Difference between revisions of "Team:Amsterdam/Project/emulsions"

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                               <h3>Background</h3>
 
                               <h3>Background</h3>
 
                              
 
                              
                             <p>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 this parameters over a long period of time.
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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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                               <h3>Aim</h3>
 
                               <h3>Aim</h3>
 
                              
 
                              
                             <p>We aim to use different cultivation strategies to characterize  growth and production rates of carbon producing <i>Synechocystis</i> strains and their stability.
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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>
 
               <h3>Approach</h3>
 
               <h3>Approach</h3>
 
                              
 
                              
                             <p> We have used turbidostat cultivation system to determine the stability of the physiological parameters
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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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<li>We have demonstrated the instability of classical engineering strategies. As shown in figure 1 the strain SAA023 lose the ability to produce lactate after 300 hours of continuous culture.</li>  
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<li>We have demonstrated that <i>Synechocystis</i> a phototroph is able grow inside the emulsions. </li>  
<li>We show that the Q<sub>p</sub> in the growth coupled producer &Delta;acs remains constant over the time (figure 2).</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>  
<li>We have estimated Q<sub>p</sub> and growth rates for six <i>Synechocystis</i> (Table 1).</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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                    <ul style = "font-family: 'Montserrat', sans-serif">
 
                    <ul style = "font-family: 'Montserrat', sans-serif">
 
<li><a href="https://2015.igem.org/Team:Amsterdam/Project/Stability">Stable Romance:</a> Measure stability.</li>   
 
<li><a href="https://2015.igem.org/Team:Amsterdam/Project/Stability">Stable Romance:</a> Measure stability.</li>   
<li><a href = "https://2015.igem.org/Team:Amsterdam/Project/Eng_rom/Photosyn_car">Engineering Romance:</a> Estimate parameters of new strains.</li>
 
<li><a href = "https://2015.igem.org/Team:Amsterdam/Project/Simulations">Simulating Romance:</a> Provide parameters.</li>
 
 
</ul>
 
</ul>
 
                             </section>                   
 
                             </section>                   
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  <figure class ="image fit">
 
  <figure class ="image fit">
   <img src="https://static.igem.org/mediawiki/2015/3/3b/Amsterdam_qp_lactate.png" alt="Lactate Qp and growth">
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   <img src="https://static.igem.org/mediawiki/2015/0/0a/Amsterdam_Nico_bars.png" alt="Lactate Qp and growth">
   <figcaption>Figure 1. - Growth and Q<sub>p</sub> of strain SAA023 over 900 hours of continuous culture showing the drop in production.</figcaption>
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   <figcaption>Figure 1. - Growth of <i>Synechocystis</i> in emulsion after 7 days. Initial experiment to test if <i>Synechocystis</i> could grow in emulsion.</figcaption>
 
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   <img src="https://static.igem.org/mediawiki/2015/6/68/Amsterdam_qp_acetate.png" alt="Acetate Qp and growth">
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   <img src="https://static.igem.org/mediawiki/2015/c/c8/Amsterdam_Nico_lac_Ace.png" alt="Lactate Qp and growth">
   <figcaption>Figure 2. - Growth and Q<sub>p</sub> of strain &Delta;acs over 900 hours of continuous culture showing a constant production over the duration of the experiment.</figcaption>
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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 emulsions. This was done by making the emulsion of both strains and breaking them open throughout a week.</figcaption>
 
</figure>  
 
</figure>  
 
 
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   <img src="https://static.igem.org/mediawiki/2015/f/f8/Amsterdam_table_qp.png" alt=" Qp and growth">
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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">
   <figcaption>Table 1. - Estimated Growth and Q<sub>p</sub> for different <i>Synechocystis</i> strains.</figcaption>
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   <figcaption>Figure 3. - Recovery rates of both <i>Synechocystis</i> and <i>E.coli</i> from a co-culture. Results clearly indicate that both organisms can be recovered</figcaption>
 
