Literature DB >> 24032656

Genetic sensor for strong methylating compounds.

Felix Moser, Andrew Horwitz, Jacinto Chen, Wendell Lim, Christopher A Voigt.   

Abstract

Methylating chemicals are common in industry and agriculture and are often toxic, partly due to their propensity to methylate DNA. The Escherichia coli Ada protein detects methylating compounds by sensing aberrant methyl adducts on the phosphoester backbone of DNA. We characterize this system as a genetic sensor and engineer it to lower the detection threshold. By overexpressing Ada from a plasmid, we improve the sensor’s dynamic range to 350-fold induction and lower its detection threshold to 40 μM for methyl iodide. In eukaryotes, there is no known sensor of methyl adducts on the phosphoester backbone of DNA. By fusing the N-terminal domain of Ada to the Gal4 transcriptional activation domain, we built a functional sensor for methyl phosphotriester adducts in Saccharomyces cerevisiae. This sensor can be tuned to variable specifications by altering the expression level of the chimeric sensor and changing the number of Ada operators upstream of the Gal4-sensitive reporter promoter. These changes result in a detection threshold of 28 μM and 5.2-fold induction in response to methyl iodide. When the yeast sensor is exposed to different SN1 and SN2 alkylating compounds, its response profile is similar to that observed for the native Ada protein in E. coli, indicating that its native function is retained in yeast. Finally, we demonstrate that the specifications achieved for the yeast sensor are suitable for detecting methylating compounds at relevant concentrations in environmental samples. This work demonstrates the movement of a sensor from a prokaryotic to eukaryotic system and its rational tuning to achieve desired specifications.

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Year:  2013        PMID: 24032656      PMCID: PMC3859139          DOI: 10.1021/sb400086p

Source DB:  PubMed          Journal:  ACS Synth Biol        ISSN: 2161-5063            Impact factor:   5.110


  71 in total

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2.  Construction and characterization of Escherichia coli whole-cell biosensors for toluene and related compounds.

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Review 4.  Chemical biology of mutagenesis and DNA repair: cellular responses to DNA alkylation.

Authors:  Nidhi Shrivastav; Deyu Li; John M Essigmann
Journal:  Carcinogenesis       Date:  2009-10-29       Impact factor: 4.944

5.  The mode of action of N-methyl-N'-nitro-N-nitrosoguanidine in mutagenesis. VII. The transfer of the methyl group of N-methyl-N'-nitro-N-nitrosoguanidine.

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6.  The solution structure of the methylated form of the N-terminal 16-kDa domain of Escherichia coli Ada protein.

Authors:  Hiroto Takinowaki; Yasuhiro Matsuda; Takuya Yoshida; Yuji Kobayashi; Tadayasu Ohkubo
Journal:  Protein Sci       Date:  2006-02-01       Impact factor: 6.725

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8.  Identification of a methyl jasmonate-responsive domain in the soybean vspB promoter.

Authors:  H S Mason; D B DeWald; J E Mullet
Journal:  Plant Cell       Date:  1993-03       Impact factor: 11.277

9.  Synthesis of methyl halides from biomass using engineered microbes.

Authors:  Travis S Bayer; Daniel M Widmaier; Karsten Temme; Ethan A Mirsky; Daniel V Santi; Christopher A Voigt
Journal:  J Am Chem Soc       Date:  2009-05-13       Impact factor: 15.419

10.  Automated design of synthetic ribosome binding sites to control protein expression.

Authors:  Howard M Salis; Ethan A Mirsky; Christopher A Voigt
Journal:  Nat Biotechnol       Date:  2009-10-04       Impact factor: 54.908

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  13 in total

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Journal:  Genetics       Date:  2018-12-04       Impact factor: 4.562

2.  Synthetic biosensors for precise gene control and real-time monitoring of metabolites.

Authors:  Jameson K Rogers; Christopher D Guzman; Noah D Taylor; Srivatsan Raman; Kelley Anderson; George M Church
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3.  Shining light on molecular communication.

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Journal:  ACM Int Conf Nanoscale Comput Commun (2020)       Date:  2020-10-07

Review 4.  Synthetic biology expands chemical control of microorganisms.

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Journal:  Curr Opin Chem Biol       Date:  2015-06-05       Impact factor: 8.822

5.  Amplification of small molecule-inducible gene expression via tuning of intracellular receptor densities.

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6.  Puzzle Imaging: Using Large-Scale Dimensionality Reduction Algorithms for Localization.

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Review 7.  Microbially derived biosensors for diagnosis, monitoring and epidemiology.

Authors:  Hung-Ju Chang; Peter L Voyvodic; Ana Zúñiga; Jérôme Bonnet
Journal:  Microb Biotechnol       Date:  2017-08-03       Impact factor: 5.813

8.  Lighting up yeast cell factories by transcription factor-based biosensors.

Authors:  Vasil D'Ambrosio; Michael K Jensen
Journal:  FEMS Yeast Res       Date:  2017-11-01       Impact factor: 2.796

9.  Engineering transcription factor-based biosensors for repressive regulation through transcriptional deactivation design in Saccharomyces cerevisiae.

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10.  Dynamic control of endogenous metabolism with combinatorial logic circuits.

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Journal:  Mol Syst Biol       Date:  2018-11-27       Impact factor: 11.429

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