Journal article Open Access

Synthetic control systems for high performance gene expression in mammalian cells

Lillccci, Gabriele; Benenson, Yaakov; Khammash, Mustafa

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  "DOI": "10.1093/nar/gky795", 
  "container_title": "Nucleic Acids Research", 
  "title": "Synthetic control systems for high performance gene expression in mammalian cells", 
  "issued": {
    "date-parts": [
  "abstract": "<p><strong>Abstract</strong></p>\n\n<p>Tunable induction of gene expression is an essential tool in biology and biotechnology. In spite of that, current induction systems often exhibit unpredictable behavior and performance shortcomings, including high sensitivity to transactivator dosage and plasmid take-up variation, and excessive consumption of cellular resources. To mitigate these limitations, we introduce here a novel family of gene expression control systems of varying complexity with significantly enhanced performance. These include: (i) an incoherent feedforward circuit that exhibits output tunability and robustness to plasmid take-up variation; (ii) a negative feedback circuit that reduces burden and provides robustness to transactivator dosage variability; and (iii) a new hybrid circuit integrating negative feedback and incoherent feedforward that combines the benefits of both. As with endogenous circuits, the complexity of our genetic controllers is not gratuitous, but is the necessary outcome of more stringent performance requirements. We demonstrate the benefits of these controllers in two applications. In a culture of CHO cells for protein manufacturing, the circuits result in up to a 2.6-fold yield improvement over a standard system. In human-induced pluripotent stem cells they enable precisely regulated expression of an otherwise poorly tolerated gene of interest, resulting in a significant increase in the viability of the transfected cells.</p>", 
  "author": [
      "family": "Lillccci, Gabriele"
      "family": "Benenson, Yaakov"
      "family": "Khammash,  Mustafa"
  "page": "9855-9863", 
  "volume": "46", 
  "type": "article-journal", 
  "issue": "18", 
  "id": "2668750"
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