Fig 1.
Mechanisms (reaction schemas) representing transcription.
Fig 2.
BioCRNpyler parameter defaulting hierarchy.
If a specific ParameterKey (orange boxes) cannot be found, the ParameterDatabase automatically defaults to other ParameterKeys. This allows for parameter sharing and rapid construction of complex models from relatively few non-specific (e.g. lower in the hierarchy) parameters.
Fig 3.
A. the organization of classes in BioCRNpyler. Gray arrows indicate the hierarchical organization of objects (e.g. Components are contained in a Mixture). Dark gray arrows take precedence over light gray arrows (e.g. a Component will search for Mechanisms in itself before looking at its Mixture). Colored arrows denote the generate of objects: Components are orange, parameters are blue, and CRN species and reactions are yellow. B. The compilation sequence in BioCRNpyler. The numbers on the arrows in (A) indicate which part of compilation these connections are involved in.
Fig 4.
The idealized models (A, B, and C) do not model the cellular environment; genes and transcripts transcribe and translate catalytically. A. Schematic and simulation of a constituitively active repressor gene repressing a reporter. B. Schematic and simulations of of a toggle switch created by having two genes, A and B, mutually repress each other. C. Schematic and dynamics of a 3-repressor oscillator. The detailed models (D, E, & F) model the cellular environment by including ribosomes, RNAases and background resource competition for cellular resources. D. A dCas9-guideRNA complex binds to the promoter of a reporter and inhibiting transcription. Heatmap shows retroactivity caused by varying the amount of dCas9 and guide-RNA expressed. The sharing of transcription and translational resources gives rise to increases and decreases of reporter even when there is very little repressor. E. A proposed model for a non-transcriptional toggle switch formed by homodimer-RNAase; the homodimer-RNAase made from subunit A selectively degrades the mRNA producing subunit B and visa-versa. F. A model of the Repressillator exploring the effects of multiple ribosomes binding to the same mRNA. G. Histogram comparing the sizes of models A-F and the amount of BioCRNpyler code needed to generate them.
Fig 5.
A model of the lac operon compiled using BioCRNpyler specifications with 141 species and 271 reactions using ∼50 lines of code.
A. A Mixture contains a set of Components and Mechanisms. The Component classes used for each element of the model are shown in brackets. The colored circles show how Components correspond to compiled CRN species in panel C. B. A schematic of the lac operon and the three looped and one open conformation it can take. Each conformation contains a combinatoric number of states based upon the accessible binding sites: R are lac repressor binding sites; C is the activator c-CRP binding site; P is the promoter; and Z, Y, A are the three lac genes. The conformations are placed over clusters of identically colored species corresponding to that conformation in the compiled CRN. C. A graph representation of the compiled CRN. Each circle is a unique chemical species. Square boxes show how chemical species interact via reactions generated by specific Mechanisms. D. Simulated output of the model.
Fig 6.
Examples involving component enumeration.
A. Schematic of local component enumeration for a gene expression circuit where a single DNA Component generates multiple RNA Components. B. The CRN for (A) represented graphically. Colored dots are species corresponding to the components adjacent to the dots in (A). C. Simulated output from the CRN in (B). D. Schematic of global component enumeration in an integrase circuit where one or more DNA Components recombine to produce new DNA Components. Note that the larger DNA outputs could also recombined analogously but this is not shown. E. The CRN for (D) represented graphically. Colored dots are species which correspond to the components adjacent to the dots in (D). F. A genetic circuit which combines global and local component enumeration to flip a promoter which drives gene expression. G. The CRN for the circuit in (F). Colored dots are species representing the components adjacent to the dots in (F). H. Simulated output of the CRN.
Table 1.
Comparison of different simulation software.
Abstraction: how models can be represented in the software. Library: whether there is a substantial library of pre-existing parts/components/sub-models that can be reused. Simulator: whether the software simulates models numerically. Source: the language(s) the software is written in. UI: the primary way a user interacts with the software. API: the primary programming language the software is designed to be accessed with.