What can we learn when fitting a simple telegraph model to a complex gene expression model?
Fig 6
Unravelling the regulation mechanism in a synthetic gene network integrated in human kidney cells [82].
A: In the network, a bidirectional promoter transcribes the zsGreen-LacI and dsRed transcripts. The gene network includes two architectures: a negative-feedback network and a network with no feedback. The zsGreen-LacI transcripts are inhibited by LacI, forming a network with negative autoregulation. The dsRed transcripts are not regulated, forming a network with no feedback. The activity of the promoter can be activated in the presence of Dox, and the negative feedback strength can be tuned by induction of IPTG. B: Under both high and low Dox levels, fitting the distributions of zsGreen levels under different IPTG concentrations to the telegraph model leads to increasing , decreasing
, and almost invariant
against the mean expression level. Such variation pattern of the three effective parameters coincides with that in the negative feedback model when the feedback strength ν is tuned. C: Under both high and low Dox levels, fitting the distributions of dsRed levels under different IPTG concentrations to the telegraph model leads to almost invariant values of
and
against the mean expression level. The error bars in B and C show the standard deviation of three repeated experiments [82].