TXTL matlab toolbox
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1. The next step is to define the DNA sequences to be added to tube3 This is done using the txt1 add dna command dna deGFP txtl add dna tube3 p70 50 rbs 20 deGFP 1000 1 plasmid Refer to the description of the txt1 add dna command in 83 2 for full details of its usage For our purposes it suffices to know that this DNA is loaded onto a plasmid and contains a p70 promoter constitutive 50 base pairs BP in length a 20BP RBS domain and a 1000BP deGFP gene Furthermore the DNA is such that the final concentration of this DNA in the combined tube will be 4nM We then simply combine the extract buffer and DNA Mobj txtl combine tubei tube2 tube3 We now have to set the amount of time we want our simulation to run for and calling the txt1_runsim command as follows simData txtl runsim Mobj 14 60 60 t ode simData Time x ode simData Data This call to txt1_runsim takes the Simbiology model object and the experiment duration to be simulated and runs the simulation from time zero to time 14 hours It returns simData object from which we can extract a vector of time points in that range t ode and a matrix x ode where each column is the concentrations of a species in the model at time points corresponding to t ode For more information please refer to CHAPTER 3 OVERVIEW OF THE CORE PROCESSES Finally the modelling toolbox contains a set of plotting tools that simplify the plottin2. Input e tube pointer to the model object to add the DNA to e prom spec string string representing promoter See below for details e rbs spec string ribosome binding site with optional length in Base Pairs e gene spec string gene string See below e dna amount double amount of DNA to be added in nM This will be the final concentration in the experiment after the tubes have been combined e type string type of DNA linear or plasmid Output dna pointer to DNA object Usage dna tetR txtl add dna tube3 thio junk 500 ptet 50 rbs 20 tetR 647 1 40 terminator 100 16 linear The prom spec is a string containing the name of the promoter to be used this is a necessary argument and needs the corresponding promoter file to be present in the MATLAB search path with an optional length in base pairs If the length is not specified the default length specified in atxtl_ param lt promoterName gt csv file is used There are two other optional strings that can be specified a thio and a junk n where n is an optional integer value The thio string tells the Toolbox that a thiosulfate group is present and this confers protection to the DNA from degradation As of this release the amount of protection is arbitrarily set and will be corrected once the relevant experiments and system ID are carried out Similarly junk DNA slows down the DNA degradation
3. tags although for the functioning of this toolbox this name change is inconsequential The reaction rate parameters for CIpXP s action are currently in the process of being determined The second DNA deGFP is just like in the gene expression exampe except that in this case it is mounted on a linear DNA and therefore can be degraded The third DNA gamS is mounted onto a plasmid and is thus safe from degradation GamS helps to se quester the RecBCD exonuclease providing protection tot the DNA 3 2 3 Results Figure 3 3 illustrates a number of features expression of gamS tetR and the tetR dimer the respective mRNAs and resources The first thing to note is that expression levels in this example are an order of magnitude lower than in gene expression There are two reasons for this The use of linear DNA which means that RecBCD mediated DNA degradation is active and the quick depletion of the RNA due to the greater amount of RNA produced 150 Species amounts nM mRNA amounts nM 100 50 Gene Expression protein gams ms protein sigma28 protein sigma protein tetR 7 100 200 300 400 500 600 700 800 900 and mRNA Resource usage RNA rbs tetR 1E EZ 1 220 5 mM as mM co 5 RNAP nM 0 52 0 c ES e D 2 05 500 1000 0 500
