Real‐time monitoring of influenza virus production kinetics in HEK293 cell cultures

Petiot, Emma; Kamen, Amine

doi:10.1002/btpr.1601

Cited by 25 publications

(12 citation statements)

References 73 publications

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“…For other virus-mammalian host cells, higher optimal multiplicity of infection values (1) than those obtained in the present work were obtained, but they were not tested herein. 26 However, similar values of rabies virus production were observed with respect to other study with same fetal calf serum in culture medium, even with differences in multiplicity of infections. 27 In general, the multivariate nature of virus production suggests unique factor combinations for each system, hence, reducing experiments is a main task for development of this kind of bioprocess.…”

Section: Discussionsupporting

confidence: 90%

Use of uniform designs in combination with neural networks for viral infection process development

Buenno¹,

Rocha²,

Leme

et al. 2015

Biotechnology Progress

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This work aimed to compare the predictive capacity of empirical models, based on the uniform design utilization combined to artificial neural networks with respect to classical factorial designs in bioprocess, using as example the rabies virus replication in BHK-21 cells. The viral infection process parameters under study were temperature (34°C, 37°C), multiplicity of infection (0.04, 0.07, 0.1), times of infection, and harvest (24, 48, 72 hours) and the monitored output parameter was viral production. A multilevel factorial experimental design was performed for the study of this system. Fractions of this experimental approach (18, 24, 30, 36 and 42 runs), defined according uniform designs, were used as alternative for modelling through artificial neural network and thereafter an output variable optimization was carried out by means of genetic algorithm methodology. Model prediction capacities for all uniform design approaches under study were better than that found for classical factorial design approach. It was demonstrated that uniform design in combination with artificial neural network could be an efficient experimental approach for modelling complex bioprocess like viral production. For the present study case, 67% of experimental resources were saved when compared to a classical factorial design approach. In the near future, this strategy could replace the established factorial designs used in the bioprocess development activities performed within biopharmaceutical organizations because of the improvements gained in the economics of experimentation that do not sacrifice the quality of decisions.

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Section: Discussionsupporting

confidence: 90%

Use of uniform designs in combination with neural networks for viral infection process development

Buenno¹,

Rocha²,

Leme

et al. 2015

Biotechnology Progress

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“…This observation suggests that reassortment is limited when the life cycles of co-infecting viruses are at markedly asynchronous. Given that released virus was sampled 12 h after the second inoculation, however, there was enough time for the second virus to undergo a full cycle of replication [31], sampling all stages of the life cycle. Thus, perhaps the predominance of progeny carrying full var genotypes was simply due to a predominance of var genomes within the co-infected cells.…”

Section: Discussionmentioning

confidence: 99%

Influenza Virus Reassortment Occurs with High Frequency in the Absence of Segment Mismatch

et al. 2013

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Reassortment is fundamental to the evolution of influenza viruses and plays a key role in the generation of epidemiologically significant strains. Previous studies indicate that reassortment is restricted by segment mismatch, arising from functional incompatibilities among components of two viruses. Additional factors that dictate the efficiency of reassortment remain poorly characterized. Thus, it is unclear what conditions are favorable for reassortment and therefore under what circumstances novel influenza A viruses might arise in nature. Herein, we describe a system for studying reassortment in the absence of segment mismatch and exploit this system to determine the baseline efficiency of reassortment and the effects of infection dose and timing. Silent mutations were introduced into A/Panama/2007/99 virus such that high-resolution melt analysis could be used to differentiate all eight segments of the wild-type and the silently mutated variant virus. The use of phenotypically identical parent viruses ensured that all progeny were equally fit, allowing reassortment to be measured without selection bias. Using this system, we found that reassortment occurred efficiently (88.4%) following high multiplicity infection, suggesting the process is not appreciably limited by intracellular compartmentalization. That co-infection is the major determinant of reassortment efficiency in the absence of segment mismatch was confirmed with the observation that the proportion of viruses with reassortant genotypes increased exponentially with the proportion of cells co-infected. The number of reassortants shed from co-infected guinea pigs was likewise dependent on dose. With 106 PFU inocula, 46%–86% of viruses isolated from guinea pigs were reassortants. The introduction of a delay between infections also had a strong impact on reassortment and allowed definition of time windows during which super-infection led to reassortment in culture and in vivo. Overall, our results indicate that reassortment between two like influenza viruses is efficient but also strongly dependent on dose and timing of the infections.

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“…During a virus production process, the radius/volume of the host cell changes due to the infection process (Druzinec et al, 2013;Emma & Kamen, 2012;Justice et al, 2011;Negrete et al, 2007). By applying DS, the cell radius r can be calculated using the critical frequency fc, considering the intracellular and extracellular conductivities, σ i and σ e (Petiot et al, 2010;Schwan, 1957).…”

Section: Discussionmentioning

confidence: 99%

High titer oncolytic measles virus production process by integration of dielectric spectroscopy as online monitoring system

Grein

Loewe

Dieken

et al. 2018

Biotech & Bioengineering

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Oncolytic viruses offer new hope to millions of patients with incurable cancer. One promising class of oncolytic viruses is Measles virus, but its broad administration to cancer patients is currently hampered by the inability to produce the large amounts of virus needed for treatment (10 -10 virus particles per dose). Measles virus is unstable, leading to very low virus titers during production. The time of infection and time of harvest are therefore critical parameters in a Measles virus production process, and their optimization requires an accurate online monitoring system. We integrated a probe based on dielectric spectroscopy (DS) into a stirred tank reactor to characterize the Measles virus production process in adherent growing Vero cells. We found that DS could be used to monitor cell adhesion on the microcarrier and that the optimal virus harvest time correlated with the global maximum permittivity signal. In 16 independent bioreactor runs, the maximum Measles virus titer was achieved approximately 40 hr after the permittivity maximum. Compared to an uncontrolled Measles virus production process, the integration of DS increased the maximum virus concentration by more than three orders of magnitude. This was sufficient to achieve an active Measles virus concentration of > 10 TCID ml .

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Real‐time monitoring of influenza virus production kinetics in HEK293 cell cultures

Cited by 25 publications

References 73 publications

Use of uniform designs in combination with neural networks for viral infection process development

Use of uniform designs in combination with neural networks for viral infection process development

Influenza Virus Reassortment Occurs with High Frequency in the Absence of Segment Mismatch

High titer oncolytic measles virus production process by integration of dielectric spectroscopy as online monitoring system

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