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

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   <figcaption style="color: #2C3539">Figure 3. - Determining droplet integrity and size under a microscope. </figcaption>
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   <figcaption style="color: #2C3539">Figure 8. - In this figure three output graphs from the FACS machine 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 <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 to the right one to <i>Synechocytis</i>.
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<h4>Estimating parameters</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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<h5>Production rate</h5>
 
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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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<h4>Stability</h4>
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<h4>Growth in Emulsions</h4>
 
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<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>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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<h4>Parameters</h4>
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<h5>Growth rate</h5>
 
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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>.
 
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<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(link protocol). 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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  <figcaption style="color: #2C3539"> Figure 9. - Presents the Recovery Rate of E.coli for different starting volumes of 150 &mu;l and 300 &mu;l and pH of 5.5, 7.7, 9. 
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Revision as of 23:32, 18 September 2015

iGEM Amsterdam 2015

Evolving Romance

Moving in Together

Overview

Background

Emulsion based Culturing methods can be used to select for organisms with high yield strategies. Thus this technique has the potential use for the discovery and optimization of consortia. It can be used to fish out consortia with high yield strategies. As well as take advantage of the genetic variability in a population to optimize for individuals who interact more efficiently between each other.

Aim

Our aim is to develop a emulsion culturing method that would allow us to select for "naturally" occurring consortia. Added bonus we can use the protocol to optimize natural or genetically engineered consortia.

Approach

We adapted the method of Bachmann et al. to create emulsion. Also methods were developed to count cell of Co-cultures using the Coulter Counter and Florescence-Activated Cell Sorting(FACS).

Results

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

Connections

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.

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. Illustrations of the Uses of the Emulsion Technique
Figure 5. - Droplets filled with Synechocystis and E.coli .

Methods summary

Emulsion method

Emulsions were created using 700ul 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 30oC. 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 700ul of medium. Emulsion integrity is determined using a microscope and viewing average size of the emulsion.

Figure 6. - Determining 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 (link showing that final ratios are independent than starting ODs); (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 (link to plates with consortia); it is quite reasonable to expect that this will work in the near future when implemented.

Processing Emulsion Cell Count

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. - In this figure we can see the output graph of the Coulter Counter. Two peaks are visible each at different diameters. 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.

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. - In this figure three output graphs from the FACS machine 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 to 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.

Growth rate

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(link protocol). 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. - Presents the Recovery Rate of E.coli for different starting volumes of 150 μl and 300 μl and pH of 5.5, 7.7, 9.
Lactate Qp and growth
Figure 1. - Growth rate (median value in segments of 48 hours with a band of 1 standard deviation) and Qp (dots represent technical replicates) of strain SAA023 over 900 hours of continuous culture showing the drop in production.

Acetate Qp and growth
Figure 2. - Growth rate (median value in segments of 48 hours with a band of 1 standard deviation) and Qp (dots represent technical replicates)of strain Δacs over 900 hours of continuous culture showing a constant production over the duration of the experiment.

Acetate Qp and growth
Table 1. - Estimated Growth and Qp for different Synechocystis strains in the two cultivation systems.