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<section id="intro" class="wrapper style5">
 
<section id="intro" class="wrapper style5">
 
<header class = "major">
 
<header class = "major">
<h2>How to measure stability?</h2>
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<h2>Fishing out a Consortia </h2>
 
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<p>
 
<p>
One faces two main problems when trying to study the stability of the aforementioned parameters in <i>Synechocystis</i>. One is how to maintain a culture originated from the same population growing for many generations giving the opportunity to the cells to accumulate mutations and evolve. One option is to grow the cells on a flask until they reach the lag phase then reinoculate a fraction of this culture to a new fresh medium. Although this method allows the population to evolve it can take a long time to observe mutations because during the  lag and the stationary phase of bacterial growth cells do not divide. This can seems trivial but due to the slow growth rate of <i>Synechocystis</i> it can make a difference.
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Stable Romances tend to evolve when there is a perfect understanding between the individuals. Whether a match is a perfect fit (or not!) can be tested when partners are forced to interact for instance, when people move in together. So imagine applying the same principle to consortia were we deduced that an underlying property of all consortia is that ultimately they will display a so-called “high-yield strategy”. By High-yield strategy, it is meant that a more efficient use of natural resources leading to a greater number of individuals will be observed. This is even more so the case when instability is a serious threat.
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,<p>
 +
<p>
 +
What if there was a way to select these high-yield strategy consortia and actually make them interact better? How would one do this? Well… just like with people, this is possible to test by making microbes move in together.  
 +
 
 +
<p>
 +
We decided to tackle this problem by looking at studies done using emulsion based techniques selecting for high-yield strategies (Bachmann et al.). In this paper, the authors discuss the tradeoff that occurs between growth rate and growth yield in microbes. They demonstrate that compartmentalizing the availability of public goods while serial propagating leads to the selection of organisms with increased yield strategy, i.e. able to generate ever higher cell numbers (biomass) from the same portion of substrate. We apply the same logic to consortia by developing a dedicated emulsion-based protocol.
 
</p>
 
</p>
 
<figure class ="image fit">
 
  <img src="https://static.igem.org/mediawiki/2015/d/db/Amsterdam_turbidostat.gif" alt=" Turbidostat">
 
  <figcaption style="color: #2C3539">Figure 3. - How a turbidostat works for dummies. </figcaption>
 
</figure>
 
 
 
<p>    
 
<p>    
Turbidostat are culture devices that allow to maintain the cells in constant exponential growth. This is achieved by automatically diluting the culture, i.e. pumping in fresh medium and pumping out culture medium, when a certain threshold is reached. Its name refers to the fact that the turbidity of the medium, so  the amount of cells, it maintained (-stat from static) on a certain range. This requires a three compartment system where the first contains the cultures, the second holds a reservoir of fresh medium and the third collect the medium extracted from the cultures. Pumps move the medium between containers. The cell density is recorded at regular intervals by a spectrophotometer and based on this value a software decides when the culture is diluted.  
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The basic principle is that by randomly combining different individuals of each side of the partnership in isolated compartments (micro-droplets), perfect matches will lead to increased numbers of offspring of both photo- and chemotroph. If propagated in time, ultimately this will enrich the mixture in both photo- and chemotrophs that do well when placed in a consortium while purging the population of the ones that do not.
 
</p>
 
</p>
 +
<p>
 +
This method can be used to select “naturally” occurring consortia, or to evolve the synthetic consortia that have been rationally engineered. For example, chemotrophs that use more efficiently the carbon source provided by the phototroph can be co-selected at the same time that the population is enriched in phototrophs that, not only grow efficiently on the required nutrient produced by the chemotroph, but also are more capable of fixing CO<sub>2</sub> and “willing” to release the C-source. After this process, biobricks of choice can be added to the chemotroph in order to produce a compound with the knowledge that the chemotroph consumes the produced carbon more efficiently – and hence (if all things alike) is potentially able to make the product of interest also more efficiently. 
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</p>
 
