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                <h3 class="subhead subhead--dark">IGEM 2018</h3>
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                <h1 class="display-1 display-1--light">Model</h1>
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                <h1 class="display-2">Rationale and Aim</h1>
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<p><font size="3">We have chosen to use Pseudomonas fluorescens (DSM 25356) as a chassis organism due to its rapid and abundant colonisation abilities within the rhizosphere. To ensure P. fluorescens can colonise effectively, the metabolic load and resource drain of our system on the cell must be kept to a minimum in order to conserve natural homeostasis and minimise waste. As our system utilises enzymes found in flavonoid production, our naringenin synthesis pathway will be most taxing on resources used to maintain the natural homeostasis of flavonoid pathways. Some of these resources (ATP, CoA and Malonyl CoA, for example) are included but not restricted to flavonoid production. If we are to program a cell to produce an amount of naringenin per unit time, we need to consider what range of output works best in terms of maintaining the cells homeostasis.</font></p>
 
  
<p><font size="3">On top of maintaining the cells homeostasis, sufficient naringenin needs to be produced by the pathway to attract the desired nitrogen fixing bacteria. The results of our chemotaxis experiments and previous research have shown higher concentrations of naringenin to inhibit growth of multiple soil microbes (1). It is therefore important that production by our system is stable in variable environmental conditions such that there are no detrimental effects on the rhizosphere community. By creating an enzymatic model of the pathway, we aimed to alter the operon design in order to minimise resource drain and stabilise naringenin production as a means of increasing system optimisation and robustness. </font></p>
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                <h3>Alternative Roots</h3>
  
</font>The chemotaxis modelling and wetware element to our project characterise the production rate of naringenin required for chemotaxis to occur. When the production rates of naringenin by our endophytic chassis have been characterised, the pathway model will give us the tools to alter the operon in order to optimise production.</font></p>
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                    Modelling Overview
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                        <div class="text">All soils have a unique, diverse microbial community</div>
 
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                        <div class="text">Within each microbial community there are many microbes with useful abilities </div>
 
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                        <div class="text">The bacterium Pseudomonas fluorescens lives in plant roots and helps them to grow</div>
 
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                        <div class="text">By introducing new genes for our Pseudomonas to express we can influence the microbial community</div>
 
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                        <div class="text">We can attract or repel certain species in any way desired </div>
 
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                        <div class="text">In our case, we use flavonoids to attract free-living nitrogen fixers, that convert nitrogen gas to nitrate for plant growth</div>
 
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                        <div class="text">P. fluorescens has many other abilities, including the ability to repel parasitic nematode worms [1], produce antifungals and insecticides [2] and induce plant stress tolerance [3]</div>
 
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<p><font size="3">We used two different mathematical modelling approaches to describe and simulate different aspects of our project. We built an <a href="https://2018.igem.org/Team:Newcastle/Modelling/Community" class="black">agent-based model</a> to understand the behaviour of nitrogen fixing bacteria in response to the chemoattractant naringenin. We used Simbiotics to visualise stochastic simulations via real-time animations. These models guided experimental work and were then informed by data from our chemotaxis experiments and bacterial growth characterisation. Our model provided insight into the biofilm formation process, including biofilm thickness and number of cells of each nitrogen-fixing species present. We also built a <a href="https://2018.igem.org/Team:Newcastle/Naringenin_Pathway" class="black">kinetic model</a> describing metabolic flux through the naringenin biosynthetic pathway. Our model employed mass action kinetics to describe the behaviour of reactants and products for each step in the pathway. By coupling this information with models describing the rates of production and turnover of the four naringenin biosynthetic enzymes we developed an improved genetic design for our biosynthetic devices.<font></p>
  
                    <p><font size="3">An effective solution would overcome both the energy expenditure and pollution associated with inorganic fertilisers but without losing properties such as broad and simple usage. Therefore our solution aims to create a single-application, broad host range sustainable alternative in the form of an engineered root endophyte that acts as a microbial adapter. This endophyte is Pseudomonas fluorescens.</font></p>
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<p><font size="3">In addition to mathematical models, our team also utilised statistical models for optimising both competent cell buffers and a defined media for <i>E. coli</i> DH5α transformation efficiency and growth respectively. Statistically driven design of experiments (DoE) was performed using JMP Pro 12 statistical software (SAS Institute Inc., USA), allowing the maximum design space coverage with minimum experimental runs. The least squares and partial least squares models produced for transformation efficiency and defined media respectively allowed identification of significant factors and predicted optimal buffer and media compositions. Additionally, the JMP screening platform predicted significant interaction affects using the principle of effect sparsity.<font></p>
  
