Difference between revisions of "Team:Amsterdam/Produce"

 
Line 1,017: Line 1,017:
 
         Daytime production
 
         Daytime production
 
         </p>
 
         </p>
         From the diurnal batch culture, we were able to calculate the daytime production for the two strains (N=4 for both strains). After 72 hours at an OD
+
         <p>
        <sub>
+
        From the diurnal batch culture, we were able to calculate the daytime production for the two strains (N=4 for both strains). After 72 hours at an OD
        720
+
        <sub>
        </sub>
+
          720
        of ~2, which is realistic for industrial settings, both the
+
        </sub>
        <i>
+
        of ~2, which is realistic for industrial settings, both the
        Δ
+
        <i>
        </i>
+
          Δ
        <i>
+
        </i>
        fumC
+
        <i>
        </i>
+
          fumC
        and the
+
        </i>
        <i>
+
        and the
        Δ
+
        <i>
        </i>
+
          Δ
        <i>
+
        </i>
        fumC
+
        <i>
        </i>
+
          fumC
        <i>
+
        </i>
        Δ
+
        <i>
        </i>
+
          Δ
        <i>
+
        </i>
        zwf
+
        <i>
        </i>
+
          zwf
        strain produce fumarate with a maximum Qp
+
        </i>
        <sub>
+
        strain produce fumarate with a maximum Qp
        day
+
        <sub>
        </sub>
+
          day
        of 58.7 µM grDW
+
        </sub>
        <sup>
+
        of 58.7 µM grDW
        -1
+
        <sup>
        </sup>
+
          -1
        hour
+
        </sup>
        <sup>
+
        hour
        -1
+
        <sup>
        </sup>
+
          -1
        for the
+
        </sup>
        <i>
+
        for the
        Δ
+
        <i>
        </i>
+
          Δ
        <i>
+
        </i>
        fumC
+
        <i>
        </i>
+
          fumC
        and 52.0 µM grDW
+
        </i>
        <sup>
+
        and 52.0 µM grDW
        -1
+
        <sup>
        </sup>
+
          -1
        hour
+
        </sup>
        <sup>
+
        hour
        -1
+
        <sup>
        </sup>
+
          -1
        for the
+
        </sup>
        <i>
+
        for the
        Δ
+
        <i>
        </i>
+
          Δ
        <i>
+
        </i>
        fumC
+
        <i>
        </i>
+
          fumC
        <i>
+
        </i>
        Δ
+
        <i>
        </i>
+
          Δ
        <i>
+
        </i>
        zwf
+
        <i>
        </i>
+
          zwf
        over the course of one day fig.2.6. This confirms that (i) the
+
        </i>
        <i>
+
        over the course of one day fig.2.6. This confirms that (i) the
        Δ
+
        <i>
        </i>
+
          Δ
        <i>
+
        </i>
        fumC
+
        <i>
        </i>
+
          fumC
        is able to produce during the day, when mimicking industrial settings with a diurnal and sinusoidal light regime, and (ii) the
+
        </i>
        <i>
+
        is able to produce during the day, when mimicking industrial settings with a diurnal and sinusoidal light regime, and (ii) the
        Δ
+
        <i>
        </i>
+
          Δ
        <i>
+
        </i>
        fumC
+
        <i>
        </i>
+
          fumC
        <i>
+
        </i>
        Δ
+
        <i>
        </i>
+
          Δ
        <i>
+
        </i>
        zwf
+
        <i>
        </i>
+
          zwf
        produces a similar amount of fumarate during the day as the
+
        </i>
        <i>
+
        produces a similar amount of fumarate during the day as the
        Δ
+
        <i>
        </i>
+
          Δ
        <i>
+
        </i>
        fumC
+
        <i>
        </i>
+
          fumC
        . As expected both the WT and the
+
        </i>
        <i>
+
        . As expected both the WT and the
        Δ
+
        <i>
        </i>
+
          Δ
        <i>
+
        </i>
        zwf
+
        <i>
        </i>
+
          zwf
        strain did not produce fumarate during the day.
+
        </i>
 +
        strain did not produce fumarate during the day.
 +
        </p>
 
         <figure id="fig26">
 
         <figure id="fig26">
 
         <img class="module-figure-image" src="https://static.igem.org/mediawiki/2017/c/c0/TAmsterdam_amsterdam_production_2.6.png"/>
 
         <img class="module-figure-image" src="https://static.igem.org/mediawiki/2017/c/c0/TAmsterdam_amsterdam_production_2.6.png"/>
Line 1,990: Line 1,992:
 