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  <img src="https://static.igem.org/mediawiki/2015/a/a2/Amsterdam_Nico_infograph_David.png">
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  <figcaption style="color: #2C3539">Figure 4. Schematic overview of intended uses for the emulsion technique. </figcaption>
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</figure>
  
<p>
 
  
This system allow us to reduce the time of observing a mutation but now it comes the second problem. How do we know if a mutation leading to a change in the parameters has happened? The first option that comes to our synthetic biologist mind is by sequencing periodically the genome of the population and screen it for mutations. The major drawback of sequencing is that it does not inform whether the mutation affects the parameters or not. The remaining solution is then to estimate the physiological parameters with high time definition to spot when the mutation has occurred. Using the turbidostat it would be possible to store all the values recorded by the spectrophotometer and calculate the growth rate from these data. This is done by fitting a linear model to the logarithm of the OD over the time. The production rate can obtained by periodically measuring the amount of product in the medium (link to protocols for enzymatic assays and HPLC).
 
</p>
 
 
  <figure class ="image fit">
 
  <figure class ="image fit">
   <img src="https://static.igem.org/mediawiki/2015/b/b6/Amsterdam_MC.png" alt=" Turbidostat">
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   <img src="https://static.igem.org/mediawiki/2015/8/86/Amsterdam_Nico_Emulsions_with_syne_and_ecoli_1.png">
   <figcaption style="color: #2C3539">Figure 4. - The multicultivator. </figcaption>
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   <figcaption style="color: #2C3539">Figure 5. - Droplets filled with <i>Synechocystis</i> and <i>E.coli</i> . </figcaption>
 
</figure>  
 
</figure>  
<p>  
 
Luckily for us  when we came to the lab there was a master student, Joeri Jongbloets{link}, who had transformed a multicultivator (MC) like this{link} in a 8 channel turbidostat. For his internship he wrote the program that connect with the MC hardware and control the pumps to dilute the culture when necessary. In addition the software stores the measurements from the MC spectrophotometers in a database and analyzes it to obtain the growth rate. Thanks to this impressive piece of software engineering we were able to run long term experiments and observe evolution.
 
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<header>
 
<header>
<h4>Cultivation conditions</h4>
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<h4>Emulsion method</h4>
 
</header>
 
</header>
<p>The strains producing glycerol, lactate and acetate (&Delta;acs) were grown in turbidostats for 900 hours under constant LED lights providing 20 &mu;E/ m<sup>2</sup>* s * OD. </p>
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<p>Emulsions were created using 700&mu;l HFE 7500 mixed with 0.2% picosurf as a surfactant. This was mixed with 300&mu;l of medium (BG11 enriched with TES buffer, Bicarbonate and 5mM ammonium chloride) with the expectation to create 4.6x106 emulsion with an average size of 50&mu;m (Figure 1). Incubation was performed under high light conditions at 30&#176;C. The breaking of the emulsion was performed using breaking solution (1H,1H,2H,2H-perfluorooctanol), It is important to note that the oil in this solution was heavier than the water thus the medium phase remains on top and is easily extractable after adding 700&mu;l of medium. Emulsion integrity is determined using a microscope and viewing average size of the emulsion. </p>
<p>The Pta1, Pta2, &Delta;acs and Ack strains were cultured on photostats. This systems, also implemented by Joeri Jongbloets in the MC, is basically a batch culture where the light intensity per OD provided to the cells is maintained constant. In this case the light intensity per OD was set to  20 &mu;E/ m<sup>2</sup>* s. </p>
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<p>In both cases the culture medium was BG-11 supplemented with NO<sub>3-</sub> and TES buffer {link to recipe}.</p>
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<div class="4u">
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<figure class ="image fit">
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  <img src="https://static.igem.org/mediawiki/2015/b/b9/Amsterdam_Nico_Emulsions_numbers.jpeg">
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  <figcaption style="color: #2C3539">Figure 6. - Assessing droplet integrity and size under a microscope.  </figcaption>
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</figure>
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</div>
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<p>
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We first determine the number of cells needed to inoculate as many droplets as possible with two cells. This is performed by calculating Poisson distributions where the lambda is determined by the number of cells in 300 μl divided by the number of emulsion created by 300 &mu;l  of medium in 700 &mu;l of oil. Once the emulsions are created and broke open, the number of cells are counted and diluted to the concentration that allows for two cell to be inside each droplet. Serial propagation is needed to test whether the method works. The duration of such seral cultivation depends greatly on the organisms being used. With <i>Synechocystis</i>, this technique would take a few months due to its generation time, consequently, it is not possible to do within an iGEM project. Nonetheless, since (i) all simulations suggest this is  <a href="https://2015.igem.org/Team:Amsterdam/Project/testing_rom">possible</a>; (ii) evidence is provided below showing that we can successful recover cells of both partners; and (iii) we also show that the synthetic <a href="https://2015.igem.org/Team:Amsterdam/Project/testing_rom">consortium works</a>; it is quite reasonable to expect that this will work in the near future when implemented.
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</p>
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</section>
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<section id="Methods" class="wrapper style1">
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<header class="major">
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<h4>Processing Emulsion Cell Count</h4>
  
