Difference between revisions of "Team:TU Darmstadt/Lab/MetabolicBurden"

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<h6>Measurement of the Metabolic Burden via Microplate Reader</h6>
 
<h6>Measurement of the Metabolic Burden via Microplate Reader</h6>
 
<p> In addition to the stress forced onto the cell, the total amount of formed GFP is significantly influenced by the cell amount. For this reason the measurement of GFP with a microplate reader was performed under continuous observation of the cell density. With this kind of measurement a high number of samples, like in <i>96&#8209;well&#8209;plates</i>, could be analyzed. Since the measurement of different combinations of plasmid and cell&#8209;type, would enable to determine the artificially caused stress on the cells proportional to the decrease in GFP expression, this kind of measurement is assumed to be a more economical approach than the  single cell measurement described in the next paragraph.</p>
 
<p> In addition to the stress forced onto the cell, the total amount of formed GFP is significantly influenced by the cell amount. For this reason the measurement of GFP with a microplate reader was performed under continuous observation of the cell density. With this kind of measurement a high number of samples, like in <i>96&#8209;well&#8209;plates</i>, could be analyzed. Since the measurement of different combinations of plasmid and cell&#8209;type, would enable to determine the artificially caused stress on the cells proportional to the decrease in GFP expression, this kind of measurement is assumed to be a more economical approach than the  single cell measurement described in the next paragraph.</p>
<h6>Single-cell-measurement</h6>
+
<h6>Single-Cell-Measurement</h6>
 
<p>While measuring every single cell individually, the cell density can be neglected which concludes in a smaller error in the analysis of the fluorescence. This method enables the detection of the influence of the metabolic burden based on the GFP production. Therefore, it is assumed to be a more exact method than the previously described method using a microplate reader.</p>
 
<p>While measuring every single cell individually, the cell density can be neglected which concludes in a smaller error in the analysis of the fluorescence. This method enables the detection of the influence of the metabolic burden based on the GFP production. Therefore, it is assumed to be a more exact method than the previously described method using a microplate reader.</p>
  

Revision as of 18:20, 15 October 2016

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ABSTRACT

Artificial plasmids are a significant burden to the host. The design of our pathways, for example the combination of a promoter and RBS, results in different amounts of product. The measurement of the metabolic burden is the key for a quantitative optimization in metabolic engineering. We want to establish a new approach to iGEM by providing a measurement strain to the community. As described by F. Ceroni et al., we genomically integrated one copy of GFP into E. coli, which offers us a highly accurate and instantaneous measurement of the impact of our plasmids on the host. This is of economical interest because it enables academic and industrial researchers to test a lot of different pathways at once in a short time just by using a microplate reader. For the integration we used the λ‑Integrase site‑specific recombination pathway, described by A. Landy in 2015 [9]. Therefore, we designed two plasmids (BBa_K1976000 and BBa_K1976001) and measured them using single cell measurement and via microplate reader.

Metabolic Burden

In synthetic biology, the term "metabolic burden" describes the influence of heterologously expressed genes on the distribution availability of resources in the host‑cell. Thereby the extent of metabolic burden is not only dependent on the consumption of energy and reaction equivalents but is also influenced by a number of different factors. In addition to size and copy number of the used plasmid [1], the specific properties of the heterologous proteins play an important role. Proteins that interfere with the host's metabolism, influence the proton gradient or are toxic in a different way can pose a strong burden for the cell already at low expression levels [1, 2]. I. Shachrai et al. could furthermore show that ribosome availability represents a big portion of metabolic burden as a limiting factor [3].
If the metabolic burden on the host cell is too high, the physiology and biochemistry of the cell will be drastically altered. In this case, for example the viability or proliferation of the cell could be disturbed. Since there is a higher error rate in the translation which heightens the immunogenicity of the incorporated proteins and can lead to a reduced protein activity and stability [1] the metabolic burden is a big problem especially in the industrial sector [4]. Because of the big impact on expression efficiency the amount of obtained product would be low.
Often used methods to reduce the metabolic burden include for example the separation of the biosynthetic pathway into multiple organisms through co‑cultivating them or the identification and deletion of expendable genes as a part of strain optimization [6]. Another approach is the regulation of protein expression with Dynamic Sensor and Regulatory Systems (DSRSs). Such systems are based on the usage of transcription factors that can detect certain key‑metabolites and regulate the transcription simultaneously [7].
One possibility to quantify the metabolic burden in vivo was described by F. Ceroni et al. In this method a GFP reporter gene is integrated in the genome of E. coli using the λ‑integrase [8]. Through measuring the fluorescence it could be shown that the constitutive expression of GFP after transformation with expression‑plasmids drastically decreases in comparison to not transformed cells.

Measurement of the Metabolic Burden via Microplate Reader

In addition to the stress forced onto the cell, the total amount of formed GFP is significantly influenced by the cell amount. For this reason the measurement of GFP with a microplate reader was performed under continuous observation of the cell density. With this kind of measurement a high number of samples, like in 96‑well‑plates, could be analyzed. Since the measurement of different combinations of plasmid and cell‑type, would enable to determine the artificially caused stress on the cells proportional to the decrease in GFP expression, this kind of measurement is assumed to be a more economical approach than the single cell measurement described in the next paragraph.