         TCA cycle, but also increase the flux towards fumarate production, by feeding into reactions which produce electron carriers - one of the main roles of the TCA cycle [17]. This would potentially align fumarate production with an increase in fitness during the night, providing the type of positive selection pressure, which could be used to stabilize the expression of this heterologous pathway in a production strain as advised by
 
         TCA cycle, but also increase the flux towards fumarate production, by feeding into reactions which produce electron carriers - one of the main roles of the TCA cycle [17]. This would potentially align fumarate production with an increase in fitness during the night, providing the type of positive selection pressure, which could be used to stabilize the expression of this heterologous pathway in a production strain as advised by
 
         <a class="in-text-link" href="https://2017.igem.org/Team:Amsterdam/HP/Gold_Integrated" target="_blank">
 
         <a class="in-text-link" href="https://2017.igem.org/Team:Amsterdam/HP/Gold_Integrated" target="_blank">
           experts.
+
           experts
 
         </a>
 
         </a>
         <br>
+
         .
          We have explored this idea by introducing the glyoxylate shunt into the genome-scale metabolic model that had been guiding our metabolic engineering strategies thus far. We found that our hypothesis is corroborated by
+
        </p>
          <a class="in-text-link" href="https://2017.igem.org/Team:Amsterdam/Model" target="_blank">
+
        <p>
          model simulations
+
        We have explored this idea by introducing the glyoxylate shunt into the genome-scale metabolic model that had been guiding our metabolic engineering strategies thus far. We found that our hypothesis is corroborated by
          </a>
+
        <a class="in-text-link" href="https://2017.igem.org/Team:Amsterdam/Model" target="_blank">
          . However, timing the activation of this pathway turned out to be of the essence when engineering a stable strain. This led us to the construction of the first fully-segregated (i.e all copies of the chromosome have the same allele) promoter library in a polyploid organism such as the cyanobacterium we work with (
+
          model simulations
          <i>
+
        </a>
          Synechocystis
+
        . However, timing the activation of this pathway turned out to be of the essence when engineering a stable strain. This led us to the construction of the first fully-segregated (i.e all copies of the chromosome have the same allele) promoter library in a polyploid organism such as the cyanobacterium we work with (
          </i>
+
        <i>
          ), but not without first developing a method to do so.
+
          Synechocystis
        </br>
+
        </i>
 +
        ), but not without first developing a method to do so.
 
         </p>
 
         </p>
 
         <p class="collapsible-main-header" id="results3">
 
         <p class="collapsible-main-header" id="results3">
Line 2,333: Line 2,336:
 
         <p>
 
         <p>
 
           Every day, the cells were plated on the three different BG-11 plates using a dilution series droplet design (fig. 2.16).
 
           Every day, the cells were plated on the three different BG-11 plates using a dilution series droplet design (fig. 2.16).
           <br/>
+
           <br>
          The OD
+
          The OD
          <sub>
+
          <sub>
          730
+
            730
          </sub>
+
          </sub>
          of the cultures were measured, after which the dilution series was prepared using a 96 well-plate and a multichannel pipet. First, all the BG-11 was added in appropriate amounts to the wells following the pipetting scheme, after which the inoculum from the different cultures was added to row A. After mixing properly, the dilution series were made by pipetting 10 μL from row A to B. After mixing, 10 μL was pipetted from row B to C, and so on, resulting in a dilution series that contained two rows per culture:
+
          of the cultures were measured, after which the dilution series was prepared using a 96 well-plate and a multichannel pipet. First, all the BG-11 was added in appropriate amounts to the wells following the pipetting scheme, after which the inoculum from the different cultures was added to row A. After mixing properly, the dilution series were made by pipetting 10 μL from row A to B. After mixing, 10 μL was pipetted from row B to C, and so on, resulting in a dilution series that contained two rows per culture:
          <br/>
+
          <br/>
          <br/>
+
          <br/>
          10
+
          10
          <sup>
+
          <sup>
          0
+
            0
          </sup>
+
          </sup>
          , 10
+
          , 10
          <sup>
+
          <sup>
          -1
+
            -1
          </sup>
+
          </sup>
          , 10
+
          , 10
          <sup>
+
          <sup>
          -2
+
            -2
          </sup>
+
          </sup>
          , 10
+
          , 10
          <sup>
+
          <sup>
          -3
+
            -3
          </sup>
+
          </sup>
          , 10
+
          , 10
          <sup>
+
          <sup>
          -4
+
            -4
          </sup>
+
          </sup>
          , 10
+
          , 10
          <sup>
+
          <sup>
          -5
+
            -5
          </sup>
+
          </sup>
          , 10
+
          , 10
          <sup>
+
          <sup>
          -6
+
            -6
          </sup>
+
          </sup>
          , 10
+
          , 10
          <sup>
+
          <sup>
          -7
+
            -7
          </sup>
+
          </sup>
          .
+
          .
          <br/>
+
          <br/>
          10
+
          10
          <sup>
+
          <sup>
          -0.5
+
            -0.5
          </sup>
+
          </sup>
          , 10
+
          , 10
          <sup>
+
          <sup>
          -1.5
+
            -1.5
          </sup>
+
          </sup>
          , 10
+
          , 10
          <sup>
+
          <sup>
          -2.5
+
            -2.5
          </sup>
+
          </sup>
          , 10
+
          , 10
          <sup>
+
          <sup>
          -3.5
+
            -3.5
          </sup>
+
          </sup>
          , 10
+
          , 10
          <sup>
+
          <sup>
          -4.5
+
            -4.5
          </sup>
+
          </sup>
          , 10
+
          , 10
          <sup>
+
          <sup>
          -5.5
+
            -5.5
          </sup>
+
          </sup>
          , 10
+
          , 10
          <sup>
+
          <sup>
          -6.5
+
            -6.5
          </sup>
+
          </sup>
          , 10
+
          , 10
          <sup>
+
          <sup>
          -7.5
+
            -7.5
          </sup>
+
          </sup>
          <br/>
+
          <br/>
          <br/>
+
          <br/>
          From each well, 5 μL will be plated in droplets on the three types of BG-11 plates.
+
          From each well, 5 μL will be plated in droplets on the three types of BG-11 plates.
 +
          </br>
 