  
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<h4>Measuring product</h4>
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<p>Samples were taken from the cultures and centrifuged (5 min, 14.500 rpm) to obtain the supernatant. Product concentration was then estimated by enzymatic assays {links to protocols} in the case of lactate and acetate and by HPLC for glycerol {links to protocols}. </p>
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<header>
<h4>Estimating parameters</h4>
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<h4>Coulter Counter</h4>
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<h5>Growth rate</h5>
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<p>Growth rates were estimated by fitting a regression model to the logarithm of the OD over the time during the exponential phase of growth. The slope of this model is considered as  the growth rate since it shows how much the OD changes per unit of time. Its unit is 1 / h. </p>  
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<p>Cell counts were determined using a Coulter Counter. Cells suspended in electrolyte are separated via a microchannel compartment. The cell is drawn in causing a brief change in electrical impedance, which is recorded by the machine. In our case, one could clearly distinguish between <i>Synechocystis</i> and <i>E.coli</i> cells due to the fact that E.coli is on average 1μm and Synechocystis about 2-3μm  </p>
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<figure class ="image fit">
 +
  <img src="https://static.igem.org/mediawiki/2015/3/33/Amsterdam_Coulter_counter_2.png">
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  <figcaption style="color: #2C3539">Figure 7. - Output graph of the Coulter Counter. Two peaks are visible, each at different diameters (<i>x</i>-axis). The peaks at diameter 1 &mu;m belongs to <i>E.coli</i> which are about 1 &mu;m in size and the peak at a diameter or 2 &mu;m belongs to <i>Synechocystis</i>. By calculating the area under the curves one can obtain the number of cells for each organism. </figcaption>
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<header>
 
<header>
<h5>Production rate</h5>
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<h4>FACS</h4>
</header>
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<p>Q<sub>p</sub> are obtained by dividing the the concentration of measured product by the biomass of the culture estimated from OD (1 OD unit = 0.2 gDW). This value is in fact the production yield, that is, how much product the cells excrete per amount of biomass. To get the production rate, Q<sub>p</sub>, we multiply this value by the estimated growth rate. Its units are amount of product (in mmol) / gDW * h.</p>
 
