Journal article
Statistical modeling of cell‐to‐cell variability in viral infection during passaging in suspension cell culture: Application in Monte‐Carlo simulation
Biotechnology and bioengineering, Vol.117(5), pp.1483-1501
05/2020
DOI: 10.1002/bit.27295
PMID: 32017023
Abstract
Packaging during the passaging of viruses in cell cultures yields various phenotypes and is regulated by viral protein expression in infected cells. Although such a packaging mechanism has a profound effect in controlling the virus yield, little is known about the underlying statistical models followed by virus packaging and protein expression among cells infected with the virus. A predictive framework combining identification of the probability density function (PDF) based on log‐likelihood and using the PDF for Monte‐Carlo simulations is developed. The Birnbaum–Saunders distribution was found to be consistent with all three‐virus packaging levels, including nucleocapsids/occlusion‐derived virus (ODV), ODVs/polyhedra, and polyhedra/cell for both wild‐type and genetically modified AcMNPV. Next, it was demonstrated that PDF fitting could be used to compare two viruses having distinctly different genetic configurations. Finally, the identified PDF can be incorporated in RNA synthesis parameters for baculovirus infection to predict the cell‐to‐cell variability in protein expression using Monte‐Carlo simulations. The proposed tool can be used for the estimation of uncertainty in the kinetic parameter and prediction of cell‐to‐cell variability for other biological systems.
Schematic representation of characterization of heterogeneity in baculovirus infection process using single cell imaging and statistical modeling: Combination of data acquisition, identification of underlying probability density function and monte carlo simulation.
Details
- Title: Subtitle
- Statistical modeling of cell‐to‐cell variability in viral infection during passaging in suspension cell culture: Application in Monte‐Carlo simulation
- Creators
- Abha Saxena - Indian Institute of Technology HyderabadSuryateja Ravutla - Indian Institute of Technology HyderabadVikas Upadhyay - Indian Institute of Technology HyderabadSoumya Jana - Indian Institute of Technology HyderabadDavid Murhammer - University of IowaLopamudra Giri - Indian Institute of Technology Hyderabad
- Resource Type
- Journal article
- Publication Details
- Biotechnology and bioengineering, Vol.117(5), pp.1483-1501
- DOI
- 10.1002/bit.27295
- PMID
- 32017023
- ISSN
- 0006-3592
- eISSN
- 1097-0290
- Number of pages
- 19
- Language
- English
- Date published
- 05/2020
- Academic Unit
- Chemical and Biochemical Engineering
- Record Identifier
- 9984197098402771
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