Difference between revisions of "Team:Newcastle/Modelling/Community"

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<p><font size="3">One of the applications for root-colonising Pseudomonas fluorescens (CT 364) as a chassis organism proposed was to produce a naturally occurring chemical – naringenin. The substance, as demonstrated in our laboratory (link), attracts free-living nitrogen fixing bacteria. Under the right conditions, this would benefit the plant’s nitrogen nourishment and possibly reduce synthetic nitrogen fertilizers usage. Although we already transformed Pseudomonas fluorescens with an operon with genes for naringenin biosynthesis, there is still a long way to test the system on plants. Plants need a lot of time to grow compared to microorganisms. Understanding how the root-colonising bacteria and the nitrogen fixers behave in the soil would be time intensive. To have an early insight and provide visualisations for the public, we developed the microbial community modelling to imitate what is happening in the soil around the inoculated root. </font></p>
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<p><font size="3">One application of root-colonising Pseudomonas sp. strain CT 364, as a proposed chassis endophyte, was to produce the naturally-occurring chemical, naringenin, in and around plant roots. The substance, as demonstrated in our laboratory (link), attracts free-living nitrogen fixing bacteria. Under the right conditions, this would benefit the plant by increasing nitrogen availability, and possibly reduce the need for synthetic nitrogen fertiliser use. </font></p>
 +
<p><font size="3">In the lab, we demonstrated that Pseudomonas sp. was a genetically tractable chassis organism, and that it could be used to colonise Arabidopsis roots. Based on this evidence, we propose that plant roots, colonised with Pseudomas sp. expressing an operon with genes for naringenin biosynthesis, would create a naringenin concentration gradient in the surrounding soil environment. To provide an early insight into the effect that naringenin production would have on the surrounding microbial community, and to provide visualisations for the public, we developed the microbial community modelling to imitate what is happening in the soil around the colonised root.</font></p>
  
  
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                   <p><font size="3">The method of modelling we have chosen is an agent-based model that allows us to see how changes in the rate of naringenin production influences the behaviour of the whole nitrogen fixing bacteria community. The software we used is SimBiotics [1], the agent-based modelling tool developed at Newcastle University. SimBiotics presents a way to visualise our stochastic simulations via real-time animations. Supported by the data from our chemotaxis experiments and growth curves <a href="https://2018.igem.org/Team:Newcastle/Experiments">(link)</a>, the model can accurately predict the biofilm formation process.</font></p>
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                   <p><font size="3">The method of chosen is an agent-based model that allows us to see the behaviour of the whole nitrogen fixing bacteria community under the influence of chemoattractant – naringenin. The software used is SimBiotics [1], the agent-based modelling tool developed at Newcastle University. SimBiotics provides a way to visualise stochastic simulations via real-time animations. Supported by data from our chemotaxis experiments and growth curves (link), the model was able to accurately predict the microbes' behaviour.</font></p>
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<p><font size="3">Due to a lack of time and computational resources, we have excluded competition factor from the model assuming an infinite amount of resources. To make the model even simpler we have set the Pseudomonas layer to be steady. As no Pseudomonas growth is observed so we can focus solely on the nitrogen fixers behaviour. </font></p>
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<p><font size="3">The model assumes infinite resources, hence no competition between the species as that scenario would be the most probable in the soil. The model consists of three bacterial species (<i>Pseudomonas sp.</i>, <i>Herbaspirillum seropedicae</i>, and <i>Azospirillum brasilense</i>). To focus on the formation of the biofilm itself, we have set the <i>Pseudomonas sp.</i> layer to be steady. There are 30 Pseudomonas cells distributed and attached to the top side of the modelled area representing rhizosphere and 100 cells of initial populations of each nitrogen fixing species performing chemotaxis. </font></p>
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<p><font size="3">The other bacteria growth is described by the first order kinetics (Reaction 1). To obtain understanding of bacterial growth, we monitored the change in absorbance (600nm) of our 3 nitrogen fixing bacteria grown at 30˚c for 72 hours. This data was then converted into cell density after experiments to identify cell count at specific optical densities. Through doing this, we obtained a conversion ratio. This allowed us to understand growth rate in a way that could be accurately incorporated into the model. </font></p>
+
<p><font size="3">The growth of the nitrogen fixing bacteria is described by the first order kinetics (Reaction 1). To obtain understanding of bacterial growth, we monitored the change in absorbance (600 nm) of our nitrogen fixing bacteria grown at 30 ˚C for 72 hours. These data were then converted into cell density after experiments to identify cell count at specific optical densities. Through doing this, we obtained a conversion ratio. This allowed us to understand growth rates in a way that could be accurately incorporated into the model. As soon as the bacteria reaches the length equal twice of the initial length (Table 1) it divides into two identical cells. </font></p>
 
<p><font size="3">The bacteria’s chemotactic movement is modelled with a modified version of micromotility and tumble run. Cells perform run and tumble, sample the chemoattractant concentration in periods of time  &Delta;<sub>t memory</sub> and compare it to the current concentration; C(t). If the value of C(t) - C(t – &Delta;<sub>t memory</sub>) is lower than one, the cell is more likely to tumble. Otherwise, a probability to tumble decreases with increasing gradient and the bacterium is less likely to stop running [1]. </font></p>
 