Single-Cell-Measurement

While measuring every single cell individually, the cell density can be neglected which concludes in a smaller error in the analysis of the fluorescence. This method enables the detection of the influence of the metabolic burden based on the GFP production. Therefore, it is assumed to be a more exact method than the previously described method using a microplate reader.

Genomic Integration

The λ‑integrase, originally derived from the λ‑Phage, catalyzes the excessive and integrative recombination of the phage's genome with the chromosomal genome of a host in combination with several assisting proteins. Therefore, two attachment sites are necessary: one located on the bacterial genome (attB) and the other located on the λ‑genome (attP), which also contains several binding sites for regulatory proteins. The attachment sites contain homologous recognition sequences, called BOB' Region (attB) and COC' Region (attP). These regions can be connected by the λ‑integrase and the bacterial integration host factor (IHF) via Holliday junction forming an intasome, a DNA‑protein‑complex, producing hybrid attachment sites attL and attR.

Integration Plasmid and Helper Plasmid

For the integration of the gene of interest (GOI) into the chromosomal genome of E. coli two plasmids are needed. The integration plasmid contains the constitutively expressed GOI GFP which, as previously mentioned, is also the necessary reporter for the measurement of the metabolic burden and should be integrated into the genome of E. coli. To ensure the detection the temporary fluorescence only, a LVA degradation tag was added to the GFP. The plasmid also contains the attP site that enables the integration. Additionally, two bidirectional terminators are located on each side of the attP to protect the GFP operon from the transcription of the other neighbouring genes. To create the integration plasmid E0240 (RBS(BB0032+GFP)) was ligated on J61002 to locate the GFP behind the promoter J23101. The construct J23101+E0240 was then transformed into the high copy vector pSB1C3 to increase the yield of the plasmid preparation after a mutagenesis PCR which was necessary for the optimization of BBa_I11023, mutating attp2 to λ‑attP. Furthermore, the final construct was transformed into the backbone pSB4A5 which possesses a low copy ori to facilitate the later performed plasmid curing. The second plasmid is a helper plasmid which is necessary for transposing the GFP into the chromosomal genome as it contains the synthesized protein λ‑integrase with a ribosomal binding site (RBS). For inscription in the registry the construct was transformed on a pSB1C3 and to facilitate additional performed plasmid curing via sustained lack of selection pressure we again chose a low copy vector pSB4K5 .
To verify whether the recombination was successful a PCR using specific primers to the attB site of the E. coli and the VR Primer which binds on every BioBrick compliant plasmid was performed. Since the first primer binds to the genome and the other is complimentary to the plasmid a PCR amplicon could be optained only if the integration has succeeded.

Plasmid Curing

.....

Integration Strains

A suitable genomic integration strain needs to carry the attB sequence which is necessary for the λ‑integrase mediated homologous recombination. Since many commonly used E. Coli strains already carry the λ‑phage integrated in their genome it was difficult to select a suitable strain. Also, the attB site which is needed for the integration is blocked in λ (DE3) phages. ERKLAEREN!WAS BEDEUTET DAS?
For our integration we chose the E. Coli JM109 strain because it matched all our demands and was also freely and easily available to us.

References
  • [1] B. Glick, Metabolic load and heterologous gene expression, Biotechnology Advances, vol. 13, pp. 247261, 1995.
  • [2] M. Eames and T. Kortemme, Cost-benet tradeos in engineered lac operons, Science, vol. 336, pp. 911915, 2012.
  • [3] I. Shachrai, A. Zaslaver, U. Alon, and E. Dekel, Cost of unneeded proteins in E. coli is reduced after several generations in exponential growth, Molecular Cell, vol. 38, pp. 758767, 2010.
  • [4] G. Wu, Q. Yan, J. Jones, Y. Trang, S. Fong, and M. Koas, Metabolic burden: Cornerstones in synthetic biology and metabolic engineering applications, Trends in Bio- technology, 2016.
  • [5] H. Zhang, B. Peireira, Z. Li, and G. Stephanopoulos, Cost of unneeded proteins in E. coli is reduced after several generations in exponential growth, Proc Natl Acad Sci, vol. 112, pp. 82668271, 2015.
  • [6] H. Westers, R. Dorenbos, J. M. van Dijl, J. Kabel, T. Flanagan, K. M. Devine, F. Jude, S. J. Seror, A. C. Beekman, E. Darmon, C. Eschevins, A. de Jong, S. Bron, O. P. Kuipers, A. M. Albertini, H. Antelmann, M. Hecker, N. Zamboni, U. Sauer, C. Bruand, D. S. Ehrlich, J. C. Alonso, M. Salas, and W. J. Quax, Genome engineering reveals large dispensable regions in Bacillus subtilis, Proc Nat Acad Sci, vol. 20, pp. 20762090, 2003.
  • [7] F. Zhang, J. Carothers, and J. Keasling, Design of a dynamic sensor-regulatory system for production of chemicals and fuels derived from fatty acids, Nature Biotechnology, vol. 30, pp. 354359, 2012.
  • [8] F. Ceroni, R. Algar, G.-B. Stan, and T. Ellis, Quantifying cellular capacity identies gene expression designs with reduced burden, Nature Methods, vol. 12, pp. 415418, 2015.
  • [9] A. Landy, Dynamic, structural, and regulatory aspects of lambda site-specific recombination, Annual Review of Biochemisty, vol. 58, pp. 913-949, 1989.