                    <p><font size="3">A gram-negative bacterium with a diverse metabolism, P. fluorescens has been highlighted as a diverse plant growth promoting bacterium [1] capable of colonising a broad range of plant roots [2].</font></p>
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                    <p><font size="3">Pseudomonas fluorescens is known as a natural plant growth promoter for numerous reasons;</font></p>
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<ul style="list-style-type:circle; overflow:visible; display:grid; text-align:left;">
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<li>It produces a siderophore that liberates iron [3], consequentially liberating phosphorus too.[4]</li>
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<li>It has anti-fungal properties (protecting from pathogens).[5]</li>
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<li>It is nematophagous and produces nematode/protozoa repellents, protecting from parasites. [6]</li>
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<li>Produces anti-insectal toxins, protecting from pests. [6]</li>
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<li>Induces systemic resistance and tolerance.[7]</li>
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<p><font size="3">With all these features, pseudomonas fluorescens is already an ideal organism for improving crop yields, but the Newcastle iGEM project takes this a step further.</font></p>
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<p><font size="3">By engineering P. fluorescens to express novel genes the team aims to manipulate the soil microbial community via chemical attraction/repulsion to achieve desired processes. In our case this is a nutrient sustaining soil but there are no limits! From soil remediation to pest control, this project aims to create achassis out of Pseudomonas fluorescens so future scientists can manipulate the soil community in any way they like.</font></p>
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<p><font size="3">Our prototype focuses on sustaining the amount of Nitrogen present in soils without adding fertiliser or causing run-off. To combat this, we have introduced flavonoid biosynthesis genes to Pseudomonas fluorescens that attract free-living/non-nodulating nitrogen fixing bacteria to improve the nitrogen content of the soil [8].</font></p>
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<p><font size="3">This method means that one application is all that is needed to improve the nutrient availability for a plants life-time. This combined with the other protective roles of P. fluorescens acts to improve crop yields without genetically modifying plants and without Nitrogen/Phosphorus fertilisers. Even if we only reduce fertiliser use by a tiny amount, globally this would make a huge difference in terms of energy usage and pollution.</font></p>
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<p class="about-para"><font size="2">1) Bergey, D. H., et al. (1984). Bergey's manual of systematic bacteriology. Baltimore, MD, Williams & Wilkins.<font></p>
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<p class="about-para"><font size="2">2) Gómez-Lama Cabanás C, Schilirò E, Valverde-Corredor A, & Mercado-Blanco J (2014) The biocontrol endophytic bacterium Pseudomonas fluorescens PICF7 induces systemic defense responses in aerial tissues upon colonization of olive roots. Frontiers in Microbiology 5:427.
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<font></p>
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<p class="about-para"><font size="2">3) Gross, H. and J. Loper (2009). Genomics of secondary metabolite production by Pseudomonas spp.
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<font></p>
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<p class="about-para"><font size="2">4) Sharma SB, Sayyed RZ, Trivedi MH, & Gobi TA (2013) Phosphate solubilizing microbes: sustainable approach for managing phosphorus deficiency in agricultural soils. SpringerPlus 2:587.
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<font></p>
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<p class="about-para"><font size="2">5) Ruffner, B., et al. (2013). "Oral insecticidal activity of plant-associated pseudomonads." Environmental Microbiology 15(3): 751-763.
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<font></p>
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<p class="about-para"><font size="2">6) Jousset, A., et al. (2009). "Predators promote defence of rhizosphere bacterial populations by selective feeding on non-toxic cheaters." The Isme Journal 3: 666
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<font></p>
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<p class="about-para"><font size="2">7) Vanitha SC & Umesha S (2011) Pseudomonas fluorescens mediated systemic resistance in tomato is driven through an elevated synthesis of defense enzymes. Biologia Plantarum 55(2):317-322.
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<font></p>
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<p class="about-para"><font size="2">8) Maheshwari DK (2012) Bacteria in Agrobiology: Plant Probiotics (Springer Berlin Heidelberg).
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                             <h3 class=><font color="white">GROWING IN URBAN SPACES</font></h3>
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                 <h1 class="display-2"><font color="white">Advantages of Contained Agriculture</font></h1>
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                    <p>The effects of climate change are becoming more noticeable as time progresses; we are losing staggering amounts of valuable farmland due to mass flooding, freak weather events, soil erosion, infectious diseases and deforestation. Over the next 50 years, farming is going to become even more marginalised [1].</p>
 