4. and to provide insight into circuit behaviour 1 1 Protocol Overview The cell free circuit breadboard family is a collection of in vitro protocols that can be used to test tran scription and translation TX TL circuits in a set of systematically constructed environments that explore different elements of the external conditions in which the circuits must operate This breadboard is based on the work of Vincent Noireaux at U Minnesota The transcription and translation machineries are extracted from E coli cells Shin and Noireaux 2010 The endogenous DNA and mRNA from the cells are eliminated during the preparation The resulting protein synthesis machinery is used to program cell free TX TL gene circuits in reactions of 12uL The gene circuits can engineered in the laboratory using standard molecular cloning techniques but it is also possible to use PCR products linear DNA which substantially decreases the design cycle time The TXTL toolbox commands follow the experimental protocols closely and a sample code is given below with brief explanations of the commands More detailed explanations can be found in the Core Functionalities chapter More examples can be found in the Examples Directory and are documented in the Examples Chapter below The following code sets up a simple simulation of a negatively autoregulated gene in the TXTL system negautoreg m in the examples directory Set up the standard TX TL tubes tubel t
5. Add protein to the model We used txt1 add dna to set up its reactions gamS txtl addspecies tube3 protein gamS 100 Define levels of aTc to use count 1 levels 0 2 5 10 20 40 100 300 1000 11 colors Pr b 25 mm 2 2 Combine tubes Mobj txtl combine tubei tube2 tube3 Iteratively Simulate the model with different levels of aTc for atc levels configsetObj getconfigset Mobj active set configsetObj StopTime 6 60 60 t ode x ode Mobj simData txtl runsim Mobj configset0Obj figure 2 hold on itetR findspecies Mobj protein tetR plot t ode x ode itetR colors count labelscount int2str atc nM aTc if count size levels 2 inducer txtl addspecies Mobj aTc levels count 1 levels count count count 1 end end title Time Responses lgh legend labels Location Northwest legend lgh boxoff ylabel Species amounts nM xlabel C Time min 3 3 3 Results Figure 3 5 shows the concentrations of tetR Note that this is not the standard plot generated in the previ ous two examples We used the findspecies function to obtain the index of the species to plot protein tetR by using that index to access the relevant column of the data vector x ode We note that as the aTc concentration is increased the level of tetR in the system increases due
6. configuration file associated with this class is used to define the contents of the tubes created by the txtl extract and txtl buffer the integer lt n gt in the name of the file refers to the label of the buffer and extract in the TXTL experimental protocol For instance if we use extract E6 and buffer B6 in the experimental protocol for a circuit we would create a configuration file named E6 config csv which would encapsulate the variations between batches of the buffer and extract We use this file in the modelling toolbox as follows tubel txtl_extract F6 tube2 txtl_buffer F6 Note that we do not define two separate configuration files for the buffer and extract All the information needed is stored in one file Figure 5 1 shows a screenshot of the configuration file E6 config csv This file is a Comma Separated Value file and is best opened in the MATLAB editor with the File gt Open as Text option One can create custom configuration files by modifying the parameter values in this file and saving it under a different name according to the naming convention defined above txtl component config class The txtl_ component config class enables users to input custom reaction parameters for the components they are using in their model Components are found in the components directory in the main directory and contain files that define proteins and promoters The parameters present in the class and the
7. corresponding 22 configuration files are dependent on the components being used but are highly analogous to the previous section Editing of the configuration files is also carried out as above 5 2 List of Core Reactions These reactions are currently those of Dan and refer to the Toxin Antitoxin System We will modify them so that they correspond to the reactions in the TXTL toolbox 5 2 1 Basic RNAP RNAP RNAP gt RNAP gt 07 ATP ADP RecBCD RecBCD 5 2 2 Transcription DNA RNAP RNAP DNA RNAP DNA NTP NTP RNAP DNA NTP RNAP DNA gt DNA RNA RNAP Dummy reaction for NTP consumption see previous section for rates NTP RNAP DNA gt DNA RNAP 5 2 3 Translation RNA Ribo Ribo RNA Ribo ATP AA ATP Ribo RNA AA ATP Ribo RNA RNA protein Ribo Dummy reaction for AA consumption see previous section for rates AA ATP Ribo RNA gt Ribo 5 2 4 Protein Degradation if tagged ClpX gt ClpX protein CIpX protein ClpX protein ClpX ATP gt 1 ClpX gt 23 5 27 5 28 5 29 5 30 5 31 5 32 5 33 5 34 5 2 5 Protein reactions Multimerization protein protein protein dimer 5 39 protein dimer protein dimer protein tetramer 5 40 Repression Here the DNA has a promoter which is repressed by protein A For example tet dimer can repress ptet