  
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</header>               
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<p>
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Another method used for counting was Fluorescence-activated cell sorting (FACS). This method allowed for cell identification based upon fluorescence and specific light scattering techniques. We could clearly differentiate between <i>Synechocystis</i>, which presents fluorescence at the far red spectrum in contrast to <i>E.coli</i> that shows no autofluorescence. 
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<figure class ="image fit">
 +
  <img src="https://static.igem.org/mediawiki/2015/9/9c/Amsterdam_Nico_Facs_1.png">
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  <figcaption style="color: #2C3539">Figure 8. - Output graphs from the FACS are shown. The first graph illustrates how events are distributed by forward and side scatter. Two distinct clusters are visible, the left cluster represents <i>E.coli</i>, the right <i>Synechocystis</i>. Graph 2 and 3 illustrate the detection of fluorescent events at two different wavelengths where two peaks can be clearly distinguished. The left peak belongs to <i>E.coli</i> and the right one to <i>Synechocytis</i>.
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</section>
 
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<section id="Results" class="wrapper style1">
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<header class="major">
 
<header class="major">
 
<h2>Results</h2>
 
<h2>Results</h2>
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<header>
 
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<h4>Stability</h4>
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<h4>Growth in Emulsions</h4>
 
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</header>
<p> In Our turbidostat experiments we observed the results we expected. In the lactate strain (figure 1), a non growth coupled carbon producer, we started to observe an increase in growth rate about 300 hours after the beginning of the experiment. At the same time point we recorded a drop in the production of lactate. This result confirms our hypothesis about how mutations leading to the loss of production can be quickly fixated inasmuch as it releases the burden imposed by the carbon production increasing the fitness of the mutated cells.  
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<p> As shown by Bachmann et al., the emulsion technique has already been used with Lactococcus lactis, a chemotroph. We wanted to test if Synechocystis, a photoautotroph, could grow inside the emulsion droplets. Problems we could have encountered include 1) nature of the medium which is different from lactis, 2) whether CO2 is possible of entering into the medium and 3) whether Synechocystis received enough light.
 
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</p>
<p>
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<p>Our results demonstrate that Synechocystis is in fact able to grow inside the emulsions and we are able to break the emulsion droplets open to extract higher number of cells than the initial concentration. However, after day 7, Synechocystis only undergoes 2 doublings which is slow given that it’s usual generation time is between 12-17 hours. We believe that by optimizing the growth conditions more doublings could be achieved. One possible modification would be to grow Synechocystis inside an incubator where each sample freely receives the same amount of light with little shading from other samples. The use of a Tube roller could improve the amount of light received by the emulsions, however initial attempts at this showed that after a few days emulsion integrity was compromised.  
On the other hand the growth coupled acetate producer, &Delta;acs, shown a constant production and growth rate over the length of the experiment (figure 2) demonstrating that <a href = "https://2015.igem.org/Team:Amsterdam/Project/Eng_rom/Photosyn_car">this strategy</a> is more stable than the classical engineering approach. The  Q<sub>p</sub> estimated around 400 hours shows a decrease in the production but it is probably due to experimental failure. In the turbidostat cells were grown at very low OD (threshold was set to 0.35) therefore the concentration of acetate was below the detection limit of the enzymatic assay method. To overcome this problem we dehydrate the samples by lyophilization, also called freeze-drying, then dilute them in an smaller volume therefore increasing the concentration above the detection limit. Although this method worked (we obtained similar Q<sub>p</sub> values using different culture systems), the sample processing could have introduce noise in this measurement.  
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</p>
 
</p>
<header>
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<header>
<h4>Parameters</h4>
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<h5>Recovery Rates</h5>
 
</header>
 
</header>
<p>
 
In table 2 the physiological parameters obtained for six strains producing glycerol, lactate and acetate are presented. The lactate strain shown the highest Q<sub>p</sub> followed by &Delta;acs and Syn1413. An intriguing results is the differences in Q<sub>p</sub> and growth rate of &Delta;acs between cultivation methods. In the turbidostat the length of the exponential phase from where the growth rate is calculated is smaller than in photostat which could be influencing the estimation. For the Q<sub>p</sub> the previously discussed argument could also be an explanation for this difference. In addition it is possible that the photostat conditions are more favourable for the growth of <i>Synechocystis</i>.
 
