access icon openaccess Analytical approach for the calculation of promoter activities based on fluorescent protein expression data

This is an open access article published by the IET under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/)
Received 20/02/2017, Accepted 30/08/2017, Revised 10/07/2017, Published 25/10/2017

Characterisation of promoters, repressors, enhancers and so on, is not only essential for unravelling the inner workings of gene regulation, but also to enable the rational engineering of novel synthetic elements. Each putative regulatory region requires experimental assessment across a range of chassis and growth conditions, in order to be categorised as a fully defined functional element. In most studies, promoter activity is represented as the magnitude of a reporter signal, usually fluorescence, normalised to the biomass, as given by the optical density (OD). Such experimental values are often obtained from a coupled time-series experiment. Applying simple mathematical reasoning, a tool that describes promoter activity at each time point has been implemented. Protein expression and maturation, are modelled as first-order differential equations, taking into account the degradation and maturation rates which need to be known in advance. The promoter activity is then expressed based on the measured values of fluorescence and OD with a formula derived by mathematical manipulations of the defined quantities and the differential equations that comprise the model. Continuous expressions for fluorescence and OD are obtained from Gaussian process regression. Validation of the tool with experimental data from several constructs showed the expected behaviour of promoter activities.

Inspec keywords: proteins; Gaussian processes; time series; differential equations; molecular biophysics; fluorescence; genetics

Other keywords: repressors; coupled time-series experiment; enhancers; first-order differential equations; protein maturation; biomass; gene regulation; Gaussian process regression; optical density; fluorescent protein expression data; promoter activities

Subjects: Model reactions in molecular biophysics; Biomolecular dynamics, molecular probes, molecular pattern recognition; Interactions with radiations at the biomolecular level; Probability theory, stochastic processes, and statistics; Physics of subcellular structures

References

    1. 1)
      • 14. ‘Anderson Promoter Collection’, accessed2017.
    2. 2)
      • 30. Rasmussen, C.E., Williams, C.K.: ‘Gaussian processes for machine learning’ (vol. 1, MIT Press, Cambridge, 2006).
    3. 3)
    4. 4)
    5. 5)
    6. 6)
      • 22. ‘Fmincon – Mathworks’, accessed 2017.
    7. 7)
    8. 8)
      • 12. Andersen, J.B., Sternberg, C., Poulsen, L.K., et al: ‘New unstable variants of green fluorescent protein for studies of transient gene expression in bacteria’, Appl. Environ. Microbiol., 1998, 64, (6), pp. 2240–2246.
    9. 9)
    10. 10)
    11. 11)
    12. 12)
    13. 13)
    14. 14)
    15. 15)
    16. 16)
      • 38. Andersen, J.T., Poulsen, P., Jensen, K.F.: ‘Attenuation in the Rph-Pyre operon of Escherichia coli and processing of the dicistronic mRNA’, The FEBS Journal, 1992, 206, (2), 381–390.
    17. 17)
    18. 18)
    19. 19)
    20. 20)
    21. 21)
    22. 22)
    23. 23)
    24. 24)
    25. 25)
    26. 26)
    27. 27)
      • 21. Zwietering, M.H., Jongenburger, I., Rombouts, F.M., et al: ‘Modeling of the bacterial growth curve’, Appl. Environ. Microbiol., 1990, 56, (6), pp. 1875–1881.
    28. 28)
    29. 29)
    30. 30)
    31. 31)
    32. 32)
    33. 33)
    34. 34)
    35. 35)
      • 29. McHutchon, A.: ‘Differentiating Gaussian processes’, in Cambridge (ed.), 2013.
    36. 36)
    37. 37)
      • 8. Ma, J.: ‘Promoter fusions to study gene expression’. Els (John Wiley & Sons, Ltd., 2014).
    38. 38)
    39. 39)
      • 16. Sambrook, J., Fritsch, E.F., Maniatis, T.: ‘Molecular cloning: a laboratory manual’ (Cold Spring Harbor, 1989).
    40. 40)
    41. 41)
    42. 42)
http://iet.metastore.ingenta.com/content/journals/10.1049/enb.2017.0002
Loading

Related content

content/journals/10.1049/enb.2017.0002
pub_keyword,iet_inspecKeyword,pub_concept
6
6
Loading