  
                    <p style="font-size:100%">One way of protecting our crops and the land we use for agriculture is by growing within controlled, contained environments. Growing indoors is already a well-established practice; greenhouses are widely used and guarantee a safer, and more predictable method of growing all year round. There are many benefits of applying the contained, controlled environments found in greenhouses into urban spaces, these include:</p>
 
  
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<li>Providing cities with fresh produce all year round.</li>
 
<li>Reducing the Carbon footprint of crop production due to reduced food millage.</li>
 
<li>No agricultural run-off.</li>
 
<li>Limited need for pesticides and herbicides.</li>
 
<li>Safer crops as there is less risk of contamination.</li>
 
<li>Reduced spoilage because of shorter transportation times and reduced handling.</li>
 
<li>Less agricultural pollution.</li></ul>
 
  
                    <p style="font-size:100%"><br>With developing technologies in the field of sustainable energy, it could one day be possible to engineer contained growth systems that are self-sustaining in regards to its energy usage. By carefully controlling the parameters within these environments, we are able to emulate perfect surroundings that allow the crops to grow to their full potential, maximising yield.</p>
 
  
  
                    <p style="font-size:100%">Our project plans to use genetically modified bacteria, which means we will be working with GMO’s, but what are GMO’s? - “Genetically modified organisms (GMOs) can be defined as organisms (i.e. plants, animals or microorganisms) in which the genetic material (DNA) has been altered in a way that does not occur naturally by mating and/or natural recombination.”[2]</p>
 
  
                    <p style="font-size:100%">Integrations of GMO’s into the natural environment pose many concerns to both science and ecological communities. Introducing gm crops into the wild holds the potential to introduce engineered genes into foreign species. The effects of GMO release are widely unidentified, this is the main area of concern as there so many unknowns.</p>
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                    <p style="font-size:100%">The use of GM bacteria means that we have to take precautions when integrating it into the real world. We have identified the ways to ensure systems are enclosed and risk of GM run-off is minimised on our  <a href="https://2018.igem.org/Team:Newcastle/Safety">Safety Page</a>.</p>
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<p class="about-para"><font size="2"><strong>Attributions: Frank Eardley, Patrycja Ubysz, Matthew Burridge and Sam Went
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<p class="about-para"><font size="2">1. Despommier D (2011) The vertical farm: Controlled environment agriculture carried out in tall buildings would create greater food safety and security for large urban populations. J fur Verbraucherschutz und Leb 6(2):233–236.<font></p>
 
<p class="about-para"><font size="2">2.World Health Organization. (2018). Q&A: genetically modified food. [online] Available at: http://www.who.int/foodsafety/areas_work/food-technology/faq-genetically-modified-food/en/ [Accessed 13 Sep. 2018]..
 
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Latest revision as of 19:09, 17 October 2018

Alternative Roots/Notebook

Background

We used two different mathematical modelling approaches to describe and simulate different aspects of our project. We built an agent-based model to understand the behaviour of nitrogen fixing bacteria in response to the chemoattractant naringenin. We used Simbiotics to visualise stochastic simulations via real-time animations. These models guided experimental work and were then informed by data from our chemotaxis experiments and bacterial growth characterisation. Our model provided insight into the biofilm formation process, including biofilm thickness and number of cells of each nitrogen-fixing species present. We also built a kinetic model describing metabolic flux through the naringenin biosynthetic pathway. Our model employed mass action kinetics to describe the behaviour of reactants and products for each step in the pathway. By coupling this information with models describing the rates of production and turnover of the four naringenin biosynthetic enzymes we developed an improved genetic design for our biosynthetic devices.

In addition to mathematical models, our team also utilised statistical models for optimising both competent cell buffers and a defined media for E. coli DH5α transformation efficiency and growth respectively. Statistically driven design of experiments (DoE) was performed using JMP Pro 12 statistical software (SAS Institute Inc., USA), allowing the maximum design space coverage with minimum experimental runs. The least squares and partial least squares models produced for transformation efficiency and defined media respectively allowed identification of significant factors and predicted optimal buffer and media compositions. Additionally, the JMP screening platform predicted significant interaction affects using the principle of effect sparsity.







References & Attributions

Attributions: Frank Eardley, Patrycja Ubysz, Matthew Burridge and Sam Went