</p>
 
  
 +
<p>To establish a working emulsion method, we had to prove that we would not lose a lot of cells by creating and breaking the emulsions. This is important because we want to have enough cells to serially propagate. First, recovery rate experiments were carried out on each organism separately. The first experiment was done at different pH levels to determine the effect of pH on recovery rates as <i>Synechocystis</i> makes the medium basic whereas <i>E. coli</i> makes it acidic. This was done in BG11 without addition of TES buffer. Data showed that <i>E.coli</i> has a much larger recovery rate than <i>Synechocystis</i> but in contrast it has large variance due to pH (Figure 9). <i>Synechocystis</i> shows a smaller recovery rate but is affected much less by pH change. </p>
 
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  <img src="https://static.igem.org/mediawiki/2015/4/49/Amsterdam_Nico_RR_e_coli_2.png">
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  <figcaption> Figure 9. -  Recovery rate of <i>E.coli</i> for different starting volumes of 150 &mu;l and 300 &mu;l and pH of 5.5, 7.7, 9.   
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   <img src="https://static.igem.org/mediawiki/2015/b/b1/Amsterdam_Nico_RR_syne_1.png">
   <figcaption>Figure 1. - Growth rate (median value in segments of 48 hours with a band of 1 standard deviation) and Q<sub>p</sub> (dots represent technical replicates) of strain SAA023 over 900 hours of continuous culture showing the drop in production.</figcaption>
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   <figcaption>Figure 10. Recovery Rates of <i>Synechocystis</i> for different starting volumes of 150 &mu;l and 300 &mu;l and pH of 5.5, 7.7, 9.  
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  <img src="https://static.igem.org/mediawiki/2015/6/68/Amsterdam_qp_acetate.png" alt="Acetate Qp and growth">
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  <figcaption>Figure 2. - Growth rate (median value in segments of 48 hours with a band of 1 standard deviation)  and Q<sub>p</sub> (dots represent technical replicates)of strain &Delta;acs over 900 hours of continuous culture showing a constant production over the duration of the experiment.</figcaption>
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  <figcaption>Table 1. - Estimated Growth and Q<sub>p</sub> for different <i>Synechocystis</i> strains in the two cultivation systems.</figcaption>
 
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                    <header><h2 style = "text-align:center;">Next Steps</h2></header>
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<p>The developed emulsion method needs to be tested with a mutually interacting consortium. Testing the method on a co-culture with <i>Synechocystis</i> and <i>E.coli</i> with only a one-way interaction results in only selecting for <i>Synechocystis</i>. This can be seen by analyzing the <a href="https://2015.igem.org/Team:Amsterdam/Project/testing_rom">plate experiments</a> where <i>Synechocystis</i> by itself has high-yield strategy than when put together with <i>E.coli</i>.
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<p>Only with a working consortia can our method be tested by adding a selfish <i>E.coli</i> into the mix and serial propagating over time. Also with a working consortium you can optimize it by just serial propagating the consortium. However, these experiments would take a few months to complete due to <i>Synechocystis</i> growth rate.
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                    <header><h2>References</h2></header>
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                        Bachmann, H. et al. Availability of public goods shapes the evolution of competing metabolic strategies. Proc. Natl Acad. Sci. USA 110, 14302–14307 (2013).
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Latest revision as of 02:55, 19 September 2015

iGEM Amsterdam 2015

Evolving Romance

Moving in Together

Overview

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).

Results

  • We have demonstrated that Synechocystis a phototroph is able grow inside the emulsions.
  • We demostrated that Synechcystis and E.coli can be recovered from the emulsion both separately and in co-culture.
  • We developed methods for the detection and counting of Synechocystis and E.col using either a Coulter Counter or a FACS.
.

