Lindenberger C, Pflug L, Hübner H, Buchholz R (2012)
Publication Language: English
Publication Status: Published
Publication Type: Journal article, Original article
Publication year: 2012
Publisher: Springer Verlag (Germany)
Book Volume: 17
Pages Range: 211-217
Journal Issue: 1
URI: http://link.springer.com/article/10.1007/s12257-011-0371-5
DOI: 10.1007/s12257-011-0371-5
In this paper, a new Ansatz for modelling the Baculovirus infection cycle is presented. The base of this model is the cell cycle distribution at the time of infection. It is possible to calculate the growth of the culture and the initiation of virus processing by considering cell cycle distribution. By taking into account the length of the viral genome and the polymerase activity, it is possible to calculate the virus production rate, which underlies a logistic growth. In the present work, a new hypothesis explaining the accelerated death rates of infected cells has been introduced. This assumption provides the possibilities of performing calculation without any fixed time intervals. The simulation was tested by comparing experimental data with the model prediction. Therefore, cell cycle distributions over the culture time and the growth behaviour of infected and non-infected insect cells were measured. A model, Baculovirus coding for GFP was employed for the present investigation, as it allows tracking the infection and determining the effectiveness of the infection, which is highly dependent on the cell density at the time of infection (TOI). Furthermore, the new model is is taken to simulate data gained from literature about virus release and adsorption. The new assumptions make the model more independent to fit into different cultivation systems.
APA:
Lindenberger, C., Pflug, L., Hübner, H., & Buchholz, R. (2012). A novel model for studying baculovirus infection process. Biotechnology and Bioprocess Engineering, 17(1), 211-217. https://dx.doi.org/10.1007/s12257-011-0371-5
MLA:
Lindenberger, Christoph, et al. "A novel model for studying baculovirus infection process." Biotechnology and Bioprocess Engineering 17.1 (2012): 211-217.
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