Synthetic incoherent feedforward circuits show adaptation to the amount of their genetic template

Abstract

Natural and synthetic biological networks must function reliably in the face of fluctuating stoichiometry of their molecular components. These fluctuations are caused in part by changes in relative expression efficiency and the DNA template amount of the network-coding genes. Gene product levels could potentially be decoupled from these changes via built-in adaptation mechanisms, thereby boosting network reliability. Here, we show that a mechanism based on an incoherent feedforward motif enables adaptive gene expression in mammalian cells. We modeled, synthesized, and tested transcriptional and post-transcriptional incoherent loops and found that in all cases the gene product adapts to changes in DNA template abundance. We also observed that the post-transcriptional form results in superior adaptation behavior, higher absolute expression levels, and lower intrinsic fluctuations. Our results support a previously hypothesized endogenous role in gene dosage compensation for such motifs and suggest that their incorporation in synthetic networks will improve their robustness and reliability.

Figure 1

Schematics of the synthetic networks. Pointed and blunt arrows denote activation and repression, respectively. In all constructs, the output protein and the repressor are transcribed from the same bidirectional promoter in the constant and non-limiting presence of the TF rtTA that does not constitute an input to the system. In the diagrams, I indicates input node, I_R is the input reporter, A is the auxiliary regulator, and O is the output. (A) Transcriptional type I incoherent feedforward motif (tI1-FFL): the output protein is DsRed and the auxiliary repressor is LacI. The plasmid copy number is reported by the ZsGreen1 fluorescent protein, cotranslated with the LacI protein using IRES. Corresponding control circuit is also shown. (B) Post-transcriptional type I incoherent feedforward motif version I (ptI1-FFL_I): the output protein is AmCyan and the auxiliary repressor is a microRNA. Plasmid copy number is reported by the DsRed protein coexpressed with the output. DsRed mRNA also contains an intron coding for the regulator microRNA. Corresponding control circuit is also shown. (C) Post-transcriptional type I incoherent feedforward motif version II (ptI1-FFL_II): the output protein is DsRed, repressed by a microRNA processed from the intron in its own mRNA. The input is reported by the divergently expressed AmCyan protein. The control circuit is identical to the one in (B). (D) Transcriptional negative autoregulation motif (tAM): auxiliary repressor LacI becomes the output and represses its own transcription as well as the level of the ZsGreen output reporter contranslated via IRES. The input is reported by a divergently expressed DsRed protein.

Figure 2

Simulations for the transcriptional and post-transcriptional (ptI1-FFL_I) type I incoherent feedforward motif. (A) Noise-free parametric simulations of the tI1-FFL with increasing binding strength of the LacI inhibition, from weak inhibition case (black curve) to strong inhibition (orange curve). Binding rate constants in 1/(mol^*sec) units used to generate the different curves are similarly color coded. (B) Noise-free parametric simulations of the ptI1-FFL_I with increasing efficiency of the miRNA inhibition, from weak inhibition (gray curve) to strong inhibition (green curve). Identically color-coded binding rate constant values are shown in 1/(mol^*sec) units. (C) Fitted EC₅₀ values of the simulated tI1-FFL response for the binding rate constants in panel (A). (D) Fitted EC₅₀ values of the simulated ptI1-FFL_I response for the binding rate constants in panel (B). (E) Two special cases in circuits' response. The orange curve shows a biphasic input–output behavior of the tI1-FFL, while the green curve shows the first derivative of the output in ptI1-FFL_I consistent with the transition from a saturated to a proportional response. (F) Noisy simulations of the tI1-FFL for increasing binding of the LacI. The colors correspond to the LacI-binding rate constants in panel (A). (G) The coefficients of variation obtained in the noisy simulations of tI1-FFL. The colors correspond to the LacI-binding rate constants of panel (A). (H) Noisy simulations of the ptI1-FFL_I for increasing strength of the miRNA binding. The colors correspond to the binding rate constants in panel (B). (I) Coefficients of variation of the noisy simulations of the ptI1-FFL_I. The colors correspond to the miRNA-binding rate constants of panel (B).

Figure 3

Experimental results with tI1-FFL motifs. Microscopy images are used for illustration, accompanied by the quantitative data obtained from flow cytometry analysis of at least 200 000 cells from each transfected well. (A) Experimentally measured input–output response of tI1-FFL. Red curve corresponds to wild-type LacO; orange, dark cyan, green, and light green curves represent four mutants with gradually decreasing LacI binding; brown curve is the negative control. (B) Coefficient of variation for each of the constructs illustrated in panel (A) using identical color coding. (C) Representative microscopy images of the circuits and controls. (D) Processed flow cytometry data measured for six tI1-FFL constructs, showing mean output values and their s.d. in each bin. Source data is available for this figure at www.nature.com/msb.

Figure 4

Experimental results obtained with ptI1-FFL_I and ptI1-FFL_II motifs. Microscopy images are used for illustration, accompanied by the quantitative data obtained from flow cytometry analysis of at least 200 000 cells from each transfected well. (A) ptI1-FFL_I; left: correct target, right: negative control, (B) ptI1-FFL_II; left: correct target, right: negative control, (C) Overlap of the input–output responses of the two versions (blue, ptI1-FFL_I and orange, ptI1-FFL_II). (D) Coefficients of variation of the two motifs (blue, ptI1-FFL_I and orange, ptI1-FFL_II). (E) Representative microscopy images. Source data is available for this figure at www.nature.com/msb.

Figure 5

Experimental results obtained with tAM motifs. Microscopy images are used for illustration, accompanied by the quantitative data obtained from flow cytometry analysis of at least 200 000 cells from each transfected well. (A) Input–output behavior of the tAM motifs. (Left) Negative control response measured in the presence of IPTG; (middle) single LacO repeat; (right) double LacO repeat. (B) Representative microscopy images. (C) Juxtaposed mean output values obtained for the different circuits (dark gray curve: IPTG control, orange curve: single LacO repeat, light brown curve: double LacO repeat). (D) Coefficients of variation in the output values measured in the experiments shown in panel (A). Color coding is the same as in panel (C). (E) Plots of log(output) versus log(input) constructed using the mean output values measured in three replicas for each circuit variant. Source data is available for this figure at www.nature.com/msb.