Connections

Lactate Qp and growth
Figure 1. - Growth of Synechocystis in emulsion after 7 days. Initial 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 emulsions. This was done by making the emulsion of both strains and breaking them open throughout a week.
 Qp and growth
Figure 3. - Recovery rates of both Synechocystis and E.coli from a co-culture. Results clearly indicate that both organisms can be recovered

Fishing out a Consortia

Stable Romances tend to evolve when there is a perfect understanding between the individuals. Whether a match is a perfect fit (or not!) can be tested when partners are forced to interact for instance, when people move in together. So imagine applying the same principle to consortia were we deduced that an underlying property of all consortia is that ultimately they will display a so-called “high-yield strategy”. By High-yield strategy, it is meant that a more efficient use of natural resources leading to a greater number of individuals will be observed. This is even more so the case when instability is a serious threat. ,

What if there was a way to select these high-yield strategy consortia and actually make them interact better? How would one do this? Well… just like with people, this is possible to test by making microbes move in together.

We decided to tackle this problem by looking at studies done using emulsion based techniques selecting for high-yield strategies (Bachmann et al.). In this paper, the authors discuss the tradeoff that occurs between growth rate and growth yield in microbes. They demonstrate that compartmentalizing the availability of public goods while serial propagating leads to the selection of organisms with increased yield strategy, i.e. able to generate ever higher cell numbers (biomass) from the same portion of substrate. We apply the same logic to consortia by developing a dedicated emulsion-based protocol.

The basic principle is that by randomly combining different individuals of each side of the partnership in isolated compartments (micro-droplets), perfect matches will lead to increased numbers of offspring of both photo- and chemotroph. If propagated in time, ultimately this will enrich the mixture in both photo- and chemotrophs that do well when placed in a consortium while purging the population of the ones that do not.

This method can be used to select “naturally” occurring consortia, or to evolve the synthetic consortia that have been rationally engineered. For example, chemotrophs that use more efficiently the carbon source provided by the phototroph can be co-selected at the same time that the population is enriched in phototrophs that, not only grow efficiently on the required nutrient produced by the chemotroph, but also are more capable of fixing CO2 and “willing” to release the C-source. After this process, biobricks of choice can be added to the chemotroph in order to produce a compound with the knowledge that the chemotroph consumes the produced carbon more efficiently – and hence (if all things alike) is potentially able to make the product of interest also more efficiently.

Figure 4. Schematic overview of intended uses for the emulsion technique.
Figure 5. - Droplets filled with Synechocystis and E.coli .

Methods summary

Emulsion method

Emulsions were created using 700μl HFE 7500 mixed with 0.2% picosurf as a surfactant. This was mixed with 300μl of medium (BG11 enriched with TES buffer, Bicarbonate and 5mM ammonium chloride) with the expectation to create 4.6x106 emulsion with an average size of 50μm (Figure 1). Incubation was performed under high light conditions at 30°C. The breaking of the emulsion was performed using breaking solution (1H,1H,2H,2H-perfluorooctanol), It is important to note that the oil in this solution was heavier than the water thus the medium phase remains on top and is easily extractable after adding 700μl of medium. Emulsion integrity is determined using a microscope and viewing average size of the emulsion.

Figure 6. - Assessing droplet integrity and size under a microscope.

We first determine the number of cells needed to inoculate as many droplets as possible with two cells. This is performed by calculating Poisson distributions where the lambda is determined by the number of cells in 300 μl divided by the number of emulsion created by 300 μl of medium in 700 μl of oil. Once the emulsions are created and broke open, the number of cells are counted and diluted to the concentration that allows for two cell to be inside each droplet. Serial propagation is needed to test whether the method works. The duration of such seral cultivation depends greatly on the organisms being used. With Synechocystis, this technique would take a few months due to its generation time, consequently, it is not possible to do within an iGEM project. Nonetheless, since (i) all simulations suggest this is possible; (ii) evidence is provided below showing that we can successful recover cells of both partners; and (iii) we also show that the synthetic consortium works; it is quite reasonable to expect that this will work in the near future when implemented.