<p><font size="3">The bacteria’s chemotactic movement is modelled with a modified version of micromotility and tumble run. Cells perform run and tumble, sample the chemoattractant concentration in periods of time  &Delta;<sub>t memory</sub> and compare it to the current concentration; C(t). If the value of C(t) - C(t – &Delta;<sub>t memory</sub>) is lower than one, the cell is more likely to tumble. Otherwise, a probability to tumble decreases with increasing gradient and the bacterium is less likely to stop running [1]. </font></p>
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<p><font size="3">Naringenin forms the gradient according to the finite volume method of Fick’s law. The simulation domain is divided into nonoverlapping subdomains and the flux between them is calculated with the equation shown in Reaction 2. The chemical is degraded with rate kA [1](Reaction 3). All data and sources are provided in Table 1. </font></p>
+
<p><font size="3">Naringenin forms the gradient according to the finite volume method of Fick’s law. The simulation domain is divided into nonoverlapping subdomains and the flux between them is calculated with the equation shown in Reaction 2. The chemical is degraded with rate kA [1](Reaction 3).</font></p>
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<p><font size="3">Above certain concentrations, naringenin kills bacteria. The thresholds we set for the bacteria species (excluding Pseudomonas) is based on the experiments we conducted in the biological laboratory and its value is 150μM.</font></p>
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<p><font size="3">Above certain concentrations, naringenin kills bacteria. The threshold we set for the bacterial species (excluding <i>Pseudomonas sp.</i>) is based on the experiments we conducted in the biological laboratory where a concentration of 150 μM was found to be toxic</font></p>
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<p><font size="3">The model consists of three bacterial species (<i>Pseudomonas fluorescens</i>, <i>Herbaspirillum seropedicae</i>, and <i>Azospirillum brasilense</i>). <i>Pseudomonas</i> attaches to the top side of the modelled area which represents the rhizoplane. We described growth of nitrogen fixing bacteria using data from the laboratory and their morphology based on literature sources.</font></p>
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         <tr>
 
         <tr>
 
           <td>Growth Rate <i>Herbaspirillum seropedicae</i></td>
 
           <td>Growth Rate <i>Herbaspirillum seropedicae</i></td>
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           <td>4*10<sup>-4</sup> cell per second</td>
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           <td>4*10<sup>-4</sup> fg per second</td>
 
           <td>growth curves (link)</td>
 
           <td>growth curves (link)</td>
 
            
 
            
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         <tr>
 
         <tr>
 
           <td>Growth Rate <i>Azospirillum brasilense</i></td>
 
           <td>Growth Rate <i>Azospirillum brasilense</i></td>
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           <td>1.314*10<sup>-4</sup> cell per second</td>
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           <td>1.314*10<sup>-4</sup> fg per second</td>
 
           <td>growth curves (link)</td>
 
           <td>growth curves (link)</td>
 
          
 
          
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         </tr>
 
         </tr>
 
         <tr>
 
         <tr>
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           <td>Diameter, length of <i>Herbaspirillum seropedicae</i></td>
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           <td>Diameter, initial length of <i>Herbaspirillum seropedicae</i></td>
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           <td>0.7um, 1.5-5um</td>
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           <td>0.7μm, 1.5μm</td>
 
           <td>[2]</td>
 
           <td>[2]</td>
 
          
 
          
 
         </tr>
 
         </tr>
 
         <tr>
 
         <tr>
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           <td>Diameter, length of <i>Azospirillum brasilense</i></td>
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           <td>Diameter, initial length of <i>Azospirillum brasilense</i></td>
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           <td>0.5um, 2.9 um</td>
+
           <td>0.5μm, 2.9 μm</td>
 
           <td>[3]</td>
 
           <td>[3]</td>
 
        
 
        
 
         </tr>
 
         </tr>
 
  <tr>
 
  <tr>
−
           <td>Diameter, length of <i>Pseudomonas fluorescens</i></td>
+
           <td>Diameter, initial length of <i>Pseudomonas sp.</i></td>
−
           <td>0.5um, 1.5um</td>
+
           <td>0.5μm, 1.5μm</td>
 
           <td>[4]</td>
 
           <td>[4]</td>
 
        
 
        

Revision as of 09:31, 12 October 2018

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Model

Alternative Roots

Microbial Community

Introduction Model Design

Introduction

One application of root-colonising Pseudomonas sp. strain CT 364, as a proposed chassis endophyte, was to produce the naturally-occurring chemical, naringenin, in and around plant roots. The substance, as demonstrated in our laboratory (link), attracts free-living nitrogen fixing bacteria. Under the right conditions, this would benefit the plant by increasing nitrogen availability, and possibly reduce the need for synthetic nitrogen fertiliser use.