8. rbs gene protein A DNA A DNA A protein A 5 41 Notice that in the transcription step there is no reaction for RNA polymerase binding to the protein bound DNA hence repression Maturation A few proteins like ClpX and deGF P undergo maturation protein protein 5 42 5 2 6 Other Degradation DNA RecBCD DNA RecBCD 5 43 DNA RecBCD gt RecBCD 5 44 RNA RNase RNase 5 45 RNase RNase 5 46 Ribo RNA RNase Ribo RNA RNase 5 47 Ribo RNA RNase RNase Ribo 5 48 AA ATP Ribo RNA RNase AA ATP Ribo RNA RNase 5 49 AA ATP Ribo RNA RNase RNase ATP Ribo 5 50 24
9. 1000 Time min Figure 3 3 Negative Autoregulation Output 10 alc 1 I 2o schematic png Figure 3 4 Schematic of the induction circuit 3 3 Induction of Gene Expression using aTc induction 3 3 1 Overview In this circuit we explore the effect of varying levels of the inducer aTc on the expression of a gene under the control of the tetR repressed ptet promoter The expressed gene is precisely the tetR protein leading to a negative autoregulation circuit as in the previous example This DNA is loaded onto a plasmid DNA and so no DNA degradation occurs Figure B 4 shows the circuit diagram for this example Note that in the diagram the deGFP and tetR are fused while in the simulation we only use the tetR gene but we set its length to be 1200 comparable to the length of the tetR deGFP fusion DNA 3 3 2 Code This code uses the txtl_addspecies command to add increasing amounts of aTc to the model object and executes the simulation The Figure 3 5 below plots the levels of tetR protein at different aTc con centrations Set up tubes tubel txtl_extract E6 tube2 txtl_buffer E6 tube3 txtl_newtube circuit Construct DNA and add to tube3 dna tetR txtl add dna tube3 thio junk 500 ptet 50 rbs 20 tetR 1200 lva 40 16 plasmid dna gamS txtl add dna tube3 p70 50 rbs 20 gamS 1000 0 plasmid
10. 21 B D E F G NTPmodel ANumeric 2 NTP model in use see documentation 2 AAmodel Numeric 2 AAmodel in use see documentation 3 Transcription Rate Expression log 2 RNA Length 50 50 NTP second transcription 4 Translation Rate Expression log 2 Protein Length 1 1 5 AA second translation 5 6 DNA RecBCD Forward Numeric 0 4 7 DNA RecBCD Reverse Numeric 0 1 8 DNA RecBCD complex deg Numeric 0 5 9 10 Protein CIpXP Forward Numeric 0 5 11 Protein CIpXP Reverse Numeric 0 0001 12 Protein CIpXP complex deg Numeric 0 1 13 14 RNAP S70 F Numeric 100 15 RNAP S70 Numeric 0 01 16 17 GamS_RecBCD_F Numeric 1 TODO update these numbers based on measurements 18 19 AA Forward Expression log 2 0 001 binding rate of 1 ms 20 AA Reverse Expression 100 log 2 0 001 Km of 100 for amino acid usage 10uM 21 22 RNA_deg Expression log 2 60 12 mRNA degradation 12 min half life 23 24 Ribosome Binding F Expression log 2 0 1 100 ms bind rate 25 Ribosome_Binding_R Expression 0 05 log 2 0 1 Km of 0 05 from VN model 26 27 NTP Forward Expression log 2 0 001 binding rate of 1 ms 28 NTP Reverse Expression 5000 log 2 0 001 Km of 100 for NTP usage 500uM 29 30 NTP Concentration Expression 4 12000 0 4 4 types of NTPs 2096 usability 31 AA Concentration Expression 20 15000 0 2 20 tyes of AAs 2096 usability 32 Figure 5 1 Screenshot of file config csv Configuration file lt gt config csv The
11. TXTL MATLAB TOOLBOX USER S MANUAL ZOLTAN A TUZA VIPUL SINGHAL RICHARD M MURRAY VERSION 1 1 Contents 1 THE TXTL MODELLING TOOLBOX 1 1 PROTOCOL OVERVIEW 2 INSTALLATION 2 1 PREREQUISITES zu 2 4 hoe dec ev cs 2 2 INSTALLING THE 3 EXAMPLES 3 1 GENE EXPRESSION WITH FLUORESCENT REPORTER GENEEXPR 3 1 1 OVERVIEW 3 1 2 WALK THROUGH 31 3 RESULTS 233 a 3 2 NEGATIVE AUTOREGULATION NEGAUTOREG 3 2 1 OVERVIEW 3 3 INDUCTION OF GENE EXPRESSION USING ATO INDUCTION 3 3 1 4 CORE FUNCTIONALITIES 4 1 USER COMMANDSL 0000084 5 APPENDIX 5 1 EXTERNALLY SPECIFIED PARAMETERS 822 MO ODEs t feck ndings ok cate edie 32 3 _ RESULTS a aye ate a Ae ee x OVERVIEW ss eee Gong xui 3 9 2 CODES ul eines a Gods dE 3 9 9 RESULTS xoc Xue dede XXe eoe WDR Chapter 1 THE TXTL MODELLING TOOLBOX The TXTL modelling toolbox for MATLAB is a companion to the TXTL Breadboards Cell free expression project being developed at the California Institute of Technology and the University of Minnesota This toolbox aims to allow n silico prototyping of circuits before they are built in vitro
