turtles-own [ energy ] patches-own [ nutrition ] breed [ Xanthomonas Xanthomona ] breed [ contaminants contaminant ] globals [ xanthan biomass viscosity ] to setup clear-all set xanthan 0.0001 ask patches [ set pcolor green set nutrition substrate-quality ] set-default-shape Xanthomonas "bug" create-Xanthomonas num-Xanthomonas [ set color yellow set energy 1 + random 10 setxy random-xcor random-ycor] foul determine-biomass reset-ticks ;; begins defining a procedure named "setup" ;; resets the world to an initial, empty state ;; creates 100 turtles, they start out standing at the origin 0,0 ;; set default shape so I don't have to tell it every time ;; A turtle's color variable is random until specified ;; setxy command with next two numbers as inputs ;; chooses random reporters for allowable x and y coordinates End to foul set-default-shape contaminants "wheel" if Contamination? [create-contaminants num-contaminants [set color red set energy random (10 + Contaminant-advantage) setxy random-xcor random-ycor ] ] end to determine-biomass ifelse Contamination? [set biomass num-Xanthomonas + num-contaminants ] [set biomass num-Xanthomonas ] end to go if ticks >= 2000 [ stop ] if count turtles > 2000 [ stop ] if count turtles = 0 [ stop ] feed move-turtles ask turtles [ eat-glucose ] ask turtles [ reproduce ] check-death thicken tick end to Feed if Continuous-feed? [ ask patches [if random 100 < 3 [set pcolor green set nutrition nutrition + substrate-quality ] ] ] end to move-turtles ;; says that each turtle should run the commands in the brackets ;; random doesn't include the number you give it as a possible result ;; uses a reporter, each turtle picks a random whole number between 0 and 359 ;; makes the turtle move forward one step ;;specify what you're defining will lose 1 energy per step ifelse viscosity? [ask turtles [right random 360 forward 2 set energy energy - viscosity ]] [ask turtles [right random 360 forward 2 set energy energy - 1 ]] end to thicken if viscosity? [set viscosity round ( log xanthan 3 )] end to eat-glucose ifelse breed = Xanthomonas [ if pcolor = green [ set energy energy + 10 set nutrition nutrition - 50 set pcolor gray ] ] [ if pcolor = green [ set energy energy + 10 + Contaminant-advantage set nutrition nutrition - 50 set pcolor gray ] ] ifelse show-energy? [ set label energy ] [ set label "" ] ;;ask turtles before "if" ;;if when true, and only then will the turtle run the commands inside the brackets (otherwise it skips them) ;;true/false questions, if true, will do first set of brackets ;;false means turtle runs commands in second set of bracket ;;energy (elements) will default to zero end to reproduce ifelse breed = Xanthomonas [ if energy > 50 [set energy energy - 50 set xanthan xanthan + 1 hatch-Xanthomonas 1 [set biomass biomass + 1 rt random-float 360 fd 1 ] ] ] [ if energy > 50 - Contaminant-advantage [set energy energy - 50 + Contaminant-advantage hatch-contaminants 1 [set biomass biomass + 1 rt random-float 360 fd 1 ] ] ] end to check-death ask turtles [ if energy < 0 [ die ] ] end to add-substrate ask patches [ if random 100 < 10 [ set pcolor green set nutrition nutrition + substrate-quality ] ] end to Contaminate crt num-contaminants [ set color red set shape "wheel" setxy random-xcor random-ycor ] end @#$#@#$#@ GRAPHICS-WINDOW 219 10 656 448 -1 -1 13.0 1 10 1 1 1 0 1 0 1 -16 16 -16 16 1 1 1 ticks 30.0 BUTTON 243 457 307 490 Setup Setup NIL 1 T OBSERVER NIL NIL NIL NIL 1 BUTTON 330 457 393 490 NIL Go T 1 T OBSERVER NIL NIL NIL NIL 0 MONITOR 1083 11 1166 56 Viable Cells count turtles 17 1 11 MONITOR 1083 117 1176 162 Substrate Count patches with [pcolor = green] 17 1 11 SWITCH 31 256 170 289 show-energy? show-energy? 0 1 -1000 PLOT 664 10 1073 289 population size time number of microbes 0.0 10.0 0.0 10.0 true true "" "" PENS "Contaminant" 1.0 0 -5298144 true "" "plot count turtles with [color = red]" "Xanthomonas " 1.0 0 -1184463 true "" "plot count turtles with [color = yellow]" MONITOR 1083 171 1172 216 Contaminants count turtles with [color = red] 17 1 11 SLIDER 30 10 202 43 num-Xanthomonas num-Xanthomonas 1 10 5.0 1 1 NIL HORIZONTAL SWITCH 29 174 183 207 Continuous-feed? Continuous-feed? 1 1 -1000 BUTTON 554 456 665 489 Add Substrate add-substrate NIL 1 T OBSERVER NIL NIL NIL NIL 0 MONITOR 1083 65 1169 110 Xanthan gum round sum [ xanthan ] of patches 17 1 11 PLOT 873 294 1073 448 Xanthan gum time [P] xanthan gum 0.0 10.0 0.0 10.0 true false "" "" PENS "default" 1.0 0 -16777216 true "" "plot SUM [ xanthan ] of patches" PLOT 664 294 864 448 Substrate time [ S ] Substrate 0.0 10.0 0.0 10.0 true false "" "" PENS "default" 1.0 0 -11085214 true "" "plot count patches with [pcolor = green]" SWITCH 29 50 170 83 Contamination? Contamination? 