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Synthetic incoherent feedforward circuits show adaptation to the amount of their genetic template

Authors: Bleris, Leonidas; Xie, Zhen; Glass, David; Adadey, Asa; Sontag, Eduardo; Benenson, Yaakov;

Synthetic incoherent feedforward circuits show adaptation to the amount of their genetic template

Abstract

Natural and synthetic biological networks must function reliably in the face of fluctuating stoichiometry of their molecular components. These fluctuations are caused in part by changes in relative expression efficiency and the DNA template amount of the network‐coding genes. Gene product levels could potentially be decoupled from these changes via built‐in adaptation mechanisms, thereby boosting network reliability. Here, we show that a mechanism based on an incoherent feedforward motif enables adaptive gene expression in mammalian cells. We modeled, synthesized, and tested transcriptional and post‐transcriptional incoherent loops and found that in all cases the gene product adapts to changes in DNA template abundance. We also observed that the post‐transcriptional form results in superior adaptation behavior, higher absolute expression levels, and lower intrinsic fluctuations. Our results support a previously hypothesized endogenous role in gene dosage compensation for such motifs and suggest that their incorporation in synthetic networks will improve their robustness and reliability.

Molecular Systems Biology, 7 (1)

ISSN:1744-4292

Countries
United States, Switzerland
Keywords

Medicine (General), QH301-705.5, Gene Dosage, Feedforward motifs; Gene dosage and noise; Mammalian cells; MicroRNAs; Negative autoregulation, Transfection, Models, Biological, General Biochemistry, Genetics and Molecular Biology, Article, feedforward motifs, R5-920, Databases, Genetic, Humans, Gene Regulatory Networks, mammalian cells, Biology (General), General Immunology and Microbiology, Gene dosage and noise, Applied Mathematics, gene dosage and noise, Mammalian cells, Templates, Genetic, negative autoregulation, microRNAs, MicroRNAs, HEK293 Cells, Computational Theory and Mathematics, Gene Expression Regulation, RNA Interference, Synthetic Biology, General Agricultural and Biological Sciences, Feedforward motifs, Information Systems, Plasmids, Transcription Factors, Negative autoregulation

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    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    156
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 1%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 1%
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
156
Top 1%
Top 10%
Top 1%
Green
gold