Difference between revisions of "Team:Amsterdam/Results"

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<h2>  Main Results  </h2>
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<h6> A highlight of what we have achieved </h6>
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<!-- Overview -->
 
<!-- Overview -->
 
<section id="carbon_prod" class="wrapper styleBlack">
 
<section id="carbon_prod" class="wrapper styleBlack">
 
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<header class="major">
<h2>Engineering Stable Carbon Production</h2>
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<h2><a href="https://2015.igem.org/Team:Amsterdam/Project/Eng_rom/Photosyn_car">Engineering Stable Carbon Production</a> </h2>
 
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   <img src="https://static.igem.org/mediawiki/2015/f/f8/Amsterdam_table_qp.png" alt=" Qp and growth">
 
   <img src="https://static.igem.org/mediawiki/2015/f/f8/Amsterdam_table_qp.png" alt=" Qp and growth">
 
   <figcaption>Table 1. - Estimated Growth and Q<sub>p</sub> for different <i>Synechocystis</i> strains.</figcaption>
 
   <figcaption>Table 1. - Estimated Growth and Q<sub>p</sub> for different <i>Synechocystis</i> strains.</figcaption>
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        <!-- Overview -->
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<header class="major">
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<h2><a href Evolving Romance</h2>
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                              <h3>Background</h3>
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                            <p>Emulsion culturing methods can be used to select for organisms with so called high-yield strategy. Compartmentalizing public goods and separating individuals allows for those who optimize nutrient to grow and produce more biomass - thus - over time taking over the culture. We deduced one elemental characteristic of consortia: the capacity to carryout high-yield strategy. 
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</p>
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                              <h3>Aim</h3>
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                            <p> Our aim is to develop an emulsion culturing method that allows us to select for "naturally" occurring consortia and evolve synthetic consortia to perform even better.
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</p>
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              <h3>Approach</h3>
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                            <p> We adapted the method used in the paper “availability of public goods shapes the evolution of competing metabolic strategies” by Bachmann et al. Also methods were developed to accurately count cells in co-cultures using the Coulter Counter and Florescence-Activated Cell Sorting(FACS).   
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                        <section>
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                              <h3>Results</h3>
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                            <ul style = "font-family: 'Montserrat', sans-serif">
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<li>We have demonstrated that <i>Synechocystis</i> a phototroph is able grow inside the emulsions. </li>
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<li>We demostrated that <i>Synechcystis</i> and <i>E.coli</i> can be recovered from the emulsion both separately and in co-culture.</li>
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<li>We developed methods for the detection and counting of <i>Synechocystis</i> and <i>E.col</i> using either a Coulter Counter or a FACS.</li>
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                              <h3>Connections</h3>
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                    <ul style = "font-family: 'Montserrat', sans-serif">
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<li><a href="https://2015.igem.org/Team:Amsterdam/Project/Stability">Stable Romance:</a> Measure stability.</li> 
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<figure class ="image fit">
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  <img src="https://static.igem.org/mediawiki/2015/0/0a/Amsterdam_Nico_bars.png" alt="Lactate Qp and growth">
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  <figcaption>Figure 1. - Growth of <i>Synechocystis</i> in emulsion after 7 days. First experiment to test if <i>Synechocystis</i> could grow in emulsion.</figcaption>
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<figure class ="image fit">
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  <img src="https://static.igem.org/mediawiki/2015/c/c8/Amsterdam_Nico_lac_Ace.png" alt="Lactate Qp and growth">
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  <figcaption>Figure 2. - The graph presents the growth after Seven days of the &Delta;acs acetate producing strain and SAA023 Lactate producing strain <i>Synechocystis</i> in emulsion. This was done by making the emulsion of both strains and breaking open at different days.</figcaption>
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</div>
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<div class="8u">
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<figure class ="image fit">
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  <img src="https://static.igem.org/mediawiki/2015/2/2a/Amsterdam_Nico_RR_e_coli_syne_1.png" alt=" Qp and growth">
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  <figcaption>Figure 3. - Recovery Rates of both <i>Sybechocystis</i> and <i>E.coli</i> from a co-culture.You can se that both organisms are recoverd however we have a large error seen in <i>E.coli</i> recovery rates.</figcaption>
 
</figure>  
 
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Revision as of 02:27, 19 September 2015

iGEM Amsterdam 2015

Main Results

A highlight of what we have achieved

Engineering Stable Carbon Production

Background

The driving force of our consortium's romance is the phototrophic carbon-sharing module: an engineered Synechocystis that fixes CO2 and produces compounds that can be used by a chemotroph to create desired end-products like biofuels.

Aim

Productive relationships need to stand the test of time. Having experienced the perils of instability firsthand, we sought to engineer carbon production in way that would last.