1 1 -1000 SLIDER 29 91 201 124 num-contaminants num-contaminants 1 10 5.0 1 1 NIL HORIZONTAL BUTTON 449 456 551 489 NIL Contaminate NIL 1 T OBSERVER NIL NIL NIL NIL 0 MONITOR 1084 224 1172 269 Total biomass Biomass 17 1 11 SLIDER 29 214 201 247 substrate-quality substrate-quality 10 100 50.0 10 1 NIL HORIZONTAL SLIDER 29 131 214 164 Contaminant-advantage Contaminant-advantage -20 20 5.0 1 1 NIL HORIZONTAL SWITCH 31 296 140 329 Viscosity? Viscosity? 0 1 -1000 MONITOR 1085 277 1145 322 NIL Viscosity 17 1 11 @#$#@#$#@ ## WHAT IS IT? This model seeks to recapitulate population dynamics and productivity observed within a bioreactor producing xanthan gum, an important natural polysaccharide. Industrial bioreactors utilize _Xanthomonas campestris_ to produce xanthan gum to be used as a thickener and stabilizer in food, pharmaceutical, and cosmetic products. Microbes within a substrate-limited environment experience competition, which constrains their population size. Additionally, there is the possibility the reactor becomes contaminated, which can reduce product yield or fully out-compete _X. campestris_. Other factors impacting the overall efficiency of the process include the increasing viscosity as xanthan gum accumulates, making it more difficult for microbes to acquire nutrition. ## HOW IT WORKS Different substrates can be explored, with varying energetic value to the cells. The model can simulate batch, fed-batch, or continuous culture conditions. The environment represents the medium conditions inside the bioreactor: * Substrate available (green patches) * Substrate depleted (gray patches) There are up to two types of microbe represented: * _X. campestris_ (yellow bug) * Unknown contaminant (red wheel) _X. campestris_ and the contaminant enact the following behaviors: 1. Cells move within the environment, as we are assuming the reactor is well-mixed. -As cells move and time passes, the cells use energy for maintenance metabolism. -When viscosity is considered, it takes more time to gather enough substrate for reproduction. 2. Cells eat substrate, giving themselves energy and depleting the medium. -Contaminants could have varying levels of fitness, and thus could be more or less effective at converting substrate to energy, which is their budget for maintenance and reproduction. 3. Cells reproduce themselves when they have enough energy. -In this model, reproduction is accompanied by xanthan gum production. 4. Cells die when they run out of energy. This can be used as a closed batch or the observer can tamper with the environment by adding more substrate or perhaps contaminating the bioreactor while taking a sample. ## HOW TO USE IT 1. You can set the initial population size of _X. campestris_ using the slider labeled "num-Xanthomonas" 2. Decide whether this reaction will start off contaminated using the "Contamination?" switch -If you decide to contaminate the reactor, you can adjust the initial number of contaminating agents using the slider labeled "num-contaminants". If you choose to contaminate a batch mid-reaction, this slider also controls the number of contaminating agents that are inoculated when clicking the "Contaminate" button. -The contaminant's fitness advantage can be adjusted using the "Contaminant-advantage" slider. This controls the contaminant's ability to utilize substrate for reproduction, relative to _X. campestris_. Note that you can also put the contaminant's metabolic efficiency to be equal to or less than that of _X. campestris_. 3. Setting the "Continuous-feed" switch to on will simulate a continuous culture reactor by continuously providing substrate. Note that this does not always ensure the microbe community does not die out. 4. The "substrate-quality" slider controls how much nutrition a patch receives upon setup and subsequent feedings, which can occur when running Continuous-feed and whenever you push the button labeled "Add Substrate". 