         </p>
 
         </p>
 
         <figure id="fig216">
 
         <figure id="fig216">

Latest revision as of 19:52, 15 December 2017

Production


A major requisite of cyano-cell factories, according to expert's opinion, is that they must be able to produce in a stable fashion under industrial conditions. A recent quantitative analysis of the various ways to convert the energy of photons to chemical bonds has revealed that the direct utilization of sunlight is the most efficient [1]. This however means that cells will be exposed to diurnal regimes in which they will inevitably be exposed to periods of darkness. Our goal here is to achieve the first photoautotrophic cell factories that are able to stably produce fumarate around the clock.

Produce

Overview

Synechocystis does not naturally produce fumarate. However, model guided engineering found that removing a single gene within Synechocystis leads to a stable cell factory that produces fumarate as it grows during the day. Nevertheless, at night our cells do not produce fumarate, since at night, they don't grow. To overcome this challenge, we have taken a systems biology approach which interweaves theory, modeling, and experimentation to implement stable nighttime production of fumarate. We theorized that we can redirect the nighttime flux towards fumarate production by removing a competing pathway via knockout of the zwf gene. Additionally, we also took inspiration from nature and speculated that the incorporation of the glyoxylate shunt would further increase our nighttime production of fumarate. Our models corroborate these predictions, however, they also suggest that the stability of the glyoxylate shunt is sensitive to the timing of when the shunt is turned on (i.e. expressed). We therefore took a robust approach to incorporate the glyoxylate shunt enzymes under ideal expression conditions.

Highlights

  • Engineered a Δ fumC Δ zwf Synechocystis strain, that uses different fumarate production strategies during day and night.
  • Developed a method to make fully segregated libraries in polyploid organisms
  • Created the first fully segregated library representing the entire genome (99.9% confidence) of Synechocystis upstream of the glyoxylate shunt genes. This library is now ready to be tested to further increase nighttime fumarate production.
  • Stable production of fumarate directly from CO 2 around the clock Qp night of 12.7 µM grDW -1 hour -1 Qp day of 52.0 µM grDW -1 hour -1

