberger; Tara L Deans
Journal:  J Ind Microbiol Biotechnol       Date:  2018-03-19       Impact factor: 3.346

Review 6.  MicroRNAs in orthopaedic research: Disease associations, potential therapeutic applications, and perspectives.

Authors:  Audrey McAlinden; Gun-Il Im
Journal:  J Orthop Res       Date:  2017-12-19       Impact factor: 3.494

7.  miRNA-Mediated Regulation of Synthetic Gene Circuits in the Green Alga Chlamydomonas reinhardtii.

Authors:  Francisco J Navarro; David C Baulcombe
Journal:  ACS Synth Biol       Date:  2019-01-24       Impact factor: 5.110

8.  Bioengineering of Genetically Encoded Gene Promoter Repressed by the Flavonoid Apigenin for Constructing Intracellular Sensor for Molecular Events.

Authors:  Nicole M Desmet; Kalyani Dhusia; Wenjie Qi; Andrea I Doseff; Sudin Bhattacharya; Assaf A Gilad
Journal:  Biosensors (Basel)       Date:  2021-04-28

9.  Synthetic feedback control using an RNAi-based gene-regulatory device.

Authors:  Ryan J Bloom; Sally M Winkler; Christina D Smolke
Journal:  J Biol Eng       Date:  2015-04-14       Impact factor: 4.355

Review 10.  Opportunities in the design and application of RNA for gene expression control.

Authors:  Maureen McKeague; Remus S Wong; Christina D Smolke
Journal:  Nucleic Acids Res       Date:  2016-03-11       Impact factor: 16.971

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