In the lab, we demonstrated that Pseudomonas sp. was a genetically tractable chassis organism, and that it could be used to colonise Arabidopsis roots. Based on this evidence, we propose that plant roots, colonised with Pseudomas sp. expressing an operon with genes for naringenin biosynthesis, would create a naringenin concentration gradient in the surrounding soil environment. To provide an early insight into the effect that naringenin production would have on the surrounding microbial community, and to provide visualisations for the public, we developed the microbial community modelling to imitate what is happening in the soil around the colonised root.

Model Design

The method of chosen is an agent-based model that allows us to see the behaviour of the whole nitrogen fixing bacteria community under the influence of chemoattractant – naringenin. The software used is SimBiotics [1], the agent-based modelling tool developed at Newcastle University. SimBiotics provides a way to visualise stochastic simulations via real-time animations. Supported by data from our chemotaxis experiments and growth curves (link), the model was able to accurately predict the microbes' behaviour.

The model assumes infinite resources, hence no competition between the species as that scenario would be the most probable in the soil. The model consists of three bacterial species (Pseudomonas sp., Herbaspirillum seropedicae, and Azospirillum brasilense). To focus on the formation of the biofilm itself, we have set the Pseudomonas sp. layer to be steady. There are 30 Pseudomonas cells distributed and attached to the top side of the modelled area representing rhizosphere and 100 cells of initial populations of each nitrogen fixing species performing chemotaxis.

The growth of the nitrogen fixing bacteria is described by the first order kinetics (Reaction 1). To obtain understanding of bacterial growth, we monitored the change in absorbance (600 nm) of our nitrogen fixing bacteria grown at 30 ˚C for 72 hours. These data were then converted into cell density after experiments to identify cell count at specific optical densities. Through doing this, we obtained a conversion ratio. This allowed us to understand growth rates in a way that could be accurately incorporated into the model. As soon as the bacteria reaches the length equal twice of the initial length (Table 1) it divides into two identical cells.

The bacteria’s chemotactic movement is modelled with a modified version of micromotility and tumble run. Cells perform run and tumble, sample the chemoattractant concentration in periods of time Δt memory and compare it to the current concentration; C(t). If the value of C(t) - C(t – Δt memory) is lower than one, the cell is more likely to tumble. Otherwise, a probability to tumble decreases with increasing gradient and the bacterium is less likely to stop running [1].

Naringenin forms the gradient according to the finite volume method of Fick’s law. The simulation domain is divided into nonoverlapping subdomains and the flux between them is calculated with the equation shown in Reaction 2. The chemical is degraded with rate kA [1](Reaction 3).

Above certain concentrations, naringenin kills bacteria. The threshold we set for the bacterial species (excluding Pseudomonas sp.) is based on the experiments we conducted in the biological laboratory where a concentration of 150 μM was found to be toxic

μ = Gr ± Gv
Reaction 1. first order kinetics

Ji→j = DcSij/dij(uj-ui)
Reaction 2. flux between neighbouring subdomains (finite volume method of Fick's Law)
Dc - diffusion coefficient, Sij - cross-section, dij distance between the centres of the two subdomains, uj and ui concentrations in the subdomains

A → ⌀ kA
Reaction 3: degradation of naringenin.

Parameter Value Source
Growth Rate Herbaspirillum seropedicae 4*10-4 fg per second growth curves (link)
Growth Rate Azospirillum brasilense 1.314*10-4 fg per second growth curves (link)
Naringenin concentration threshold 150 μM Experiment (link)
Diameter, initial length of Herbaspirillum seropedicae 0.7μm, 1.5μm [2]
Diameter, initial length of Azospirillum brasilense 0.5μm, 2.9 μm [3]
Diameter, initial length of Pseudomonas sp. 0.5μm, 1.5μm [4]
Table 1: Table of the parameters used to create the soil community model and the references.





REFERENCES & Attributions

1. Naylor J, Fellermann H, Ding Y, Mohammed W, Jakubovics N, Mukherjee J, Biggs C, Wright P, Krasnogor N (2016) Simbiotics: A Multiscale Integrative Platform for 3D Modeling of Bacterial Populations. ACS Synthetic Biology 2016 DOI: 10.1021/acssynbio.6b00315 (link)

2. Baldani JI, Baldani VLD, Seldin L, Doebereiner J (1986) Characterization of Herbaspirillum seropedicae gen. nov., sp. nov., a Root-Associated Nitrogen-Fixing Bacterium International Journal of Systematic and Evolutionary Microbiology 36: 86-93, doi: 10.1099/00207713-36-1-86

3. Tarrand JJ, Kried NR, Doebereiner J (1978) A taxonomic study of the Spirillum lipoferum group, with descriptions of a new genus, Azospirillum gen. nov. and two species, Azospirillum lipoferum (Beijerinck) comb. nov. and Azospirillum brasilense sp. nov. Canadian Journal of Microbiology 24: 967-980

4. Rhodes ME (1959) The Characterization of Pseudomonas fluorescens Journal of general Microbiology 21: 221-263

Attributions: Patrycja Ubysz, Connor Trotter