12. atively low steady state concentration 3 2 2 Code Please work through the Gene Expression example above to get basic familiarity with the commands and their usage This example is slightly more complex than geneexpr We provide the entire code for this example below tubel txtl_extract F9 tube2 txtl_buffer F9 tube3 txtl_newtube negautoreg dna tetR txtl add dna tube3 thio junk 500 ptet 50 rbs 20 tetR 647 lva 40 16 linear dna deGFP txtl add dna tube3 p70 50 rbs 20 deGFP 1000 16 linear dna gamS txtl add dna tube3 p70 50 rbs 20 gamS 1000 1 plasmid Mobj txtl combine tubei tube2 tube3 simulationTime 8 60 60 t ode x ode m0bj simData txtl runsim Mobj simulationTime txtl plot t ode x ode Mobj The important differences from the gene expression examples are that here we add 3 pieces of DNA into tube 3 two of which are linear The tetR DNA uses a ptet promoter which is repressed by the tetR protein dimer Attached to the ptet promoter there are two domains thiosulfate thio and junk DNA junk which lower the rate of DNA degradation by the exonuclease RecBCD The tetR DNA also shows an lva tag which attaches a amino acid sequence to the tetR protein and marks it for degradation by the protease CIpXP In a futire version all the tags will be replaced by the ssrA
13. ch column containing data corresponding to the time evolution of the concentration of once species in the model See txtl runsim for more details e Mobj pointer to the model object associated with the data to be plotted e dataGroups these are optional cell arrays of strings which enable the user to customize what is plotted We will provide documentation on these in a future version of this manual Usage txtl plot t ode x ode Mobj where t ode x ode and Mobj are the variables defined in the file txtl addspecies txtl addspecies allows the addition of any species directly to the model object If this species is al ready present in the model the function simply increases its concentration by the amount that is added If the species is protein and is not present in the model then txtl addspecies adds the protein and sets up all the associated species dimers complexes and reactions repression induction degradation etc Syntax simBioSpecies txtl addspecies tube name amount Input e tube pointer to the model object to add the species to e name string name of the species to be added See below for format of string e amount double amount in nM of the species to add or to increase existing Species concentration by Output simBioSpecies pointer to the species object just added Usage inducer txtl addspecies Mobj aTc 20 Note that name strings have the following format 18 Sta
14. g of standard species like Proteins DNA RNA and resources We use txt1 plot to accomplish this One may simply call txt1 plot with the data and model object as follows txtl plot t ode x ode Mobj leading to a default set of species to be plotted 3 1 3 Results Figure 3 2 shows the output of the plotting command for this example The top plot shows the protein species present in the model the bottom left plot shows the DNA and mRNAs in the system and the bottom right plot displays the resource usage We observe that deGFP almost entirely exists in the mature state and rises constantly for the first 200 minutes before reaching a steady state of about 2uM Species amounts nM mRNA amounts nM Gene Expression 2000 protein deGFP protein deGFP protein gamS protein sigma28 protein sigma 1500 1000 500 y 100 200 300 400 500 600 700 800 900 Time min DNA and mRNA Resource usage 1 58 1 RNA rbs deGFP ES 1 85 mM 255 E AA mM SE RNAP nM 0 52 Ribo nM D 0 500 1000 D 500 1000 Time min Time min Figure 3 2 Gene Expression Output 3 2 Negative Autoregulation negautoreg 3 2 1 Overview Negative autoregulation refers to the repression of gene expression by a protein encoded by that very gene In this code we will show that dimerized tetR protein represses its own production and thus leads to a rel
15. gene is then transcribed into mRNA which is translated into DNA 3 2 shows the output plot for this example 3 1 2 Walk through Tf you have not already done so ensure that you are in the trunk directory and run txt1 init to add the necessary directories to the MATLAB search path The first step is to decide on a extract to use The extract contains RNAP Ribo 028 and 070 RecBCD RNA ase and sets up the reactions for the formation of RNAP70 and sequestration of RecBCD The extract we will be using will be created using parameters defined in the external configuration file E15 config csv and is implemented as N 07 Pro deGFP ta schematic png Figure 3 1 Schematic of the gene expression circuit tubel txtl_extract E15 Note that this command returns a handle to a Simbiology model object This is stored in the aptly named variable tube1 We will later combine the contents of this tube with those of other tubes just like we do in the experimental protocol One may read about Simbiology model objects at o ear detongect html Next we define the buffer containing AA and NTP to use and store it in tube2 Once again the buffer contents are drawn from the configuration file E15 config csv tube2 txtl_buffer E15 We then use the txt1 newtube command to create a new model object which will contain the DNA we wish to use This is done as follows tube3 txtl_newtube gene_expression
