Modular, rule-based modeling for the design of eukaryotic synthetic gene circuits

Abstract

Background: The modular design of synthetic gene circuits via composable parts (DNA segments) and pools of signal carriers (molecules such as RNA polymerases and ribosomes) has been successfully applied to bacterial systems. However, eukaryotic cells are becoming a preferential host for new synthetic biology applications. Therefore, an accurate description of the intricate network of reactions that take place inside eukaryotic parts and pools is necessary. Rule-based modeling approaches are increasingly used to obtain compact representations of reaction networks in biological systems. However, this approach is intrinsically non-modular and not suitable per se for the description of composable genetic modules. In contrast, the Model Description Language (MDL) adopted by the modeling tool ProMoT is highly modular and it enables a faithful representation of biological parts and pools.

Results: We developed a computational framework for the design of complex (eukaryotic) gene circuits by generating dynamic models of parts and pools via the joint usage of the BioNetGen rule-based modeling approach and MDL. The framework converts the specification of a part (or pool) structure into rules that serve as inputs for BioNetGen to calculate the part's species and reactions. The BioNetGen output is translated into an MDL file that gives a complete description of all the reactions that take place inside the part (or pool) together with a proper interface to connect it to other modules in the circuit. In proof-of-principle applications to eukaryotic Boolean circuits with more than ten genes and more than one thousand reactions, our framework yielded proper representations of the circuits' truth tables.

Conclusions: For the model-based design of increasingly complex gene circuits, it is critical to achieve exact and systematic representations of the biological processes with minimal effort. Our computational framework provides such a detailed and intuitive way to design new and complex synthetic gene circuits.

Figure 1

A one-step cascade in bacteria. This simple circuit is made of two transcription units: the upper expresses a repressor that, in the absence of chemicals, binds the promoter along the second transcription unit and suppresses the synthesis of a reporter (fluorescent) protein. When chemicals enter the cell, they bind and inactivate the repressors, switching on cell fluorescence. The role of pools as interfaces either between transcription units or between the cell and the environment is apparent. Simple straight lines here represent a mere exchange of molecules; the one ending with a circle symbolizes translation; the one with an orthogonal segment stands for repression; the one with an open arrow induction (see Additional file 1 for an outline of all the symbols used throughout this paper). FaPS means Factors Per Second and it is the flux associated with repressors from one to another transcription unit; SiPS–the flux of chemicals into the cell–stands for Signals Per Second. RNAPS–RNA Per Second–is the acronym for the flux of small RNAs, the only signal carrier not present in this circuit.

Figure 2

Computational architecture for the design of modular, rule-based parts and pools. An input (text) file is converted into an MDL file in six steps. MDL files corresponding to parts and pools are loaded into ProMoT where they are wired up into circuits. Finally, ProMoT allows exporting gene circuits into SBML and Matlab format in order to simulate their dynamics.

Figure 3

Synthetic eukaryotic promoter and mRNA.A) In the configuration here shown, a promoter is bound by a repressor R₁ and an activator A₁. Every operator is labeled with the name of the corresponding transcription factor and the position with respect to the TSS (the lower the integer, the closer the operator to the TSS). A star marks the operators with the highest affinity in case of cooperativity. B) mRNA with four riboswitches along the 5’-UTR (three of them are tandem ones) and two siRNA binding sites on the 3’-UTR region. The ribosome binding site is sequestered by the riboswitches nearby when they are in their inactive configuration.

Figure 4

Gene circuits in eukaryotic cells. In the circuit, fluorescence expression is under the control of an activator and an siRNA. For the sake of simplicity we do not show all the terminators and all pools; RNA polymerase, ribosome, spliceosome, Dicer, and RISC pools were removed. Every full arrow represents a transcription process.

Figure 5

RNAi-based logic evaluator.A) Conversion of a chemical into a siRNA. Following Rinaudo et at., signal a inhibits siRNA-a and promotes siRNA-$\overline{a}$ expression. This double function is mimicked by requiring that this chemical binds and deactivates two different transcription factors. When a is present, only siRNA-$\overline{a}$ is transcribed thus–neglecting other signals in the circuit– AND₂ mRNA is cleaved whereas AND₁ produces fluorescence; vice versa in absence of a. B) Cytoplasmic AND gates. C) Comparison of in silico simulations and in vivo measurements. For each truth table entry, we calculated the ratio between the corresponding fluorescent protein concentration and the minimal 1-output value (absolute values are shown in Additional file 1). This is the procedure followed by Rinaudo and co-authors (in their case, the lowest 1 concentration is at the entry “0010”). They, however, measured fluorescence.

Figure 6

Transcription repression-based logic evaluator.A) Conversion of a chemical into a repressor. When signal a is present, only repressor $\overline{a}$ is expressed. Therefore–neglecting the other signals– p_and1 is not regulated and can lead to fluorescence production; vice versa when a is absent. This configuration requires two genes less than the siRNA-based one. B) Nuclear AND gates. C) Comparison of in silico simulations and in vivo measurements. Calculations are performed as in the RNAi-based circuit.