Approach

Using genetic engineering strategies guided by modelling results, we used a combination of gene knock-outs and over-expressions to target a pathway that would result in growth-coupled acetate production.

Results

  • We engineered growth-coupled acetate production by knocking out the acs gene, showing that this indeed leads to stable acetate production
  • We over-expressed the Pta and AckA1 proteins to increase the flux towards acetate formation, but found that the burden this puts on growth comes at a cost.
.

Connections

Acetate Qp and growth
Figure 1. - Growth and Qp of strain Δacs over 900 hours of continuous culture showing a constant production over the duration of the experiment.
 acetate concentrations
Figure 2. - Acetate concentrations over time in the variety of engineered Synechocystis strains.

Algorithms

Background

In our project we focussed on the stability in different ways. One way is genetic stability, which we needed to engineer a stable producing strain. Another was the stability of our consortium itself. We needed an auxotrophic organism in order to be able to create a strong interdependent consortium.

Aim

We need to find out what genes we could knock out to create a stable carbon producer. We also need to know what genes we should knock out in order to make an auxotrophic organism.

Approach

Here we present to you two novel algorithms which work with genome-scale FBA models. They can be used for any organism for which a genome-scale FBA model is available. One algorithm, the Stable Compound Generator, searches for ways to make a strain genetically stable produce carbon compounds. The second algorithm searches for ways to create an auxotrophic strain. Therefore we called it the Auxotrophy Sniper.

Results

  • We have created the Stable Compound Generator which find ways to stably produce a carbon compound in any organism.
  • We have created the Auxotrophy Sniper, which is able to find ways to crate an auxotrophic organism.
  • With the first algorithm we found a list products which could be stably produced by Synechocystis. We chose acetate from the list.
  • With the second algorithm we found out that it is possible to make a Synechocystis strain dependent on argenine, thus creating an auxotroph.

Connections

Sometimes modellers tend to be the lone wolfs in a project. We didn't want this to happen, so there are some clear connections between the tools we created with modelling and the wet lab. Initially the need to search for compounds which could be produced genetically stable, came from the wet lab, where we saw that most producing strains are unstable. Before we even started engineering Synechocystis, we wanted to find out whether we could produce a compound genetically stable. This is where the Stable Compound Generater comes in. We also needed to engineer an auxotroph in order to to use serial propagations of consortia in emulsions to find a more robust consortium. Both algorithms provided information which was really used in the lab.

Synechocystis physiological parameters

Background

Estimating physiological parameters is necessary for building meaningful models that can help us to rationally design our consortium. In addition, production stability can be assessed by estimating these parameters over a long cultivation periods.

Aim

We aim to use different cultivation strategies to characterize growth and production rates of carbon producing Synechocystis strains, while assessing their stability.

Approach

We have used a turbidostat cultivation system to determine the stability of the physiological parameters

Results

  • We have demonstrated the instability of classical engineering strategies. As shown in figure 1 the strain SAA023 loses the ability to produce lactate after 300 hours of continuous cultivation.
  • We show that the Qp in the growth coupled producer Δacs remains constant over that time (figure 2).
  • We have determined Qp and growth rates for six Synechocystis constructs (Table 1).
.

Connections

Lactate Qp and growth
Figure 1. - Growth and Qp of strain SAA023 over 900 hours of continuous culture showing the drop in production.
Acetate Qp and growth
Figure 2. - Growth and Qp of strain Δacs over 900 hours of continuous culture showing a constant production over the duration of the experiment.
 Qp and growth
Table 1. - Estimated Growth and Qp for different Synechocystis strains.

Background

Emulsion culturing methods can be used to select for organisms with so called high-yield strategy. Compartmentalizing public goods and separating individuals allows for those who optimize nutrient to grow and produce more biomass - thus - over time taking over the culture. We deduced one elemental characteristic of consortia: the capacity to carryout high-yield strategy.

Aim

Our aim is to develop an emulsion culturing method that allows us to select for "naturally" occurring consortia and evolve synthetic consortia to perform even better.

Approach

We adapted the method used in the paper “availability of public goods shapes the evolution of competing metabolic strategies” by Bachmann et al. Also methods were developed to accurately count cells in co-cultures using the Coulter Counter and Florescence-Activated Cell Sorting(FACS).

Lactate Qp and growth
Figure 1. - Growth of Synechocystis in emulsion after 7 days. First experiment to test if Synechocystis could grow in emulsion.
Lactate Qp and growth
Figure 2. - The graph presents the growth after Seven days of the Δacs acetate producing strain and SAA023 Lactate producing strain Synechocystis in emulsion. This was done by making the emulsion of both strains and breaking open at different days.
 Qp and growth
Figure 3. - Recovery Rates of both Sybechocystis and E.coli from a co-culture.You can se that both organisms are recoverd however we have a large error seen in E.coli recovery rates.