CHEME 3130 Final Project Based on ACS Paper "Sequence Specific Modeling of E. coli Cell-Free Protein Synthesis"

The following is the Readme file for the original paper's repository:

Sequence Specific Flux Balance Analysis (ssFBA) for Cell-Free Protein Synthesis

Sequence specific constraint based model (ssFBA) for static stoichiometric models (SSM) written in the Julia programming language. SSM models were created with JuNQC-Generator (https://github.com/varnerlab/JuNQC-Generator). The code uses the GLPK solver to solve the metabolic flux balance analysis program. The model is described in:

Vilkhovoy et al (2017) Sequence Specific Modeling of E. coli Cell-Free Protein Synthesis. bioRxiv 139774; doi: https://doi.org/10.1101/139774

Installation and Requirements

You can download this repository as a zip file, or clone or pull it by using the command (from the command-line):

$ git pull https://github.com/varnerlab/Sequence-Specific-FBA-CFPS-Publication-Code.git

or

$ git clone https://github.com/varnerlab/Sequence-Specific-FBA-CFPS-Publication-Code.git

Julia must be installed on your machine along with GLPK linear programming solver. Julia can be downloaded/installed on any platform. To install the GLPK program issue the command:

julia> Pkg.add("GLPK")

in the Julia REPL.

Running the model

To run the model, first copy the files from the protein folder you wish to simulate and paste them into the Model folder. Set the directory to the Model folder and issue the command include("Solve.jl") in the Julia REPL.

The Solve.jl script has several user inputs available:

Variable	User Input	Description
Case	1 = Amino Acid Uptake & Synthesis, 2 = Amino Acid Uptake w/o Synthesis, 3 = Amino Acid Synthesis w/o Uptake	Set the case to simulate
Promoter_model	1 = T7 promoter model, 2 = P70a promoter model	Set the promoter model
plasmid_concentration	default = 5, plasmid concentration is in nM	Set plasmid concentration of the protein of interest to be expressed

The script gives several outputs:

Output	Description
objective__value	The objective value of the reaction set to be optimized. The default is set to optimize the export of the protein of interest
flux_array	The flux distribution throughout the network. The reaction index can be looked up in Debug.txt
dual_array	Shadow cost
uptake_array	Species array
exit_flag	Status of glpk solver. Solution undefined = 1, solution is feasible = 2, problem has no feasible solution = 4, solution is optimal = 5

What each file does

file	description
DataDictionary.jl	Encodes the species and reaction bounds arrays and the objective array. Data is stored in a Julia dictionary type and can be accessed through the appropriate key.
Debug.txt	List of reactions and species used to generate the model code.
FluxDriver.jl	Julia interface with the GLPK solver. Users should NEVER, UNDER ANY CIRCUMSTANCES, EVER edit this file.
Include.jl	Encodes all the include statements for the project. Should be included at the top of top-level driver scripts.
Network.dat	Stoichiometric array for the model.
Solve.jl	Default top-level driver implementation.
Bounds.jl	Updates the species and reaction bounds and sets the transcription and translation rates.
TXTLDictionary.jl	Encodes the cell-free protein synthesis parameters. Data is stored in a Julia dictionary type and can be accessed through the appropriate key.
Performance.jl	Evaluates the carbon yield, energy efficiency, and productivity of a protein of interest.
Ensemble.jl	Generates an ensemble of solutions for a range of transcription and translation parameters