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      miRNAs confer phenotypic robustness to gene networks by suppressing biological noise

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          Abstract

          miRNAs are small non-coding RNAs able to modulate target-gene expression. It has been postulated that miRNAs confer robustness to biological processes, but a clear experimental evidence is still missing. Using a synthetic biology approach, we demonstrate that microRNAs provide phenotypic robustness to transcriptional regulatory networks by buffering fluctuations in protein levels. Here we construct a network motif in mammalian cells exhibiting a “toggle - switch” phenotype in which two alternative protein expression levels define its ON and OFF states. The motif consists of an inducible transcription factor that self-regulates its own transcription and that of a miRNA against the transcription factor itself. We confirm, using mathematical modeling and experimental approaches, that the microRNA confers robustness to the toggle-switch by enabling the cell to maintain and transmit its state. When absent, a dramatic increase in protein noise level occurs, causing the cell to randomly switch between the two states.

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          Most cited references37

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          Nature, nurture, or chance: stochastic gene expression and its consequences.

          Gene expression is a fundamentally stochastic process, with randomness in transcription and translation leading to cell-to-cell variations in mRNA and protein levels. This variation appears in organisms ranging from microbes to metazoans, and its characteristics depend both on the biophysical parameters governing gene expression and on gene network structure. Stochastic gene expression has important consequences for cellular function, being beneficial in some contexts and harmful in others. These situations include the stress response, metabolism, development, the cell cycle, circadian rhythms, and aging.
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            Stochasticity in gene expression: from theories to phenotypes.

            Genetically identical cells exposed to the same environmental conditions can show significant variation in molecular content and marked differences in phenotypic characteristics. This variability is linked to stochasticity in gene expression, which is generally viewed as having detrimental effects on cellular function with potential implications for disease. However, stochasticity in gene expression can also be advantageous. It can provide the flexibility needed by cells to adapt to fluctuating environments or respond to sudden stresses, and a mechanism by which population heterogeneity can be established during cellular differentiation and development.
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              Roles for microRNAs in conferring robustness to biological processes.

              Biological systems use a variety of mechanisms to maintain their functions in the face of environmental and genetic perturbations. Increasing evidence suggests that, among their roles as posttranscriptional repressors of gene expression, microRNAs (miRNAs) help to confer robustness to biological processes by reinforcing transcriptional programs and attenuating aberrant transcripts, and they may in some network contexts help suppress random fluctuations in transcript copy number. These activities have important consequences for normal development and physiology, disease, and evolution. Here, we will discuss examples and principles of miRNAs that contribute to robustness in animal systems. Copyright © 2012 Elsevier Inc. All rights reserved.
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                Author and article information

                Journal
                101528555
                37539
                Nat Commun
                Nat Commun
                Nature communications
                2041-1723
                6 August 2013
                2013
                21 November 2013
                : 4
                : 10.1038/ncomms3364
                Affiliations
                [a ]Telethon Institute of Genetics and Medicine (TIGEM), Via P. Castellino 111, 80131, Naples, Italy
                [c ]Dept. of Electrical Engineering and Information Technology, University of Naples FEDERICO II, Via Claudio 21, 80125
                Author notes
                [* ]Principal corresponding author dibernardo@ 123456tigem.it
                [b]

                present address: Department of Biological Engineering, Massachusetts Institute of Technology. 77 Massachusetts Avenue, Cambridge, Massachusetts 02139, USA.

                [1]

                These authors contributed equally to this work

                Author Contributions V.S. conceived and constructed the synthetic networks. I.G. developed the mathematical models and performed the analysis. C.F. did all the microfluidcs experiments. C.F. and S.V. generated clonal cells and helped with network contruction. S.V. and S.C. performed FACS analysis. DdB conceived the idea and directed the project.

                Article
                EMS54189
                10.1038/ncomms3364
                3836244
                24077216
                4bb09bc0-3f15-4711-b2fc-15338ad247e1

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                History
                Funding
                Funded by: Telethon :
                Award ID: TGM11SB1 || TI_
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