16. n was run on e simData output optional structure containing simulation data such as names of species Usage t ode x ode Mobj simData txtl runsim Mobj simulationTime t ode x ode useful feature of txt1_runsimis that is allows one to continue a simulation from the end point of a previous run with new species of more of existing species added before the simulation is continued This models the situation when additional reagents like inducers or proteins are added to an experimental preparation after the experiment has commenced This can be done as follows First call to txt runsim t ode x ode Mobj simData txtl runsim Mobj simulationTime Execute other code say add some inducer txtl_addspecies m0bj aTc 50 Continue simulation t ode2 x_ode2 Mobj simData txtl runsim Mobj t ode x ode simData 17 The new arrays t_ode2 x ode2 contain the results of the first simulation appended to the results of the second simulation Thus one can simply plot these to view the results since the beginning of the first simulation txtl plot Plotting command that simplifies the plotting of the evolution of the concentrations of the standard species Proteins of interest Resources and DNA and RNA concentrations Syntax txtl plot t ode x ode Mobj or txtl plot t ode x ode Mobj dataGroups Input e t ode vector array containing time point data e x ode matrix array with ea
17. nd MATLAB 2011b 2012a for Windows 2 2 Installing the toolbox 1 Download the toolbox zip archive txtl 0 42a tgz from the project s SourceForge page sourceforge net p txtl wiki Home 2 Unzip the file into a directory of your choice In windows this may take two unzip steps Ultimately you should have a folder named txt 0 42a 3 Set the MATLAB working directory to the folder txtl 0 42a or a parent folder 4 You may either run txtl init beginning of each MATLAB session or add the directories there to the search path and save 5 All done Try opening and running negautoreg m in the Examples directory If this runs without error you have successfully installed the TXTL modelling toolbox Congrats Chapter 3 EXAMPLES 3 1 Gene Expression with Fluorescent Reporter geneexpr 3 1 1 Overview This example shows constitutive expression of the destabilized enhanced Green Fluorescent Protein deGFP from a gene on a plasmid It shows one of the simplest circuits that can be modelled with the modelling toolbox and in doing so illustrates its basic features These include displaying the evolution of the expressed protein deGFP levels resource usage Amino Acids AA and Nucleotide Pairs NTPs the evolution of the DNA and mRNA concentrations Figure 3 1 shows a schematic of this circuit The diagram shows the DNA made of the p70 promoter the most common constitutive promoter in the toolbox followed by the deGFP gene The
18. ndard lt of specie Species Examples aTc IPTG 1 Expressed protein name of protein proteins Examples protein tetR protein lacI txtl_findspecies txtl findspecies is a useful function to find the column index of a given species in the matrix data array x ode returned by txt1 runsim This enables the user to access the trajectory of any species in the model Syntax indexlist findspecies Mobj namelist Input e Mobj pointer to the model object get species indices from e namelist string or cell array name of the species to be searched for or a cell array of such strings Output indexlist integer or vector of integers index of the species in the list of species in the model object and in the data array x ode returned by txt1 runsim The vector is returned when namelist is a cell array and the entries of the vector correspond to the indices for the entires in namelist Usage iGFP findspecies Mobj protein deGFP iRNAP28 DNA complex findspecies Mobj RNAP28 DNA p28_ptet rbs deGFP We can use the output of this function to plot the trajectory of the species as follows iGFP findspecies Mobj protein plot t ode x_ode iGFP or use the index directly plot t ode x ode findspecies Mobj DNA p28_ptet rbs deGFP protein tetRdimer r Note one can see a list of all the species in the model by runni