Processing Emulsion Cell Count

Coulter Counter

Cell counts were determined using a Coulter Counter. Cells suspended in electrolyte are separated via a microchannel compartment. The cell is drawn in causing a brief change in electrical impedance, which is recorded by the machine. In our case, one could clearly distinguish between Synechocystis and E.coli cells due to the fact that E.coli is on average 1μm and Synechocystis about 2-3μm

Figure 7. - Output graph of the Coulter Counter. Two peaks are visible, each at different diameters (x-axis). The peaks at diameter 1 μm belongs to E.coli which are about 1 μm in size and the peak at a diameter or 2 μm belongs to Synechocystis. By calculating the area under the curves one can obtain the number of cells for each organism.

FACS

Another method used for counting was Fluorescence-activated cell sorting (FACS). This method allowed for cell identification based upon fluorescence and specific light scattering techniques. We could clearly differentiate between Synechocystis, which presents fluorescence at the far red spectrum in contrast to E.coli that shows no autofluorescence.

Figure 8. - Output graphs from the FACS are shown. The first graph illustrates how events are distributed by forward and side scatter. Two distinct clusters are visible, the left cluster represents E.coli, the right Synechocystis. Graph 2 and 3 illustrate the detection of fluorescent events at two different wavelengths where two peaks can be clearly distinguished. The left peak belongs to E.coli and the right one to Synechocytis.

Results

Growth in Emulsions

As shown by Bachmann et al., the emulsion technique has already been used with Lactococcus lactis, a chemotroph. We wanted to test if Synechocystis, a photoautotroph, could grow inside the emulsion droplets. Problems we could have encountered include 1) nature of the medium which is different from lactis, 2) whether CO2 is possible of entering into the medium and 3) whether Synechocystis received enough light.

Our results demonstrate that Synechocystis is in fact able to grow inside the emulsions and we are able to break the emulsion droplets open to extract higher number of cells than the initial concentration. However, after day 7, Synechocystis only undergoes 2 doublings which is slow given that it’s usual generation time is between 12-17 hours. We believe that by optimizing the growth conditions more doublings could be achieved. One possible modification would be to grow Synechocystis inside an incubator where each sample freely receives the same amount of light with little shading from other samples. The use of a Tube roller could improve the amount of light received by the emulsions, however initial attempts at this showed that after a few days emulsion integrity was compromised.

Recovery Rates

To establish a working emulsion method, we had to prove that we would not lose a lot of cells by creating and breaking the emulsions. This is important because we want to have enough cells to serially propagate. First, recovery rate experiments were carried out on each organism separately. The first experiment was done at different pH levels to determine the effect of pH on recovery rates as Synechocystis makes the medium basic whereas E. coli makes it acidic. This was done in BG11 without addition of TES buffer. Data showed that E.coli has a much larger recovery rate than Synechocystis but in contrast it has large variance due to pH (Figure 9). Synechocystis shows a smaller recovery rate but is affected much less by pH change.

Figure 9. - Recovery rate of E.coli for different starting volumes of 150 μl and 300 μl and pH of 5.5, 7.7, 9.
Figure 10. Recovery Rates of Synechocystis for different starting volumes of 150 μl and 300 μl and pH of 5.5, 7.7, 9. -

Next Steps

The developed emulsion method needs to be tested with a mutually interacting consortium. Testing the method on a co-culture with Synechocystis and E.coli with only a one-way interaction results in only selecting for Synechocystis. This can be seen by analyzing the plate experiments where Synechocystis by itself has high-yield strategy than when put together with E.coli.

Only with a working consortia can our method be tested by adding a selfish E.coli into the mix and serial propagating over time. Also with a working consortium you can optimize it by just serial propagating the consortium. However, these experiments would take a few months to complete due to Synechocystis growth rate.

References

Bachmann, H. et al. Availability of public goods shapes the evolution of competing metabolic strategies. Proc. Natl Acad. Sci. USA 110, 14302–14307 (2013).