Biomolecular Breadboards:Models

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==== Standard complexes ====
==== Standard complexes ====
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As part of the reactions that are set up by the toolbox, a number of standard species are created:
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* [RNAP70:DNA prom=utr=gene] - RNA polymerase bound to DNA, corresponding roughly to the closed complex
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* [NTP:RNAP70:DNA prom=utr=gene] - RNA polymerase bound to DNA, with NTP utilization (used for modeling transcription)
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* [Ribo:RNA utr=gene] - Ribosome bound to mRNA
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* [AA:Ribo:RNA utr=gene] - Ribosome bound to mRNA, with amino acid utilization (used for modeling translation)
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* [RecBCD:DNA prom=utr=gene] - Exonuclease bound to DNA.  This disables transcription.
=== TXTL toolbox functions ===
=== TXTL toolbox functions ===

Revision as of 11:43, 11 September 2012

Home Protocols DNA parts Preliminary Data Models More Info

This page contains information about models for simulation and analysis of biomolecular breadboard circuits.

Contents

TX-TL Toolbox for MATLAB

The TX-TL toolbox for MATLAB is a set of MATLAB functions that are designed to simplify the modeling of circuits used in the TX-TL cell free expression system. The source code for the toolbox is available via SourceForge.

Simple example

The following code sets up a simple simulation of a negatively autoregulated gene in the TXTL system:

MATLAB code (plotting commands omitted):

% Set up the standard TXTL tubes
tube1 = txtl_extract('e1');
tube2 = txtl_buffer('b1');

% Set up a tube that will contain our DNA
tube3 = txtl_newtube('circuit');
dna_tetR = txtl_dna(tube3, 'ptet', 'rbs', 'tetR', 100, 'linear');
dna_gamS = txtl_dna(tube3, 'p70', 'rbs', 'gamS', 10, 'plasmid');

% Mix the contents of the individual tubes and add some inducer
Mobj = txtl_combine([tube1, tube2, tube3], [6, 2, 2]);
txtl_addspecies(Mobj, 'aTc', 0.1);

% Run a simulaton
[t_ode, x_ode, names] = sbiosimulate(Mobj, configsetObj);

TXTL naming conventions

The TXTL toolbox uses a set of standard names for molecular species and compounds. If new components are added to the system, they must follow these naming conventions.

DNA, RNA and protein names

In order to allow automatic processing of reactions, the DNA, mRNA and proteins associated with a given gene have specific naming conventions:

  • DNA: [DNA prom=utr=gene]
  • mRNA: [RNA utr=gene]
  • Protein: [protein gene]

The domain names for promoter (prom), untranslated region (utr), and gene can be arbitrary strings, but should generally consist of letters and numbers. In future extensions of the toolbox, DNA domains will be specified as "dom1(len1)-dom2(len2)-..." where dom1 is a valid variable name and "(len1)" is an optional construct defining the length of the domain (in nucleotides).

Standard species

A number of species are defined by the TXTL library and used to implement core processes:

  • RNAP70 [nM]: core RNAP polymerase bound to sigma70
  • Ribo [nM]: Ribosomes
  • AA [unit]: amino acid "units". One unit of amino acid is equal to 100 nM. [AA] represents the total amino acid concentration.
  • NTP [unit]: necleotide "units". One unit of nucleotide is equal to 100 nM. [NTP] represents the total concentration of nucleotides.
  • RecBCD [nM]: exonuclease used to model degradation of linear DNA

Standard complexes

As part of the reactions that are set up by the toolbox, a number of standard species are created:

  • [RNAP70:DNA prom=utr=gene] - RNA polymerase bound to DNA, corresponding roughly to the closed complex
  • [NTP:RNAP70:DNA prom=utr=gene] - RNA polymerase bound to DNA, with NTP utilization (used for modeling transcription)
  • [Ribo:RNA utr=gene] - Ribosome bound to mRNA
  • [AA:Ribo:RNA utr=gene] - Ribosome bound to mRNA, with amino acid utilization (used for modeling translation)
  • [RecBCD:DNA prom=utr=gene] - Exonuclease bound to DNA. This disables transcription.

TXTL toolbox functions

TXTL components

Additional Models

In addition to the TX-TL toolbox, several additional models have been developed for individual breadboard projects.

GamS modeling

For linear DNA, GamS can be used to reduce the rate of degradation of DNA and increase the expression level (see preliminary data for more information). The figure below shows the results of a preliminary model that we are developing to capture the affects of gamS.


Figure 1. Protein expression as a function of gamS concentration. The simulation results show the output of the model in 'protsynt81bis.m', generated with the script 'gamS_plot.m'.

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