19. ng the command speciesNames get Mobj species name where Mobj is the model object 19 Chapter 5 APPENDIX 5 1 Externally Specified Parameters txtl reaction config class The txtl_ reaction config class enables users to input custom reaction parameters for the TXTL extract into their model This is done via a comma separated value csv file The parameters controlled by this class are given in the properties of this class List of Parameters 1 NTPMODEL There are two models for transcription that the toolbox can switch between model 1 and 2 We recommend keeping this setting at model 2 since model 1 suffers from stiffness of the differential equations to be solved and is primarily used for testing purposes 2 AAMODEL Similar to NTP model above we recommend keeping this setting at 2 3 TRANSCRIPTION RATE NTP RNAP DNA gt DNA RNAP 5 1 5 2 This is the reaction for transcription with transcription rate calculated as log 2 x 50 TRANSCRIPTION RATE 7 5 3 RNA length 8 8 5 4 and a dummy reaction for NTP consumption with rate l RANSCRIPTION RATE DUMMY NTP RNAP DNA gt DNA RNAP 5 5 NA_length TRANSCRIPTION RATE DUMMY Ss 1 X TRANSCRIPTION RATE 5 6 20 10 11 12 13 TRANSLATION RATE Reaction rate for ATP AA Ribo RNA gt Protein RNA Ribo 5 7 e lt This is the reaction for translation wi
20. nitial amounts defined in the txtl_reaction_config class See txtl_reaction_config in 3 3 for more infor mation This function also sets up the initial amounts for Ribosomes RNAP 028 and 070 Their values can be found in the file including the references they were extracted from txtl_buffer Set up a tube containing the TXTL Buffer This sets up the NTP and AA species with initial concentra tions from the supplied configuration file same as the one used for the Extract Syntax tube txtl_buffer name Input name string name of buffer Output tube pointer to Simbiology model object Usage tube2 txtl_buffer E6 Species NTP and AA 14 txtl_newtube Create a new model object tube containing one compartment called contents Syntax tube txtl newtube name Input name string name of new tube Output tube pointer to Simbiology model object Usage tube3 txtl_newtube circuit txtl_add_dna This function creates a piece of DNA that the user specifies and sets up all the associated species and reaction objects initial concentrations and reaction rate parameters The tube the DNA is placed in the initial amount and the type of DNA linear or plasmid are specified by the user The function returns a pointer to the DNA species object This is summarized below Syntax dna txtl_add_dna tube prom_spec rbs_spec gene_spec dna_amount type
21. rate by an amount proportional to the length of this DNA added with the constant of proportionality to be determined As an example a full specification of this string would look like thio junk 500 ptet 50 Note that only linear DNA can be degraded plasmid DNA does not degrade in this toolbox The gene spec string works similarly to the prom spec string The name of the gene is required and this must be associated with an existing protein file Defaults work similarly as in prom spec with a required component configuration file The optional strings are ssrA n and terminator n where ssRA is a degradation tag length n which marks the protein for degradation and the terminator will have capabilities in future releases of the toolbox 15 Note Generally the lengths in BP are used to calculate transcription and translation rates These lengths will have greater prevalence in the calculation of reaction rates in future versions of the toolbox txtl combine Combine the contents species and reactions of tubes to form a new tube Syntax Mobj txtl combine tubelist vollist Input tubelist vector of pointers A list of tubes to combine together Output Mobj pointer to the new tube Usage Mobj txtl combine tubei tube2 tube3 txtl runsim Simulate model txt1_runsim is the main function to execute the MATLAB differential equation solvers to solve for the species concentration trajectories fo
