Modeling the behavior of plasmid‐harboring cells in nonselective media

Satyagal, Vasuki N.; Agrawal, Piyush

doi:10.1002/bit.260340216

Cited by 8 publications

(3 citation statements)

References 21 publications

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“…1992). Even before Mosrati and coworkers (1993) quantified this variation, others such as Satyagal and Agrawal (1989) and Weber and San (1989) had recognised this fact. Since the latter two groups of authors attribute this to the nonconstant difference between the specific growth rates of plasmid-bearing and plasmid-free cells, this difference, A p , was computed for both cyclic and constant dilution rates.…”

Section: Resultsmentioning

confidence: 98%

“…Studying the effect of square-wave variations in dilution rate on an Escherichia coli RR1 strain, San (1987, 1989) found it difficult to reconcile their data to a constant probability model. Satyagal and Agrawal (1989) allude to a varying probability by expressing it as a function of the number of DNA molecules in the mother cell at the time of cell division, a number which varies with time. Recognizing these observations, Mosrati and coworkers (1993) studied fermentation by an E. coli C600 gal K strain, which contained the plasmid.…”

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confidence: 99%

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Effect of feed cycling on plasmid stabilization during continuous fermentation: The case of variable plasmid loss probability

Patnaik

1994

Can J Chem Eng

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The effect of feed cycling on the stability of plasmid-bearing cells during continuous fermentation has been analysed for the case where the probability of loss of the plasmid varies with time. The model consists of a system of delayed differential equations. By using a square-wave profile of the dilution rate, a two-fold increase in the concentration of plasmid-bearing cells and the recombinant product can be achieved over what is possible with a constant dilution rate. The dilution rate has a stronger effect than the frequency. These results agree qualitatively with reported experiments. The plasmid loss probability and the differential growth rate show fluctuations for a square-wave variation in the dilution rate, and even with a constant dilution rate they stabilise only after a length of time. These observations show that it is particularly important to account for variable plasmid loss probability in the initial phase of fermentation.On a analysk I'effet du cyclage de I'alimentation sur la stabilitC des cellules porteuses de plasmide en fermentation continue pour le cas oa la probabilitd de perte de plasmide varie dans le temps. Le modtle se compose d'un systtme d'kquations diffkrentielles retardkes. Avec un profil en ondes carrtes de la vitesse de dilution, on peut obtenir une augmentation dans la concentration de cellules porteuses de plasmide et le produit recombinant d'un facteur deux en comparaison & ce qui est possible avec une vitesse de dilution constante. La vitesse de dilution exerce un effet plus grand que la frequence. Ces rksultats montrent un bon accord qualitatif avec les expkriences dtcrites. La probabilitk de perte de plasmide et le taux de croissance diffkrentiel montrent des fluctuations pour une vitesse de dilution qui varie en ondes carrees, et m&me avec une vitesse de dilution constante ces deux facteurs se stabilisent seulement aprts un certain temps. Ces observations montrent qu'il est particulitrement important de tenir compte de la variabilitk de la probabilitk de perte de plasmide dans la phase initiale de fermentation.

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Section: Resultsmentioning

confidence: 98%

mentioning

confidence: 99%

Effect of feed cycling on plasmid stabilization during continuous fermentation: The case of variable plasmid loss probability

Patnaik

1994

Can J Chem Eng

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“…Modeling of Recombinant Cultures. Ollis and Chang (1982) and Satyagal and Agrawal (1989b) developed mathematical models to describe the behavior of plasmidharboring cells and associated product formation. Both of the models are based on the framework reported by Imanaka and Aiba (1981).…”

Section: Model Developmentmentioning

confidence: 99%

A Model for β‐Galactosidase Production with a Recombinant Yeast Saccharomyces cerevisiae in Fed‐Batch Culture

Hardjito

Greenfield

Lee

1992

Biotechnology Progress

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An unstructured model is developed to describe the growth and product formation behavior of a recombinant yeast Saccharomyces cerevisiae using beta-galactosidase as a model protein. The model shows good agreement with the experimental data over a range of conditions. It also accurately predicts the effect of growth rate on yield coefficient and gene expression. The simplicity and accuracy of the model make it suitable for designing and implementing control and optimization strategies for the production of recombinant proteins at large scale.

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Cellular plasmid content and cloned‐gene expression: Some useful equations

Satyagal¹,

Agrawal²

1990

Biotech & Bioengineering

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Cellular plasmid content determines the yield of closed-gene product, affects plasmid replication, and influences the behavior of the culture by dictating the extent of metabolic burden on the host cell and plasmid segregation at cell division. Hence, it is a variable of primary importance in the study of recombinant cell cultures. In this article, equations are developed to enable the conversion of experimental determinations of cellular plasmid content into theoretically important units. The importance of different units in characterizing plasmid effect on cell response is highlighted. Also, equations that relate cellular plasmid content to cloned-gene expression are developed and successfully tested on several sets of data from literature.

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Modeling the behavior of plasmid‐harboring cells in nonselective media

Cited by 8 publications

References 21 publications

Effect of feed cycling on plasmid stabilization during continuous fermentation: The case of variable plasmid loss probability

Effect of feed cycling on plasmid stabilization during continuous fermentation: The case of variable plasmid loss probability

A Model for β‐Galactosidase Production with a Recombinant Yeast Saccharomyces cerevisiae in Fed‐Batch Culture

Cellular plasmid content and cloned‐gene expression: Some useful equations

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