Team:Tsinghua-A/Wetlab

Based on modeling work, we find that negative feedback can contribute to the network’s adaptation to DNA copy number variation. So we analysed the following three-node networks, A and B. The difference between A and B is the output nodes of network A has negative feedback.
We transfected this two circuits into mammalian cells (Hela cell). By testing the mean value of EYFP (Enhance Yellow Fluorescent Protein, the output of our circuits), and the relationship between the EYFP and the DNA copy number, we can prove the hypothesis.

We constructed the following circuit A ,B and C .The circuit A corresponds to the network A ,while the circuit B is the implementation of network B. Circuit C is used as a control design to testify the function of A and B.
In circuit A, as we can see, the input is miR-21, which can repress the plasmid pz371 and K1116002(The plasmid’s information can be found in parts). K1116002 induced by rtTA and Dox, serves as an auxiliary node, producing the LacI gene to inhibit the expression of EYFP. EYFP(Enhance Yellow Fluorescent Protein )is used as output. Besides, the miR-FF3 restrains the expression of LacI. The reason that we get the most of post-transcriptional control can be seen in Supplementary text.
In circuit B, however, the plasmid K1116003 does not have FF3 target, leading to the contrast between circuit A and B. We can see miR-21 can’t target at pZ349 and pZ331 in circuit C , that is, there is no input in circuit C. The miR-21, used to distinguish cancer cell from normal cells ,is endogenous in Hela cell.

Supplementary text

miRNAs function as posttranscriptional regulators which have distinguished features compared to transcriptional regulators, intervening late in gene expression process, with the capability to counteract variation from the upstream processes (Margaret et al., 2012). Research shows that while conducting experiment on an incoherent feedforward motif in mammalian cells, posttranscriptional regulation results in superior adaptation behavior, higher absolute expression levels and lower intrinsic fluctuations (Bleris et al., 2011). miRNAs can serve as buffers against variation during gene expression; transient increases in transcription factor activity would propagate to increases in target miRNA transcription while would be counteracted by increased miRNA and vice versa. Therefore, under the miRNA posttranscriptional regulation, protein output can be uncoupled from fluctuations in transcription factor concentration or activity (Margaret et al., 2012). miRNAs also possess good stability which, consistent with theoretical constraints, meets the need for enough molecules of a regulator to achieve a small reduction in the noise of a target gene (Lestas et al., 2010).