Results
Construction of an Abstract IFFL Model:
Based on our understanding that incoherent feedforward loops (IFFL) could serve as temporal distinguishers, the first goal of our project was to replicate the model from Zhang, et al. (2016)[1]. We constructed an abstract kinetics based IFFL model, and found that IFFLs are indeed temporal classifiers. We found that when an IFFL was given an oscillatory input signal it will give qualitatively different outputs depending on the length input signals (Figure 1). In the presence of long input signals, an IFFL will give output pulses of a fixed height, whereas in the presence of shorter input signals it will produce a staircase like output where the output concentration increases with each new input pulse.
The ultimate source of this behavior is the dynamics of the inhibitor; when inputs are short, the amount of inhibitor never crosses the threshold at which it efficiently degrades the output, leading to stepwise increases in the output. Conversely, when inputs are long the inhibitor crosses the threshold and reduces the concentration of the output. Importantly for our project, these results showed that IFFLs are capable of distinguishing the temporal properties of inputs, giving different outputs depending on the length of the input signal. That means that an IFFL can provide the basis for a system that is attempting to interpret dynamic, i.e. time encoded information.
Creating a Protease Based IFFL:
With the knowledge that an IFFL would provide a suitable architecture for the construction of our decoder in hand, we decided to utilize a previously characterized IFFL system that utilizes the mf-Lon protease system [2,3]. In this system the mf-Lon protease acts as an inhibitor by degrading a reporter with a protein degradation tag (pdt) (Figure 2).