Recapitulation of the forward nuclear auxin response pathway in yeast

Abstract

Auxin influences nearly every aspect of plant biology through a simple signaling pathway; however, it remains unclear how much of the diversity in auxin effects is explained by variation in the core signaling components and which properties of these components may contribute to diversification in response dynamics. Here, we recapitulated the entire Arabidopsis thaliana forward nuclear auxin signal transduction pathway in Saccharomyces cerevisiae to test whether signaling module composition enables tuning of the dynamic response. Sensitivity analysis guided by a small mathematical model revealed the centrality of auxin/indole-3-acetic acid (Aux/IAA) transcriptional corepressors in controlling response dynamics and highlighted the strong influence of natural variation in Aux/IAA degradation rates on circuit performance. When the basic auxin response circuit was expanded to include multiple Aux/IAAs, we found that dominance relationships between coexpressed Aux/IAAs were sufficient to generate distinct response modules similar to those seen during plant development. Our work provides a new method for dissecting auxin signaling and demonstrates the key role of Aux/IAAs in tuning auxin response dynamics.

Keywords: signaling dynamics; synthetic biology.

Fig. 1.

Auxin-induced transcription in yeast. (A) Network diagram of the forward auxin response pathway in yeast. An auxin input increases association of a member of the TIR1/AFB family of F-box proteins (AFB) and an IAA protein fused to the first 100 aa of the TPL corepressor (TPL-IAA). Auxin-induced association of an AFB and a TPL-IAA leads to degradation of the TPL-IAA, thereby freeing a transcriptional activator in the ARF family to induce expression of an output gene driven by a promoter containing an auxin response element (pARE). (B) The five A. thaliana components needed to recapitulate auxin response in S. cerevisiae are shown in light green. They were an AFB F-box receptor, an IAA, a TPL corepressor, an ARF transcription factor, and an auxin-responsive promoter. The remaining cellular machinery (gray) was supplied by yeast. Fluorescence from a GFP reporter was used as a quantitative output. (C) Synthetic auxin-reversible repression required fusion of a specific TPL truncation to the IAA protein. Flow cytometry was used to monitor the induction of a GFP reporter following auxin treatment in circuits containing either IAA14 with no repression domain (NO RD), shown in gray, or two different C-terminal TPL truncations fused to IAA14. Auxin was added at time 0. TPL-N300 (dark blue) includes the first 300 aa of TPL and excludes the multiple C-terminal WD repeats. Fusion of TPL-N300 to IAA proteins results in reporter repression that is largely auxin-insensitive. TPL-N100 (light blue) includes only the first 100 aa of TPL. When fused to an IAA, TPL-N100 provides auxin-reversible repression. Two replicate induction curves are shown for each circuit. (D) Auxin-induced IAA degradation and subsequent transcriptional activation could be simultaneously monitored in dual-labeled yeast strains. YFP-TPL-IAA3 and a Cerulean reporter driven by the auxin-responsive IAA19 promoter (pIAA19-CFP) were monitored following auxin treatment using time-lapse microscopy and a microfluidic chamber.

Fig. 2.

IAAs drive auxin response dynamics. Representative auxin-induced reporter fluorescence curves are shown for ARCs with ARF7 (light blue) or ARF19 (dark blue) in the context of different IAAs. Auxin was added at time 0 in all graphs. ARF7 and ARF19 showed qualitatively similar patterns of auxin response, whereas the identity of the IAA had a dramatic effect on ARC dynamics. ARC^Sc recapitulated regulatory features of plant ARC function. Transcriptional repression required the known ARF–IAA interaction domain, because an IAA lacking this domain (IAA17deg) had no effect on ARF activity. In addition, auxin response was mediated by IAA degradation, because a naturally occurring IAA lacking a degron (IAA20) rendered the circuit insensitive to auxin treatment.

Fig. 3.

Model selection and sensitivity analysis of the auxin response pathway. (A) Gray-box model of the auxin response pathway. The auxin input is represented by the variable u and the GFP output of the reporter is represented by the variable g. The variable x represents a lumped internal state, which combines multiple reactions including the binding of auxin to the AFB receptor, and the variable y represents IAA protein levels. The model has eight parameters (k_1–8) that intuitively correspond to the biological processes listed in Table 1. We focused on three parameters with strong effect on ARC dynamics: IAA expression level (k₃), rate of auxin-induced IAA degradation (k₅), and ARF-IAA affinity (k₈). (B) A graphical representation of the two performance metrics used for sensitivity analysis: the preauxin steady state g₀ and the activation time ΔT (t₉₀–t₁₀). Sample data from one ARC is shown as blue dots with a sample model fit in red. (C and D) Sensitivity analysis of preauxin steady state g₀ (C) and activation time ΔT (D) to model parameter values of k₃, k₅, and k₈ for each IAA. Each parameter was varied across its entire range of estimated values derived from our experimental dataset, and all other parameters were held constant. Each IAA is plotted as a single point, and the red line indicates the sensitivity curve computed from the model. The preauxin steady state g₀ was accurately predicted by k₃ (expression level) and to a lesser extent by k₈ (ARF affinity), with k₅ having little effect. In contrast, activation time ΔT was predicted with high accuracy by k₅ (auxin-induced degradation) alone. Error bars represent SD (n = 2). More details can be found in SI Appendix.

Fig. 4.

IAA coexpression reveals dominance relationships between IAAs. (A) Modified ARF19 circuits were built that contained pairs of IAAs (IAAx and IAAy). (B) Schematic showing the simplified sequence of lateral root development: founder cell specification, first cell division and patterning/outgrowth. Auxin response modules are proposed to be sequentially triggered by degradation of the indicated IAAs. (C) One IAA could dictate the auxin response dynamics of yeast cells expressing multiple IAAs. Comparisons are shown between circuits containing two copies of the same IAA (colored points) or one copy of each IAA (gray points). Model fits are shown as solid lines. (D) α (AFB binding competiveness) or β (ARF binding competitiveness) can affect the contribution of an IAA to ARC dynamics. Estimated α and β values from the modified model are shown for each of the IAAs tested here. More details can be found in SI Appendix.