4.7 Article

MicroRNA-Based Single-Gene Circuits Buffer Protein Synthesis Rates against Perturbations

Journal

ACS SYNTHETIC BIOLOGY
Volume 3, Issue 5, Pages 324-331

Publisher

AMER CHEMICAL SOC
DOI: 10.1021/sb4001867

Keywords

adaptation; noise; microRNA; feed-forward loop

Funding

  1. National Science Foundation (NSF) CAREER Award [0954566]
  2. Burroughs Wellcome Career Award at the Scientific Interface
  3. Directorate For Engineering
  4. Div Of Chem, Bioeng, Env, & Transp Sys [0954566] Funding Source: National Science Foundation
  5. Division of Computing and Communication Foundations
  6. Direct For Computer & Info Scie & Enginr [1317694] Funding Source: National Science Foundation

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Achieving precise control of mammalian transgene expression has remained a long-standing, and increasingly urgent, challenge in biomedical science. Despite much work, single-cell methods have consistently revealed that mammalian gene expression levels remain susceptible to fluctuations (noise) and external perturbations. Here, we show that precise control of protein synthesis can be realized using a single gene microRNA (miRNA)-based feed-forward loop (sgFFL). This minimal autoregulatory gene circuit consists of an intronic miRNA that targets its own transcript In response to a step-like increase in transcription rate, the network generated a transient protein expression pulse before returning to a lower steady state level, thus exhibiting adaptation. Critically, the steady state protein levels were independent of the size of the stimulus, demonstrating that this simple network architecture effectively buffered protein production against changes in transcription. The single-gene network architecture was also effective in buffering against transcriptional noise, leading to reduced cell-to-cell variability in protein synthesis. Noise was up to 5-fold lower for a sgFFL than for an unregulated control gene with equal mean protein levels. The noise buffering capability varied predictably with the strength of the rniRNA-target interaction. Together, these results suggest that the sgFFL single-gene motif provides a general and broadly applicable platform for robust gene expression in synthetic and natural gene circuits.

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