5. The "show-energy?" slider allows the user to toggle whether turtles display their current energy value. 6. The "Viscosity?" switch allows users to account for the increasing viscosity of the medium as xanthan gum accumulates. Switching it off allows the user to consider bioreactors where the population is not affected by the product or a situation in which the product is continuously removed. 7. Click "Setup" 8. Click "Go". The model can be paused by pressing "Go" again. Varying the above parameters will simulate various reactor operating conditions and microbial metabolic variations. ## THINGS TO NOTICE * As you vary the parameters above, take note of the final biomass and xanthan gum produced. * When substrate is limited we see exponential growth in _X. campestris_, followed by a decline as substrate becomes more depleted. * Poorer substrates result in lower overall xanthan gum production. * Contamination substantially reduces overall xanthan gum production. * Viscous conditions prevent microbes from utilizing all the substrate available, which leads to waste. There are three graphs: 1. Population fluctuation over time -This tracks the number of viable microbes currently in the reactor, where yellow represents Xanthomonas and red is the contaminant. -Note that the Biomass monitor tracks the number of cells that have ever lived. 2. Substrate -in a batch model you will see the rate of substrate consumption increase, then decrease as the substrate is depeted by the growing population of microbes. 3. Xanthan gum produced ## THINGS TO TRY * Move the ticks slider to "slower". Right-click any microbe and choose "inspect" from the pop-up menu. It is easiest to click on a microbe when the model is paused. You can then watch the microbe wander around ant track its energy level as it moves, eats, and reproduces. * Set the "Continuous-feed?" switch to "On". Right click any patch and choose "inspect" from the pop-up menu. You can now watch the nutritious content of that patch fluctuate as microbes eat and as substrate is replenished. Change the "substrate-quality" slider and see how this affects the nutrient cycling on a patch. * Run multiple iterations. Use the data obtained to compare to existing logistic equations for batch cultures. ## EXTENDING THE MODEL There are different types of microbial interactions possible. You can expand this model by including a contaminant with a more direct effect on _X. camperis_. This can include predatory microbes or phages. You could also program the contaminant organism to perform other disruptive behavior, such as forming biofilms that obstruct thorough mixing of the culture. The expectation is that this would limit _X. camperis_ access to resources and lead to early culture death and lower product yields. You could also incorporate multiple substrates, rather than having one substrate on a slider. In culture, it is observed that microbes will first consume their preferred substrate (e.g. glucose) before metabolizing a secondary sugar, such as sucrose. When the preferred substrate is depleted, there is a lag in population growth before the microbes resume exponential growth. This delay is believed to be caused by the amount of time it takes the microbes to build the enzymes they need to break down the second substrate. ## CREDITS AND REFERENCES Ginovart, M., & Prats, C. (2012). A Bacterial Individual-Based Virtual Bioreactor to Test Handling Protocols in a NetLogo Platform. Mathematical Modeling, 7(1). http://doi.org/10.3182/20120215-3-AT-3016.00115 Wilensky, U. 1999. NetLogo. http://ccl.northwestern.edu/netlogo/. Center for Connected Learning and Computer-Based Modeling, Northwestern University. Evanston, IL. Wilensky, U. (2005). NetLogo Wolf Sheep Predation (System Dynamics) model. http://ccl.northwestern.edu/netlogo/models/WolfSheepPredation(SystemDynamics). Center for Connected Learning and Computer-Based Modeling, Northwestern University, Evanston, IL. ## HOW TO CITE To cite the model itself: Sanderlin, V. (2017). Xanthan Gum Bioreactor 2017. http://ccl.northwestern.edu/netlogo/models/community/Xanthan_Gum_Bioreactor. To cite the NetLogo software: Wilensky, U. (1999). NetLogo. http://ccl.northwestern.edu/netlogo/. Center for Connected Learning and Computer-Based Modeling, Northwestern University, Evanston, IL. 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