22. rward in time from a specified initial condition It returns a vector array t ode output containing time points and a matrix array x ode output containing the cor responding species concentration values x ode output is arranged such that each column corresponds to a species and contains that species concentrations at the time points corresponding to the points specified in t ode output 16 Syntax simData txtl runsim modelO0bj simulationTime with the following variations Input Mobj Mobj simulationTime Mobj simulationTime simData Mobj simulationTime t ode x ode Output simData t ode x ode t ode x ode Mobj t ode x ode Mobj simData Input e model0bj pointer to the model object to simulate This is the Simbiology model object returned by txt1 combine e t ode optional vector array containing time point data from previous runs See below for more information e x ode optional matrix array containing species concentration trajectory data from previous runs See below for more information e simData optional structure containing simulation data such as names of species and previous simulation data Output e t ode output vector array containing time point data from this run appended to data from previous runs if any e x ode output matrix array containing species concentration trajectory data from this run appended to data from previous runs if any e Mobj model object the simulatio
23. th reaction rate calculated as log 2 x 0 64 TRANSLATION RATE 5 9 T protein_length 5 10 and a dummy reaction for AA consumption with rate TRANSLATION DUMMY AA Ribo RNA Ribo ATP 5 11 tien length TRANSLATION_ RATE DUMMY 8 TRANSLATION RATE 5 12 DNA RECBCD FonwARD AND DNA_RECBCD_ REVERSE Complex formation and dissociation rate between RecBCD enzyme and DNA DNA RecBCD DNA RecBCD 5 13 DNA RECBCD coMPLEX DEG Degradation rate of RecBCD DNA complex DNA RecBCD gt RecBCD 5 14 PROTEIN CLPXP_ FORWARD AND PROTEIN CLPXP REVERSE Complex formation and dissociation rate between CIpXP enzyme and a protein tagged for degradation Protein CIpXP Protein ClpXP 5 15 PROTEIN CcoMPLEX DEG Degradation rate of CIpXP Protein complex Protein CIpXP CIpXP 5 16 RNAP S70 RNAP S70 RNAP7O formation and dissociation rate RNAP RNAP 5 17 AA FORWARD AND _ REVERSE Binding and dissociation of AA to Ribosome mRNA complex AA Ribo RNA AA Ribo RNA 5 18 RiBosoME BINDING_F AND RiBOSOME BINDING_R Binding and dissociation rated fro RNA Ribosome complex Ribo RNA Ribo RNA 5 19 RNA_DEG RNA degradation rate RNA RNAase gt RNAase 5 20 NTP _ FORWARD AND NTP_ REVERSE Binding and dissociation of NTP to the RNAP70 DNA com plex NTP RNAP DNA NTP RNAP DNA 5 21
24. to reduced repression of ptet by protein tetRdimer 12 t e e co e ew e e e e e Species amounts nM co e Time Responses oo _ ee O nM aTc 2 nM 5 nM aTc 10 nM aTc n 20 nM aTc ilf 40 nM j 100 nM aTc fj 300 nM aTe fj 1000 nM aTc 0 5 1 15 2 2 5 Time min 10 Figure 3 5 Induction of tetR expression due to aTc 13 Chapter 4 CORE FUNCTIONALITIES 4 1 User Commands Here we give details about the various functions you will be using in the modelling toolbox txtl extract Set up a tube containing the TXTL Extract This is usually the first function to be called and sets up various basic reaction rates species and reactions It takes the name of a configuration file containing pa rameter values as an input and returns pointer to a Simbiology model object The syntax and the usage of this function are summarized below along with the species reactions pa rameters and initial concentrations the function sets up Syntax tube txtl extract name Input name string name of extract Output tube pointer to Simbiology model object Usage tubel txtl_extract E6 Species RNAP Ribo 028 and 070 RecBCD RNA ase Reactions Formation of RNAP70 and sequestration of RecBCD Parameters Set up reaction rates AA and NTP models and i
25. xtl extract E9 tube2 txtl_buffer F9 Set up a tube that will contain our DNA tube3 txtl_newtube negautoreg dna tetR txtl add dna tube3 ptet 50 rbs 20 tetR 1200 1 plasmid 4 Mix the contents of the individual tubes Mobj txtl combine tubei tube2 tube3 txtl addspecies Mobj aTc 600 Run a simulation Gene Expression __ 150 eT CES 2 100 QUARE protein sigma28 5 protein sigma7 50 a protein tetR 5 0 ee a 7 S 0 100 200 300 400 500 600 70D 80 900 Time min DNA and mRNA Resource usage 15 18 1 RNA rbs tetR 3 10 1 220 5 NTP mM z 25 mM E SE RNAP nM e 5 095 0 Set t oZ E ac 0 0 9 05 0 500 1000 5 0 500 1000 Time min Time min Figure 1 1 Sample simulation of a negatively autoregulated transcriptional circuit simulationTime 14 60 60 tic simData txtl runsim Mobj simulationTime toc t ode simData Time x ode simData Data Plot the results txtl plot t ode x ode Mobj Figure 1 1 shows the output from this code plotted using the function Chapter 2 INSTALLATION 2 1 Prerequisites Our toolbox builds upon basic MATLAB functionality and the Simbiology toolbox Therefore the presence of Simbiology is essential for our TXTL toolbox to work The toolbox was tested on MATLAB 2012 for Mac OSX MATLAB 2010a for Linux a
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