References

  1. Lips, D., Schuurmans, J. M. M., dos Santos, F. B., & Hellingwerf, K. J. (2017). Many ways towards "solar fuel": Quantitative analysis of the most promising strategies and the main challenges during scale-up. Energy & Environmental Science.
  2. René H. Wijffels, Olaf Kruse, and Klaas J. Hellingwerf. "Potential of industrial biotechnology with cyanobacteria and eukaryotic microalgae". In: Current Opinion in Biotechnology 24.3 (2013), pp. 405-413.
  3. Patrik R. Jones. "Genetic Instability in Cyanobacteria - An Elephant in the Room?" In: Frontiers in Bioengineering and Biotechnology 2.May (2014), pp. 1-5.
  4. Wei Du, S. Andreas Angermayr, Joeri A. Jongbloets, Douwe Molenaar, Herwig Bachmann, Klaas J. Hellingwerf, and Filipe Branco dos Santos. "Nonhierarchical flux regulation exposes the fitness burden associated with lactate production in Synechocystis sp. PCC6803". In: ACS Synthetic Biology (2016), acssynbio.6b00235.
  5. Wei Du, Joeri A. Jongbloets, Coco van Boxtel, Hugo Pineda Hernandez, David Lips, Brett G. Oliver, Klaas J. Hellingwerf, and Filipe Branco dos Santos. "Alignment of microbial fitness with engineered product formation: Obligatory coupling between acetate production and photoautotrophic growth". 2017.
  6. Teusink B, Smid EJ. Modelling strategies for the industrial exploitation of lactic acid bacteria. Nat Rev Microbiol. 2006;4:46-56
  7. Darmon E, Leach DR. Bacterial genome instability. Microbiol Mol Biol Rev. 2014;78:1-39.
  8. Renda BA, Hammerling MJ, Barrick JE. Engineering reduced evolutionary potential for synthetic biology. Mol Biosyst. 2014;10:1668-78.
  9. Feist AM, Zielinski DC, Orth JD, Schellenberger J, Herrgard MJ, Palsson BO. Model-driven evaluation of the production potential for growth-coupled products of Escherichia coli . Metab Eng. 2010;12:173-86
  10. Erdrich P, Knoop H, Steuer R, Klamt S. Cyanobacterial biofuels: new insights and strain design strategies revealed by computational modeling. Microb Cell Fact. 2014;13:128.
  11. Nogales, J., Gudmundsson, S., Knight, E. M., Palsson, B. O., & Thiele, I. (2012). Detailing the optimality of photosynthesis in cyanobacteria through systems biology analysis. Proceedings of the National Academy of Sciences, 109(7), 2678-2683.
  12. Bachmann H, Molenaar D, Branco dos Santos F, Teusink B. Experimental evolution and the adjustment of metabolic strategies in lactic acid bacteria. FEMS Microbiol Rev. 2017;41 Supp_1:S201-19.
  13. Bryson V, Szybalski W. Microbial Selection. Science. 1952;116:45-51.
  14. Angermayr, S. A. & Hellingwerf, K. J. On the Use of Metabolic Control Analysis in the Optimization of Cyanobacterial Biosolar Cell Factories. J. Phys. Chem. B (2013). doi:10.1021/jp4013152
  15. Ni Wan, Drew M. DeLorenzo, Lian He, Le You, Cheryl M. Immethun, George Wang, Ed- ward E.K. Baidoo, Whitney Hollinshead, Jay D. Keasling, Tae Seok Moon, and Yinjie J. Tang. "Cyanobacterial carbon metabolism: Fluxome plasticity and oxygen dependence". In: Biotechnology and Bioengineering 114.7 (2017), pp. 1593-1602.
  16. Du, W., Jongbloets, J. A., Hernandez, H. P., Bruggeman, F. J., Hellingwerf, K. J., & dos Santos, F. B. (2016). Photonfluxostat: A method for light-limited batch cultivation of cyanobacteria at different, yet constant, growth rates. Algal Research, 20, 118-125.
  17. Lee J. Sweetlove, Katherine F M Beard, Adriano Nunes-Nesi, Alisdair R. Fernie, and R. George Ratcliffe. "Not just a circle: Flux modes in the plant TCA cycle". In: Trends in Plant Science 15.8 (2010), pp. 462-470
  18. Tu, Benjamin P., and Steven L. McKnight. "Metabolic cycles as an underlying basis of biological oscillations." Nature reviews Molecular cell biology 7.9 (2006): 696-701.
  19. Biology, C. & Soppa, J. Microbiology The ploidy level of Synechocystis sp. PCC 6803 is highly variable and is influenced by growth phase and by chemical and physical external parameters. (2016)
  20. Cheah, Y.E., Albers, S.C. & Peebles, C.A.M. A novel counter-selection method for markerless genetic modification in Synechocystis sp. PCC 6803. Biotechnol. Prog. 29, 23-30 (2013).
  21. Lopez-maury, L., Garcia-dominguez, M., Florencio, F. J. & Reyes, J.C. A two-component signal transduction system involved in nickel sensing in the cyanobacterium. 43, 247-256 (2002).
  22. Griese, M. & Lange, C. Ploidy in cyanobacteria. 323, 124-131 (2011).
  23. Zhang, Shuyi, and Donald A. Bryant. "Biochemical validation of the glyoxylate cycle in the cyanobacterium Chlorogloeopsis fritschii strain PCC 9212." Journal of Biological Chemistry 290.22 (2015): 14019-14030.