Published December 25, 2020 | Version v1
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Biochemical and Phenomenological Models For A Shinethanogen System

Authors/Creators

  • 1. University of St Andrews

Description

This section of in silico molecular modelling effectively served as our experimental workbench, fine-tuning the shinethanogen system gene circuit and testing our approach to experimental design. The molecular model of the gene circuit behaviour was dissected, taking account of the designed properties we sought in the design and research section of our engineering cycle and the intrinsic properties of the system (diffusion rates, association/dissociation, promoter dynamics). Therefore, the ultimate target of this section was to paint a picture of the behaviour of the gene circuit overall. Systems of ODEs were built for the thanogen and shinogen independently and deterministic and stochastic models were produced using kinetic parameters derived from the literature and approximated where unavailable.

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Is identical to
10.13140/RG.2.2.30987.82720 (DOI)

References

  • Allen, R. J., Waclaw, B. (2019). Bacterial growth: a statistical physicist's guide. reports on progress in physics. Physical Society (Great Britain), 82(1), 016601. doi:10.1088/1361-6633/aae546.
  • Ay A. and Arnosti D. N. (2011). Mathematical modeling of gene expres- sion: a guide for the perplexed biologist. Critical reviews in biochemistry and molecular biology, 46(2), 137–151. doi:10.3109/10409238.2011. 556597.
  • Bethke, Jin, Qusheng and Craig M. (2007). The thermodynamics and kinetics of microbial metabolism. American Journal of Science, 307(4), 643–677. doi:10.2475/04.2007.01.
  • Chan, Clement T.Y., Jeong Wook Lee, D. Ewen Cameron, Caleb J. Bashor, and James J. Collins. (2016). 'deadman' and 'passcode' microbial kill switches for bacterial containment. Nature Chemical Biology, 12(2), 82–86. doi:10. 1038/nchembio.1979.
  • Chandran, D., W. B. Copeland, S. C. Sleight, and H. M. Sauro. (2008). Math- ematical modeling and synthetic biology. Drug Discovery Today: Disease Models, 5(4), 299–309. doi:10.1016/j.ddmod.2009.07.002.
  • Cohen, Barner. (1954). Studies on unbalanced growth in escherichia coli. Proc Natl Acad Sci U S A, (pp. 885–893).
  • CONTOIS, D E. (1959). Kinetics of bacterial growth: relationship between population density and specific growth rate of continuous cultures. J Gen Microbiol, (pp. 40–50).
  • D A Ratkowsky, R K Lowry, T A McMeekin, A N Stokes, and R E Chan- dler (1983). Model for bacterial culture growth rate throughout the entire biokinetic temperature range. J Bacteriol, (pp. 1222–1226).
  • D S Kompala, D Ramkrishna, N B Jansen, G T Tsao (1986). Investigation of bacterial growth on mixed substrates: experimental evaluation of cybernetic models. Biotechnol Bioeng, (pp. 1044–1055).
  • Fange, David, Harriet Mellenius, Patrick P. Dennis, and Måns Ehrenberg (2014). Thermodynamic modeling of variations in the rate of rna chain elongation of e. coli rrn operons. Biophysical Journal 106, 1, 55–64. doi:10.1016/j.bpj.2013.11.4487.
  • Frank, Heiner Hoffman and Michael E. (1965). Synchrony of division in clonal microcolonies of escherichia coli. J Bacteriol, 2(89), 513–517.
  • Grant, Waclaw, Allen, Cicuta. (2014). The role of mechanical forces in the planar to bulk transition in growing e. coli microcolonies, .
  • Hao, Nan, Adam C. Palmer, Alexandra Ahlgren-Berg, Keith E. Shearwin, and Ian B. Dodd. (2016). The role of repressor kinetics in relief of transcrip- tional interference between convergent promoters. Nucleic Acids Research, 44(14), 6625–38. doi:10.1093/nar/gkw600.
  • Hedges and Whitehead. (2005). Photodegradation and photosensitization of mycosporine-like amino acids. Journal of Photochemistry and Photobiology B: Biology, (pp. 115–121). doi:10.1016/j.jphotobiol.2005.03.008.
  • Jaime Sa ́nchez-Navarrete, Nancy Jannet Ruiz-Pe ́rez, Armando Guerra-Trejo and Julia Dolores Toscano-Garibay. (2020). Simplified modeling of e. coli mortality after genome damage induced by uv-c light exposure. Sci Rep 10, (p. 11240). doi:10.1038/s41598-020-67838-1.
  • Leppek, Kathrin, Rhiju Das, and Maria Barna. (2018). Functional 5 utr mrna structures in eukaryotic translation regulation and how to find them. Nature Reviews Molecular Cell Biology, 19(3), 158–74. doi:10.1038/nrm.2017. 103.
  • Li, Mingji, Junshu Wang, Yanping Geng, Yikui Li, Qian Wang, Quanfeng Liang, and Qingsheng Qi. (2018). A strategy of gene overexpression based on tandem repetitive promoters in escherichia coli. Microbial Cell Factories, 11, 1–10. doi:10.1186/1475-2859-11-19.
  • Murray, James D. (2007). Mathematical Biology: I. An Introduction. Springer Science Business Media.
  • Presser, K. A., Ratkowsky, D. A. and Ross, T. (1997). Modelling the growth rate of escherichia coli as a function of ph and lactic acid concentration. Applied and environmental microbiology, 63(6), 2355–2360. doi:10.1128/ aem.63.6.2355- 2360.1997.
  • Vandervelde, Alexandra, Igor Drobnak, San Hadzˇi, Yann G.J. Sterckx, Thomas Welte, Henri De Greve, Daniel Charlier, Rouslan Efremov, Remy Loris, and Jurij Lah. (2017). Molecular mechanism governing ratio-dependent tran- scription regulation in the ccdab operon. Nucleic Acids Research, 45(6), 2937–50. doi:10.1093/nar/gkx108.