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Fold-Change Detection (FCD) Synthetic Circuits

EasyChair Preprint no. 9118

4 pagesDate: October 24, 2022

Abstract

Cellular sensory systems often detect the input signal’s relative change rather than its absolute value to eliminate the background noise and obtain more accurate signal detection. This property is known as fold-change detection (FCD), determined by the ratio between the ON and OFF states. Recent studies demonstrated that applying incoherent type-1 feedforward loops(I1-FFL) could lead to gene circuits that can compute FCD. In I1-FFL networks, the input signal is split into two pathways, where both control the output positively and negatively. The FCD could only be achieved when the strengths of the negative and positive pathways are optimized for specific values, limiting the implementation of l1-FFL in gene circuits. In this study, we present and analyze a new motif that coupled I1-FFL with a negative feedback loop for FCD. The simulation shows a significant improvement in the FCD performance and robustness with a wider-range input response.

Keyphrases: Fold Change Detection, in silico design, synthetic biology

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
@Booklet{EasyChair:9118,
  author = {Rongying Huang and Ramez Daniel},
  title = {Fold-Change Detection (FCD) Synthetic Circuits},
  howpublished = {EasyChair Preprint no. 9118},

  year = {EasyChair, 2022}}
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